Conservation practitioners are usually tasked with a very diverse set of activities within their job. A typical week for a reserve manager might involve managing staff, volunteers, contractors and budgets; liaising with people both within and outside of their organisation; dealing with health and safety and other legal obligations; taking part in a range of meetings; and replying to numerous emails about a wide range of topics. If the site is heavily visited, there will invariably be many tasks regarding visitors. In addition, practitioners also have to decide how best to manage their site for conservation.
In this chapter, we describe the processes that organisations and practitioners use to make conservation decisions, the trade-offs between resources spent monitoring and carrying out conservation management, and the types of information practitioners use to inform these decisions. We then discuss ways to ensure that decisions at sites are based on good evidence. We combine literature and theory on what constitutes best practice for reserve management with our practical experience. While our examples are focused on conservation land management at the site level, these frameworks and processes are generally applicable to decision-making in many other conservation contexts.
9.2 Types of conservation decisions made by practitioners
Decisions about the conservation management of sites are often complex. There are several reasons for this. First, many types of habitat management aim to achieve multiple objectives, and these will differ between sites. For example, a fire regime might aim to prevent an area of grassland from succeeding to scrub, while also aiming to maintain or increase plant species richness and provide a continuity of suitable conditions for particular bird species. Habitat management can also involve using different techniques in combination. For example, a wetland might be managed using a combination of livestock grazing and water-level control, while an area of dwarf-shrub heath might be managed through a combination of grazing, cutting and burning. Good management of sites, therefore, rarely involves simply implementing ‘off-the-shelf’ conservation actions. Furthermore, even where a single technique is used to benefit a single species (or group of species), practitioners usually still need to tailor the details of how it is implemented to the specific circumstances at their site.
Finally, decisions can also involve trade-offs between ecological, social and economic factors, and there may also be great uncertainty about the risks and benefits of each option. Meanwhile, practitioners are often working with limited resources, the scientific evidence may be conflicting, multiple decision-makers and stakeholders might have different preferences and opinions, and people inherently often do not make rational decisions.
9.3 Decision-making processes used by conservation organisations
The conservation management of nature reserves and other protected areas is usually the product of several levels of decision-making: strategic-level decisions, site-level management planning and what we will call ‘day-to-day decision-making’ by practitioners. Decisions taken at each of these levels are influenced by the decision-making process, the people involved in decisions and the evidence used to inform them (Table 9.1).
Decisions at the strategic level focus on the overall aims of the reserve network in which individual reserves sit, as well as the formulation of policies within which these reserves operate. An example of a policy might be an organisation’s approach to allowing wildlife hunting on its land, including the range of acceptable methods allowed. Strategic decisions are discussed elsewhere and we will not focus on these here (Margules & Pressey, Reference Margules and Pressey2000; Pressey et al., Reference Pressey, Cabeza and Watts2007; Wilson et al., Reference Wilson, Cabeza, Klein, Moilanen, Wilson and Possingham2009).
Site-level management planning processes (or site action planning) help practitioners develop objectives for reserves and identify the management actions needed to achieve them. For example, they might help decide the aims of managing a wetland, the desired water-level regime and proportions of swamp and open water, and the frequency of cutting the swamp vegetation needed to achieve these. These processes are also used to decide what monitoring is needed to determine whether the actions are achieving these objectives, or to detect other important changes, particularly those that might trigger management actions.
Finally, the actions agreed through the site-level planning decisions are implemented via ‘day-to-day decision-making’ by practitioners. For example, a practitioner wanting to install boxes to provide roosting habitat for bats would need to decide which trees would be suitable, and at what height and orientation on the tree the boxes would be most effective.
9.3.1 Site-level management planning processes
Management planning processes and frameworks help practitioners make conservation decisions and ensure that the decisions made are based on logic. We provide two examples of organisations’ management planning procedures in Box 9.1.
Royal Society for the Protection of Birds (RSPB): a land-owning, science-based conservation non-governmental organisation (NGO) in the UK, whose 215 reserves comprise mainly intensively managed cultural landscapes.
The overall aims for the RSPB’s nature reserve network are set out in its Reserves Strategy,Footnote 1 which is usually reviewed every five years. The strategy lists the particular species and habitats that the network aims to benefit, together with, for example, how the organisation aims to use the network to help people connect with nature. This strategy therefore sets the context within which the objectives of individual reserves are made.
Each RSPB reserve has a management plan, based on a standard template. This plan is ‘owned’ by the site’s practitioners, but its preparation involves a meeting with key individuals to agree on the long-term vision and objectives for the site, together with subsequent discussions. These key individuals are the practitioner’s line manager, an ecological adviser, a land agent and, if required, other scientists and specialists. Preparation of the plan can also include discussions with members of the local community.
Each management plan contains the reserve’s long-term vision, objectives, management and monitoring actions and five-year work programme. The Features–Attributes–Factors framework is used to decide these actions (Box 9.2). The draft management plan is checked and approved at both regional and national levels of the organisation and, if the site is a nationally designated site for protection, also by the relevant statutory agency.
Each reserve reports the progress towards achieving its management objectives annually and this report is audited by ecological advisers. An annual site-based meeting is also held at all key sites, involving site-based staff, their manager and an ecological adviser to help resolve any outstanding issues and plan work for the following year. Sites that are failing to make good progress are discussed with regional and national staff and a plan is developed to resolve any issues.
Conservation management in New Zealand is guided by the New Zealand Biodiversity Strategy and Action PlanFootnote 2 and the draft Threatened Species Strategy,Footnote 3 which are produced by DOC. This is in addition to management plans for broader landscape management issues, National Parks, site-based management prescriptions for ecosystems and speciesFootnote 4 and Threatened Species Recovery Plans.Footnote 5 An annual ‘5-year Statement of Intent’ sets out the longer-term directions for the DOC, as well as the management actions to be undertaken that year.
These plans are written variously by managers, policy staff, scientists and operations staff within the organisation, in partnership with Tangata whenua (NZ’s indigenous people) and in consultation with the public, private land-owners, relevant agencies and organisations. Collectively these plans outline objectives, targets or goals (often quantitative), time-bound management actions, research priorities and monitoring activities. They inform annual operational work programmes and provide the basis for output and outcome monitoring and annual reporting.Footnote 6
The planning process for DOC ecosystems and threatened species management focuses on producing specific, consistent and transparent action-based work projects in priority order to best meet agreed outcome-based objectives. Some of these outcome objectives include condition of ecosystems and long-term persistence of threatened species. Projects list the actions required to mitigate key pressures at sites. These projects are embedded directly into the Department’s Business Planning software, and when budgets are agreed the approved projects are simply ‘activated’ in the software and are then available for operations staff to work on. Key elements include having stable, overarching, outcome-based objectives; having standardised database entry of prescriptions that feed directly into the Department’s business planning processes; and having the ability to identify the most cost-effective set of prescriptions based on different priorities. Research, monitoring and evaluation of management are built into the planning and decision-making processes through DOC’s Biodiversity Monitoring and Reporting System. This system helps to identify changes and monitor success.
The procedures used by different organisations to set priorities and create management plans vary according to differences in their organisational structure, objectives and culture. However, in our experience, effective management and decision-making systems include the following six features.
1. They involve a range of people who, collectively, possess the expertise and knowledge needed to make well-informed decisions. They include site-based practitioners, their line managers and other advisers, scientists, experts and other stakeholders.
2. They involve an explicit process that helps identify appropriate actions. A variety of frameworks are used in management planning to help aid decision-making. We describe two examples in Box 9.2. Other methods used to help practitioners identify solutions for complex environmental problems include structured decision-making (Gregory et al., Reference Gregory, Failing and Harstone2012), multi-criteria decision-making (Davis et al., Reference Davis, Stoms and Costello2003) and risk analysis (Pollard et al., Reference Pollard, Davies and Coley2008).
3. Practitioners are involved in the decision-making and have ‘ownership’ of the final management actions. There are many examples of site management plans that have been produced by consultants and other people not involved in managing the site, which just sit on shelves gathering dust. Practitioners typically have a lot to do, and want to focus on managing their sites. Therefore, decision-making frameworks need to be as straightforward and unbureaucratic as possible, while still ensuring that decisions are the result of a logical process.
4. Decisions should be underpinned by good scientific evidence. Evidence-based decision-making involves the integration of scientific research, expertise and local knowledge (Sutherland et al., Reference Sutherland, Pullin and Dolman2004; Walsh, Reference Walsh2015). Scientific evidence can be obtained from scientific studies, reviews, summaries of evidence, decision support tools or advice from scientific advisors. In cases where evidence and data are limited, all available knowledge, including expertise and opinion, can be used for initial management decisions. This should be accompanied with monitoring, evaluation and experimentation where possible to learn and generate the required evidence.
5. The contents of the site management plan are checked and ‘signed off’ by colleagues who are involved in producing it. This ensures that standards are maintained, and that the contents of the management plan are sensible, feasible and consistent with regional, national and in some cases international priorities. It also helps to ensure ‘buy-in’ from relevant people in the rest of the organisation, some of whom might be involved in allocating resources for the site.
6. They include a process for evaluating and reviewing whether the site is achieving its objectives and, if not, helps identifies what to change. This process is a key component of adaptive management (Runge, Reference Runge2011; Westgate et al., Reference Westgate, Likens and Lindenmayer2013; Murphy & Weiland, Reference Murphy and Weiland2014), which has been adopted in principle by many conservation organisations and agencies. However, research suggests that successful implementation of adaptive management remains elusive in many projects (Keith et al., Reference Keith, Martin and McDonald-Madden2011; McFadden et al., Reference McFadden, Hiller and Tyre2011).
This framework has been widely used to develop environmental indicators, e.g. by Birdlife International for monitoring Important Bird Areas (Organisation for Economic Co-operation and Development, 1993; Birdlife International, 2006). It identifies negative pressures on habitats and species at a site; the state these habitats and populations are in; and what responses are required to reduce, or prevent, the impacts of these pressures.
For example, for an area of forest the pressures might be illegal logging and hunting; it might define the state of the forest in terms of its extent and population abundance of key species, while the response or interventions might be changes in conservation designation or protection and other projects aimed at preventing illegal logging and hunting.
This is the UK government’s framework for identifying actions to carry out in protected areas (JNCC, 2004). The first step is to identify the important conservation features at the site. These features can be species, assemblages of species, habitats or, more rarely, processes.
The second step is to identify the best measures of condition of these features, and to set targets (or target ranges) for them. These measures of condition are called attributes. Commonly used attributes for a species will be its population size and productivity. Attributes for a habitat might include measures of its structure and of the abundance of positive or negative indicator species.
The final step is to identify the main factors that are thought to determine whether a feature’s attribute will achieve its target condition and to set targets (or target ranges) for these factors. For a species, factors that might affect whether it attains its target population size could include levels of illegal persecution or its food supply. For a habitat, factors that might affect whether it attains its target condition might include levels of nutrient run-off and the management regime.
9.3.2 Day-to-day decision-making
To implement actions agreed in a site’s management plan, practitioners still need to make frequent decisions about the details of the interventions. Consider this example about protecting the nests of ground-nesting waders in the UK. The scientific evidence shows that predator-exclusion fencing can be used to increase the nest survival and overall breeding success of ground-nesting waders (Sutherland et al., Reference Sutherland, Dicks and Ockendon2018) and the site’s management plan includes an action to install predator-exclusion fencing. However, practitioners still need to consider many minute details before installing the fencing, to address local circumstances and try to maximise the effectiveness of the fencing (Figure 9.1).
When making decisions about the details of site management, a practitioner or their adviser will usually have a mental image of what they consider to be ideal habitat for a particular species or set of species. They will then compare the habitat present at a site with this ideal state and, based on a combination of past experience and other information, identify what they think needs to take place. This process will typically involve a visual assessment of the site, together with information from surveys and monitoring, the presence and population trends of key species, and their own and others’ experience of the impacts of management actions in the past and at other sites.
9.4 Monitoring information used in decision-making
The resources that practitioners have available for monitoring (i.e. staff time and money) usually come from the same ‘pot’ as those used for carrying out conservation work. Therefore, practitioners must make a trade-off decision. They need to conduct sufficient monitoring to reliably inform whether actions are having their desired effect, but not so much that it unnecessarily diverts resources away from the conservation work itself. Similarly, practitioners need to target surveillance efforts to detecting changes that, if they occur, would trigger conservation action. This is a different approach to that of a conservation scientist, who may be interested in investigating the underlying mechanisms causing a change, the effectiveness of an action (or set of actions) and in disentangling the effects of different actions. To do this would usually involve replicates and controls, and detailed monitoring sufficient for the results to be published.
These trade-offs are important to get right, because monitoring and surveillance can be expensive. For example, on the RSPB’s reserve network, monitoring, one-off surveys and surveillance are pared down to the minimum considered necessary to reliably inform management and contribute data to a small number of national monitoring schemes. Despite this, they still cost an estimated 7% of the total costs of maintaining this reserve network.
The type and quality of data collected during monitoring depends on the management question. At the one extreme, detailed monitoring is not needed to determine whether cutting grass reduces its height. At the other extreme, considerable resources can be required to determine levels of predation, or changes in the botanical composition of species-rich grassland. Practitioners and their advisers may invest more resources into monitoring if they are using a novel technique, applying a standard technique in a novel situation, if there is a high level of uncertainty about the results, or if the results are difficult to observe visually. The results would then ideally feedback into the planning processes to inform future decisions, and also be written up and disseminated to other practitioners.
9.5 Information used by practitioners to inform decision-making
Multiple studies have investigated the types of information used by practitioners from the UK, South Africa, Australia, Brazil and the USA, their level of access, and which sources they find most useful (Pullin et al., Reference Pullin, Knight and Stone2004; Pullin & Knight, Reference Pullin and Knight2005; Cook et al., Reference Cook, Hockings and Carter2010, Reference Cook, Carter and Fuller2012; Seavy & Howell, Reference Seavy and Howell2010; Bayliss & Randall, Reference Bayliss and Randall2011; Young & Van Aarde, Reference Young and Van Aarde2011; Matzek et al., Reference Matzek, Covino and Funk2014; Walsh, Reference Walsh2015; Giehl et al., Reference Giehl, Moretti and Walsh2017). These have shown that practitioners use a wide range of sources to inform conservation management decisions, with ‘personal experience’ the most common source of information usually reported. For example, practitioners from government and non-government agencies in the UK and South Africa said they use personal experience, monitoring data and advice from scientific advisors and managers most frequently when making management decisions (Walsh, Reference Walsh2015). Management plans, policy documents and decision support tools were less-frequently used. In contrast, scientific papers and unpublished research were rarely used directly to inform decisions (Walsh, Reference Walsh2015).
However, given the complexity of the types of decisions that practitioners make, we need to be cautious in concluding, from the results of simplified surveys, that most conservation decisions are based on personal experience, rather than scientific evidence.
First, as described in Section 9.3, practitioners’ decisions usually, but not always (see Pullin et al., Reference Pullin, Knight and Stone2004), take place within the context of ‘higher-level’ decisions, which have involved different people and thereby been based on different sources of information, potentially including scientific evidence.
Second, as described in Section 9.2, conservation management often involves the use of a combination of methods to benefit a wide range of species, tailored to specific circumstances at a site. Therefore, even if the decision to undertake an action (or set of actions) is underpinned by scientific evidence, the details of how best to implement it will usually require an additional ‘layer’ of personal experience and ecological ‘nous’ and expertise.
Third, ‘personal experience’ in any case consists of a mixture and accumulation of experiential and scientific knowledge, which is difficult to disentangle. An experienced practitioner may have read a relevant scientific paper a decade ago, or been informed of best practice that was itself based on scientific evidence. However, having since carried out the same or similar management activity for many years, they may now consider their source of information to be ‘personal experience’.
Scientific and ecological advisors provide an important link between science and practice by giving practitioners direct advice and bite-size information chunks of up-to-date, relevant scientific research. There is clear evidence of the value of advisers in increasing the effectiveness of conservation actions (Ingram, Reference Ingram2008; Ewen et al., Reference Ewen, Adams and Renwick2013). While a scientist will typically have in-depth knowledge of a particular subject area, a good ecological adviser will have a broader range of knowledge and experience of conservation management across multiple sites. Most importantly, good ecological advisers will have the ability to translate the results of science into practical management advice, which will involve their experience of the use of similar management actions at other sites.
On RSPB reserves, practitioners place a higher value on the advice given by dedicated ecological advisers than on advice provided by scientists, although the latter is still highly valued (Figure 9.2). The full role of these ecological advisers entails:
providing ecological advice to practitioners, through the management planning process, project teams and other ad-hoc means;
‘signing off’ all important ecological decisions made on these reserves;
annually auditing the effectiveness of reserve management; and
developing and encouraging the use of best practice, both within and outside the organisation.
These advisers need to have credibility with practitioners, many of whom will have a more detailed knowledge of, and close emotional attachment to, the land on which advice is being given. Similar advisers also have a critical role within government agencies, which provide grants to landowners through agri-environment and land management schemes.
The cost of providing these services by the dedicated ecological advisers at the RSPB is about 4% of the total costs of managing the reserve network. Therefore, if the provision of this advice increases the cost-effectiveness of reserve management by more than 4%, employing these advisers is a good use of conservation resources.
9.6 How important is it to use scientific evidence in decision-making?
There is an underlying assumption that decisions based on scientific evidence are more effective than those based solely on personal experience. However, there is little evidence in the conservation field to support the assumption that scientific evidence improves conservation outcomes. In the medical field, however, there are several examples where medical procedures and drugs that were once considered ‘best practice’ were found to be ineffective or caused severe unintended consequences once the scientific evidence had been collated and synthesised (Sackett & Rosenberg, Reference Sackett and Rosenberg1995; Morris et al., Reference Morris, Wooding and Grant2011).
The best evidence demonstrating the impact of using scientific evidence for conservation decisions comes from a study that measured practitioners’ likelihood of using different methods of reducing predation on birds before and after providing them with a summary of scientific evidence about the efficacy of each intervention (Walsh et al., Reference Walsh, Dicks and Sutherland2014). After reading the summarised scientific information, each participant was asked whether they were more or less likely to use each intervention. On average, practitioners changed their likelihood of using 46% of the interventions shown. Practitioners were more likely to use effective interventions after reading the evidence and less likely to use ineffective actions, suggesting access to the summarised scientific evidence could improve some conservation decisions. Even so, most participants said they would continue using their existing method(s), which they still considered to be the best solution for their set of circumstances (Walsh et al., Reference Walsh, Dicks and Sutherland2014).
The importance of scientific evidence will vary according to the type of decisions being made. For example, we would hope that a practitioner would check the latest scientific evidence on the best way to control a newly arrived, invasive non-native species. We would not, though, expect an experienced wetland manager to check the scientific literature every time they make a decision about manipulating water levels, although it would still be valuable for them to keep up-to-date with the results of new research. This might be via scientific summaries, magazines, or other information sources that synthesise new research into an accessible format, through meetings with relevant societies and by talking with scientific advisors.
We also suspect that the extent to which resources are wasted on implementing ineffective, non-evidence–based interventions varies greatly in different situations. In the case of widely adopted management interventions carried out by science-based organisations with good systems of planning and adaptive management, most interventions are likely to be underpinned by good evidence, but with actions tailored with personal experience to suit the site’s specific circumstances, and achieve its often complex objectives.
On the other hand, it is possible that ineffective interventions are implemented more frequently where there is less access to scientific advisers and the results of published science (e.g. Giehl et al., Reference Giehl, Moretti and Walsh2017). Another situation where ineffective interventions may also be more widespread is where a developer and their consultants put in place compensatory or offsetting measures that enable them to proceed with development, but have little or no interest in whether these measures prove effective (e.g. Harper & Quigley, Reference Harper and Quigley2005; Chapter 4). The consequences and wasted resources of ineffective interventions will be amplified if they are integrated into policy, and widely applied through standardised prescriptions, as occurred when the scientific evidence was not consulted while designing some European Union agri-environment scheme prescriptions (Dicks et al., Reference Dicks, Hodge and Randall2014).
9.7 Ways to increase the use of scientific evidence in decision-making
Despite the infrequent direct use of scientific papers by most practitioners, and the perceived low level of usefulness of scientific papers in informing decision-making, it is striking that practitioners typically value advice given to them by scientists (Walsh, Reference Walsh2015). Therefore, any lack of evidence-based decision-making in conservation is clearly not driven by practitioners’ aversion to the use of scientific evidence.
However, there are a number of barriers to the use of scientific papers by practitioners (Walsh et al., Reference Walsh, Dicks, Raymond and Sutherland2019). Only a small proportion of papers published in ecological journals contain information that is useful for practitioners (Matzek et al., Reference Matzek, Covino and Funk2014), while the results described in many papers are often fairly incomprehensible to most people outside of academia, often due to the complex statistical techniques used. In addition, many scientific papers are unavailable to practitioners due to publishers’ paywalls, although the increase in open-access journals will help with this (Fuller et al., Reference Fuller, Lee and Watson2014). Therefore, given that scientific papers on their own are unlikely to bridge the gap between science and practice, this leaves two complementary approaches. The first is increasing the synthesis and translation of scientific research into more easily accessible, practical information. The second is ensuring that decision-making processes involve advisors and scientists who help interpret the science and ensure that decisions are based on sound evidence.
Systematic reviews published through the Collaboration for Environmental Evidence are considered the most robust, unbiased level of evidence (Chapter 7). While systematic reviews are invaluable in informing medical practice and are becoming more popular in environmental management, they are often of limited use to conservation practitioners, because their conclusions are usually too generic (Cook et al., Reference Cook, Possingham and Fuller2013). To return to our previous example, a meta-analysis might conclude that predator-exclusion fences usually increase nesting success of a range of bird species, across a range of habitats (e.g. Smith et al., Reference Smith, Pullin and Stewart2011). However, practitioners are unlikely to be interested in their effect across a range of species and habitats. Instead, they will usually be more interested in knowing how to maximise the effectiveness of fencing at protecting a particular species against a specific predator, or set of predators, under similar conditions to those which occur at their site (see Figure 9.1). Because of this, summaries of scientific research that evaluate the success of more specific actions may be of greater use to practitioners. Examples of these include Conservation Evidence synopses (www.conservationevidence.com/synopsis/) and ‘What Works in Conservation’ (Sutherland et al., Reference Sutherland, Dicks and Ockendon2018).
In addition to the use of evidence summaries, in our experience, the most favoured forms of communication about the effectiveness of conservation actions by practitioners are: one-to-one advice; practical management workshops; practical management handbooks and case studies; visiting sites where the interventions have been implemented; and discussions with fellow practitioners who have practical experience of implementing the technique.
