Coffee forests are the most valuable land-use systems that provide multiple benefits such as biodiversity conservation, carbon sequestration and source of income. This study aimed to estimate the carbon stock of coffee agroforestry systems and the contribution of coffee plants (Coffea arabica L.) to carbon sequestration in the entire coffee agroforestry systems in southwestern Ethiopia. The carbon stock in trees was estimated by field-based measurements and allometric equations, whereas the carbon stocks in litter and soil were determined using field sampling and laboratory analysis. The carbon stocks of the coffee agroforestry systems in the study site ranged from 254.9 t C/ha in the Syzygium-shaded coffee forest to 321.8 t C/ha in the Albizia-shaded coffee forest. The overall mean carbon sequestration in the present coffee agroforestry systems was 287.1 t C/ha. The net carbon sequestered by coffee plants in the agroforestry systems ranged from 18.8 t C/ha in the Syzygium-shaded coffee stratum to 48.5 t C/ha in the Albizia-shaded coffee stratum. This demonstrates that Albizia is the most compatible shade tree for coffee plants. On average, coffee plants contributed 37.5 t C/ha, accounting for approximately 12.8% of the total carbon sequestered in the coffee agroforestry systems. Hence, we recommend coffee forests for all-in-one benefits such as climate change mitigation, sustainable landscape management and income generation.

Composting from organic municipal solid waste (MSW), such as a separate waste collection, is a valid tool for eliminating a considerable amount of waste that would otherwise be destined for landfills and incinerators, thus representing an effective complement to traditional forms of recycling. It allows organic substance to be recovered and reintegrated into the soil, thus preventing erosion phenomena, increasing the biological fertility of the soil and contributing significantly to the restoration of impoverished sites. Modern winegrowing must address the issue of vineyard fertility in the sustainability context. The goal of this study was to assess the advantages of distributing a sustainable product to the vineyard that can achieve vine balance (vegetative and productive equilibrium). In a Vitis vinifera L. Sangiovese cv., vineyard, four soil treatments were applied (three compost rates and a control): municipal solid waste compost (40 tons per hectare – MSW40, 15 tons per hectare – MSW15, 2.5 tons per hectare – MSW2.5), and no compost (CTRL). The vine physiology (leaf gas exchange and water potential) and berry compositions (phenolic and technological maturity) were studied during the 2018–2019 growing seasons in the Sieci area, Italy. The results of this experiment provide some general insights showing that MSW compost options can be expected to reduce water stress, balanced vine performance and provide sustainable recirculation of organic matter. MSW compost is a true agronomic and environmental resource.

Understanding and representing the transformation of agricultural production systems has attracted increasing interest due to its importance for identifying drivers of changes and coping mechanisms in response to global challenges. These challenges are all the most pressing in North African countries exposed to a dramatic reduction in rainfall and increasing temperatures that affect sustainability in more than half of this semi-arid territory. This paper describes an improved way to understand such transformations through a cross-cutting analysis of crop–livestock system indicators over a period of 10 years in one community in Southern Tunisia. Our methodology is divided into four steps: (i) systems identification, (ii) indicator-based assessment of system crop–livestock sustainability, (iii) hierarchical clustering to identify sustainable intensification (SI)-based farm types and, finally, (iv) analysis of trajectories of these farm types. Results showed that the sustainability of the systems studied increasingly depends on diversification rather than intensification, which dominated in the 2000s. However, diversification has not necessarily improved socio-economic viability. Over the 10-year period, results revealed a dramatic increase of almost 50% in the population of small-scale farms whose viability depends on a range of on- and off-farm activities to meet the short-term needs that correspond to a buffer strategy. Additionally, the dominant SI processes were shown to be mostly based on diversification to livestock activities with both milking and fattening. Our holistic and timeline approach to system transformation makes it possible to account for sustainability between (systems) generations, which will be highly needed in future discussions about sustainability.

Livestock plays a crucial role in food and nutrition security. However, livestock production accounts for 0.18 of global greenhouse gas emissions. India has one of the highest livestock densities globally, mainly produced under traditional systems. Specifically, the emission and particularly nitrogen losses from cattle in traditional systems cannot be ignored. Nitrogen emission is substantial when cattle roam free and waste is not collected or managed efficiently. This paper reviews the literature to piece together the available information on nitrogen emissions from cattle in India to synthesize the evidence, identify gaps and contribute to further understanding of the problem. At the same time, the paper highlights the solutions to reduce nitrogen pollution from cattle production in India. The main findings are that most cattle in India are not reared to provide meat protein. The implication is that reactive nitrogen per capita consumption is lower than most developed countries. However, there are substantial inefficiencies in feed conversion, feed nitrogen use and manure management in India. As a result, nitrogen losses and wastage are considerable in the different production systems. Furthermore, the review suggests that social, cultural and economic factors such as convergent social behaviour, urbanization, regulations, changing consumption patterns, the demand for cheap fuel sources, culture and religion influence the production systems and, consequently, the emissions from livestock. Suggested solutions to reduce nitrogen pollution from cattle production in India are improving livestock productivity, adopting better feeding, manure and pasture management practices and using behavioural nudges.