In conclusion, we suggest five key requirements to delivering effective conservation interventions at a site. These are:
ensuring there are sufficient resources;
ensuring good decision-making, planning processes and adaptive management are in place, and that these involve people who have relevant expertise;
employing skilled ecological advisors who can keep up-to-date with the relevant scientific and other literature, spread best practice and who are able to advise practitioners on site-specific solutions based on a combination of science and experience;
developing projects and collaborations with in-house conservation scientists and universities; and
employing skilled and knowledgeable practitioners who care about the effectiveness of what they are doing, keep up-to-date with accessible forms of information and who are subsequently able to make informed ecological decisions on a day-to-day basis (as well as being able to do a myriad of other things).
This chapter offers advice on how the conservation science community can effectively engage with decision-makers. The rationales for why we, as scientists, need to do this have been widely discussed in the literature. Often, the reasons offered are normative, pragmatic, or instrumental (de Vente et al., Reference de Vente, Reed and Stringer2016); in other words, there is a belief that engaging with decision-makers leads to better-informed, more acceptable decisions. Indeed, better engagement may lead to the greater uptake of evidence for conservation decisions, something which some scholars argue is a priority for effective management (e.g. Sutherland & Wordley, Reference Sutherland and Wordley2017; Gardner et al., Reference Gardner, Waeber and Razafindratsima2018).
Engagement with decision-makers of all types is needed because scientific evidence rarely influences policy and practice in a straightforward way; rather, evidence is considered as one part of a ‘messy’ decision-making progress alongside other forms of knowledge, interests, beliefs, pragmatics and other factors (Lawton, Reference Lawton2007; Adams & Sandbrook, Reference Adams and Sandbrook2013; Rose, Reference Rose2014a; Young et al., Reference Young, Waylen and Sarkki2014; Evans et al., Reference Evans, Davilla and Toomey2017). This is particularly true in the case of complex problems, such as biodiversity conservation, where the science is often uncertain, solutions are not readily apparent and the implementation of conservation interventions affects a range of stakeholders with different values and interests (Jarvis et al., Reference Jarvis, Borrelle and Bollard Breen2015a; Maron et al., Reference Maron, Ives and Kujala2016; Alford & Head, Reference Alford and Head2017; Rose, Reference Rose2018). Appreciating and understanding this complexity is a necessary step for scientists who wish to learn how they can most effectively engage with and influence conservation decision-making (Toomey et al., Reference Toomey, Knight and Barlow2016; Evans et al., Reference Evans, Davilla and Toomey2017; Chapter 2).
Effective engagement with decision-makers can facilitate the use of scientific evidence in decision-making, while building support for interventions that are to be implemented on the ground (de Vente, 2016; Bodin, Reference Bodin2017; Roux et al., Reference Roux, Nel and Cundill2017). Indeed, there has recently been renewed calls for a ‘new kind of science’ (Keeler et al., Reference Keeler, Chaplin-Kramer and Guerry2017) that is more democratic and inclusive, and explicitly recognises the need to engage stakeholders in the production and utilisation of scientific knowledge (Enquist et al., Reference Enquist, Jackson and Garfin2017; Hallett et al., Reference Hallett, Morelli and Gerber2017; Wall et al., Reference Wall, McNie and Garfin2017).
We define engagement as the process by which decision-makers and other stakeholders (including scientists) influence how and what decisions are made. Engagement is a key component of doing conservation work, since conservation decisions will always affect, or be affected, by people (Kareiva & Marvier, Reference Kareiva and Marvier2007; Kothari et al., Reference Kothari, Camill and Brown2013). Poorly conducted engagement, however, has the potential to lead to detrimental outcomes (Young et al., Reference Young, Jordan and Searle2013; Bodin, Reference Bodin2017; Reed et al., Reference Reed, Vella and Challies2017), for example by failing to include all decision-makers in a representative, valued way, or by reinforcing existing power imbalances and inequality (e.g. Chambers, Reference Chambers1997; Brockington, Reference Brockington2007).
So, what does ‘effective’ engagement look like? Communication is unsurprisingly a fundamental component. Differences in organisational culture, incentives and language can make it difficult for decision-makers and scientists to understand one another (Caplan, Reference Caplan1979; Head, Reference Head2015; Newman et al., Reference Newman, Cherney and Head2016) and this can lead to scientific evidence being mismatched with the needs of policy-makers and practitioners (Jarvis, 2015). Many other studies in conservation have noted that academic science is not always immediately relevant for practitioners (see Walsh et al., Reference Walsh, Dicks and Sutherland2015). Difficulties in communication include science being presented in jargonistic, unusable formats (Walsh et al., Reference Walsh, Dicks and Sutherland2015; Marshall et al., Reference Marshall, Adger and Attwood2017;), the lack of open access publishing (Arlettaz et al., Reference Arlettaz, Schaub and Fournier2010), communicating only in one language (Amano et al., Reference Amano, González-Varo and Sutherland2016) and poorly communicated policy demands (Neßhöver et al., Reference Neßhöver, Vandewalle and Wittmer2016). Overall, Farwig et al. (Reference Farwig, Ammer and Annighöfer2017) found that major differences in workflows, background and objectives create a ‘research–implementation gap’ (Cook et al., Reference Cook, Mascia and Schwartz2013; Jarvis et al., Reference Jarvis, Borrelle and Bollard Breen2015a), which is difficult to bridge. Rose et al. (2018a) found agreement on the major barriers to the use of evidence in conservation policy among policy-makers, scientists and practitioners, but noted that solutions needed to be implemented.
However, effective engagement is not simply a matter of improving communication (Cash et al., Reference Cash, Clark and Alcock2002; Evans et al., Reference Evans, Davilla and Toomey2017). Knowledge is inevitably co-produced (Miller & Wyborn, Reference Miller and Wyborn2018) by multiple groups of people through an iterative process of knowledge exchange, mutual learning, negotiation and adaptation (Cash et al., Reference Cash, Clark and Alcock2002; Wyborn, Reference Wyborn2015). While scientists cannot change the fact that scientific evidence is (necessarily) just one input into conservation decision-making, through effective engagement it is possible to influence how and what knowledge (and decisions) are co-produced (Miller & Wyborn, Reference Miller and Wyborn2018).
Although it is impossible to construct a framework for good engagement that will work in all contexts (de Vente et al., Reference de Vente, Reed and Stringer2016; Bodin, Reference Bodin2017; Reed et al., Reference Reed, Vella and Challies2017) common principles of effective engagement include trust, reciprocity, respect, transparency, clear benefits to participants, co-learning and identifying all necessary decision-makers (see Table 10.1; de Vente et al., Reference de Vente, Reed and Stringer2016; Enquist et al., Reference Enquist, Jackson and Garfin2017; Reed et al., Reference Reed, Vella and Challies2017; Roux et al., Reference Roux, Nel and Cundill2017; Sterling et al., Reference Sterling, Betley and Sigouin2017). Engagement processes should be sensitive to cultural context and power relations and seek to disrupt existing inequalities, rather than reinforce them (Reed et al., Reference Reed, Vella and Challies2017; Sterling et al., Reference Sterling, Betley and Sigouin2017).
|Paper title and reference||Context||Key principles for good engagement|
|How does the context and design of participatory decision-making processes affect their outcomes? Evidence from sustainable land management in global drylands (de Vente et al., Reference de Vente, Reed and Stringer2016)||Sustainable land management in global drylands|
|Foundations of translational ecology (Enquist et al., Reference Enquist, Jackson and Garfin2017)||Considers what a new ‘translational ecology’ looks like – i.e. ecology that is trans-disciplinary and inclusive of stakeholders beyond academia|
|A theory of participation: what makes stakeholder and public engagement in environmental management work? (Reed et al., Reference Reed, Vella and Challies2017)||Narrative literature search (multiple contexts)|
|Trans-disciplinary research for systemic change: who to learn with, what to learn about and how to learn (Roux et al., Reference Roux, Nel and Cundill2017)||Contemporary conservation issues in South Africa|
|Assessing the evidence for stakeholder engagement in biodiversity conservation (Sterling et al., Reference Sterling, Betley and Sigouin2017)||Literature review (multiple contexts)|
In this chapter, we seek to illustrate common principles of effective engagement using several case studies. We first describe in more detail who the decision-makers in conservation are and how to ensure they are all identified and effectively engaged in a particular context. Next, we outline four case studies that provide examples of good engagement: the development of environmental offsets policy in Australia; community engagement in carnivore conservation in Costa Rica; participatory marine spatial planning in New Zealand; and the development of a code of conduct for marine conservation globally between researchers and NGOs. We conclude by providing 10 ‘top tips’ for scientists engaging with decision-makers, by drawing on the literature, aforementioned case studies and our own experiences.
10.2 Who are decision-makers in conservation?
Conservation decisions are made by various individuals and organisations at different levels of governance (Newell et al., Reference Newell, Pattberg and Schroeder2012; Evans et al., Reference Evans, Davilla and Toomey2017). Throughout this chapter we use ‘decision-makers’ as an umbrella term to refer to the multiple groups that are involved in conservation policy and practice. The decision-makers involved in a particular conservation issue will vary, as will the local cultures, priorities, knowledge types, values and workflows. Engagement with decision-makers is more likely to be effective if scientists first work to gain an understanding of who may affect or be affected by conservation decisions in a particular context (Waylen et al., Reference Waylen, Fischer and McGowan2010; Enquist et al., Reference Enquist, Jackson and Garfin2017; Sterling et al., Reference Sterling, Betley and Sigouin2017).
It cannot be assumed that good practice for working with one type of decision-maker is transferable to working with another (de Vente et al., Reference de Vente, Reed and Stringer2016; Reed et al., Reference Reed, Vella and Challies2017). For example, it is likely that the most appropriate approaches will differ between a government policy-maker, an NGO practitioner, an academic researcher, a farmer and a local resident. Decision-makers will use varying language, hold particular, and personal, worldviews and be part of different decision-making cultures (Blicharska & Grandin, Reference Blicharska and Grandin2015).
Before engaging, a representative list of key decision-makers needs to be created. Reed et al. (Reference Reed, Graves and Dandy2009) argue that three stages of stakeholder analysis are required at the start of collaborative forms of engagement: (1) identify all key actors; (2) differentiate between them by working to understand individual workflows, values, cultures and interests; and (3) understand relationships between actors, to help build alliances or prevent conflict (see also Colvin et al., Reference Colvin, Witt and Lacey2016). A range of methods can be used to map influential decision-makers (see Reed et al., Reference Reed, Vella and Challies2017 for a typology), including interviews, focus groups, Q-methodology, community workshops and the Delphi technique (Amit & Jacobson, Reference Amit and Jacobson2018; Mukherjee et al., Reference Mukherjee, Zabala and Hugé2018; Nyumba et al., Reference Nyumba, Wilson and Derrick2018; Young et al., Reference Young, Rose and Mumby2018). Such techniques can help to identify key decision-makers, elucidate how different individuals use and value their land, understand their views on conservation and manage differences between groups.
There is also heterogeneity within groups of decision-makers. For example, in the context of tropical reforestation, Lazos-Chavero et al. (Reference Lazos-Chavero, Zinda and Bennett-Curry2016) noted that cattle ranchers vary by their age, herd size and educational background. It proved important to engage with a representative group of cattle ranchers because the workflows and priorities of farmers varied with farm size and this influenced uptake of management practices. Indeed, the literature details many such cases where knowledge exchange with practitioners or the public was ineffective because groups were assumed to be homogeneous (Chilvers & Kearnes, Reference Chilvers and Kearnes2016). Taking account of intra-group hetereogeneity as well as inter-group variance thus adds an extra challenge to collaborative processes.
10.3 Case studies of good engagement
Many good examples of effective engagement in conservation exist in the literature from terrestrial (Fraser et al., Reference Fraser, Dougill and Mabee2006), freshwater (Nel et al., Reference Nel, Roux and Driver2016) and marine systems (Granek & Brown, Reference Granek and Brown2005). The nature of these successes varies from fostering an increased interest in conservation or natural resource management among local communities (e.g. Granek & Brown, Reference Granek and Brown2005; Fraser et al., Reference Fraser, Dougill and Mabee2006; Roux et al., Reference Roux, Nel and Cundill2017) to traditional knowledge being valued alongside scientific information and fostering inclusivity and trust (Granek & Brown, Reference Granek and Brown2005) to the formation of better decisions (Fraser et al., Reference Fraser, Dougill and Mabee2006; Nel et al., Reference Nel, Roux and Driver2016).
Here, we highlight four case studies where engagement with decision-makers has helped conservation. They present examples of engagement with different types of decision-maker: first with government policy-makers, second with stakeholders at the community level, third with multiple stakeholders at a regional level, and fourth with multiple stakeholders at a global level.
10.3.1 Case Study 1: Engaging with policy-makers – development of the Australian Environmental Offsets Policy
In 2012, Australian academic researchers formulated a calculation-based approach that set a new standard for determining environmental offset requirements. In collaboration with federal policy-makers in the Australian Department of the Environment, the calculation approach was developed into a tool for making fair and robust decisions about offsets. This became the Offsets Assessment Guide, which underpins the Australian Environmental Offsets Policy (2012) (see www.environment.gov.au/system/files/resources/12630bb4-2c10-4c8e-815f-2d7862bf87e7/files/offsets-policy_2.pdf) and remains the tool for determining offsets for significant impacts on more than 1800 threatened species and ecological communities in Australia (Gibbons et al., Reference Gibbons, Evans and Maron2015; Miller et al., Reference Miller, Trezise and Kraus2015). This collaborative effort between academics and policy-makers was enabled by long-term, effective relationships, significant government investment in research specifically to improve environmental decision-making,Footnote 1 support of senior executive members of the department and a decade of scientific research led by the research team and many colleagues.
Environmental offsets are routinely used as a tool to compensate for unavoidable impacts on biodiversity as a result of development activities such as mining, urban development and agricultural expansion (Maron et al., Reference Maron, Ives and Kujala2016). In Australia, offsets have been used as conditions of development approval by state and federal governments since the early 2000s (Maron et al., Reference Maron, Bull and Evans2015; Evans, Reference Evans2016). Regulatory decisions under Australia’s federal environmental law was guided by a draft policy from 2007 onwards, but stakeholder dissatisfaction with this framework led to a policy review and development of a new draft environmental offsets policy in 2011 (Miller et al., Reference Miller, Trezise and Kraus2015).
Stakeholder consultation led by the federal Department of the Environment indicated broad stakeholder agreement with the new draft policy principles, but also a clear desire for a scientifically robust framework for estimating offset requirements (Miller et al., Reference Miller, Trezise and Kraus2015). The Department then approached academic researchers to develop an offset calculation framework that would enable impacts on threatened species and ecological communities to be adequately and effectively compensated, give effect to the policy principles and be accessible and easy-to-use for all stakeholders (Miller et al., Reference Miller, Trezise and Kraus2015).
The development of the Offsets Assessment Guide was highly collaborative and iterative. Each major revision of the calculation framework produced by the academic researchers was tested by federal government operations staff to ensure ease of use, applicability to a range of decision contexts and adherence to the policy principles. This process of co-design enabled mutual learning and fostered a shared understanding of the different constraints and incentives that policy-makers and academic researchers work under. There was intense negotiation, compromise and robust debate. The researchers had to operate within a much shorter timeframe than is normally permitted in academia and learned to appreciate the government decision processes and ministerial requirements. The Department of the Environment recognised the need for the collaboration to result in academic publications for the researchers, and publication of work in the academic literature was considered a priority (Miller et al., Reference Miller, Trezise and Kraus2015).
The research outcomes have now shaped environmental offsetting around the world (IUCN, 2016; Maseyk et al., Reference Maseyk, Barea and Stephens2016; Cowie et al., Reference Cowie, Orr and Castillo Sanchez2018). The researchers continue to work with governments, industry, local communities and international convening bodies to boost public and policy-maker capacity to engage with environmental offsets. The final independent report to the Australian Government on the $154 M National Environmental Research Program highlighted this work as one of the Program’s most important impacts (Spencer et al., Reference Spencer, McVay and Sheridan2014):
The Offsets Calculator has provided a useful tool to improve the efficiency and effectiveness of regulating development under the EPBC Act by assessing the suitability of offset proposals and assisting with planning and estimating future offset requirements … The department credits the standing, expertise and assistance of the NERP Environmental Decisions Hub in building stakeholder understanding, trust and acceptance of the offsets policy and calculator, including by industry, NGOs and the jurisdictions. Stakeholder acceptance is crucial to its successful adoption and implementation of this policy.
10.3.2 Case Study 2: Engaging local communities – co-existence with large carnivores in Costa Rica
Amit and Jacobson (Reference Amit and Jacobson2018) present an example of community engagement in a project designed to facilitate co-existence between large carnivores (jaguars and pumas) and people in Costa Rica. Through the use of a group decision-making technique based on the Delphi process (see Mukherjee et al., Reference Mukherjee, Hugé and Sutherland2015), they engaged 133 members of seven communities, as well as 25 multi-disciplinary experts from government, NGOs and academic science. Four decision-making rounds were undertaken.
Round one: community representatives were identified by using a database of ranches with the potential for big cat attacks on livestock. After selecting two ranchers and two community leaders from each of seven ‘attack hotspots’, further participants were identified in consultation with them. At a workshop held at the University of Costa Rica, these local representatives were used to define the project agenda, to identify the major problems, and to brainstorm potential solutions. Draft solutions to incentivise co-existence were developed.
Rounds two and three: the draft incentives were reviewed through online questionnaires sent to a panel of multi-disciplinary experts (NGOs, academics, government). The draft list of incentives was iteratively developed based on the opinions of these experts.
Round four: a workshop was held with the communities in each of the seven ‘attack hotspots’. They had an average duration of three hours and were conducted by five facilitators at venues such as schools and community halls. Through anonymous voting, and a satisfaction questionnaire, the study team were able to test for consensus, and the willingness of participants to pilot particular incentives.
Detailed results and other methodological information are presented in the original paper (Amit & Jacobson, Reference Amit and Jacobson2018). The authors claim that their structured, bottom-up communication process stimulated social learning in a trusting, transparent, collaborative environment. Although one community declined to take part in future research, citing a lack of information provided in the process, the study team argued that the list of incentives for co-existence was able to integrate issues of governance, equity and social norms. As a result, support for the incentives, and for working in a transdisciplinary way, was strengthened in many of the communities.
10.3.3 Case Study 3: Engagement of multiple stakeholders and decision-makers at a regional level – the Sea Change – Tai Timu Tai Pari marine spatial planning process
In 2000 the Hauraki Gulf Marine Park (HGMP) was established to recognise the national significance of the Hauraki Gulf/Tīkapa Moana (also known as Te Moananui-ā-Toi) in New Zealand. While a number of management plans were developed over the years to mitigate key threats in the HGMP, they were never implemented. This lack of implementation was due to a lack of stakeholder involvement, weak governance and ineffective management (Hauraki Gulf Forum, 2011, 2014).
In response, Sea Change – Tai Timu Tai Pari was developed in 2013 as a new marine conservation and spatial planning process for the region. In contrast to previous planning efforts, Sea Change – Tai Timu Tai Pari was created as a collaborative, stakeholder-led, co-governance process to design, develop and action a new plan for the HGMP. A Stakeholder Working Group and a number of issues-based roundtables were established to navigate the co-development of the plan in consultation with mana whenua iwi and hapū (indigenous Māori tribes and sub-tribes), technical experts, local communities and stakeholders across a range of issues and priorities. This work was supported and assisted by five key partner agencies, including the Hauraki Gulf Forum, Waikato Regional Council, Auckland Council, the Ministry of Primary Industries and the Department of Conservation. In addition, conservation scientists were invited to collaborate with Sea Change – Tai Timu Tai Pari to develop participatory tools and approaches to enhance public and stakeholder engagement, while incorporating local knowledge and diverse values, views and priorities into the planning process (Jarvis et al., Reference Jarvis, Bollard Breen and Krägeloh2015b, Reference Jarvis, Bollard Breen and Krägeloh2016; Jarvis, Reference Jarvis2016). The final plan was released in April 2017 (Sea Change – Tai Timu Tai Pari, 2017).
Effective engagement and collaboration was seen as critical for the Sea Change – Tai Timu Tai Pari process and the development of the plan. This highly collaborative approach required negotiation, perseverance and sacrifice, in addition to the vision and commitment offered by those involved. While some work is already underway, the next step of the plan will be broad implementation across all goals and key principles. Strong and effective co-governance will be key to continuing engagement and effective implementation. There are high hopes that mana whenua iwi and hapū, communities, agencies and government will continue to work together to protect and conserve the future of the HGMP, support healthy and prosperous communities and safeguard this precious natural resource.
10.3.4 Case Study 4: Engagement of researchers, practitioners and NGOs at a global level – developing a code of conduct for marine conservation
As marine conservation gathers pace around the globe to achieve our conservation targets and the Sustainable Development Goals, there is a risk that these efforts fail to engage stakeholders and local people effectively. As a result, some actions taken may undermine the rights, dignity and freedoms of local people by not considering their needs or involving them in conservation processes. In response, a code of conduct (COC) was developed to provide a social baseline for how marine conservation should be undertaken, while raising the profile of effective engagement practices and the need for community and stakeholder involvement (Bennett et al., 2017a).
The COC was developed to promote fair governance and decision-making, support social justice and promote transparency and accountability in our marine conservation actions. This includes principles of human rights, indigenous rights and food security, as well as ensuring that marine conservation is carried out in a fair, inclusive way that supports local people. The COC has the potential to have wide-ranging impacts in the way scientists and practitioners undertake marine conservation to ensure it is socially just and environmentally effective.
The lead authors of the proposed code of conduct undertook an initial scoping review and prepared an initial list of principles for discussion with the broader marine conservation community (Bennett et al., 2017a). Next, they convened a meeting with a diverse group of leading experts in marine conservation at the IUCN 2016 World Conservation Congress in Hawaii to debate what is considered acceptable and unacceptable in marine conservation with researchers and practitioners from universities, non-profit organisations and government agencies from around the world. The final list of principles was agreed after several rounds of iterations with the authors and workshop participants, incorporating a thorough review of peer-reviewed literature, conservation policies and procedures and foundational policy documents.
The COC (Bennett et al., 2017a) was the result of this collaborative process and was communicated in a wide variety of formats to different media around the world, presented to policy-makers and discussed at high-level meetings, such as the United Nations Ocean Conference in June 2017. As a result, the COC has already been adopted as guiding principles for the Global Environment Facility Blue Carbon Project (GEF, 2017), with partners and beneficiaries that include the United Nations, 40 NGOs and a number of academic institutions, practitioners and members of the scientific community. The objective is for all Blue Carbon Projects to be developed following the COC by 2020. Engagement and discussion around the application of COC more broadly is ongoing. The goal is to establish the COC as a clearly articulated and comprehensive set of social standards to guide marine conservation actions at multiple scales and ensure that marine conservation goals are met through effective engagement, fair decision-making, accountability and inclusive participatory processes.
10.4 Ten tips for achieving good engagement
There have been few attempts to derive general principles of effective engagement from examples implemented in practice (Nguyen et al., Reference Nguyen, Young and Cooke2017; Reed et al., Reference Reed, Vella and Challies2017), as environmental management is such a context-specific endeavour (de Vente et al., Reference de Vente, Reed and Stringer2016). As such, Reed et al. (Reference Reed, Graves and Dandy2009) suggested that approaches to engagement should be flexible, adaptive and iterative based on local circumstances. With this in mind, we highlight 10 tips based on the case studies, the literature and our own experience (see also Table 10.1 for key factors identified in five other studies).
1. Know who you need to talk to
This important theme of inclusivity is commonplace in the literature (see Table 10.1). All relevant decision-makers need to be engaged with, or vital knowledge may be missed or unnecessary conflicts created (e.g. de Vente et al., Reference de Vente, Reed and Stringer2016; Enquist et al., Reference Enquist, Jackson and Garfin2017; Lazos-Chaveros et al., Reference Lazos-Chavero, Zinda and Bennett-Curry2016; Reed et al., Reference Reed, Vella and Challies2017). The composition of key decision-makers will always vary with context and may depend on the specific impact that is sought, but robust stakeholder analyses should be conducted before commencement of work (Reed et al., Reference Reed, Graves and Dandy2009; de Vente et al., Reference de Vente, Reed and Stringer2016). If time or resources are short, then decision-makers may be classified by the extent to which they are affected by a conservation issue (Reed et al., Reference Reed, Graves and Dandy2009), as Amit and Jacobson (Reference Amit and Jacobson2018) did by identifying ‘predator attack hotspots’.
Once decision-makers are identified and engaged with, scientists should seek to differentiate between different groups and understand relationships between them. Part of this process can be an attempt to understand their workflows, their values and culture and even the constraints under which they work. Once groups have been differentiated, then different styles of engagement and conflict management might be needed to work with each (Blicharska & Grandin, Reference Blicharska and Grandin2015). Furthermore, an appreciation and understanding of political, social and cultural context is always useful (Sterling et al., Reference Sterling, Betley and Sigouin2017).
2. Engage early, with clearly defined aims
Decision-maker engagement must have a clear purpose in order for all participants to work together towards a clear goal and outcome (Enquist et al., Reference Enquist, Jackson and Garfin2017). Involving decision-makers at an early stage of a project may provide ownership of a project to local communities, building support, legitimacy, and trust, as well as leading to the production of relevant, ‘use-inspired’, or ‘actionable’ knowledge (Wall et al., Reference Wall, McNie and Garfin2017). The need for local community-led engagement was illustrated by the examples of human-carnivore co-existence in Costa Rica (Amit & Jacobson, Reference Amit and Jacobson2018), marine conservation in New Zealand (Jarvis, Reference Jarvis2015; Jarvis et al., Reference Jarvis, Borrelle and Bollard Breen2015) and the biodiversity offsetting project stimulated by the Australian Department of the Environment (Miller et al., Reference Miller, Trezise and Kraus2015).
3. Decision-makers should find it easy to engage
Participation for all decision-makers must be easy (de Vente et al., Reference de Vente, Reed and Stringer2016). For example, meetings should be held in a convenient place for all and project timescales should consider the busy and varied workflows of all decision-makers involved, so as not to disincentivise engagement. Language should also be geared towards participants, and thus a common language and understanding should be developed wherever possible (Amano et al., Reference Amano, González-Varo and Sutherland2016; de Vente et al., Reference de Vente, Reed and Stringer2016). While we do not necessarily condone offering financial incentives for attendance, researchers could at least consider what the relative advantage of engagement is for decision-makers (what do different decision-makers gain from being part of the process?) and cover costs at the very least (particularly where poorer communities are being involved).
4. Embrace and include multiple knowledge(s), perspectives and worldviews
Engagement with decision-makers must be meaningful, and the perspectives and opinions of all stakeholders must be genuinely valued throughout the process (see all studies in Table 10.1). Participation should not merely be tokenistic. The first step towards this is humility on the part of researchers, which fosters a genuine sense to learn from others, while also accepting and appreciating that science is just one input into policy and practical processes. In their study of co-management in South African freshwater ecosystems, Roux et al. (Reference Roux, Nel and Cundill2017) warn against perceived scientific authority, and an attitude that bemoans some decisions made by policy-makers and other stakeholders as irrational if they are not ‘evidence-based’. The second step is to find ways of integrating multiple knowledge types into a project, including lay and indigenous knowledges, and local experiential knowledges, and ultimately fostering respect and understanding across different values and motivations (Sterling et al., Reference Sterling, Betley and Sigouin2017). The final step is to be able to reflect on your own values and motivations as a conservationist and be prepared to learn from those held by others (Bodin, Reference Bodin2017).
If these steps are followed, it is more likely that a truly collaborative spirit of cooperation will be achieved, which will help to build common understanding of an issue. This will not always mean that everyone agrees, but it will still be possible for all participants to understand each other’s point of view. Such a collaborative spirit has been shown to help a range of conservation projects, including in the case studies highlighted above.
5. Think hard about power
As researchers, we must do more than simply speak truth to the most obvious powers-that-be (Chambers, Reference Chambers1997); rather, we should seek to understand how communities work as thoroughly as possible, something that may require long-term engagement (e.g. using ethnography). Lazos-Chavero et al. (Reference Lazos-Chavero, Zinda and Bennett-Curry2016) found that paying attention to gender, generational and power disparities in a given region was essential to the success of tropical reforestation schemes. Furthermore, Kleiber et al. (Reference Kleiber, Harris and Vincent2015) showed that including women in the management of fisheries is essential for conservation success because a significant proportion of fishers are women (something that had often been ignored in previous studies). Thus, ensuring that all stakeholders have equal decision-making power is important for effective engagement. This also includes the balance of power between the stakeholders and the researchers themselves.
6. Build mutual trust
This theme is just about universally accepted in the literature and needs little explanation (see Table 10.1). Without mutual trust, transparency and respect, then engagement exercises with decision-makers are doomed to failure. Although Lacey et al. (Reference Lacey, Howden and Cvitanovic2018) warn against too much trust (e.g. because this could lead to facts being accepted on ‘blind faith’), it is logical to expect that relationships built on trust will yield better results. This is because participants will feel valued and able to challenge the opinion of others. Good practices for building trust include respecting participant confidentiality, following through on promises and committing to long-term engagement if it has been offered.
7. Good facilitation is key
Engagement processes need to have good facilitators (de Vente et al., Reference de Vente, Reed and Stringer2016). As illustrated by guides on how to conduct participatory methods, such as focus groups (Nyumba et al., Reference Nyumba, Wilson and Derrick2018), the facilitator plays a key role in managing group dynamics, encouraging stakeholder input and building trust. A good facilitator will be aware of potential sensitivities within the group (Gibbons et al., Reference Gibbons, Zammit and Youngentob2008) and be able to skilfully avoid and manage conflict, which is so important for a healthy engagement process (Amit & Jacobson, Reference Amit and Jacobson2018; Chapter 14). In controversial cases in particular, which are not unusual when dealing with the complex problem of biodiversity loss, the potential for conflict is more pronounced.
8. Learn new skills for good engagement
Good engagement and facilitation is helped if the individual is a good communicator. As individuals, it will become increasingly important to develop a range of different skills (as per Jackson et al., Reference Jackson, Garfin and Enquist2017) and be able to communicate differently with different people. In doing so, it is important to recognise that conservation can greatly benefit from better use of qualitative methods that improve communication, enhance engagement and give voice to others (Mukherjee et al., Reference Mukherjee, Zabala and Hugé2018). However, it may not be possible for individuals to learn all the different skills key for good engagement themselves. Therefore the development of truly inter- and trans-disciplinary teams could be one approach to bring all the necessary tools and skills together and co-design research that properly integrates the natural and social sciences (Bennett et al., 2017b, 2017c) while engaging with stakeholders from the outset and throughout conservation processes (Reed et al., Reference Reed, Vella and Challies2017). Where scientists feel unable to facilitate engagement processes effectively, much of the literature suggests using knowledge brokers (alternatively called boundary spanners or bridging agents; Cvitanovic et al., Reference Cvitanovic, Hobday and van Kerkhoff2015; de Vente et al., Reference de Vente, Reed and Stringer2016; Roux et al., Reference Roux, Nel and Cundill2017; Bednarek et al. Reference Bednarek, Wyborn and Cvitanovic2018). These individuals have the skills to bridge the gap between varying backgrounds, cultures, interests and languages.
9. You don’t have to reinvent the wheel – consider making use of existing spaces and opportunities
In conservation, there are several good schemes that encourage scientists to engage better with decision-makers across research, policy and practice (see Elliott et al., Reference Elliott, Ryan and Wyborn2018 for a global database of 650 conservation capacity initiatives). Such schemes have been developed to reflect requirements for the foundational skills necessary for good engagement while also providing existing opportunities for conservationists to develop their own capacity for effective communication, interpersonal interaction and boundary-crossing. By making use of such schemes, conservation scientists can develop their engagement skills while also being able to better adapt to the changing needs of conservation.
An additional point worthy of consideration is whether conservation researchers make the most of existing informal spaces of engagement to harness the views of decision-makers. Chilvers et al. (Reference Chilvers, Pallett and Hargreaves2017) criticise engagement processes for usually being established on the terms of researchers. In other words, groups of stakeholders are assembled to talk about an issue that is framed and defined by researchers or policy-makers, such as through public forums (see Chilvers & Kearnes, Reference Chilvers and Kearnes2016). Very rarely do we seek to ‘listen in’ on existing spaces of public participation (e.g. in the village hall, in the pub, on social media) to see what people are concerned about. Could the same criticism be levelled at conservation engagement exercises? Do we seek to assemble groups of decision-makers to discuss conservation issues that we have already framed, rather than asking, for example, local communities to devise the questions of interest (see tip 4)? We suggest that it is important to consider these questions in order that engagement exercises are led by communities, rather than done to them.
10. Don’t give up!
The need for long-term engagement is commonly highlighted in the literature (see Table 10.1). One important aspect to take from our recommendations is that they will not always yield immediate, tangible rewards, but this should not be the sole aim of practising good engagement. Rather, ongoing, long-term engagement can lead to a change in the overall policy framing of problems and solutions (Rose et al., Reference Rose, Mukherjee and Simmons2017), something which can occur diffusely over long timescales (Owens, Reference Owens2015). Reed et al. (Reference Reed, Vella and Challies2017) argue that engagement in controversial issues, where people hold deep core values, will need to be more long term (de Vente, Reference de Vente, Reed and Stringer2016; Roux et al., Reference Roux, Nel and Cundill2017). It can take some time to build the trust and confidence for stakeholders to contribute, and continued engagement after implementation is usually required for conservation projects (Lazos-Chavero et al., Reference Lazos-Chavero, Zinda and Bennett-Curry2016). So it is vital not to give up; as Amit and Jacobson (Reference Amit and Jacobson2018) argue, ‘participatory decision-making has an inherent phase of struggle and frustration’, which is perfectly normal. Sterling et al. (Reference Sterling, Betley and Sigouin2017) further describe knowledge co-production as a ‘slow’ process because it requires long-term committed engagement from all sides.
However, it is also important to note that flexibility of process is also key (Sterling et al., Reference Sterling, Betley and Sigouin2017). When inviting decision-makers to contribute to a project, the outcome might be different to the one that the researcher envisaged. Indeed, because you are incorporating multiple values and perspectives into decision-making, the unexpected may be the norm. Most importantly, expect the unexpected and don’t give up!
We acknowledge that it is not easy for conservation scientists to initiate and manage collaborative research projects, particularly those that work with a variety of stakeholder groups outside of academia. There are certainly challenges in achieving the new kind of science that Keeler et al. (Reference Keeler, Chaplin-Kramer and Guerry2017) envisaged (or in embracing the ‘post-normal’ reality, see Colloff et al., Reference Colloff, Lavorel and van Kerkhoff2017; Rose, Reference Rose2018), which would be more inclusive of people beyond academia. This includes practical difficulties (e.g. time, money) of engaging decision-makers (Sutherland et al., Reference Sutherland, Shackelford and Rose2017), as well as the challenge for conservation scientists of developing the skills needed to engage with people, a task for which many of us are not traditionally trained (Jackson et al., Reference Jackson, Garfin and Enquist2017). Furthermore, being actively involved with decision-makers might not be something that appeals to individual conservation scientists. Although the boundaries between science, policy and practice are fluid (Rose, Reference Rose2014b; Toomey et al., Reference Toomey, Knight and Barlow2016), scientists sometimes worry about moving beyond their comfort zone. Yet, if there is a scientific discipline in which advocacy is easier to do, then it should be mission-driven conservation biology (Soulé, Reference Soulé1985; Rose et al., Reference Rose, Sutherland and Amano2018b).
Ultimately, achieving effective engagement and conservation impact may mean changing the way conservationists work, including those housed in universities and research institutions. One significant challenge is for academic conservation scientists to find the time, motivation and support to engage decision-makers (Chapin, Reference Chapin2017; Keeler et al., Reference Keeler, Chaplin-Kramer and Guerry2017; Littell et al., Reference Littell, Terrando and Morelli2017). Often, academics are not rewarded adequately for producing tangible impacts (Jarvis et al., Reference Jarvis, Borrelle and Bollard Breen2015; Tyler, Reference Tyler2017), and activities focused on delivering these impacts are still widely sidelined in favour of career-enhancing academic publication. However, there is no real reason why impact cannot be better incentivised, and new opportunities developed to explore the different ways we can better navigate science, policy and practice. Why, for example, cannot academic departments have dedicated policy teams to highlight policy demand and to foster collaboration with decision-makers? A new kind of conservation science could certainly be imagined, which would reward outreach and incentivise inter-, multi- and trans-disciplinary collaborative work. Where we are unable to invest the time to engage with decision-makers ourselves, we could make much better use of knowledge brokers or boundary spanners (Bednarek et al., Reference Bednarek, Wyborn and Cvitanovic2018).
This research was supported by the Australian Government’s National Environmental Science Program through the Threatened Species Recovery Hub (MCE).
1 Specifically, through partnerships with the Australian Government’s Commonwealth Environmental Research Facilities (CERF) program (2004–2008), National Environmental Research Program (NERP, 2011–2015) and National Environmental Science Programme (NESP, 2016–2020).
Scientific evidence is fundamental to solving a suite of real-world issues and research is crucial in informing solutions to pressing issues such as climate change, food security, evolved resistance and land management (Thomas et al., Reference Thomas, Cameron and Green2004; Godfray et al., Reference Godfray, Beddington and Crute2010; Hicks et al., Reference Hicks, Comont and Coutts2018; Watson et al., Reference Watson, Evans and Venter2018). This evidence takes a range of forms, including the results of small- and large-scale experiments (Firbank et al., Reference Firbank, Heard and Woiwod2003), meta-analyses (Johnson & Curtis, Reference Johnson and Curtis2001; Batáry et al., Reference Batáry, Báldi and Kleijn2011), systematic reviews (Pullin & Stewart, Reference Pullin and Stewart2006) and predictive models (Taylor & Hastings, Reference Taylor and Hastings2004; Stratonovitch et al., Reference Stratonovitch, Storkey and Semenov2012). Decision-makers need to be able to choose between options using the best evidence available (Sutherland & Freckleton, Reference Sutherland and Freckleton2012).
Unfortunately, ecological systems are enormously variable at just about every scale that we study them (Holling, Reference Holling1973). This variability has numerous sources and, collectively, they contribute to what may be known as ‘uncertainty’. In recognising the role of uncertainty, it is important to recognise that this may arise both as an intrinsic property of the system as well as a nuisance through inadequate data or observation. In terms of intrinsic sources, for example, spatial variability results from variations in conditions from place to place (Tilman & Karieva, Reference Tilman and Karieva1997), while temporal variability similarly results from variations in systems through time (Huston, Reference Huston1994). On the other hand, the measurements of the system may contain inaccuracies. For instance, observational variance is a consequence of our inability to perfectly measure systems, instead relying on sampling in order to build up a picture of the dynamical properties of the system (Dennis et al., Reference Dennis, Ponciano and Lele2006; Freckleton et al., Reference Freckleton, Watkinson and Green2006).
Addressing all types of variability and stochasticity is important in making decisions, and we need to recognise the different sources and how they contribute to uncertainty. Consider a simple example: imagine that we are attempting to implement a conservation measure to protect an organism and that a management intervention, I, may be an effective conservation action if implemented, and this yields a benefit, b. However, there is a cost, c, to implementing the action. If we know that the action is certain to work, there is a simple calculation: all other things being equal then, assuming they are measured in the same units, if b > c then it would be worth performing I. If this is not true, then I is not a favourable approach.
However, because variability is pervasive, the situation in conservation management is rarely so simple. We might not be certain that I is always effective and instead suppose that we know that I is effective with probability p; p could have multiple interpretations depending on context. For example, in a spatially variable system, I might be effective in a fraction p of sites, but not in others: p thus measures the spatial variance in outcomes. Alternatively, the evidence for I being an effective strategy might be mixed, and therefore p could measure some aspect of our belief that I works.
When such uncertainty exists, the condition for a manager choosing to apply I becomes pb > c. Note that typically c should be known reasonably accurately as this will be costed in terms of the resources required to enact I. The benefit is now weighted by the uncertainty in efficacy of I. In terms of making correct management decisions, this simple condition suggests a number of interesting observations. First, as uncertainty increases (i.e. p gets smaller) the likelihood of employing I decreases. If p measures spatial or temporal variability in outcomes, then this is sensible because if I is less likely to work, so a manager should be less inclined to choose it. On the other hand, if p measures a lack of knowledge of the effectiveness of I, then the inequality suggests conservatism: do not take action unless it is known that I is effective with a high probability (p > c/b). If p is measuring such uncertainty then the recommended action has nothing to do with the actual effectiveness of I. Being conservative thus results from ignorance.
A second significant behaviour occurs when both p and c are low: the likelihood of I working is believed to be small but the cost is also small. In this case, employing I may still be favoured by a manager if the benefit is very large and one might describe this as superstitious behaviour (i.e. doing something in the face of little evidence that it will work because the benefit is high and the cost is low). A large number of interventions possibly fall into this category.
Overall, this illustrative example demonstrates that the amount of uncertainty can contribute a great deal to the overall management outcome. In both of the hypothetical situations outlined above, the management applied, and consequent outcome, is suboptimal because it leads to biased impressions of the costs and benefits. Characterising uncertainty is thus vital.
11.2 Recognising types of uncertainty
The source of uncertainty is important and authors have proposed various approaches to classifying uncertainty in management. Regan et al. (Reference Regan, Colyvan and Burgman2002) point out that many of the sources of variability leading to uncertainty described above may be termed epistemic (i.e. uncertainty in the system itself and its measurement). They also highlight a second source of uncertainty, namely linguistic uncertainty. This results from uncertainty in the language used to describe actions or systems, as well as resulting from the conveyance of information. As an example, in the UK there was a programme for government-hired shooters to exterminate ruddy ducks (Oxyura jamaicensis). During the cull, coot (Fulica atra), black-necked grebe (Podiceps nigricollis), common pochard (Aythya ferina) and common scoter (Melanitta nigra) individuals were also shot (Henderson, Reference Henderson2009). This resulted in part from inadequate communication with shooters (Henderson, Reference Henderson2009), who were not ornithologists and failed to distinguish between species. Consequently, there is a possibility of confusion, with procedures subsequently being developed to ensure that confusion is minimised. Although such uncertainty is undoubtedly important, I will concentrate on epistemic uncertainty sensu Regan et al. (Reference Regan, Colyvan and Burgman2002), although some of the points made below could equally apply to a more inclusive definition.
Broadly speaking, it is useful to distinguish intrinsic uncertainty (analogous to the variance in model parameters in an ecological or statistical model) from knowledge uncertainty (by analogy with the measurement error or lack of data in a model). The reason for making the distinction between these two types of uncertainty is important: one is a property of the system itself, while the other is caused by a lack of understanding or data. The two are interactive, and this is perhaps the greatest challenge to making robust predictions in management. If the management outcomes are uncertain both in terms of intrinsic variability and knowledge then they will be largely unpredictable. In this circumstance, it is necessary to question the recommendations given, as well as to consider whether the approach to prediction is the correct one. Another option is to consider models that use an alternative more stable formulation (Taylor & Hastings, Reference Taylor and Hastings2004; Freckleton et al., Reference Freckleton, Sutherland and Watkinson2011).
11.3 Science versus practice: different perspectives on uncertainty
Scientists and practitioners have different perspectives, even if they are working on the same problem. The question of how to resolve this difference is a thorny one (Bradshaw & Borchers, Reference Bradshaw and Borchers2000; Sutherland & Freckleton, Reference Sutherland and Freckleton2012) and there is a pervasive perception of a science–policy gap (Bertuol-Garcia et al., Reference Bertuol-Garcia, Morsello and El-Hani2018). Bradshaw and Borchers (Reference Bradshaw and Borchers2000) highlighted a series of ways in which the perspectives of science and practice may be misaligned. Of these there are two in which uncertainty plays a particularly important role.
11.3.1 Probabilistic, qualified evidence
In the introductory example above, the evidence for the effectiveness of a management intervention was measured as a probability. In terms of providing evidence, this is a routine way in which a scientist would express their recommendation. However, for implementing management, this can be problematic. For instance, telling a manager that there is a 70% chance that the intervention will work is only partly addressing the question of the manager, namely should they undertake the action or not? How is a manager to know whether their particular circumstances are likely to lead to them being in the 70% of cases in which the intervention works or in the 30% in which it fails?
In this context, the meaning of probabilities conveyed by scientists may not always be fully clear. Consider an everyday example. We might be told by a weather forecaster that there is a 50% chance of rain today. However, the meaning of that probability is not typically explained. Here are four interpretations.
(i) It will either rain everywhere or nowhere: it could be one or other of these outcomes, for example, because it is not possible to predict the precise location of a weather system.
(ii) It will rain for 50% of the time during the forecast period: for example, there are patchy rain clouds that are continually moving.
(iii) It will rain in 50% of places: for example, there are rain clouds cover 50% of the area that do not move.
(iv) The forecaster is unable to tell us whether it will rain or not and is telling you to flip a coin.
The technical interpretation of a probability in a weather forecast is that this probability represents the fraction of times a given outcome (e.g. raining within a defined set of areas) occurs in a set of stochastic realisations. This definition, interestingly, can incorporate all four of the above interpretations. Nevertheless, the probability quoted is a form of knowledge uncertainty that has a very specific meaning: it is a measure of model uncertainty/variance.
This highlights a second aspect of scientific evidence that is problematic from the perspective of management, namely that scientific evidence is usually qualified. The statement ‘there is a 50% chance of rain’ from a scientific perspective should also be qualified by the statement ‘across a set of simulations, given the assumption that the model is correct’. If the model is wrong then the prediction could be greatly different.