The goals of this study are to analyse the impacts of 1.5 and 2.0°C scenarios on UK winter wheat using a combination of Global Climate Models (GCMs), crop models, planting dates and cultivars; to evaluate the impact of increased air temperature on winter wheat phenology and potential yield; to quantify the underlying uncertainties due to the multiple sources of variability introduced by climate scenarios, crop models and agronomic management. The data used to calibrate and evaluate three crop models were obtained from a field experiment with two irrigation amounts and two wheat cultivars that have different phenology and growth habit. After calibration, the model was applied to fifty locations across the wheat-growing area of the UK to cover all the main growing regions, with most points located in the main growing areas. Four GCMs, with two cultivars and five planting dates, were simulated at the end of the century. Results of this study showed that the UK potential wheat yield will increase by 2–8% under projected climate. Farmers will need to close such a gap in the future because it will have implications in terms of food security. Future climatic conditions might increase such a gap. Adaptation measures (e.g. moving the optimal planting time), along with climate-ready varieties bred for future conditions and with precision agriculture techniques can help to reduce this gap and ensure that the future actual UK wheat production will be close to the potential.

Tossa (Corchorus olitorius L.) is a significant cash crop, cultivated commercially in the lower flood plain of Bangladesh. The climatic regimes in Bangladesh are changing as well as the world does. However, this species is threatened by climate change. Occurrences of data on threatened and endangered species are frequently sparse which makes it difficult to analyse the species suitable habitat distribution using various modelling approaches. The current paper used maximum entropy (Maxent) and educational global climate model (EdGCM) modelling to predict and conserve the suitable habitat distributions for Tossa species in Bangladesh to the year 2100. Nine environmental variables, 239 occurrence data and two Representative Concentration Pathway scenarios (RCP4.5 and RCP8.5) were used for the Maxent modelling to project the impact of climate change on the Tossa distributions. Furthermore, the EdGCM was used to study the climatic space suitability for the Tossa species in the context of Bangladesh. Both of the climatic scenarios were used for the prediction to the year 2100. The Maxent model performed better than random for the Tossa species with a high AUC value of 0.86. Under the RCP scenarios, the Maxent model predicted habitat reduction for RCP4.5 is 2%, RCP8.5 is 9% and EdGCM is 10.2% from the current localities. The predictive modelling approach presented here is promising and can be applied to other important species for conservation planning, monitoring and management, especially those under the threat of extinction due to climate change.

High yielding ruminant livestock require high nutritive value in forage for maintenance, growth and production. Climate change has been documented as impacting on the nutritive value of forage plants. Therefore, the aim of this study was to investigate the impact of increased temperature in combination with CO2-enhancement on the nutritive value of orchard grass (cocksfoot; Dactylis glomerata L.), as a C3 model plant, widespread in mountainous permanent grassland plant communities. Functional traits and forage quality of orchard grass were investigated both under ambient (C0T0) and under simulated, future climate conditions (C2T2) with increased temperature (+3°C) and enhanced CO2 concentration (+300 ppm) under field conditions. Plant samples were taken from each of the three growths over a period of three consecutive years and numerous functional properties and forage quality parameters were determined. Special attention was paid to the determination of water-soluble carbohydrates (WSC), crude protein (CP), non-protein N (NPN) and metabolizable energy (ME) as possible indicators for different climatic conditions. It is hypothesized that (i) functional traits and (ii) forage quality of orchard grass are altered by increased temperature and higher CO2 concentration. The results showed a negative impact of C2T2 compared to C0T0 on tiller height (54.4 v. 70.6 cm) and weight (2.42 v. 3.22 g) as average over cuts and years. The NPN content was lower in C2T2 (312 g/kg CP) compared to C0T0 (339 g/kg CP). In contrast, the WSC content was higher in C2T2 (90.3 g/kg DM) compared to C0T0 (82.5 g/kg DM). Both ME content and digestibility were increased in C2T2 (9.18 ME/kg DM and 68.2%) compared to C0T0 (8.86 ME/kg DM and 65.4%). Concluding, under increased temperature and enhanced CO2, both functional traits and certain nutrients and their fractions appear to change in orchard grass.