The task of a manager is to convert such evidence into action (i.e. the binary outcome of whether to act or not). As noted in the introduction, the decision then involves costs and benefits, defined in the widest sense and including values. To continue the hypothetical example, carrying an umbrella is low cost and high benefit, so a 50% chance of rain would render this a good strategy. On the other hand, a manager who is spraying a pesticide requires good conditions, and a 50% chance of rain would potentially carry an unacceptable risk that this costly action (in terms of fuel, time and chemicals) would fail.
11.3.2 General versus situational outcomes
The aim of science is typically to find answers that are as general and robust as possible. A scientist faced with evaluating the effectiveness of a management intervention will attempt to find whether there is evidence of its effectiveness, on average, and then probably focus on understanding the mechanisms that drive it. In contrast, a manager is faced with the task of managing a given site over a defined time period. There is a potential conflict between these perspectives, as the scientific perspective typically averages over variation arising from site-specific variations, whereas this is precisely the variation that a manager is focused on. For a scientist, the local variation at a specific site is essentially nuisance variance.
Although perhaps something of a caricature, there is undoubtedly a real problem in addressing these differences in perspectives. The situation is complicated by the difference in success measures for scientists and managers: scientists prove success by presenting results that are of interest to a wide range of others and that do not focus on specific instances (e.g. in scientific papers); managers measure success based on the state of their site. This difference in perspectives is reflected in the contrasting ways that scientists and managers treat uncertainty. From the science perspective the variation around the mean is a quantity that is to be minimised where possible; in contrast, a manager needs to know where their site sits with respect to this variation, and whether local circumstances render the overall average outcome pattern inapplicable.
11.4 Addressing uncertainty
In general, it is important that uncertainty is recognised and tackled to avoid common ‘traps’ (Millner-Gulland & Shea, Reference Millner-Gulland and Shea2017). These traps are varied, but include ignoring or not accounting for uncertainty, as well as focusing on irrelevant uncertainties and not clearly stating the objectives in framing problems (Millner-Gulland & Shea, Reference Millner-Gulland and Shea2017). Here I review three case studies, showing that there is a line of argument that ignores uncertainty and another that embraces it. In each case the value of conclusions, both for the scientist and the practitioner, require that uncertainty is fully evaluated.
11.4.1 Ignoring uncertainty should not be an option
One of the most important causes of uncertainty is lack of information. This is particularly an issue when information is lacking on rare and difficult-to-observe species, meaning that clade-wide conservation assessments are potentially compromised. The International Union for Conservation of Nature (IUCN) is an important organisation that collates data on the conservation status of species from a wide range of taxa into a set of threat states (Mace & Lande, Reference Mace and Lande1991). This extensive and important exercise informs conservation strategies in a range of contexts (Rodrigues et al., Reference Rodrigues, Pilgrim and Lamoreux2006). The basis for the assessment is a five-point scale of threat status for wild extant species. Species are classified as Least Concern (LC), Near Threatened (NT), Vulnerable (VU), Endangered (EN) or Critically Endangered (CE). Extinct in the Wild and Extinct are categories of extinction beyond these five points, representing species loss.
The amount of data required to apply these criteria varies between taxa. In some cases the amount of information required is quite low. For example, the Nechisar nightjar (Camprimulgus solala) is classified as VU despite being known from only a single wing and a single sighting. On the other hand, for some groups (e.g. mammals and amphibians) the data requirements for the assignment of conservation status are more exacting. Those species for which sufficient information is not available are assigned a status termed Data Deficient (DD). The number of DD mammal species is a considerable fraction of the group (483 of 4186 species; i.e. >10%) of mammals studied by Jetz and Freckleton (Reference Jetz and Freckleton2015).
Denoting species as DD is, effectively, a way of dealing with uncertainty. It is essentially the same as ignoring missing data in an analysis. This way of dealing with data uncertainty is, however, fraught with pitfalls, and a large literature exists on dealing with missing data and associated uncertainty (Nakagawa & Freckleton, Reference Nakagawa and Freckleton2008). It is well understood that non-randomness in the pattern of ‘missingness’ can yield highly misleading analyses.
In the case of conservation assessments, the concern with DD mammal species is that the factors that drive data deficiency are closely related to those that determine extinction threat. For instance, if species are difficult to observe it is likely to be because they only occur at low density in remote locations, or population trends are unknown because they are so rare. It is easy to see that this set of criteria could lead to species being ignored from conservation assessments even though they are threatened.
Jetz and Freckleton (Reference Jetz and Freckleton2015) tested this hypothesis by applying a framework for phylo-spatial modelling of IUCN threats, then using this to predict the probability that DD species are threatened. Species that are DD are predicted to have much higher threat probabilities than those that have been assessed already (Figure 11.1). The fraction of threatened mammal species is therefore underestimated by the current system of assessment.
Interestingly, the same is not true of birds (Lee & Jetz, Reference Lee and Jetz2011), as a much smaller fraction of them are considered DD because a lower threshold of information is required to assess threat status. Thus, the recent taxonomic explosion that has led to the creation of 1000 new species of birds (del Hoyo et al., Reference del Hoyo, Collar and Christie2014, Reference del Hoyo, Collar and Christie2016) has not resulted in 1000 species being assigned to the DD category.
This example illustrates an important point about uncertainty that is relevant to conservation and management. Ignoring uncertainty by simply excluding cases where data are missing runs the risk of introducing bias and so, in general, should be addressed if at all possible (Millner-Gulland & Shea, Reference Millner-Gulland and Shea2017). In the introduction I noted that the likelihood of implementing an action is low, irrespective of its actual effectiveness, when there is great uncertainty associated with its effectiveness (i.e. the parameter p is low). In this example, data-deficiency data result in no action being taken (p is low because of uncertainty), although the evidence (Figure 11.1) is that the intervention (assigning status of ‘threatened’) is justified with high probability.
11.4.2 Providing more data/evidence
The preceding example highlights that, where possible, additional data should be used to plug gaps in knowledge. One of the ways that scientists tend to qualify conclusions (see Section 11.3.1) is to say that we cannot be confident because more data are required. As argued by Millner-Gulland and Shea (Reference Millner-Gulland and Shea2017), this can prevent effective management-relevant advice being given.
The example from Jetz and Freckleton (Reference Jetz and Freckleton2015) (see also Safi & Pettorelli, Reference Safi and Pettorelli2010; Bland et al., Reference Bland, Orme and Bielby2015) addressed this qualification by extracting as much information as possible out of the existing data using advanced statistical methods. There are a large range of techniques that have been used to infer missing data and it is not possible to review them here, except to point out that suitable methods have been developed (Nakagawa & Freckleton, Reference Nakagawa and Freckleton2008), or that the problem can be dealt with using flexible statistical frameworks, such as Bayesian modelling (Gelman et al., Reference Gelman, Carlin and Stern1995). Another recent application used models to infer the maximal population growth rate of several shark species for which this demographic rate has not been otherwise estimated (e.g. Pardo et al., Reference Pardo, Cooper and Reynolds2018).
In many cases, however, the bottom line is that sufficient data do not exist and there is no option but to collect more. Data are time-consuming and expensive to collect. Engaging in a programme of data collection will delay implementation and use up resources that could be targeted at on-the-ground management. Frequently there will not be resources available for data collection and hence the knowledge gap is never plugged.
On the assumption that more information could be obtained, a key question arises: will collecting more information improve management decisions (Maxwell et al., Reference Maxwell, Rhodes and Runge2015)? Canessa et al. (Reference Canessa, Guillera-Arroita and Lahoz-Monfort2015) highlight a measure called the ‘Value of Information’ (VoI). This measure is the difference in outcome between the expected management action based only on whatever prior information was available, and action taken with new information provided (Yokota & Thompson, Reference Yokota and Thompson2004; Canessa et al., Reference Canessa, Guillera-Arroita and Lahoz-Monfort2015). They provide an example that is typical of many in conservation or land management. Imagine that a species of conservation concern occurs in one location within a protected area. The aim of conservation is to maximise the size of the population in the area over a specified time period. In order to meet this aim, one strategy could be to create a new population. However, imagine further that there is a chance that a disease could be present that would limit the effectiveness of the reintroduction. The VoI in this case reflects the change in estimated effectiveness that would be achieved by testing for the presence of disease before starting the reintroduction programme. Thus, a test might be performed and return a positive or negative result. Given a prior estimate of the prevalence of the disease, the difference between initial and updated estimates can be calculated using Bayesian updating. These differences then measure the VoI provided by conducting testing. This represents the possible improvement in decision-making through the removal of uncertainty.
11.4.3 Addressing uncertainty through benchmarking
A manager might apply a conservation intervention which, if the outcome is positive, leads to a question of whether the intervention should be used again, or even recommended to another manager. Informal communication of outcomes of this sort are not unusual in land management (Henrich, Reference Henrich2001).
From a scientific perspective, this is not an acceptable way of proceeding unless appropriate controls and experimental design are used in the evaluation of the method. Furthermore, the intervention would ideally be evaluated at more than a single site. This reflects, of course, the tension between the situational and general perspectives of practitioners and scientists. There are pitfalls in both views. There is of course, no guarantee that if management appears to work at one site that it is not simply due to natural variation. Figure 11.2a gives an example of this from an agricultural case study. At one site a specific intervention was used and appeared to be successful. However, compared with the outcome on a set of farms that did not use the technique, there is no obviously large effect. On the other hand, if we are too picky about standards of evidence or data then there is a real danger that useful information will be discarded.
Developments such as evidence-based conservation promote the collation of evidence on the effectiveness of management (Sutherland, Reference Sutherland2003; Sutherland et al., Reference Sutherland, Pullin and Dolman2004; see also Chapter 4). The idea here is twofold. First, if the same management has been used in different places then, even if individual interventions do not meet the criteria of a randomised trial (as in Figure 11.2a), the collective body of evidence might be useful. Resources such as www.conservationevidence.com allow this work to be synthesised. Second, using systematic review approaches, it is possible to synthesise this information to provide answers to management problems (Pullin & Stewart, Reference Pullin and Stewart2006; see also Chapter 7).
In the example shown in Figure 11.2a, a single manager implemented one management intervention. On its own this is not enough to determine effectiveness. However, if many people implement the same management then it may be possible to use non-intervention cases as a benchmark and compare the difference with those places where interventions were made. For example, Figures 11.2a and 11.2b show the distribution of weed population sizes in fields subject to intervention (Figure 11.2a) compared with those in which no intervention was made (Figure 11.2b). There is an apparent difference in outcome, but clearly with a high degree of variance. Modelling the data (Figure 11.2c–11.2e) reveals that, although there is an effect of the intervention (Figure 11.2e), there is also a high degree of variance resulting from the initial state (Figure 11.2c) or from the variation in population dynamics from field to field (Figure 11.2d). Consequently, the effect of management, although measurable (Figure 11.2e), is relatively small compared with the intrinsic variability of this system. In this example, the results in Figure 11.2c–e confirm the expectation that the specific management intervention should work, but they also confirm anecdotal local reports that the effectiveness of this approach is patchy, and suggest that frequently the positive effects observed may be attributable to other factors (the large negative effect sizes in Figure 11.2c and d).
Benchmarking of this sort could be extremely valuable in aiding management decisions (Freckleton et al., Reference Freckleton, Hicks and Comont2018). Technological advances, such as widespread instrumentation of agricultural machinery, UAS technology (Paneque-Gálvez et al., Reference Paneque-Gálvez, McCall and Napoletano2014; Lambert et al., Reference Lambert, Hicks and Childs2018) and remote sensing (Kerr & Ostrovsky, Reference Kerr and Ostrovsky2003; Turner et al., Reference Turner, Spector and Gardiner2003) offer the possibility of widescale automated data collection at massive scales. When combined with ecological models, such data could provide a hitherto impossible resource for reducing uncertainty in predicting future management outcomes.
12.1 The natural capital approach
The term natural capital refers to stocks of assets, provided for free by nature which, either directly or indirectly, deliver well-being for humans. Natural capital stocks in turn deliver flows of services, often called ecosystem services, which produce the benefits upon which humans depend. Natural capital assets include stocks of fresh water, fertile soils, clean air and biodiversity. These stocks may be either renewable (e.g. fish populations) or non-renewable (e.g. oil stocks). Both stock types are vital contributors to economic activity and well-being, but can be driven to exhaustion through human action. Economic activity therefore draws and depends upon natural capital, while also affecting the stock of those assets. This intimate relationship between the environment, economy and human well-being has caught the attention of governments internationally. In this chapter, we set out how governments should incorporate the notion of natural capital into policy- and decision-making. We also consider the means by which changes can be best directed to reflect the underlying science of the environment, the incentives of the economy and the preferences of society.
12.1.1 Mainstreaming natural capital: the drivers of change
Mainstreaming natural capital involves bringing nature’s stock and flows of goods and services into decision-making. A key element of this is to provide decision-makers with an understanding of the factors that drive change in natural capital resource use. While analyses generally examine the advantage of moving from current to alternative resource use, they commonly fail to investigate how the move between these two states is to be effected. For example, it is relatively easy to demonstrate that a move from current intensive agricultural production practices to lower-input systems will deliver improvements in water quality, greenhouse gas emissions, wildlife habitat and greenspace access. These advantages are often rigorously demonstrated without guidance as to how such change should be delivered, leaving the decision-maker facing uncertainty regarding how best to act. Such natural capital analyses alone are of little practical value as they do not acknowledge that land-use change is driven by a wide array of socio-economic/market, policy and environmental forces. Understanding the drivers of change, and the consequences brought about by policy decisions, is one of the major reasons for bringing economists into decision-making.
12.1.2 Natural capital, ecosystem services, goods and values
When making policy decisions regarding the natural environment it is important to understand the linkages between the various forms of natural capital, the ecosystem services they provide and their transformation into valued goods and services (Figure 12.1). In the upper left of Figure 12.1 we have the raw inputs to this system: energy (from the sun) and matter (from the earth). Together these yield stocks of physical natural capital and natural processes. Combining these stocks and processes provides the myriad ecosystem service flows provided by the natural environment. However, as shown in the third column, goods are more typically obtained by combining ecosystem service flows with other human-derived forms of capital, such as labour, machinery and technology. Here the term ‘goods’ refers to anything which alters human well-being, ranging from tangible products like timber or food to non-tangibles, such as the positive emotions associated with knowing that biodiversity is being conserved. Similarly, while some of these goods are provided through markets and consequently have prices, others are provided outside markets and lack prices. Nonetheless, all are, by definition, of value.
Because natural capital and ecosystem services can be used to generate a wide variety of goods, it is useful to understand whether those resources could be used in better ways. In effect, we need some measure of the value of a set of goods (Figure 12.1). Many of the goods that contribute to human well-being can be assessed in economic values, and changes in these can be analysed in terms of the resultant benefits and costs. However, a few well-being–bearing goods cannot be robustly assessed in terms of economic value and therefore other, ideally quantitative, measures have to be incorporated into decisions.
In their raw, unused state, natural capital resources have high usefulness and can be employed to generate a wide range of goods, often simultaneously. However, this means that changes to the use of natural capital often generate multiple consequences. The environment is an interconnected system; changing its use in one way can have multiple effects, many of which might not have been anticipated by the decision-maker who prompted that original change (Figure 12.1). To illustrate, afforestation of farmland will typically reduce the amount of food produced. If the analysis is curtailed there, then an investment to convert farmland to woodland might often appear to yield poor value; timber values are long delayed and may well be less than the food value that can be generated over that period. Such restricted analysis is common, especially if food and timber are the only marketed, and hence priced, goods produced by such a change. However, afforestation can affect the production of a wide range of other goods. A shift from agriculture to woodland can often result in an improvement in water quality as forests require much lower inputs of fertiliser than farmland, reducing the run-off of nutrients into waterways, resulting in less-polluted rivers and higher water quality. In very many cases woodlands also reduce emissions of air pollution and store carbon, helping reduce climate change. Similarly, woodlands typically provide much greater recreational benefits than many forms of agriculture. To improve decisions regarding natural capital we need to assess all the major trade-offs arising from a proposed change and ensure that they are valued on a level playing field.
12.1.3 Decisions, trade-offs and valuation
184.108.40.206 Two inescapable facts
1. Human wants (including those with the highest possible motivations such as improving society) exceed the resources available to satisfy them all.
2. Because of these resource constraints, every time we decide to do one thing, we in effect decide not to do another; our decisions implicitly place values on each option.
This means that trade-offs are inevitable and valuations are unavoidable, as they are the essence of decision-making. The only real question is whether we leave those trade-offs and valuations implicit and hidden within a decision, or instead make them explicit and open to scrutiny. Economic analyses of environment-related investments are frequently the focus of criticism precisely because they make their valuations clear. However, failing to reveal valuations does not mean that decisions are being made without values. It merely means those values are being determined in an indistinct way, and are often not obvious even to those involved in the decision process.
220.127.116.11 The challenge of decision-making across integrated systems
Low-entropy (i.e. previously unused or raw) natural capital resources have an amazing diversity of potential uses. The more that capital is used the greater its entropy and the less available it becomes for alternative uses. In some cases this is a simple binary choice (e.g. using a soil resource to grow food often means that it cannot be simultaneously used to produce timber). Nevertheless, the relationship is frequently more complex (e.g. using water for intensive food production does not necessarily mean that it is not subsequently available for drinking, but can mean that it has to be treated before consumption). Any decision that ignores this interconnection and its consequences is clearly flawed, whether it understates or overestimates the net effects, or results in decisions that are wholly deleterious for society.
Unfortunately, such incomplete analyses are commonplace. Some decision-makers may have preconceived notions of what is important and focus upon those consequences rather than the bigger picture. Often this is because the remit of the decision is constrained. So a government department charged with increasing food security may fail to adequately consider the wider environmental and societal impacts of its actions. A classic example is the EU Common Agricultural Policy (CAP) designed to promote food security. While the CAP has been substantially revised and improved in recent years, its early operation focused almost exclusively on boosting the production of food without consideration of the environmental consequences. Indeed, an argument that one objective supersedes all others is a common hallmark of many poor policy decisions. These poor policies impose unjustified and avoidable costs upon society and natural capital, which always have to be addressed in the long term and are better avoided from the outset. The catalogue of policy reversals that characterise the history of the CAP illustrate the unsustainable nature of policies with limited focus (e.g. subsidies for hedgerow removal being superseded by subsidies for their replacement).
Within the private sector, businesses typically focus upon those consequences of investment decisions that improve profits for its owners and shareholders; this, in turn, can result in a focus upon the output of goods that have market-priced values, often at the expense of other non-market, unpriced goods. In our opinion this is not morally reprehensible as, in many legal contexts, the management of a firm is legally obliged to operate in ways that benefit its owners. However, it means that public regulators need to consider policy frameworks that align the profit incentives of businesses with the interests of wider society, including environmental sustainability.
18.104.22.168 The challenge of decision-making across non-commensurate metrics
If decision-makers are interested in the overall impact that changes will have upon society then appraisals need to be comprehensive and consider all of the impacts of an investment; not only the policy focus (e.g. boosting agricultural production) but also all consequent trade-offs (‘externalities’ such as water pollution), be they negative or positive. A substantial challenge is that impacts are often measured using an array of different metrics. For instance, flood control is most obviously assessed in terms of risk per household, drinking water quality in mg/litre of pollutants, greenhouse gases in tonnes of carbon equivalent, recreation as the number of visits, and so on. These measures are typically non-commensurate (how many recreational visits should be given up to sequester an additional tonne of a given greenhouse gas?). Given that the overall objective of natural capital investments is to improve sustainable well-being, then the logical approach is to assess the extent to which each trade-off contributes to well-being (either positively or negatively). But what is the best unit with which to assess changes in well-being? Ideally we would want a pure unit of well-being, or, as economists term it, utility. Unfortunately, this does not exist. Therefore, an alternative is to use a unit that people commonly use to express the well-being they obtain from the gain or loss of a good. This, of course, is not a challenge that is confined to natural capital, and throughout history society has solved the problem of how to exchange different goods through the medium of money.
Using money as a unit of well-being for making commensurate the multiple trade-offs associated with natural capital change has important benefits. A commonly claimed advantage is that decision-makers are familiar with money, yet this general assertion hides a more important truth. If investments are being considered by the public sector, then the government needs to ensure that the limited tax funds at its disposal are allocated wisely, in the way that will maximise well-being. Society needs a robust natural capital base and high-quality environment. However, it also needs a health service, education, transport infrastructure, employment, security, etc., all of which draw upon the finite financial resources available to the government.
This is not to claim that money is the perfect common unit with which to express diverse benefits. Conversion problems abound, but these are even more challenging when other units are used. Indeed, it would be more accurate to argue that money is simply the least-worst common unit available. The long-term failure to assess the benefits of investing in the natural environment in monetary terms has coincided with long-term over-use and degradation of natural capital, as it is seen as a net cost yielding little obvious benefit. Certainly the case for increasing spending on the environment is difficult to make when expressed in diverse and unfamiliar units. Given this, it is hardly surprising that public spending on the environment typically represents a tiny fraction of GDP.
While marketed goods are often valued with reference to their prices, a range of methods have been developed for valuing non-market goods (Freeman et al., Reference Freeman, Herriges and Kling2014; Champ et al., Reference Champ, Boyle and Brown2017). These methods can be broadly divided into three categories:
production function methods, which examine how changes in the environment and ecosystem services affect economic output (e.g. how changes in the climate affect agricultural production; Fezzi & Bateman, Reference Fezzi and Bateman2015);
revealed preference methods, which infer individuals’ preferences and hence values through observing behaviour (e.g. looking at the time/expenditure which visitors spend to reach preferred recreational sites; Herriges & Kling, Reference Herriges and Kling2008);
stated preference methods, which use experiments or surveys to ask respondents to either directly state their willingness to pay for changes, or to choose between alternative outcomes with differing costs (e.g. examining choices between different levels of water bill according to the quality of river water they offer; Metcalfe et al., Reference Metcalfe, Baker and Andrews2012).
Non-market valuation methods are important tools in the estimation of the multiple values that can arise from changes to natural capital. For example, impacts on recreation can be valued by looking at choices made by visitors across sites and relating these to the costs they incur to visit those sites (Herriges & Kling, Reference Herriges and Kling2008). If changes in recreational access can be shown to affect visitors’ health or life expectancy, then this can be valued by examining people’s willingness to pay for changes in health risk (Krupnick et al., Reference Krupnick, Alberini and Cropper2002). Alternatively, estimates of health costs can be obtained either by looking at impacts on production (Murphy & Topel, Reference Murphy and Topel2006), or the avoided costs of illness (Tarricone, Reference Tarricone2006). It is worth noting that these are social values, as reflected in individual behaviour, not the values postulated by economic experts.
22.214.171.124 Assessing impacts on biodiversity
While the majority of environmental costs and benefits can be robustly assessed using economic values, the valuation of biodiversity impacts is challenging. Certain aspects of biodiversity value can defensibly be estimated in economic terms (Hanley et al., Reference Hanley, Breeze and Ellis2015; Pascual et al., Reference Pascual, Balvanera and Díaz2017). For example, provided that we have a clear understanding of the relationships between wild species, plant pollination and crop production, the monetisation of changes in output via crop market prices is relatively trivial (Losey & Vaughan, Reference Losey and Vaughan2006; Melathopoulos et al., Reference Melathopoulos, Cutler and Tyedmers2015; Breeze et al., Reference Breeze, Gallai and Garibaldi2016). Similarly, we can look at the increase in recreation values generated by biodiversity by examining how much further, or how often, people are prepared to travel for experiences such as viewing rare birds or hunting (USNCR, 1999; Kolstoe & Cameron, Reference Kolstoe and Cameron2017). Nonetheless, it is also well established that biodiversity generates non-use value (e.g. from the knowledge that wild species continue to exist and will be bequeathed to future generations) (Kotchen & Reiling, Reference Kotchen and Reiling2000; Diafas et al., Reference Diafas, Barkmann and Mburu2017). The lack of output effects or observable human behaviour in such cases means that production function and revealed preference methods are not applicable. Arguably they may be inferred by examining direct payments for conserving wild species through donations, memberships of conservation groups and legacies (Pearce, Reference Pearce2007; Simpson, Reference Simpson2007; Atkinson et al., Reference Atkinson, Bateman and Mourato2012). However, such approaches will at best provide poor underestimates of true value (an expectation confirmed by the low values reported by such analyses), well out of synch with other measures of biodiversity conservation concern.
In theory, the non-use values associated with biodiversity can be directly estimated using stated preference methods, such as contingent valuation or choice experiments (Hanley et al., Reference Hanley, MacMillan and Patterson2003; Christie et al., Reference Christie, Warren and Hanley2004; Morse-Jones et al., Reference Morse-Jones, Bateman and Kontoleon2012). In practice, these exercises face a number of challenges. One problem is that many studies have found the general public to have ‘low awareness and poor understanding’ of what biodiversity means (Christie et al., Reference Christie, Hanley and Warren2006, p. 305). Communicating such information to survey respondents is difficult as it can alter preferences and values, making them no longer representative of the social values researchers are seeking to estimate (Samples et al., Reference Samples, Dixon and Gowen1986). Furthermore, studies seeking to estimate conservation values often cannot use scenarios in which the respondents are forced to make payments (unlike water bills as ‘payment vehicles’ for delivering changes in water quality).
So, how do we ensure that preferences regarding non-monetised values are not ignored? Fortunately, in the case of biodiversity we have plenty of other evidence regarding preferences that we can bring into play. For example, the most recent UK Public attitudes and behaviours towards the environment survey (National Statistics, 2009) revealed that 91% of respondents agreed that ‘there are many natural places that I may never visit but I am glad they exist’, while 85% agreed that ‘I do worry about the loss of species of animals and plants in the world’. This provides us with a simple yet effective way of incorporating this preference information into decision analyses, by simply requiring that any potential change to natural capital should avoid the loss of, or enhance, biodiversity. Furthermore, alongside its direct use and non-use value, biodiversity supports a variety of ecosystem service–related benefits, most of which may be too complex and poorly understood to be adequately captured in an assessment (Turner & Daily, Reference Turner and Daily2008; Mace, Reference Mace2014; Mace et al., Reference Mace, Hails and Cryle2015; Bolt et al., Reference Bolt, Cranston and Maddox2016). A precautionary, standards-based approach should therefore be taken (Bateman et al., Reference Bateman, Mace and Fezzi2011a; Harper, Reference Harper2017). Indeed, legislative support for stricter requirements being placed upon investments is evidenced in the UK Government’s 25 Year Environment Plan, which sets out the principle of net environmental gain associated with new development of land (HM Government, 2018). For simplicity, however, we adopt a no-loss constraint in this chapter, confining ourselves to proving the point that biodiversity can be defensibly integrated into a natural capital decision-making approach without having to resort to dubious estimates of the economic value of the non-use benefits it provides.
12.1.4 Payment mechanisms: uniting payers and providers of ecosystem services
As part of any investment analysis, consideration needs to be given to who will provide and fund a given natural capital change, with the ‘payment mechanism’ being an important element of the appraisal process (Table 12.1). The provision of non-market environmental goods is most commonly funded by the public sector, while the private sector provides the goods (e.g. farmers subsidised to provide conservation services). A common challenge for public funding schemes is that subsidies are often allocated as untargeted flat-rate payments across all locations, whereas the provision of biodiversity and ecosystem services varies spatially. While such an approach is easy to administer, it is highly inefficient. By combining environmental modelling and economic valuation, interventions can be targeted to where they will yield greater benefits. This ensures that funders, ultimately tax payers, receive better value for money. It also means that the same level of resource generates enhanced environmental outcomes. Further improvements in the efficiency and impact of funding can be delivered through the use of ‘natural capital markets’ to allocate support payments. By creating competitive market structures (so-called ‘reverse auction’ markets; Elliott et al., Reference Elliott, Day and Jones2015; Fooks et al., Reference Fooks, Messer and Duke2015) which induce competition between ecosystem service providers, the incentive for private firms to over-charge for their actions is reduced.
|Provider (of goods)|
|Private sector||Public sector|
|Payer (for goods)||Private sector||Payments for ecosystem services; profitable environmental improvements||Corporate social responsibility projects|
|Public sector||Payments for ecosystem services; subsidies to businesses||Taxation-funded public provision|
Of course, from a public-sector perspective, these mechanisms are further enhanced if the private sector finances these initiatives. Corporate social responsibility investments now represent a substantial source of private-sector funding for environment projects involving major multinational corporates. For example, since 2012 Microsoft’s global operations have been completely carbon-neutral (Microsoft Corp., 2017), an initiative recently taken up by Google (Google, 2016; Hölzle, Reference Hölzle2016). While such investments clearly represent short-term costs to such companies, the social and reputational benefits generated by environmental improvements may well raise sales, generate price premiums and hence improve profits (e.g. Bateman et al., 2015). Moving more in the direction of conventional profit-bearing activities, many companies invest in areas that overtly yield a mix of both private and public benefits. For example, Häagen-Dazs (2017) has invested substantially in approaches to sustain honeybee populations, recognising that they are of considerable non-use value to society, as well as being vital to the ingredients supply chain of the ice cream manufacturer. Combining these activities with competitive Payments for Ecosystem Service markets allow companies to achieve cost reductions or revenue increases at minimum cost, thereby maximising the profitability of such actions (Day et al., Reference Day, Couldrick and Welters2013; Bateman et al., Reference Bateman, Binner, Day, Daily, Mandle and Salzman2018).
12.1.5 Spatial scaling and targeting
From a pure natural science perspective it can be argued that there is no single perfect scale for decision-making involving an ecological system. This situation is further complicated by intersecting administrative jurisdictions and boundaries defined by the geographical extent of the economic benefits generated by ecosystem services (Bateman et al., Reference Bateman, Day and Georgiou2006). We have to recognise these boundaries, overlaps and conflicts when making decisions to delineate the spatial scale that is most suitable for the investment. As highlighted above, a further spatial issue concerns the degree to which policies are untargeted, effectively ignoring the natural variation in the environment. These challenges have to be acknowledged and incorporated within decision-making systems if we are to achieve the levels of value for money that limited public funding requires. In particular, the tendency towards simplistic administrative methods has to be resisted. What appears to be financially cheap can often be economically very expensive in terms of the high opportunity costs and poor value for money delivered.
12.2 Analysis for natural capital decision-making: a national-level case study
The Millennium Ecosystem Assessment (2005) highlighted global ecosystem service degradation and urged action at all governmental levels to address this problem. The first major national level response to this challenge was provided by the UK through its National Ecosystem Assessment (NEA). The NEA sought to assess the consequences of natural capital use and land-use change, and showed that over 30% of the services provided by the UK’s natural environment are in decline.
The data provided by the NEA (UK NEA, 2011) formed the basis of the models used in the assessment outlined in this case study (Bateman et al., Reference Bateman, Abson and Andrews2011b, Reference Bateman, Harwood and Mace2013, Reference Bateman, Agarwala and Binner2016). A wide range of highly detailed, spatially referenced, environmental data covering all of Great Britain were collected, ranging from soil characteristics (e.g. susceptibility to water logging), climate variables (e.g. temperature, rainfall) and land use (e.g. agricultural output) (Figure 12.2). This was complimented by similar spatially and temporally referenced data on market variables (e.g. prices, costs) and policy (e.g. subsidies, regulations such as land-use constraints). The analysis linked environmental, economic and policy factors to examine both the market and non-market consequences and values generated by land use and changes thereto. The spatial nature of these analyses also demonstrated how future policy can be targeted to most efficiently allocate available resources to maximise their net benefits.
Each analysis began from an econometric model of the environmental, economic and policy drivers of land-use (Fezzi & Bateman, Reference Fezzi and Bateman2011). This model drew upon long-term (~50 year) and high-resolution (2 × 2 km grid square or finer) national-scale data sets. The NEA set out to consider six policy scenarios (UK NEA, 2011; Bateman et al., Reference Bateman, Harwood and Mace2013), each of which integrated both high and low future greenhouse gas (GHG) emission trends (Fezzi et al., Reference Fezzi, Bateman and Askew2014). Each predicted land use served as the base data, inputting to a series of interlinked ecosystem service impact and economic valuation models detailing the delivery of food production, emission and sequestration of greenhouse gases (including CO2, CH4 and N2O), expected numbers of open-access recreational visits, levels of urban greenspace amenity and biodiversity metrics (Abson et al., Reference Abson, Termansen and Pascual2014; Bateman et al., Reference Bateman, Harwood and Abson2014; Fezzi et al., Reference Fezzi, Bateman and Askew2014; Perino et al., Reference Perino, Andrews and Kontoleon2014; Sen et al., Reference Sen, Harwood and Bateman2014).
12.2.2 Land-use–derived ecosystem services and their economic valuation
Food output provided the key, market-valued ecosystem service, determining approximately 75% of land use in the UK, including cropland, grassland, mountain, moor and heathland environments (Bateman et al., Reference Bateman, Harwood and Mace2013).
GHG sequestration had a non-market value. The quantity of GHG emission/storage associated with land was determined by the use and management of that land (e.g. cattle stocking density of cattle, other major methane producers, machinery emissions), annual flows of soil carbon due and accumulation/emission of carbon dioxide via terrestrial vegetative biomass. GHG values can be obtained through various routes, including estimates of the expected damage of climate change, the cost of abating emissions and the values of carbon traded in emission markets (Abson et al., Reference Abson, Termansen and Pascual2014).
Open-access recreational visits had a non-market value that varied across environments (e.g. mountains, coasts, forests, urban greenspaces) and location (Sen et al., Reference Sen, Harwood and Bateman2014).
Urban greenspace had a non-market value reflecting aesthetic, physical and mental health, neighbourhood, noise regulation and air pollution reduction benefits (Perino et al., Reference Perino, Andrews and Kontoleon2014).
Wild bird species diversity was used to represent biodiversity, because these species are high in the food chain and are often considered to be good indicators of wider ecosystem health (Gregory et al., Reference Gregory, van Strien and Voríšek2005). As discussed previously, current estimates of biodiversity values and, in particular, pure non-use existence values are insufficiently robust. Following the reasoning set out above, we imposed a ‘no-loss’ constraint on biodiversity as a consequence of land-use change (Bateman et al., Reference Bateman, Harwood and Mace2013).
12.2.3 Identification of the beneficiaries
The same change can yield very differing consequences to different groups of people. So we considered both the market and non-market net benefits to farmers, foresters, recreationalists, wildlife enthusiasts, etc. This allows the decision-maker to comparatively assess the scenarios and understand which provides the best value for money to society (both nationally and globally). Here, we ignore these distributional issues (but see Bateman et al., Reference Bateman, Abson and Andrews2011b; Perino et al., Reference Perino, Andrews and Kontoleon2014) and focus upon the overall benefits to society. The major beneficiaries of alternative land-uses included the following.
Farmers: the latitude and generally colder climate of the UK means that temperature rises are likely to result in farmers increasing their profits and intensive arable production in areas that are not liable to drought (Fezzi et al., Reference Fezzi, Bateman and Askew2014; Fezzi & Bateman, Reference Fezzi and Bateman2015). However, in turn, this will probably negatively impact upon water quality due to nutrient pollution (Fezzi et al., Reference Fezzi, Harwood, Lovett and Bateman2015). Lower river water quality will also impact negatively upon freshwater biodiversity and river-related recreational values (Bateman et al., Reference Bateman, Agarwala and Binner2016).
Recreationalists: open-access recreational sites benefit individuals who visit them, with the net benefit declining as distance from an individual’s home or outset point grows.
Urban residents: urban greenspace value is reflected in local property and rental value, with the value generally decaying as distance increases (Day et al., Reference Day, Bateman and Lake2007; Andrews et al., Reference Andrews, Ferrini and Bateman2017). Increasing access to urban greenspace typically generates significant aggregate social benefits. However, the distribution of benefits can be uneven and result in gentrification, which has the potential to push poorer families out to less-advantaged areas. Recently developed techniques such as Equilibrium Sorting Analyses seek to capture this effect and bring it into decision-making (Binner & Day, Reference Binner and Day2015).
Biodiversity beneficiaries: improvements in species diversity not only benefit the species being directly or indirectly (e.g. through food chains) conserved, but people who value such improvements through use (e.g. hunter, fisherman, wildlife watchers) or non-use (existence values). Biodiversity also indirectly delivers value through roles in ecosystem functioning and service provision.
12.2.4 Analysing trade-offs across alternative land-use scenarios
For simplicity, we considered the two most extreme policy scenarios in this chapter. The World Markets scenario prioritises economic growth by completely liberalising trade, removing tariffs and trade barriers and ending agricultural subsidies; as a result, farming moved towards large-scale, intensive production methods. By contrast, the Nature@Work scenario priority is to adapt to climate change and enhance ecosystem service provision.
While considering market goods alone and ignoring non-market impacts captures only a single dimension of impact, the World Markets scenario indicated values which are frequently given primacy in policy decisions. This scenario saw agricultural value increase £1.03 billion per annum because of a shift towards more intensive production (Table 12.2). Conversely, the Nature@Work scenario led to agricultural values declining by £0.13 billion per annum as farmland was converted to urban-fringe and recreational greenspace. So, if we restricted our analysis to market-priced goods alone, then the World Markets scenario almost always appeared justified. This conclusion was unaffected by varying the degree of climate change across our analysis (Bateman et al., Reference Bateman, Mace and Fezzi2011a, p. 1268).
|Scenario||Market agricultural output values||Non-market GHG emissions||Non-market recreation||Non-market urban greenspace||Total monetised values||Biodiversity|
However, when we extended our assessment to consider the impacts of land-use change upon non-market goods, we find that the Nature@Work scenario consistently yielded preferable outcomes (Table 12.2). GHG emission values in the World Markets scenario were negative in nearly all areas. In contrast, under the Nature@Work scenario, most areas saw benefits in terms of increased carbon storage; the exceptions were upland areas dominated by fragile peatlands which were vulnerable to both agricultural intensification in the World Markets scenario and increasing forestry in the Nature@Work scenario. The World Markets scenario saw losses in visitor values in almost all areas across the country, while the Nature@Work scenario led to recreational benefits over the large majority of the country. Similar results were seen for urban greenspace values. Our biodiversity metric clearly shows that the World Markets scenario resulted in major declines across large swathes of the country. In comparison, the Nature@Work scenario generated improvements across the lowlands (and, therefore, much of the UK), although the picture in the uplands was more mixed, with insignificant or weakly negative effects. This suggests that an optimal solution would combine elements of multiple policies.
In summary, the World Markets scenario increased the production of marketed agricultural output at the cost of significant declines in all other ecosystem services, which strongly outweighed the value of agricultural gains. It therefore lowered overall social value very substantially. In contrast, the Nature@Work scenario reversed this pattern, causing a relatively modest reduction in agricultural production in return for very substantial increases in all other non-market ecosystem service–related goods, and a correspondingly major increase in overall social value. This disparity was further reinforced when we considered the non-monetised biodiversity measures. If we applied our constraint that any decision that would lower biodiversity in an area is ruled ineligible then, at a national level, the World Markets scenario was unacceptable. A spatially targeted optimisation approach could avoid biodiversity losses in local areas and further enhance decision-making.
12.2.5 Policy implications
The UK Government responded quickly and positively to the challenge of the National Ecosystem Assessment, adopting an overarching policy goal to be ‘the first generation to leave the natural environment in a better state than it inherited’ (HM Government, 2011, 2018; House of Commons, 2012). As part of this ambition, the UK has invested in research seeking to develop a ‘natural capital approach’ to decision-making, which explicitly recognises the dependence of economic value and well-being on the natural capital stocks provided by the environment and the ecosystem service flows which those assets provide. To help guide this process, the 2011 Natural Environment White Paper (HM Government, 2011) set up the world’s first independent Natural Capital Committee (NCC) to advise on the restoration and improvement of natural capital as a means of sustaining and enhancing economic growth in the UK (Defra, 2012; NCC, 2013). Importantly, while it has a close relationship with the UK’s environmental department, the NCC actually reports to the country’s finance ministry. Indeed, the UK’s Chief Finance Minister, the Chancellor of the Exchequer, chairs the Economic Affairs Committee (EAC, 2017), which the NCC formally advises (NCC, 2017a).
The NCC has reported extensively on methods to ‘mainstream’ natural capital considerations into both policy and business decision-making (NCC, 2017a, 2017b). Furthermore, it has also provided extensive advice on the valuation, accounting and financing of natural capital enhancement (NCC, 2017a, 2017c). Additionally, the NCC proposed and advised on a 25-year plan for the natural environment, focusing upon the need to ensure sustainable flows of ecosystem services from the UK’s natural capital (NCC, 2015, 2017d), a recommendation which was then adopted by all of the major UK political parties and government (HM Government, 2018). This places the natural capital approach at the heart of decision- and policy-making over both the short and long term.
The authors are grateful to the Editors for their superb input to this chapter. Support for the work was provided by the consortium of funders underpinning the UK-NEA and the NERC SWEEP programme
Governments internationally have long aspired to ground policy in rigorous evidence. Without evidence, policy-makers must rely on intuition, ideology, conventional wisdom or, at best, theory (Banks, Reference Banks2009). Their evidence requirements span the physical, natural and social sciences. Policy issues in environment, natural resource management and biosecurity, in which risk and uncertainty are inherent, are prime examples. The UK government’s White Paper on Modernising Government (1999) pledged to improve the use of evidence and research to better understand policy problems (Blair & Cunningham, Reference Blair and Cunningham1999). Over the past three decades, the UK government has promoted evidence-based over ideologically driven policy (Banks, Reference Banks2009). Likewise, the Australian government’s 2012 Blueprint for Reform recommended strengthening relationships with academia to enhance strategic policy capabilities and drive innovation (Department of the Prime Minister and Cabinet, 2010). Such relationships help ensure that the government’s significant investment in science, research and innovation is harnessed to engage with contemporary policy challenges (DIISRTE, 2012).
There has been much consideration of how scientists and government policy-makers interact and of the impediments to effective communication between science and policy. Organisational structures and social norms may impede the incorporation of science into policy development, as may the different timeframes over which science and policy are developed (Burgman, Reference Burgman2015a). Governments and researchers use different approaches to improve the delivery of policy-relevant science and to enhance the likelihood that science will contribute directly to policy decisions. The working model that is used depends on different factors, such as the degree of willingness to incorporate science into policy-making, the strength of existing relationships and available funding. This chapter first outlines the factors influencing science–policy relationships and then presents possible ways for scientists and policy-makers to work together. We introduce an innovative model of research collaboration that has had practical impacts on policy in Australia. In conclusion, we reflect on the implications of these innovations for interactions between science and government elsewhere.
13.2 The science–policy interface – how well does it work?
Government policy-makers and applied scientists frequently share the aspiration that science should contribute directly to policy decisions. Despite this, significant gaps can remain between the kinds of information that scientists provide and the kinds of inputs that government policy-makers find useful. The reasons for this can depend on culture, context and values, or on the relationships between individual scientists and policy-makers.
Different workplace cultures can impede the adoption of science in policy. Scientists are not always policy-literate and can fail to understand the complexity of the policy environment. This may include the wide range of inputs required, the interactions with other policies, the intensive scrutiny to which new policy proposals are exposed and the fact that policies are not made in isolation but are typically built on existing policy positions (Tyler, Reference Tyler2013; see also Chapter 2). The context in which policy-makers propose solutions to challenging problems is complex and characterised typically by competing, and at times conflicting, objectives among diverse stakeholders. The task of the policy-maker is to balance these objectives while being guided by political mandates and the public good. In these circumstances, policy-makers may appear to disregard scientific advice for reasons that scientists might support if they were privy to the full context of the decisions. For example, a solution that is suboptimal from a single scientific perspective may be the only tenable outcome in the short term and may contribute to a more ambitious policy objective in the longer term (Burgman, Reference Burgman2015a). Similarly, policy-makers often lack the skills to interpret science effectively and rigorously for their purpose, including understanding the quality, limitations and biases of evidence (Sutherland et al., Reference Sutherland, Spiegelhalter and Burgman2013). These impediments are compounded when there is insufficient incentive for scientists and policy-makers to collaborate.
Policy-making is rarely an entirely objective process that leads to a single rational outcome. Decisions in complex situations involve both facts and values. Facts are not always certain and can be influenced by values, perceptions and emotions (Slovic, Reference Slovic1999; Burgman, Reference Burgman2015b). There is no single right way of assessing values (Gregory et al., Reference Gregory, Failing and Harstone2012). Nor are scientists entirely objective and independent (Krinitzsky, Reference Krinitzsky1993; O’Brien, Reference O’Brien2000). Lack of objectivity can sometimes lead to situations in which scientific expertise is used deliberately and strategically to support a particular policy outcome. This can be especially strident where issues are emotionally or politically charged – the science of global climate change is a contemporary example (Burgman, Reference Burgman2015a). In most practical situations, the pool of scientific experts on which policy-makers can call is small and composed of people with differing values and partially overlapping experiences (French, Reference French2012). In these circumstances, conventional science can help to clarify what might be lost or gained as a consequence of a policy decision, but can offer little to evaluate differences of opinion and the trade-offs that are often necessary to make a decision. Decision theory (French, Reference French2012; Gregory et al., Reference Gregory, Failing and Harstone2012) can provide a platform for structuring problems, engaging stakeholders, assessing alternatives and finding a solution that best achieves the aspirations of government.
The rewards systems in governments and academia are also frequently incompatible. The determinants of academic advancement are commonly skewed towards publication records, although there is a growing emphasis on the importance of practical research impact. Indeed, all major international university ranking systems now include a measure of research impact. Unfettered academic publication can be impeded by the policy-making process, in which control over the flow of information may be necessary to manage policy change among diverse stakeholders (Burgman, Reference Burgman2015a). Conversely, most government institutions do not readily reward involvement of their staff in what may be considered speculative scientific research.