Agricultural waste contributes significantly to greenhouse gas (GHG) emissions if not adequately recycled and sustainably managed. A recurring agricultural waste is livestock waste that has consistently served as feedstock for biogas systems. The objective of this study was to assess the use of animal waste digestate to mitigate GHG emissions in agricultural fields. Wheat (Triticum spp. L.) was fertilized with different types of animal waste digestate (organic fertilizers) and synthetic nitrogen fertilizer (inorganic fertilizer). The 170 kg N/ha presented in digestates were split fertilized at an application rate of 90 and 80 kg N/ha. Emissions of GHGs (carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O)) were monitored directly by a static chamber system. The soil and environmental variables were measured to determine their influence on GHG emissions. Emission peaks in N2O and CO2 after the first application of fertilizers with the emissions flattening out over the cultivating season while CH4 emission was negligible with no apparent patterns observed. Results showed individual and cumulative emissions of CO2, CH4 and N2O from the digestates were relatively low and digestate fertilization could be an efficient method for reducing GHGs from agricultural sources in temperate climate conditions.

The impact of climate change on agricultural productivity is difficult to assess. However, determining the possible effects of climate change is an absolute necessity for planning by decision-makers. The aim of the study was the evaluation of the CSM-CROPGRO-Sunflower model of DSSAT4.7 and the assessment of impact of climate change on sunflower yield under future climate projections. For this purpose, a 2-year sunflower field experiment was conducted under semi-arid conditions in the Konya province of Turkey. Rainfed and irrigated treatments were used for model analysis. For the assessment of impact of climate change, three global climate models and two representative concentration pathways, i.e. 4.5 and 8.5 were selected. The evaluation of the model showed that the model was able to simulate yield reasonably well, with normalized root mean square error of 1.3% for the irrigated treatment and 17.7% for the rainfed treatment, a d-index of 0.98 and a modelling efficiency of 0.93 for the overall model performance. For the climate change scenarios, the model predicted that yield will decrease in a range of 2.9–39.6% under rainfed conditions and will increase in a range of 7.4–38.5% under irrigated conditions. Results suggest that temperature increases due to climate change will cause a shortening of plant growth cycles. Projection results also confirmed that increasing temperatures due to climate change will cause an increase in sunflower water requirements in the future. Thus, the results reveal the necessity to apply adequate water management strategies for adaptation to climate change for sunflower production.

Shaded coffee systems can mitigate climate change by fixation of atmospheric carbon dioxide (CO2) in soil. Understanding soil organic carbon (SOC) storage and the factors influencing SOC in coffee plantations are necessary for the development of sound land management practices to prevent land degradation and minimize SOC losses. This study was conducted in the main coffee-growing regions of Yunnan; SOC concentrations and storage of shaded and unshaded coffee systems were assessed in the top 40 cm of soil. Relationships between SOC concentration and factors affecting SOC were analysed using multiple linear regression based on the forward and backward stepwise regression method. Factors analysed were soil bulk density (ρb), soil pH, total nitrogen of soil (N), mean annual temperature (MAT), mean annual moisture (MAM), mean annual precipitation (MAP) and elevations (E). Akaike's information criterion (AIC), coefficient of determination (R2), root mean square error (RMSE) and residual sum of squares (RSS) were used to describe the accuracy of multiple linear regression models. Results showed that mean SOC concentration and storage decreased significantly with depth under unshaded coffee systems. Mean SOC concentration and storage were higher in shaded than unshaded coffee systems at 20–40 cm depth. The correlations between SOC concentration and ρb, pH and N were significant. Evidence from the multiple linear regression model showed that soil bulk density (ρb), soil pH, total nitrogen of soil (N) and climatic variables had the greatest impact on soil carbon storage in the coffee system.