The timeframes over which science and policy are developed can also be a barrier for the effective use of science in policy-making. Policy-makers can be unaware of and unable to absorb scientific evidence or emerging scientific methods in the short time horizons that are often imposed on policy development. Conversely, the development of good science can be a lengthy process that lags behind the response times required by new policy challenges. In other circumstances, where relevant science already exists, scientists can underestimate the time that it takes to implement policy change, including the time taken to evaluate the social, economic and political implications of potential change.
Limited access to data and research outputs may impede policy-makers’ use of scientific evidence. This can be a simple communication issue, because it is not straightforward to write and disseminate research findings in a way that can be readily interpreted and applied by the policy community. More problematically, policy-makers may look to scientists to provide certainty. Scientists may be motivated not to disclose the full weight of uncertainty in their assumptions and results, or may be unaware of it, or not know how to communicate it to policy-makers (Sutherland et al., Reference Sutherland, Spiegelhalter and Burgman2013). This low accessibility creates an imperative for policy-makers to understand the limitations and the context of the scientists themselves, and to cross-examine their evidence.
Useful and ‘usable’ science most often arises when researchers and policy-makers work closely together to iterate through problem formulation and solutions (Dilling & Lemos, Reference Dilling and Lemos2011; Burgman Reference Burgman2015a; Chapter 10). In many cases, science contributes to public policy effectively because researchers and government policy-makers have developed personal relationships (Gibbons et al., Reference Gibbons, Zammit and Youngentob2008). In these instances, the ‘literacy’ barrier on both sides is reduced. However, roles and responsibilities can change frequently, especially in government, and can undermine the time taken to establish effective personal relationships (Burgman, Reference Burgman2015a). It is rare that informed personal relationships will consistently overcome all of the substantial barriers to the effective use of scientific evidence in policy-making.
13.3 Ways of working with government
Issues related to context, values, culture, timeframes, communication and relationships can thwart the effective use of science in policy. Participants attempt to bridge the gap between science and policy, using a range of ways of working together (Table 13.1). Here, we discuss models for science–policy interactions along a spectrum of time investment and complexity. This is not a complete list, and concepts and strategies for improving the effectiveness of partnerships evolve over time. Corroborating the dynamic nature of these elements, a recent survey indicated that Canadian scientists’ and policy-makers’ ideal way of working in the future would involve collaborative study design and analysis, indicating a shift of focus from knowledge dissemination to knowledge generation (Choi et al., Reference Choi, Liping and Yaogui2016).
|Policy briefs||A short but comprehensive analysis and discussion of a high-priority issue including solution statements and implementation considerations|
|Science–policy forums||A networking event allowing policy dialogue. Researchers and policy-makers present research findings and policy requirements in an interactive knowledge-sharing setting|
|Training courses, exchange programmes and job-shadowing||Theoretical or practical learning settings that aim to convey to scientists and policy-makers a better understanding of the content and the circumstances in which science and policy operate|
|Knowledge brokers||Intermediaries who facilitate interactions between scientists and end users but remain impartial to the decision-making process|
|Informal working groups||Ad-hoc arrangements where scientists and policy-makers collaboratively address a policy problem|
|National funding schemes||Funding schemes that explicitly support research with strong links to the objectives of other organisations such as government, industry and business|
|Shared governance model (coproduction)||Government-funded research centres where the development of research priorities and achievement of outcomes is shared between policy-makers and scientists|
13.3.1 Policy briefs
At one end of the spectrum, strategies include one-off events or communication products. For example, policy briefs are succinct documents that address a single policy issue of high interest to policy-makers. The analysis of a priority policy problem is context-specific, incorporates solutions and implementation considerations and is usually completed within days (Lavis et al., Reference Lavis, Permanand and Oxman2009a). Policy briefs are an acknowledged method for disseminating knowledge to policy-makers and are often used in the health and social sciences sectors (Lavis et al., Reference Lavis, Boyko and Oxman2009b; Rajic et al., Reference Rajic, Young and McEwen2013; Balian et al., Reference Balian, Drius and Eggermont2016). The Food and Agriculture Organization of the United Nations adopted policy briefs to disseminate information about agricultural development issues to the general public. However, the impact of policy briefs depends on the reader. Experts are less likely to change their opinion after reading a brief than non-experts (Masset et al., Reference Masset, Gaarder and Beynon2013).
13.3.2 Science–policy forums
A science–policy forum, or policy dialogue, brings stakeholders and scientists together. In contrast to policy briefs, policy dialogues may concentrate on actions in response to research evidence. The main aim of this tool is to facilitate discussion (Lavis et al., Reference Lavis, Boyko and Oxman2009b). Policy dialogues can be time-intensive to plan and organise but provide an opportunity to hear about experiences from a diversity of stakeholders. They may establish and cultivate ongoing personal relationships between decision-makers and researchers (Boydell et al., Reference Boydell, Dew and Hodgins2017). Deliberate engagement techniques, such as policy dialogues, can generate confidence among participants that their inputs will guide policy development (Gregory et al., Reference Gregory, Hartz-Karp and Watson2008).
13.3.3 Training courses, exchange programmes and job-shadowing
Training courses for researchers and policy-makers may support translation skills, communication and networking skills or understanding of subject matter or of government processes, so individuals can communicate more effectively with their counterparts (Young et al., Reference Young, Waylen and Sarkki2014). Exchange programmes such as secondments are a useful way for scientists to learn how to translate their knowledge to generate benefits in the specific decision-making contexts in which policy-makers work. They can also catalyse new relationships (Gibbons et al., Reference Gibbons, Zammit and Youngentob2008). The National Environmental Research Program in Australia 2010–2015 aimed, in part, to enhance mutual understanding by offering short-term secondments for researchers into policy settings (DIISRTE, 2012). Job-shadowing, in which individuals accompany high-level policy-makers in their daily professional interactions, is also valuable for improving understanding of the realities of decision-making (Young et al., Reference Young, Waylen and Sarkki2014).
13.3.4 Knowledge brokers
One outcome of theoretical or practical learning may be the emergence of so-called knowledge brokers, individuals or groups that facilitate interactions and knowledge transfer between researchers and end users (Rajic et al., Reference Rajic, Young and McEwen2013) by understanding and serving the needs of both. However, the effectiveness of such arrangements is not often evaluated (Ward et al., Reference Ward, House and Hamer2009; Meagher & Lyall, Reference Meagher and Lyall2013).
13.3.5 Informal working groups
When scientists and policy-makers have established relationships, they may create ad-hoc working groups to address public policy issues (Burgman, Reference Burgman2015a). If participants define problems and outputs well, and consider incentives for both parties, then working groups offer shared responsibility for objectives and the prospect of effective outcomes for policy needs (Gibbons et al., Reference Gibbons, Zammit and Youngentob2008). Working groups have the potential to grow into longer term arrangements. For example, in the USA, the ad-hoc formation of a working group of waterfowl managers and biologists from federal and state agencies led to the development of a now long-running programme based on adaptive resource management principles (Nichols et al., Reference Nichols, Johnson and Williams2015).
13.3.6 National funding schemes
National funding schemes can aim to bring scientists and policy-makers closer together by creating policy-relevant incentives for research institutions. The Australian Research Council (ARC) linkage funding scheme, for example, encourages the development of partnerships between science and government, business, industry and community organisations. ARC has also created Centres of Excellence, consisting of long-term collaborations between eligible higher education organisations and partner businesses and agencies. They focus on priority research that is identified by the Australian Government, and operate within clearly articulated governance structures (ARC, 2018). The Australian Cooperative Research Centres Association programme was established in 1990 to bring large groups of researchers in the public and private sectors together with end users (CRCA, 2018). The role of the end users is to help plan the direction of the research and monitor its progress (Burgman, Reference Burgman2015a; CRCA, 2018).
In the UK, from the early 1900s, the Haldane Principle guided government investment in research based on the philosophy that decisions about research priorities should be made by researchers. In 1972, this was replaced by the Customer Contractor Principle, which introduced a market-orientated approach to government support for research (Kogan et al., Reference Kogan, Henkel and Hanney2006; Daniels et al., Reference Daniels, Spector, Goetz, Weber and Duderstadt2014). The 2014 UK Research Excellence Framework (HEFCE, 2018) guided national research investment in universities and used impact to assess the benefits of research beyond academia (Greenhalgh & Fahy, Reference Greenhalgh and Fahy2015). Similarly, in the USA, the Office of Productivity, Technology & Innovation was created in the Department of Commerce in 1981 to advocate Research and Development Limited Partnerships at universities to accelerate the transfer and private appropriation (through patents) of federally funded technology. The US National Science Foundation now considers the benefits for society of scientist’s discoveries when allocating funding (Wiley, Reference Wiley2014; N. Voulvoulis & M. Burgman, unpublished data).
13.3.7 Shared governance
Long-term arrangements, such as Centres of Excellence and Research and Development Limited Partnerships, focus on joint research priorities. However, research centres operating under a model of shared governance go a step further. In the shared governance model, scientists and policy-makers co-develop and co-manage research priorities, business cases and project plans, and the delivery of research outcomes. Shared governance, also referred to as ‘co-production’, between scientists and policy-makers is possible when partners ‘have sufficient trust, willingness and institutional room to manoeuvre to share information and decision-making power’ (Van Kerkhoff & Lebel, Reference Van Kerkhoff and Lebel2015). This model encourages the formation of research–policy partnerships built on strong personal relationships (Gibbons et al., Reference Gibbons, Zammit and Youngentob2008) and has the potential to overcome many of the issues limiting the effective use of science in policy. The Centre of Excellence for Biosecurity Risk Analysis (CEBRA) is one example (Burgman, Reference Burgman2015a).
13.4 The Centre of Excellence for Biosecurity Risk Analysis – a collaborative approach to bring science to policy
In the biosecurity domain, CEBRA and its predecessor, the Australian Centre of Excellence for Risk Analysis (ACERA), are examples of governance arrangements that encourage close science–government interaction. ACERA was established in 2006 to develop state-of-the-art methods (tools, guidelines, procedures) to enhance risk analysis in the Australian Government. It was a collaborative agreement between the Australian Government Department of Agriculture and Water Resources and the University of Melbourne. In 2014 the partnership expanded to include New Zealand’s Ministry for Primary Industries and sharpened its focus on biosecurity risk, continuing under the new name of CEBRA. The two governments provide the majority of the financial resources to operate the centre and have signed a research agreement with the university provider.
CEBRA’s governance arrangements and operational practices include a number of features that have evolved to avoid or overcome some of the most pervasive impediments to effective communication between scientists and policy-makers. They aim to maximise the likelihood that CEBRA’s research outputs will generate pragmatic policy outcomes. A key characteristic of the governance model is shared responsibility for the development of research themes, priorities and the delivery of outcomes.
In CEBRA, policy-makers identify research themes, ideas and priorities on an annual basis, under the guidance of a steering committee that comprises senior executives of both the Australian and New Zealand governments, and considering other biosecurity research efforts in which the governments participate. CEBRA researchers and their government counterparts then collaborate to develop the prioritised research ideas into detailed project descriptions and budgets, including implementation plans. The final set of projects to be undertaken depends on the priority list and the available budget. Both the Australian and New Zealand governments have prioritised some multi-year projects that contribute to important strategic objectives. The balance between applied and more speculative research is achieved by earmarking 20% of the budget for ‘blue-sky’ research, focusing on topics that are relevant to CEBRA’s mission but that may not solve the most immediately pressing policy questions.
Shared responsibility between researchers and policy-makers extends to meeting milestones and generating deliverables. On each project, a research leader from CEBRA is teamed with a project manager from government who provides research and administrative support. In addition, a senior government executive sponsors each project and champions its delivery through government, including, where necessary, facilitating acquisition of relevant data and allocating staff time and other resources. CEBRA is responsible for finding experts to deliver the research projects, either from its own staff or in collaboration with researchers from other institutions. A science advisory committee provides assurance of the scientific integrity of project proposals and the scientific quality of research outputs, overseeing peer review and encouraging publication of results. It comprises independent and appropriately experienced scientists, who assess scientific integrity and quality using a process comparable to the peer-review process of international journals. The centre’s strategic direction and governance arrangements are overseen by an independent advisory board, comprising university, government and independent members, under an independent chair.
CEBRA’s experience has been that the close working relationships fostered between researchers and policy-makers under this model benefit the delivery of pragmatic research outcomes and increase the likelihood that research findings will be implemented. Somewhat unexpectedly, the policy demands of government led to the development of research agendas in entirely new areas. For example, CEBRA’s early investment in research on expert judgement led to a suite of experiments, tests and empirical results that have wide applications outside biosecurity (Burgman, Reference Burgman2015b), including in geopolitical forecasting for security and intelligence (Wintle et al., Reference Wintle, Mascaro, Fidler, Corkill, Coole and Valli2012), and conservation biology (Martin et al., Reference Martin, Burgman and Fidler2012). Increasing levels of trust over time have enhanced researchers’ understanding of the context in which biosecurity decisions are made and the constraints inherent in the policy-making process. This includes the timeframes for providing usable science outputs. Conversely, policy-makers teamed with researchers have the opportunity to participate in science to achieve policy-relevant outcomes, better understanding the limitations and uncertainties of the scientific results. This has proven effective even where policy-makers have minimal previous scientific experience.
A further advantage of the model is that scientists maintain their independence and are perceived to be independent by other stakeholders in industry and the wider community (Burgman, Reference Burgman2015a). The agreement between government and the university stipulates that the Centre’s work should be in the public domain. This is important for government, because biosecurity decisions can be highly contestable, including at the international level. Part of this independence is that scientists are free to publish their work or comment with the usual academic freedom. Policy-makers may or may not decide to endorse the products of the research and can dissociate themselves from advice or commentaries that they consider to be inaccurate, inappropriate or in conflict with public policy (Burgman, Reference Burgman2015a). Under this model, university researchers are able to undertake work that is directly relevant to public policy, where it can have immediate and significant impact, while maintaining their traditional academic freedoms.
Creating policy impact has been a key objective of CEBRA since its establishment and a number of projects have achieved this. For example, CEBRA designed a monitoring system for aircans (containers for aeroplane baggage) that significantly reduced the burden of intervention for the then Australian Quarantine and Inspection Service in the wake of the 2001 foot-and-mouth disease outbreak in the United Kingdom. CEBRA developed a monitoring regime for aircans based on applied statistics and the operational experience of stakeholders, but also considered the constraints of different regional offices. Under the current system (Robinson et al., Reference Robinson, Burgman and Cannon2011), the Australian Government inspects a maximum of 15,000 aircans a year, out of the almost 400,000 that arrive, while assuring the government that the pathway continues to present a very low risk.
In the area of biosecurity intelligence, CEBRA and its government collaborators found a way to monitor publicly available information on the global spread of pests and diseases systematically and cost-effectively. The department now uses innovative software, the International Biosecurity Intelligence System (IBIS), to search open-source information for emerging pest and disease threats, providing early warning. It generates daily reports that effectively monitor the disease status of Australia’s trading partners. Government staff convert the information IBIS generates into usable intelligence that informs risk identification, assessment and prioritisation (see Chapter 3 for more details of this process).
A third CEBRA research programme has led to a shift in thinking about biosecurity inspection rules and their implementation. A suite of subprojects developed and applied economic experiments and drew on principles from behavioural economics and micro-economic theory to better understand how importers react to incentives within a new compliance-based inspection scheme for a range of plant–product import pathways (Robinson et al., Reference Robinson, Bell and Woolcott2012; Rossiter et al., Reference Rossiter, Hester and Aston2015; Rossiter & Hester, Reference Rossiter and Hester2017; Leibbrandt et al., Reference Leibbrandt, Rossiter and Hester2018). The government uses this scheme to reward consistently compliant importers by imposing reduced inspections. While this work is ongoing it has had some significant practical impacts on compliance-based inspection schemes.
13.5 Lessons learnt
There are many ways in which governments work with scientists to maximise the opportunity to apply sound evidence in the policy-making process. Since its establishment in 2006, CEBRA and its predecessor ACERA have developed a model based on shared responsibility for the development of a research agenda, priorities and the delivery of outcomes. This close relationship between research objectives and policy needs has contributed to the strong uptake of research outcomes. The relationship between policy-makers and scientists has evolved since 2006 to one of mutual respect for the complementary roles and skills that each brings. This has been key to the success of the organisation.
CEBRA’s shared governance arrangement respects the conventional academic reward system. It encourages peer-reviewed publication of articles. Staff present papers at international conferences and CEBRA hosts scientists from other institutions for working groups, workshops, research projects and sabbaticals. This supports traditional pathways to advancement through the university system. Less traditionally, but just as importantly, the collaborative nature of working on public policy issues with government staff can contribute to overall job satisfaction, especially when applied research outcomes positively influence biosecurity policy or operations.
Some CEBRA projects started as one-year projects and expanded into multi-year projects. CEBRA’s longer-term funding model allows more in-depth scientific discourse on research questions related to specific policy needs. Continuation of work leads to greater development of expertise and is more likely to result in satisfactory practical outcomes for biosecurity policy. If a research project team has a productive partnership with their policy counterparts, then long-term (multi-year) projects benefit.
While the shared governance model delivers many positive outcomes for scientists and policy-makers, some challenges persist. Working in close proximity to the machinery of government, researchers may be subject to novel administrative obligations. For example, there can be a requirement for frequent verbal or written progress reports. Further, the collaborative development of a detailed business case can be time-consuming because it is an iterative process involving a number of contributors, and proposals for new projects require formal approval by senior government officials. Government internal quality assurance and contract management processes in general might have an impact on researchers’ workloads and project timeframes, although these are generally no more onerous than writing and managing conventional grants.
A close relationship between project sponsor and research provider may also lead to pressure on researchers to expand the scope of a project when new insights emerge during its progress. In contrast, researchers working under a shared governance arrangement may not put enough effort into achieving project milestones because of the long-term nature of the research centre contract. It is an issue that can be resolved, however, through a responsive, structured and transparent process of change management where all involved parties are informed of and agree to changes in project deliverables or timeframes.
One challenge for research scientists in the shared governance model is shared by all other modes of interaction. That is, the researchers have to at least partially subordinate their interests to those of their research partner. It is not enough to have an idea or a skill and to look for opportunities to apply it. Rather, the researchers have to listen carefully and understand the context of their colleague’s operational environment. Only then can they draw on the suite of skills and experience they have acquired to solve problems. They also have to be patient and persistent in searching for ways of presenting the solutions they discover in an accessible and useable form. Not all researchers are capable of such adjustments.
In conclusion, biosecurity in an Australian context has provided an example in which government regulation has been enhanced by the application of good science. The CEBRA model of collaborative governance arrangements underpinning pragmatic policy outcomes could be applied to other areas of government policy-making in which scientific considerations are important. Potential examples include public health, natural resource management and environmental issues, including conservation policy.
14.1 What do we mean by conservation conflicts and their management?
Conflicts in conservation arise between individuals or groups of stakeholders whose strongly held opinions clash over conservation objectives and when one party is perceived to assert its interests at the expense of another (Redpath et al., Reference Redpath, Young and Evely2013). Such conflicts can take many forms. For example, conflicts may occur between those wanting to conserve large carnivores and those wanting to control them due to their impacts on livestock, or between those wanting to conserve habitats in protected areas and the communities being moved out of those areas. In light of the potential negative impacts on conservation, livelihoods and well-being, managing such conflicts is key to enabling effective conservation.
Conflicts around conservation derive from the fact that the state of nature is socially constructed and has different meanings to different people. Conflicts arise from issues of identity and choices about how the land and sea are used, as well as the uneven distribution of the associated costs and benefits associated with the conservation of biodiversity and ecosystems. These issues reflect the power relations acting across societies over time (Radkau, Reference Radkau2008). The state of nature, which ties into ideas of what is ‘natural’ and ‘acceptable’, is therefore inherently mainly a political matter. As such, conflict, defined as ‘the pursuit of incompatible goals by different groups’ (Ramsbotham et al., Reference Ramsbotham, Miall and Woodhouse2011, p. 30), is intrinsic to its conservation (Adams, Reference Adams, Redpath, Gutierrez and Wood2015).
Redpath et al. (Reference Redpath, Young and Evely2013, Reference Redpath, Gutiérrez and Wood2015a) discuss several types of conflict in the field of nature conservation: conflicts of interest, conflicts over beliefs and values, over process or over information, structural conflicts (often involving power relations) and interpersonal conflicts. Often the characteristics of a conflict between people over nature are unclear and it may take considerable expertise to unpick them, but unless we do this, significant time and resources may be invested into one aspect of a problem (e.g. gathering information and evidence), when the conflict is really about something else (e.g. beliefs and values). Another key aspect of defining a conflict is understanding that the people involved will have different and varied values, worldviews and perspectives on the situation and how it should be managed, depending on their roles and agendas. Exploring the different perspectives and goals of people involved in conflicts, and being clear about the problem, its character and various dimensions, are the first steps towards finding a solution.
Finding ‘solutions’ to these problems is, however, almost as contentious as the conflicts themselves. In certain situations some stakeholders may see the solution as maintaining the status quo, if this fits with their agenda. In others, stakeholders may seek to ‘win’ the battle by imposing their own approach or views at the expense of the other party. Nevertheless, many stakeholders seek an improvement on the current situation through conflict resolution, transformation or management. In the field of peace studies, the paradigm is shifting from conflict resolution, where the emphasis is on reaching jointly agreed long-term outcomes to conflicts, to the more challenging transformation of conflicts, involving profound change in terms of outcome and process (Mitchell, Reference Mitchell2002). This implies fundamental shifts in the ways in which the people involved in the conflict reflect on the real point of conflict and the paradigms and approaches used to mitigate it, leading to the transformation of the institutions and discourses, as well as in the relationships within and between the conflict parties (Ramsbotham et al., Reference Ramsbotham, Miall and Woodhouse2011). Such shifts have yet to occur in the conservation world.
There are several challenges to understanding and managing conflict. Conflict management usually refers to the containment of conflict, but can also be used generically, to refer to all handling of conflict. We use management here to refer to any positive approach to handling a conflict (Ramsbotham et al., Reference Ramsbotham, Miall and Woodhouse2011).
Many of the challenges revolve around issues related to knowledge, communication, representation, trust and leadership (Sjölander-Lindqvist et al., Reference Sjölander-Lindqvist, Johansson and Sandström2015). However, problems can arise at the outset from the way these issues are framed. For instance, in the field of human–wildlife conflicts they are often presented as a struggle between animals and people, and the conflict between different human interest groups is ignored (Peterson et al., Reference Peterson, Birckhead and Leong2010; Redpath et al., Reference Redpath, Young and Evely2013). In reality, most of these conflicts are between conservation interests and other human interests, such as farming, hunting or fishing (Redpath et al., Reference Redpath, Bhatia and Young2015b). Representing these issues as conflicts between farmers and predators is misleading and limits the opportunities for management. To help delineate these two dimensions, Young et al. (Reference Young, Marzano and White2010) distinguished between human–wildlife impacts and human–human conflicts.