One of the major challenges in agriculture is how climate change influences crop production, for different environmental (soil type, topography, groundwater depth, etc.) and agronomic management conditions. Through systems modelling, this study aims to quantify the impact of future climate on yield risk of winter wheat for two common soil types of Eastern Denmark. The agro-ecosystem model DAISY was used to simulate arable, conventional cropping systems (CSs) and the study focused on the three main management factors: cropping sequence, usage of catch crops and cereal straw management. For the case region of Eastern Denmark, the future yield risk of wheat does not necessarily increase under climate change mainly due to lower water stress in the projections; rather, it depends on appropriate management and each CS design. Major management factors affecting the yield risk of wheat were N supply and the amount of organic material added during rotations. If a CS is characterized by straw removal and no catch crop within the rotation, an increased wheat yield risk must be expected in the future. In contrast, more favourable CSs, including catch crops and straw incorporation, maintain their capacity and result in a decreasing yield risk over time. Higher soil organic matter content, higher net nitrogen mineralization rate and higher soil organic nitrogen content were the main underlying causes for these positive effects. Furthermore, the simulation results showed better N recycling and reduced nitrate leaching for the more favourable CSs, which provide benefits for environment-friendly and sustainable crop production.

Longan is an economically important sub-tropical fruit tree native to southern China and southeast Asia. Its production has been affected significantly by climate change, but the underlying reasons remain unclear. Herein, the potential growing areas of longan were simulated by the Maxent model under current and future conditions. The results showed excellent prediction performance, with an area under curve of >0.9 for model training and validation. The key environmental variables identified were mean temperature of the coldest quarter, minimum temperature of the coldest month, annual mean temperature and mean temperature of the driest quarter. The optimum suitable areas of longan were found to be concentrated mainly in south-western, southern and eastern China, with a slight increase in optimum suitable areas under two different emission scenarios of three global climatic models. However, its future potential growing areas were predicted to differ among provinces or cities. Suitable growing areas in Sichuan, Jiangxi, Guangxi and Chongqing will first increase and then remain approximately unchanged between the 2050s and 2070s; those in Yunnan, Guangdong and Hainan will remain approximately unchanged from the present to the 2070s; those in Fujian and Guizhou will fluctuate slightly from the present to the 2050s and then increase to the 2070s; those in Taiwan will first decrease and then increase. In summary, the major future production areas of longan will be Guangdong, Hainan and Guangxi provinces, followed by Chongqing, Yunnan, Fujian and Taiwan. Thus, this study serves as a useful guide for the management of longan.

Climbing cacti with edible fruits have been proposed as new dryland fruit crops because their high water-use efficiency reduces water requirement. One lineage of climbers in the cactus family, the Hylocereus group of Selenicereus, includes several species that produce edible fruits and is currently cultivated around the world. Fruits are known as pitahayas, pitayas or dragon fruit. Here, by means of ecological niche-based modelling and analytical hierarchical modelling, the optimal areas for cultivating the three main species of this group in Mesoamerica – Selenicereus costaricensis, Selenicereus ocamponis and Selenicereus undatus – are identified. Data on distribution, physiological requirement and host preferences are taken into account to carry out ecological modelling for current and future scenarios of climate and determine its impact on cultivation. Two MIROC climatic future models, one optimistic (ssp216) and a pessimistic (ssp585) were selected and 554 records from Mexico and Central America were gathered. For all three species, temperature and precipitation seasonality, and solar radiation were the most significant variables in the niche modelling. In addition, for S. undatus the most important hosts, three species of mesquite legume trees were significant to forecast suitable areas for planting. Large areas on the Pacific side from Sinaloa to Costa Rica were predicted as favourable for cultivating the studied three species. Future scenarios of climate change predicted increase of suitable areas for two species and in particular for S. undatus the increment was the largest. Therefore, dragon fruits are corroborated as promising fruits in view of climate change.

Agroforestry systems can play an important role in mitigating the effects of climate change given their capacity to increase tree diversity and to store more carbon than conventional farming. This study aims at assessing carbon stocks and the use of shade trees in different coffee growing systems in the Northeast Peruvian Amazon. Carbon stocks in trees were estimated by field-based measurements and allometric equations. Carbon stocks in dead wood, litter and soil (upper 60 cm) were determined using field sampling and laboratory analysis. The diversity analysis drew on the Shannon–Weiner diversity index, and focus groups were used to obtain information about the local use of shade trees. The total carbon stock in the polyculture-shaded coffee system was 189 t C/ha, while the Inga-shaded and unshaded systems totalled 146 and 113 t C/ha, respectively. The soil compartment contributed the largest carbon stock in the coffee growing systems and contained 67, 82 and 96% of the total carbon stock in the polyculture-shaded, Inga-shaded and unshaded coffee systems, respectively. The Shannon–Weiner index and tree species richness values were highest for the polyculture-shaded coffee system, with a total of 18 tree species identified as important sources of fodder, food, wood, firewood and medicine. Therefore, coffee agroforestry systems play a significant role in carbon storage, while promoting conservation of useful trees in agricultural landscapes in the Peruvian Amazon.

The current research investigated the present and future projected distribution of rice (Oryza sativa L.) based on climatic suitability under three representative concentration pathways (RCPs) of the Intergovernmental Panel on Climate Change using maximum entropy (MaxEnt) modelling. The MaxEnt models predict that rice distribution in Bhutan will undergo major changes in terms of spatial range shift of varying magnitudes by 2060. Under the anthropogenic radiative forcing of RCP2.6, RCP4.5 and RCP8.5, ecological space of rice is predicted to change between 1 and 43%. Major changes are likely to take place in major rice-growing ecological zones of the country. This is likely to have a negative impact on the livelihood and food security of the people as crop production might start declining due to unfavourable climatic factors. Therefore, the findings of this study could prove beneficial for forecasting focus sites requiring interventions, including future climate research, planning, policy formulation and conservation of natural resources.

Understanding the mechanisms underlying net ecosystem CO2 exchange (NEE) in mountain grasslands is important to quantify their relevance in the global carbon budget. However, complex interactions between environmental variables and vegetation on NEE remain unclear; and there is a lack of empirical data, especially from the high elevations and the Mediterranean region. A chamber-based survey of CO2 exchange measurements was carried out in two climatically contrasted grasslands (montane v. subalpine) of the Pyrenees; assessing the relative contribution of phenology and environmental variables on CO2 exchange at the seasonal scale, and the influence of plant functional type dominance (grasses, forbs and legumes) on the NEE light response. Results show that phenology plays a crucial role as a CO2 exchange driver, suggesting a differential behaviour of the vegetation community depending on the environment. The subalpine grassland had a more delayed phenology compared to the montane, being more temperature than water constrained. However, temperature increased net CO2 uptake at a higher rate in the subalpine than in the montane grassland. During the peak biomass, productivity (+74%) and net CO2 uptake (NEE +48%) were higher in the subalpine grassland than in the montane grassland. The delayed phenology at the subalpine grassland reduced vegetation's sensitivity to summer dryness, and CO2 exchange fluxes were less constrained by low soil water content. The NEE light response suggested that legume dominated plots had higher net CO2 uptake per unit of biomass than grasses. Detailed information on phenology and vegetation composition is essential to understand elevation and climatic differences in CO2 exchange.

Potential planting area for tuber mustard was simulated using the Maxent model under current and future conditions based on 591 coordinates and 22 environmental layers. Model accuracy was excellent, with area under the receiving operator curve values of 0.967 and 0.958 for model training and testing, respectively. Dominant factors were mean diurnal range, mean temperature of the coldest quarter, annual mean temperature and minimum temperature of the coldest month, with thresholds of 6.5–7.5, 5.5–9, 16–19 and 2.0–6.5 °C, respectively. Under current conditions, suitable habitat areas (2.16% of total land in China) were concentrated mainly in Central, Southwest and East China, which can be defined as three occurrence and diffusion centres. In the 2050s and 2070s, suitable habitat areas are predicted to change to 3.72 and 3.92%, and 3.60 and 3.73% under scenarios RCP4.5 and RCP6.0, respectively, indicating that suitable habitat areas will increase slightly. However, future distribution of tuber mustard was predicted to differ among provinces or cities, i.e. predicted suitable habitat areas in Sichuan Province increased up to the 2050s but remained relatively unchanged between the 2050s and 2070s; in Chongqing city they first increased and then decreased; in Hunan, Anhui, Jiangsu, Zhejiang and Fujian Provinces they increased continuously; and in Guizhou, Hubei, Jiangxi Provinces and Shanghai city they first decreased, and then increased. The results from the current study provide useful information for management decisions of tuber mustard.

The current paper tackles a critical question in climate change literature of whether farmers will be able to fully adapt to monsoonal climate changes owing to technological developments. Making use of the climate, agricultural and social data of Thailand from 1900 to 2015, this paper estimates a technological change instrumental variable by the growth of the normalized rice yield per hectare of land. The estimation shows that 0.98 of the growth in rice yield can be attributed to technological changes while the rest is accounted for by climate, soils and social factors. In the second stage regressions with the technological change indicator, the paper estimates the normalized numbers of the six most important types of live animals in Thailand: goats, chickens, cattle, sheep, pigs and buffaloes. Over the time period studied, the number of each of these live animals has increased vastly, except for buffaloes. The second-stage regressions show that the growth is largely attributable to technological changes, but monsoonal climate variables such as normalized monsoon precipitation ratio and normalized monsoon temperature are not significant factors. The results indicate that the rate of technological changes is overwhelming the rate of climate change on agriculture in Thailand.