The problem of framing is further compounded by the fact that it is often the conservationists who, although not neutral in such settings, are the ones driving the development of management strategies. Clearly, they are likely to be biased in seeking outcomes that benefit conservation, and may not be trusted by the other party or parties. For example, a government conservation organisation may decide to tackle a conflict around a protected species. Because of the background of that organisation, other stakeholders, such as hunters, may assume that the goals are biased towards conservation interests and opposed to hunting interests, and may decide either not to engage in the process or to actively fight against it. A critical step, then, is to be aware of the framing of conflicts around the state of nature and the position different parties take. Having neutral, trusted facilitators, mediators or negotiators can help in the search for potential solutions.
Traditionally, approaches to dealing with human–wildlife conflict have largely been driven by the knowledge created by ecological research and technical fixes. Consequently, efforts to understand and manage conflicts over predators have tended to focus on monitoring, collecting genetic material, estimating predation rates and mitigation methods (such as chilli fences to discourage elephants from destroying crops, diversionary feeding of hen harriers to minimise their impacts on grouse, adapted fishing gear to reduce accidental by-catch). While ecological and technical factors are important aspects of conflict management, social aspects must also be considered. Without insight into the needs, values and positions of the people involved, it is likely that time and money will be wasted and frustration at the continuing conflict will build. This human dimension needs to be understood at both the individual and the collective scale. How do individuals perceive the conflict and react to the species, the other stakeholders involved and the different types of mitigation proposed (Johansson et al., Reference Johansson, Karlsson and Pedersen2012)? At a collective scale it is important to address how the institutions and governance structures are set up. What roles do government and stakeholders play? Who has a say in the decisions?
Knowledge is not simply a product of research by academics from the natural and social sciences and humanities. Substantial knowledge is held by farmers, fishermen and foresters, arising from their experiences, and is often called ‘local knowledge’. Typically, ecological scientific knowledge drives conflict management, while the perceptions and understanding held by local knowledge-holders is ignored or dismissed as anecdote. This is compounded by the fact that many of the administration or policy advisors also come from an ecological tradition, and may treat local knowledge in a similar way. This can create major problems for conflict management and contribute to perverse outcomes, such as the illegal killing of wolves in Finland (Pohja-Mykrä & Kurki, Reference Pohja-Mykrä and Kurki2014). One way around this issue is for researchers to collaborate with other stakeholders in transdisciplinary teams (Butler et al., Reference Butler, Young and McMyn2015). The essential value of these co-management approaches is that they are likely to broaden the scope and trust in science, and provide stakeholders with some psychological ownership of the results (Matilainen et al., Reference Matilainen, Pohja-Mykrä and Lähdesmäki2017).
Two other barriers to effective management of conflicts can arise at the policy interface. First, the response to conflicts tends to be reactive (Young et al., Reference Young, Thompson and Moore2016a). This has been seen clearly in conflicts over geese, where populations of several species have been increasing rapidly in different regions (Fox & Madsen, Reference Fox and Madsen2017), with impacts on crops and farmers’ livelihoods. Discussions about conflict management only generally begin once the conflicts have become serious. Conflict management will inevitably be more effective if the process starts earlier and invests in building relationships between stakeholder groups, as well as committing to an improved understanding of the conflict, the people involved and their views, perceptions and values (Young et al., Reference Young, Thompson and Moore2016a, Reference Young, Searle and Butler2016b). Second, policy-makers often want quick fixes and rapid conflict resolution. Yet, these conflicts are ubiquitous and persistent. We know of no example where a wildlife conflict is considered to have been resolved. Indeed, there are very few instances where they have been effectively managed in the long term to reduce conflict, although there have been some short-term, local successes. For example, the Moray Firth Seal Management Plan was developed by fishermen and other key stakeholders from conservation, government agencies, science and tourism in the north-east of Scotland striving to reach a balance between seal conservation and salmon fishing (e.g. Young et al., Reference Young, Butler and Jordan2012; Butler et al., Reference Butler, Young and McMyn2015). One possible approach to overcome these hurdles would be to horizon scan for emerging conflicts and build relationships, understanding and trust between groups before they escalate.
A further problem is that we currently do not have an informed understanding of which approach to conflict management is most effective under various circumstances. Treves et al. (Reference Treves, Chapron and López‐Bao2017) argue for more top-down approaches, with expert panels, strong policy and enforcement. Conversely, Redpath et al. (Reference Redpath, Linnell and Festa-Bianchet2017) argue for more bottom-up governance processes, built on engagement and trust.
To help overcome many of the challenges associated with wildlife conflict management, Young et al. (Reference Young, Thompson and Moore2016a) developed a decision-support tool with a government agency using a transdisciplinary approach. The tool uses a systematic stepwise approach when faced with management decisions, with six distinct stages: (i) establishing whether there is a conflict or an impact; (ii) understanding the context of the conflict, including the stakeholders affected; (iii) developing shared understanding of the conflict and goals; (iv) building a consensus on how to reach the goals; (v) implementing measures; and (vi) monitoring the outcomes. The authors argue that this new tool has wide applicability and democratic legitimacy, and offers an exciting and practical approach to improve the management of conservation conflicts (see Figure 14.1).
14.3 The limitations and challenges of conflict management
Policies seek to resolve disputes by establishing practices and standards with which relevant actors must comply. A naïve view, held by many natural scientists, is that as long as they have a working knowledge of how policy-making and conflict management function and relate to each, they can make timely contributions that will inform and improve decision-making. However, the decision of whether to conserve or exploit nature is a political and value-based choice. While the focus might appear to be on nature, conservation is also about identity, resource allocation and making choices between people. Therefore, it is intimately bound up in the political economy and granularity of governance. This is a messy business and there are many examples where policy has failed to respond to credible early evidence of problems arising across a range of environmental issues, from lead in petrol to climate change to pesticide use.
Despite the existence of more sophisticated frameworks describing the reality of policy-making, such as the Advocacy Coalition Framework (e.g. Jenkins-Smith & Sabatier, Reference Jenkins-Smith and Sabatier1994) and Multi-systems Approach (e.g. Cairney & Jones, Reference Cairney and Jones2016), much of the policy training in the public sector uses the ‘policy wheel’. In general, the process is assumed to start with a problem, which provides a rationale for a policy intervention. Objectives are then set, options appraised and a decision made. The policy is implemented and its effectiveness monitored. The outcomes are evaluated, and the lessons learned contribute to refinements of the policy or inform the definition of the next problem and new policy cycle. This schema works well for problems that are well-defined, tightly bounded and relatively uncontroversial, but there are few such examples in conservation. For more complex issues, which typify conflicts over nature, there are potential difficulties at every step in the cycle.
Many disciplines, including ecological science, history, political science, economics, anthropology, law, psychology, ethics, sociology and peace studies, can be drawn upon to understand conflicts in conservation, as well as practice in areas such as farming, forestry, fisheries and infrastructure development (Redpath et al., Reference Redpath, Gutiérrez and Wood2015a). Nevertheless, the natural sciences still tend to dominate in shaping policy and practice (e.g. Stirling, Reference Stirling, Scoones, Leach and Newell2015), with many practitioners believing that ‘science speaks truth to power’ (e.g. Collingridge & Reeve, Reference Collingridge and Reeve1986). There are a number of fundamental problems linked to this belief.
First, the belief that science trades in facts and that these are unambiguous. This is a realist ontological view that there is ‘a’ truth to reveal to those in power (e.g. Moses & Knutsen, Reference Moses and Knutsen2012). If there is doubt, further research will fill in the blanks to reveal the true picture. While this may apply in some cases, it does not hold for much of the field of scientific endeavour, which seeks to deepen our understanding of the world and how it works based on theoretical frameworks (e.g. Moon & Blackman, Reference Moon and Blackman2014). The natural sciences typically reveal multiple ‘truths’ supported by evidence, and the most successful of these can be judged based on their explanatory power and degree of consilience. Knowledge is therefore always shifting (Gee et al., Reference Gee, Grandjean and Hansen2013), meaning that conflict can arise from policy and practice that is out of step with current knowledge or specific contexts.
Second, the belief that science and ‘facts’ are independent of social context. Again, this may be true for some observations, but not for the meanings associated with them (Funtowitz & Ravetz, Reference Funtowicz, Ravetz and Costanza1991), and it is often the distinction between observation and meaning that is critical. Many scientists hold that ‘matters of fact’ lead directly to ‘matters of concern’, but in practice facts are filtered through individual ‘narratives’ or worldviews to determine matters of concern (Latour, Reference Latour2004). These worldviews, which we all have, often remain unspoken, but fuel conflicts of interest. They significantly constrain the scope and relevance of ‘expert views’ (Sutherland & Burgman, Reference Sutherland and Burgman2015), which are often brought forward to support one position or another in conflicts.
Third, even when science provides a more compelling account of natural phenomena than the alternatives, it requires belief or faith in the scientific method. Many people may struggle to accept a scientific view of an issue over another narrative that reinforces their sense of identity and worldview. Well-reasoned scepticism (Stirling, Reference Stirling, Scoones, Leach and Newell2015) is essential to guard against a potential progression to populism, ‘fake news’ and lobbying for policy that flies in the face of evidence (Corner, Reference Corner2017).
Marquand (Reference Marquand2004) observed the paradox of the requirement for both a strong citizenry, needed for an inclusive public domain, as well as the availability of expert professional viewpoints, which are by definition exclusive, to achieve evidence-based and accountable decision-making. The paradox is how professional views, where knowledge is held by the few rather than the many, contribute to the public domain. This is not necessarily a problem if professional views are in alignment with the public interest, but various checks and balances are required to control for professional interests/institutions and associated power relations. This paradox can be resolved if professionals, including ecologists and conservationists, earn and retain the trust of citizens. Funtowicz and Ravetz (Reference Funtowicz, Ravetz and Costanza1991), Marquand (Reference Marquand2004), Radkau (Reference Radkau2008) and Stirling (Reference Stirling, Scoones, Leach and Newell2015) are among many who advocate for a more participatory approach by which science can act in the public interest on complex issues, in which the evidence from science (including social science) and local knowledge is co-created and co-produced (e.g. Fazey et al., Reference Fazey, Moug and Allen2018) or co-assessed (Sutherland et al., Reference Sutherland, Shackleford and Rose2017). This potentially allows stakeholders in conflicts to give legitimacy to the authority of professionals (Fazey et al., Reference Fazey, Moug and Allen2018), thereby addressing issues of trust, bias and power.
14.4 Trust, bias and power in conflicts
Power is the uneven distribution of agency (Stirling, Reference Stirling, Voß and Freeman2016), and is a defining and unavoidable characteristic of all social interactions. It is not necessarily bad, as it can get things done. However, whether power is ‘good’ or ‘bad’ depends on your viewpoint and, hence, power and politics are intimately linked. Criticism is valid when power is neglected or denied. Similarly, everyone is biased to some extent. This is as true in science as any other field. Like power, bias is problematic when it is neglected or denied.
Decisions about natural resource use and the state of nature involve issues of trust, bias and power, which are inevitable in any set of social interactions (e.g. Young et al., Reference Young, Searle and Butler2016b). How well they are resolved depends on the governance contexts in which decisions are taken. These bring together the personal relationships of the private domain, access to wealth and power in the market domain, and the public interest of the public domain (Marquand, Reference Marquand2004). The more diverse, plural and different the views from stakeholders that are expressed and integrated into decisions about the natural environment the better (e.g. Young et al., Reference Young, Searle and Butler2016b), with power relations and biases acknowledged to keep incumbent hegemonies and vested interests in check (Stirling, Reference Stirling, Scoones, Leach and Newell2015). This is not to argue that the process is easy or that everyone can always agree, but that people can agree to differ through a well-structured process and move on from conflict: a ‘solution’ that involves winners and losers will always resurface as a conflict (Young et al., Reference Young, Thompson and Moore2016a). This argues directly against centralisation, often a dominant force in ‘command-and-control’ politics (e.g. Cooke & Muir, Reference Cooke and Muir2012).
The extent to which administrative and institutional arrangements are able to respond flexibly, in a scale-appropriate manner, and quickly to reflect the character of real-world problems, is a critical factor in successfully translating evidence into effective policy and practice (e.g. Sparrow, Reference Sparrow2011). However, there is a great deal of inertia in institutions, often as a result of their structures, processes and associated habits and ways of working. Internal arrangements designed for one set of problems may be ill-suited to others. An important distinction is whether organisations (including government) exist to ‘deliver’ or ‘enable’. The latter is essential when creating the conditions that facilitate participative approaches and the development of trusting relations.
14.5 An outlook on conflict management: focusing on worldviews around the state of nature
Identity, and specifically the worldviews on the state of nature, are of critical importance in conflict management, including the question of whether people are seen or see themselves as a part of, or apart from, nature (Fischer & Young, Reference Fischer and Young2007). This can influence the understanding and mental constructs around terms such as biodiversity, nature, ecosystem health, native, naturalness, integrity, sustainability, resilience, stability, balance, wild, land-sparing and land-sharing. In short, all of the language, concepts and ideas of conservation are open to different interpretations, which perhaps testifies to the idea that the state of ‘nature’ and ‘conservation’ are social constructs. In turn, this has implications for the institutional arrangements and approaches to conservation (e.g. what we measure, performance management frameworks). The idea that nature is unambiguous and categorical sits comfortably with more rigid measurement frameworks informed by authoritative science and used to ‘deliver’ conservation objectives. In contrast, a more fluid relationship between people and nature, based on a broad range of knowledge and possible truths, is better aligned to situational, participative and co-produced approaches.
This is not to suggest that worldviews (whether people are part of, or apart from, nature) and their consequences can be readily polarised. Indeed, these worldviews are not necessarily mutually exclusive: some people may gravitate more to one than the other, while others may hold both simultaneously. Similarly, while debates between utilitarian and intrinsic values greatly exercise many conservationists, many people hold both together without conflict. However, it appears that utilitarian values are often associated with general and replicable issues and intrinsic values are often more situational and associated with personal experience and knowledge. This serves only to illustrate that worldviews can and do shape evidence, institutional arrangements and approaches to conservation, including the way in which conflicts are managed.
Biodiversity and its importance has long been recognised and enshrined in national and international policies. While the earliest conservation policies were framed around 150 years ago and mainly consisted of national policies to protect biodiversity, over the last century conservation policies have undergone a significant shift in emphasis towards integration of, and alignment with, societal goals (Mace, Reference Mace2014). Moving from a sole focus on species and habitat protection in the early twentieth century, or ‘Nature for itself’ as framed by Mace (Reference Mace2014), policies have gradually aligned with other societal aims. This started with a recognition of ecosystem services (Daily, Reference Daily1997), as the benefits people derive from nature (‘Nature for People’), which was brought into the mainstream by the Millennium Ecosystem Assessment (MA, 2005). There has since been a move away from utilitarian values to consider ‘Nature and People’ (Mace, Reference Mace2014; Díaz et al., Reference Díaz, Pascual and Stenseke2018) as a more inclusive concept to better support synergies and negotiate trade-offs of conservation and societal goals. In this chapter, we aim to demonstrate and discuss how this increasingly integrative view is reflected in the development of international conservation policies and related institutions. After briefly sketching the historical origins of current international conservation policies, we focus on the Convention on Biological Diversity (CBD), which couples its core objective of nature conservation with human well-being. Next, we show how an integrative view on nature conservation has shaped the Intergovernmental Science–Policy Platform on Biodiversity and Ecosystem Services (IPBES). Finally, we explore the Sustainable Development Goals (SDGs) as a third global enterprise that closely links the conservation of nature to other societal aspirations. Using these three examples, we address the following questions.
1. How do these three agreements function and how are decisions made?
2. What is the role of science and evidence in the CBD, IPBES and the SDGs?
3. What are the achievements so far, and how can scientists engage to foster progress?
15.2 A short history of conservation policies
To understand current conservation policies, it is useful to reflect briefly on their development. Historically, conservation policies were created in response to a realisation of loss of natural habitat, and led to national conservation designations, notably the first big national parks. In the USA, Yellowstone was established as the first National Park worldwide by the Yellowstone National Park Act in 1872, withdrawing almost one million hectares from further land use development to be ‘dedicated and set apart as a public park … for the benefit and enjoyment of the people’. In Europe, the UK was the first country to establish national parks under the 1949 National Parks and Access to the Countryside Act, also born out of a strong demand for open public access to private land. The Peak District National Park, designated in 1951, remains one of the most-visited national parks worldwide. Many more national parks followed in the 1970s and 1980s in Africa, Europe and across all continents. Often, however, these designations showed little consideration of local communities and their livelihoods (‘Nature despite people’; Mace, Reference Mace2014), leading at times to violations of rights of indigenous people and severe conflicts (Colchester, Reference Colchester2004). Protected areas continue to provide crucial cornerstones of local, regional and international strategies for biodiversity conservation. They have significantly contributed to halting losses of species and habitats, although their performance is at times mixed and often not known (Gaston et al., Reference Gaston, Jackson and Cantú-Salazar2008; Mora & Sale, Reference Mora and Sale2011).
International conservation policy development started with a series of global conventions in the 1970s and 1980s focusing on species and habitat protection (Table 15.1). Once countries ratified these multi-lateral environmental agreements, they proved to be drivers for national law development. For example, the US Endangered Species Act of 1973 was developed as a response to the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) that had entered into force the same year. As another example, the European Union met its obligations for bird species under the Bern Convention (1979) and Bonn Convention (1979) through the Council Directive 79/409/EEC on the conservation of wild birds (Birds Directive) adopted in 1979. This has since been substantially amended several times to the Directive 2009/147/EC adopted in 2009 and sits alongside the Council Directive 92/43/EEC on the conservation of natural habitats and of wild fauna and flora (Habitats Directive) adopted in 1992. Legal mechanisms for the achievement of international conventions at national scales are at the discretion of each member state.
|Treaty name||Abbreviation||Adoption||Entry into force||Parties*||Main target|
|Convention on Wetlands of International Importance||Ramsar Convention||1971||1975||170||Conservation and sustainable use of wetlands|
|Convention Concerning the Protection of the World Cultural and Natural Heritage||WHC/World Heritage Convention||1972||175||193||Protection of the world cultural and natural heritage|
|Convention on International Trade in Endangered Species of Wild Fauna and Flora||CITES||1973||1975||183||Regulation of trade of wild plants and animals|
|Convention on the Conservation of European Wildlife and Natural Habitats||Bern Convention||1979||1982||51||Conservation of wild flora and fauna and their natural habitats, and promotion of European cooperation|
|Convention on the Conservation of Migratory Species of Wild Animals||CMS/Bonn Convention||1979||1983||126||Conservation and sustainable use of migratory animals and their habitats|
|United Nations Framework Convention on Climate Change||UNFCCC||1992||1994||197||Prevention of dangerous anthropogenic interference with the climate system, slowing global warming and mitigating its impact|
|Convention on Biological Diversity||CBD||1992||1993||196||Conservation of biological diversity, the sustainable use of its components, and the fair and equitable sharing of benefits arising from the use of genetic resources|
|United Nations Convention to Combat Desertification||UNCCD||1994||1996||197||Prevention of desertification and land degradation|
* Number of member states as of December 2018.
During the 1980s, environmental pollution, the over-use of resources and the resulting loss of species and natural habitats gained increasing attention from the public and political representatives. This led to the ‘Rio World Summit’ in 1992 (United Nations Conference on Environment and Development, UNCED), at which three new conventions were opened for signature: the United Nations Framework Convention on Climate Change (UNFCCC), the United Nations Convention to Combat Desertification (UNCCD) and the Convention on Biological Diversity (CBD). Further details of the set up, operation and achievements of these three conventions are described in the sections below.
15.3 General set up and mode of operation
15.3.1 The Convention on Biological Diversity (CBD)
The CBD is, with regards to goals addressed, the most comprehensive global treaty dealing with nature conservation. Its three overarching objectives are (Article 1 of the Convention):
(a) the conservation of biological diversity,
(b) the sustainable use of its components and
(c) the fair and equitable sharing of the benefits arising out of the utilisation of genetic resources.
Thus, the CBD’s objectives refer to both intrinsic and instrumental values of biodiversity. It does so by including an unconditional call for the conservation of biodiversity in combination with the acknowledgement that people depend on nature and need to make use of it, as well as a call for dividing the benefits that are derived from nature equitably.
In total, the Convention’s text contains 42 Articles that further define aims and assign duties to the bodies of the Convention. The CBD’s clear recognition of the interaction between nature-related and societal goals is also codified in its principles. For example, the first CBD principle states that the ‘objectives of management of land, water and living resources are a matter of societal choices’, while the twelfth acknowledges that ‘the ecosystem approach should involve all relevant sectors of society and scientific disciplines’. The CBD is a legally binding treaty. Thus, a state that has signed and ratified the Convention is obliged to implement the Convention on its territory through national policies and practical management. Every two years, representatives of the member states meet at the Conference of the Parties (COP). The COP is the highest decision-making body of the CBD and it operates according to the consensus principle. This means that the text of a decision is negotiated until a compromise is reached among all parties present. If no consensus is reached, parties do not vote. Instead, only text to which no party objects is agreed upon and a decision on unresolved questions is postponed. A CBD COP decision therefore almost always represents a compromise between states with differing views. This ‘consensus principle’ has been criticised for preventing progress and watering down any suggestion to the lowest common denominator, often resulting in general, vague or ambiguous text (Kanie, Reference Kanie, Conca and Dabelko2014; Kemp, Reference Kemp2016). However, a shift from the consensus principle to a voting system faces many obstacles, e.g. the fear that parties could perceive this as a loss of sovereignty and could therefore drop out of the Convention, or that such a reform would open a ‘Pandora’s box’ and encourage open disputes on, and possibly change in, other principles or rules of procedure (Kemp, Reference Kemp2016).
To facilitate negotiations under the consensus principle, the CBD parties are divided into groups of states that discuss and align their positions; one of their members is then responsible for representing them in the plenary of the COP. Important associations of states are the European Union and the official United Nations Regional Groups (African Group, Asia–Pacific Group, Eastern European Group, Latin America and Caribbean Group, Western European and Others Group), alongside some informal groups, such as an alliance of industrialised non-EU countries called JUSCANNZ (i.e. Japan, United States, Switzerland, Canada, Australia, Norway, New Zealand).
Meetings of the CBD COP and of many other CBD bodies (e.g. of the Subsidiary Body of Technical and Technological Advice – SBSTTA, see 15.5.1) are open to so-called ‘observers’. The observer status can be obtained by, for example, non-governmental organisations, business associations or scientific institutions and it gives the right to speak in plenary but not to veto a decision.
One way in which the CBD fosters progress towards its objectives is by setting up particular Programmes of Work, each with a vision and suggested actions that CBD parties are encouraged to support. These are concerned with topics related to Agricultural Biodiversity, Dry and Sub-humid Lands Biodiversity, Forest Biodiversity, Inland Waters Biodiversity, Island Biodiversity, Marine and Coastal Biodiversity and Mountain Biodiversity. The CBD also dedicates work to cross-cutting issues, such as Climate Change and Biodiversity; Communication, Education and Public Awareness, Economics, Trade and Incentives Measures or Identification, Monitoring, Indicators and Assessments. It aims to link work on these themes closely with other UN Conventions by collaborating with, for example, UNFCCC and UNCCD secretariats (www.unccd.int/convention/about-convention/unccd-cbd-and-unfccc-joint-liaison-group).
Approximately every five years, parties must report the steps taken to implement the CBD provisions and their effectiveness to the CBD Secretariat. These ‘National Reports’ are used by the CBD Secretariat to gain an overview of global trends in the implementation process. However, as the parties are sovereign entities, they decide individually about their national implementation approaches, and are free to set own priorities (with the exception of EU member states who coordinate their efforts and are committed to EU regulations). There are no established CBD non-compliance procedures. The degree of compliance therefore varies widely and, overall, has proven to be generally insufficient, as the CBD’s goals and targets, formulated in the Convention’s Strategic Plans, have been repeatedly missed. For the period 2002–2010, the core element of the CBD’s Strategic Plan was the ‘2010 Target’: a ‘significant reduction of the current rate of biodiversity loss at the global, regional and national level as a contribution to poverty alleviation and to the benefit of all life on Earth’ (COP-Decision VI/26). However, this 2010 Target was widely missed (Butchart et al., Reference Butchart, Walpole and Collen2010; Dirzo et al., Reference Dirzo, Young and Galetti2014).
For the following decade, the level of ambition was raised further: ‘to halt the loss of biodiversity’ by 2020. To better address the underlying causes of biodiversity loss and be more explicit about what needed to be done to make progress towards the CBD objectives, the Strategic Plan for 2011–2020 was underpinned with five strategic goals and 20 ‘Aichi Biodiversity Targets’ that formed the backbone of the Plan (see Figure 15.1). Setting up such a comprehensive framework that addressed the direct and indirect drivers of the ongoing biodiversity crises was seen as a major achievement. Furthermore, the Strategic Plan 2011–2020 has been highly relevant, beyond the global biodiversity agenda; it was endorsed by the UN General Assembly and other multi-lateral environmental agreements and therefore formed the principle global roadmap for the conservation of nature. The 20 Aichi Biodiversity Targets that formed the core of the Strategic Plan 2011–2020 were also incorporated into the global development agendas and fed into the Millennium Goals (until 2015) and subsequently the Sustainable Development Goals (until 2030).
However, despite this high political recognition, the Aichi Targets were not on track in 2018 and most will be widely missed by 2020, as indicated by the fourth Global Biodiversity Outlook report (Leadley et al., Reference Leadley, Krug and Alkemade2014) and the IPBES Global Assessment (IPBES/7/10/Add.1). Despite progress towards some Targets, the overall picture leaves no doubt: efforts need to be increased dramatically to halt and reverse the current situation, in which the drivers of biodiversity loss worldwide strongly override conservation efforts. There have been accelerated policy and management responses to the biodiversity crisis, but these are unlikely to significantly reverse trends in the state of biodiversity by 2020 (Tittensor et al., Reference Tittensor, Walpole and Hill2014).
For the post-2020 period, it is therefore crucial to focus on the implementation of the new CBD strategic framework that will then be in place. This needs to be achieved, in the first place, by the parties at the national level. Therefore, besides increased globally concerted efforts, place-based and context-specific approaches are essential for monitoring, conserving and sustainably using biodiversity.
15.3.2 Intergovernmental Science–Policy Platform on Biodiversity and Ecosystem Services (IPBES)
As a response to knowledge needs that became evident in the context of the CBD and other multi-lateral environmental agreements, the Millennium Ecosystem Assessment (MA, 2005) was conducted in 2005, followed by several national ecosystem assessments (Schröter et al., Reference Schröter, Albert and Marques2016). Building on this experience (Carpenter et al., Reference Carpenter, Mooney and Agard2009) and modelled on the Intergovernmental Panel on Climate Change (IPCC), the Intergovernmental Science–Policy Platform on Biodiversity and Ecosystem Services (IPBES) was established in 2012 to generate an integrative knowledge foundation on biodiversity, ecosystems, ecosystem services and their impact on human and societal well-being (UNEP, 2012). IPBES is not a convention but a science–policy interface that supports governments and stakeholders in decision-making at multiple scales by providing policy-relevant and scientifically credible information on the status and trends of nature and its contributions to people (Brooks et al., Reference Brooks, Lamoreux and Soberón2014). IPBES does not enforce decisions on conventions or countries, but aspires to develop an expert-based platform that provides an accessible, useful and scientifically rigorous evidence base to support biodiversity-related decision-making by national governments and international conventions (e.g. CBD, RAMSAR, CITES, UNCCD).
To achieve this, IPBES operates via four main functions – assessment, knowledge generation, policy support and capacity-building – that are implemented through voluntary participation of experts chosen by governments and organisations globally, with balanced representation across regions, gender and disciplines (IPBES, 2014). Over the coming years, IPBES aims to continue bringing together the best knowledge-holders and institutions on biodiversity around the globe, synthesising the complex dynamics of nature and their impact on human societies and the planet, providing the most credible information available through research and practice, and catalysing the generation of new knowledge to fill critical gaps in order to better conserve nature and ensure human and societal well-being (Figure 15.2).
The IPBES Plenary, where 130 member states form a governing body, meets annually to track the progress of the work programme and to make decisions on the way forward. A Multidisciplinary Expert Panel (MEP) advises on scientific and technical aspects of the programme. The expert groups, taskforces and assessment authors are the scientists and knowledge-holders. Stakeholders and observers also play significant roles in IPBES by providing diverse perspectives and forms of knowledge and acting as catalysts for conservation in their respective communities of practice. In particular, IPBES is developing a mechanism to better integrate holders of indigenous and local knowledge into the process for a more comprehensive understanding and outlook on nature’s values and futures (IPBES, 2014).
The decision-making process of IPBES is lengthy but transparent, due to the nature of the intergovernmental plenary system (Figure 15.3 shows the participants).
IPBES is an independent intergovernmental platform that works in partnership with the large United Nations Programmes such as the UN Environment Programme (UNEP), the UN Educational, Scientific and Cultural Organization (UNESCO), the Food and Agriculture Organization of the UN (FAO) and the UN Development Programme (UNDP). Its work is aligned to the CBD and other international Conventions (e.g. Ramsar, CITES, as well as the UNCCD). Its unique role is to mobilise scientific communities from multiple disciplines to harmonise research agendas on biodiversity and its impact on societies among key organisations, such as the International Union for the Conservation of Nature (IUCN), Future Earth and the Group On Earth Observations Biodiversity Observation Network (GEO BON) (IPBES, 2018a). While the social sciences and humanities are still underrepresented in the process (Vadrot et al., Reference Vadrot, Rankovic and Lapeyre2018), IPBES aims to attract more social scientists.
15.3.3 The Sustainable Development Goals
The establishment of IPBES was well timed to coincide with the inception of United Nation’s new global agenda, the Sustainable Development Goals (SDGs) (UN, 2015). Historically, the concept of sustainability builds on more than 30 years of intense political discourse, following the Brundtland Commission (1987), the Rio Declaration on Environment and Development (UN, 1992) and the eight Millennium Development Goals (MDGs) (McArthur, Reference McArthur2014). These included a goal to ‘ensure environmental sustainability’, but did not relate to biodiversity specifically. Based on the MDGs, the SDGs were developed as a more holistic and integrated approach to development following the United Nations Conference on Sustainable Development in 2012. In January 2016, the 2030 Agenda for Sustainable Development, comprising 17 SDGs with 169 targets and a declaration, were officially approved during a UN Summit attended by 193 member states (UN, 2015). The 2030 Agenda aimed to stimulate action in areas of critical importance for humanity and the planet with a set of approved goals (Figure 15.4). It provides a holistic strategy that combines economic development, social inclusion and environmental sustainability and applies to all countries – poor, rich and middle-income alike – and to all segments of society (ICSU, 2017); this is the major novelty and strength of this framework, in which biodiversity conservation is no longer isolated.
Its main decision body, the High-level Political Forum, provides a central platform for all member states to review progress towards the 2030 Agenda for Sustainable Development and the SDGs. To foster the implementation of the SDGs, the United Nations partnered with several governmental and non-governmental organisations worldwide to ensure commitment to this cause and also enhance synergies across global conventions. Several international coalitions, including the G20 and G8, have incorporated the 2030 Agenda into their policy frameworks, although reviews have indicated that the implementation of SDGs in general and the biodiversity goals in particular (SDG 14 life below water and SDG 15 life on land) are not yet sufficiently incorporated into national policies of either OECD or non-OECD countries (O’Connor et al., Reference O’Connor, Mackie and Van Esveld2016; Schmidt-Traub et al., Reference Schmidt-Traub, Kroll and Teksoz2017). Achieving the SDGs requires a willingness to cooperate at the international level and sustainable development to be anchored as a guiding principle in all policy fields at national, European and international levels (Schmidt-Traub et al., Reference Schmidt-Traub, Kroll and Teksoz2017). However, the achievement of many SDGs depends largely on action taken in member states and above all requires the development and implementation of strong operative concepts at national and regional levels (Schmidt-Traub et al., Reference Schmidt-Traub, Kroll and Teksoz2017). Governments and other stakeholders are expected to mobilise efforts to establish national and regional plans towards implementation of the SDGs (ICSU, 2017). This requires a balance between addressing the scope and systemic nature of the 2030 Agenda with budgetary, political and resource constraints that inevitably mean countries prioritise certain targets (ICSU, 2017) and the associated risk of negative effects for ‘non-prioritised’ ones, particularly if they are in a conflicting, even mutually exclusive, relationship (Schmalzbauer & Visbeck, Reference Schmalzbauer and Visbeck2016). Furthermore, the goals are rarely independent and consequently failures in one area can quickly undermine progress in other areas (Schmalzbauer & Visbeck, Reference Schmalzbauer and Visbeck2016). National policy-makers thus face the challenge of understanding the inter-dependencies across the SDGs and achieving coherent implementation to ensure that progress in some areas is not made at the expense of progress in others. In addition, national policies often have implications on neighbouring countries or across globalised value chains, i.e. we need to avoid pursuing objectives in one region that negatively affect other countries’ pursuit of their objectives (ICSU, 2017).
15.4 Joint working of the CBD and SDG 2030 Agenda
According to the CBD, the Strategic Plan for Biodiversity and the 2030 Agenda are consistent with each other and mutually supportive (CBD et al., 2017). The central role of the biosphere is explicitly acknowledged in the new illustration of the SDGs, as layers in a ‘wedding cake’ that build on one another, developed by the Stockholm Resilience Centre (see Figure 15.4). It implies a transition away from sectoral approaches embedding economy and society as parts of the biosphere and recognises that the related goals of promoting human dignity and prosperity can only be achieved sustainably if the Earth’s vital biophysical processes and ecosystem services are safeguarded (ICSU, 2017). However, working towards the implementation of the SDGs in UN member states requires a process of prioritisation. This poses a fundamental challenge and possibly a genuine risk to biodiversity conservation, as biodiversity concerns may not always be adequately anchored in other non-environmental policy sectors and thus may be overridden by other interests, especially when trade-offs arise between short-term development achievements and long-term sustainability (Schmalzbauer & Visbeck, Reference Schmalzbauer and Visbeck2016). These trade-offs will often be at the expense of biodiversity (SDGs 14 and 15), with likely negative consequences for several other SDGs, such as those related to food security, water supply and climate change mitigation. There have been some attempts to analyse these links further (Scharlemann et al., Reference Scharlemann, Mant and Balfour2016; SRC 2016; CBD et al., 2017), but the critical question of how to resolve potential trade-offs in practice remains to be negotiated at the local, national and regional scales.
15.5 Role of science and evidence
To conserve biodiversity, it is important to devise action on reliable, sound knowledge about its components. The CBD has incorporated this principle by obliging all contracting parties to identify and monitor particularly diverse ecosystems and habitats, threatened species and other biodiversity components of ecological, social, economic, cultural or scientific importance (Article 7 and Annex 1 of the Convention). To effectively conserve biodiversity, it is furthermore crucial to build action on sound evidence about the factors that lead to its loss and measures to reduce their impact, e.g. possible policy and management responses and their effectiveness.
The CBD collates, utilises and synthesises such knowledge in various ways. The CBD secretariat, for example, regularly publishes notifications that call for input with regard to particular questions. Approximately every five years, it publishes the ‘Global Biodiversity Outlook’, an assessment of global biodiversity states and trends and of the progress toward the CBD objectives (Leadley et al., Reference Leadley, Krug and Alkemade2014).
The CBD’s Subsidiary Body on Scientific, Technical and Technological Advice (SBSTTA) is responsible for processing knowledge-related tasks and providing advice and guidance to the COP with respect to scientific (and technical and technological) questions. The SBSTTA plays a crucial role because it presents recommendations that are often later followed by the COP (sometimes with modifications). Therefore, its meetings are highly politicised and cannot provide a comprehensive and balanced evidence base with regard to upcoming COP negotiations. This has long been a major criticism of the SBSTTA and was one of the major motivations for creating the Intergovernmental Platform on Biodiversity and Ecosystem Services.
As a platform of scientific communities and knowledge-holding networks, IPBES is expected to play a critical role in providing the best available, rigorous and comprehensive scientific evidence to various biodiversity-related conventions and international initiatives. Since its establishment in 2012, IPBES has brought together more than a thousand scientists and knowledge-holders from around the globe to integrate knowledge systems from multiple disciplines. The main IPBES products and deliverables are assessments, which synthesise scientific findings and evidence on biodiversity change and its impact on human well-being to inform policy decisions.
One of the first IPBES assessments, the IPBES pollination assessment (IPBES, Reference Potts, Imperatriz-Fonseca and Ngo2016) has made a significant global impact on policy development. For instance at the 13th Conference of the Parties to the Convention on Biological Diversity in Mexico in 2016 (CBD COP13), a COP decision recognised its relevance for the planned fifth edition of the Global Biodiversity Outlook and listed it among the best available scientific information. The COP also encouraged parties, other governments, relevant organisations, the scientific community and stakeholders, as well as indigenous peoples and local communities, to develop and use these tools and contribute to their further development (CBD, 2016a). The pollination assessment provides a best-practice ‘toolkit’ of the approaches that can be used to decide policies and actions by governments, the private sector and civil society. Different valuation methodologies are evaluated according to different visions, approaches and knowledge systems, as well as their policy relevance, based on the diverse conceptualisation of values of biodiversity and nature’s benefits to people, including provisioning, regulating and cultural services. As such, this assessment has generated a wide range of follow-up products, actions and policy initiatives, including the following.
A formal endorsement of the key messages of the assessment by the parties to the CBD at the 13th Conference of the Parties (COP13) in Mexico (CBD, 2016b).
The formation of a ‘Coalition of the Willing’ by a growing number of governments around the world, inspired by the assessment to act nationally to protect pollinators and promote pollination (Promote pollinators, 2018).
Publications in high-ranking scientific journals building on and reviewing the assessments (Potts et al., Reference Potts, Imperatriz-Fonseca and Ngo2016; Díaz et al., Reference Díaz, Pascual and Stenseke2018).
An expanding list of national strategies and action plans on pollination in countries including, among others, Brazil, France, Germany, the Netherlands, the Republic of Korea and South Africa.
The IPBES scientific community also made significant contributions to the controversial discourse on the appropriateness of the ecosystem service concept and paved the way to reconciling differing views on conceptualisation of the human–nature relationship (Díaz et al., Reference Díaz, Pascual and Stenseke2018; Stenseke & Larigauderie, Reference Stenseke and Larigauderie2018). It should be recognised, however, that the community will continue to use many different terms for ecosystem services or the contributions people receive from nature, depending on context, and this plurality should be welcomed (Peterson et al., Reference Peterson, Harmácková and Meacham2018). Both the open-ended stakeholder network and the new concept of nature’s contributions to people reflect the co-design and co-development aspects of IPBES as a learning organisation.
The challenges posed in IPBES are many, including a more balanced integration of scientists and experts from both natural and social sciences for a holistic understanding of biodiversity and its interactions with society and humanity (Jetzkowitz et al., Reference Jetzkowitz, van Koppen and Lidskog2018; Stenseke & Larigauderie, Reference Stenseke and Larigauderie2018). A more thorough consideration of, and improvement in, achieving the balance and quality of geographic, gender and disciplinary representations will be critical in filling the knowledge gaps and adding interdisciplinary value to the IPBES assessments (Obermeister, Reference Obermeister2017; Heubach & Lambini, Reference Heubach and Lambini2018). Moving forward, it will be important for IPBES to liaise with the private sector for greater impact on socially responsible and sustainable development, and with the public in disseminating scientific knowledge to promote changes in individual behaviour and decisions conscious of biodiversity conservation.
It is crucial that progress in the implementation of the SDGs in national policy processes is adequately monitored (Hák et al., Reference Hák, Janoušková and Moldan2016; Reyers et al., Reference Reyers, Stafford-Smith and Erb2017). To track the SDGs, the UN Statistics Commission has recommended over 230 official indicators, and countries are invited to submit voluntary national reviews of their progress to the High-Level Political Forum (Sachs et al., Reference Sachs, Schmidt-Traub and Kroll2017). However, not all of the indicators have well-established definitions or data for all UN member states. A review of reports submitted so far (Bizikova & Pinter, Reference Bizikova and Pinter2017) found they were particularly weak on the environmental SDGs 12–15 (Sachs et al., Reference Sachs, Schmidt-Traub and Kroll2017) and the assessment of interlinkages, synergies and trade-offs between targets (Allen et al., Reference Allen, Metternicht and Wiedmann2018). The evaluation of SDGs and tracking the progress to their achievement requires holistic scientific approaches to better understand the linkages between the SDGs and their underlying challenges, to understand thresholds, rebound effects and tipping points, and to explain the benefits and trade-offs of a range of development pathways that could lead to a more sustainable global society (Schmalzbauer & Visbeck, Reference Schmalzbauer and Visbeck2016).
The IPBES community of scientists can also provide best expert knowledge and scientific evidence for the sustainable development of the planet to inform the SDGs. For example, the recent IPBES assessment of land degradation and restoration (IPBES, Reference Scholes, Montanarella and Brainich2018c) mapped the relevance of land degradation against the SDG goals. This may help to mainstream biodiversity across sectors and societies and bring forth synergies between global initiatives. A well-functioning knowledge generation mechanism connecting scientific and policy bodies of the platform will be particularly important if IPBES is to become an effective catalyst and orchestrator of harmonised science, policy and practice for better conservation.
15.6 Achievements of the CBD, IPBES and SGDs
There are several developments at the national level that can directly be traced to the CBD, such as the adoption of National Biodiversity Strategies and Action Plans in 185 countries of the world (as of December 2018, according to the CBD website). Other examples of direct influence of the CBD on its member states are the national regulations that parties have adopted to comply with the provisions of the two Protocols that have arisen from the CBD: the Cartagena Protocol on biosafety and the Nagoya Protocol on Access and Benefit Sharing. However, the CBD’s influence on biodiversity governance at the national scale still appears limited. This is partly due to the power imbalances that exist among global institutions, and strong global forces that prioritise economic considerations over nature conservation, as well as power relations and societal preferences at the national scale. Furthermore, the fact that the CBD lacks a non-compliance mechanism may further weaken its influence.
Nonetheless, the CBD has provided inspiration to a great variety of state and non-state actors to initiate conservation actions. For example, the Aichi Biodiversity Targets (included in the Strategic Plan of the CBD for the period 2011–2020) have sparked debates and research on biodiversity-related questions and serve as important reference points in calls for greater efforts in nature conservation (e.g. they are often referred to by non-governmental organisations). These Targets, along with the UN Decade on Biodiversity with the same timeframe (2011–2020), have also inspired numerous actions on the ground, as documented on the CBD website (www.cbd.int/2011–2020/). Furthermore, the CBD mobilises resources and may provide finances to developing countries for the purpose of implementing the Convention (e.g. via the Global Environment Facility).
An important area where the CBD and SDGs exert influence is through fostering collaborations, between different biodiversity-related conventions and among relevant organisations and stakeholder groups at all subglobal scales. Alongside IPBES, they have also raised awareness of the values of biodiversity and their integration in other societal goals.
15.7 What next – how to engage?
As demonstrated, the past decades have seen an alignment of biodiversity-related agendas with different sectoral policies. Now the Aichi Biodiversity Targets and the SDGs need an increased implementation effort to deliver tangible results. In the national policy context this hinges on ensuring consistency within and between these two agendas and other political processes, effective governance systems, institutions and partnerships, and intellectual and financial resources (ICSU, 2017). Scientists can – jointly with societal and policy actors – help to provide supporting evidence (see also Schmalzbauer & Visbeck, Reference Schmalzbauer and Visbeck2016):
to build new partnerships across disciplines, to engage different knowledge domains and thereby foster innovation;
to develop problem- and solution-oriented metrics, tools and indicators to aid the process of continuous learning and adaptive management;
to provide open-source and open-access data and infrastructure to share knowledge and good practice;
to conduct economic, social and health cost–benefit analyses to assess joint action versus silo approaches;
to assist forecasting and informed decision-making through scenarios and models.
In order to maximise the impact of science in society through international conventions, national policies and local implementations, scientists can:
address conservation questions in their own research and proactively enhance the transferability of research results as evidence for real-world application;
actively engage with government agencies, NGOs and the public to learn about their knowledge needs, the ongoing political processes and the mode of operation, to enhance the societal relevance of their own research and better frame and communicate own research findings in a policy context (see Chapters 10 and 13);
attend meetings of CBD, SDG, IPBES and other relevant conventions and initiatives as experts, observers, stakeholders or delegations through the channels of organisations and countries;
proactively engage as authors or reviewers in IPBES assessments or other science–policy reports and contribute scientific evidence throughout the process, even if not a formal contributing author. IPBES has open calls and is open for engagement on many levels;
develop transdisciplinary research collaborations and networks with experts from agencies, NGOs and other civic organisations.
This engagement at the science–policy interface requires time, openness and willingness for true collaboration between scientists, policy advisors and practitioners. While not always easy in short-term research funding circles, this can be very rewarding for everyone involved. Overall, conservation can only move forward when aligned with other policy goals and through integral support of all disciplines and all sectors to work for ‘People and Nature’.
The authors wish to thank UFZ and iDiv colleagues for inspiring discussions and the German Network Forum for Biodiversity Research (NEFO, FKZ 01LC0831 A2) for support.