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Despite the progress in conservation risk management, conservation organizations are reluctant to interface usable risk-diversification strategies with their decision-making processes. One reason for this reluctance is that the empirical models used to develop risk-diversification strategies need the expected returns on investment (ROIs) of target assets and their variances and covariances, and the probabilities of occurrence of the scenarios needed to calculate those statistics are almost always unknown. We examine how risk diversification for conservation is influenced by the probabilities assigned to uncertainty scenarios using a case study involving the conservation of biodiversity at the county level in the central and southern Appalachian region within the framework of modern portfolio theory. A comparison of risk-mitigating portfolios with bootstrapped and fixed probability distributions shows that introducing the flexibility of an unknown probability distribution of uncertainty scenarios allows conservation organizations to spread bets more than with the inflexibility of the fixed probability distribution, while also achieving higher expected ROIs per unit of risk on average. The improvement becomes more significant when conservation organizations are less risk averse.
Conservation organizations often need to develop risk-diversification strategies that identify not just what species to protect but also where to protect them. The objective of this research is to identify optimal conservation investment allocations for both target sites and species under conditions of uncertainty. We develop a two-step approach using modern portfolio theory (MPT) to estimate percentages of conservation investment (referred to as ‘portfolio weights’) for counties and taxonomic groups in the central and southern Appalachian region under climate and market uncertainties. The portfolio weights across the counties and taxonomic groups from the two steps entail both spatial and taxonomic diversification strategies. Conservation decisions that allow for selecting sites for risk diversification fit the purpose of the first step. Likewise, conservation investments that benefit the biodiversity of particular taxonomic groups for the selected sites are made based on the relative importance of diversifying risk among species in a given area, fitting the purpose of the second step. The two-step MPT approach as a whole allows the greatest flexibility on where and what to protect for conservation investment under uncertainty, and thus would be applicable for the distribution of general conservation funds without predisposition towards protecting either specific sites or species.
Consensus does not exist for which cost forms (i.e., one accounting solely for explicit cost and the other for both explicit and opportunity costs as in relative opportunity cost) are used in calculating return on investment (ROI) for conservation-related decisions. This research examines how the cost of conservation investment with and without inclusion of the opportunity cost of the protected area results in different solutions in a multi-objective optimization framework at the county level in the Central and Southern Appalachian Region of the USA. We maximize rates of ROI of both forest-dependent biodiversity and economic impact generated by forest-based payments for ecosystem services. We find that the conservation budget is optimally distributed more narrowly among counties that are more likely to be rural when the investment cost measure is relative opportunity cost than when it is explicit cost. We also find that the sacrifice in forest-dependent biodiversity per unit increase in economic impact is higher when investment cost is measured by relative opportunity cost rather than when measured by explicit cost. By understanding the consequences of using one cost measure over the other, a conservation agency can decide on which cost measure is more appropriate for informing the agency’s decision-making process.
We analyze optimal budget allocations to acquire protected areas for carbon storage while balancing risk and return from protection under economic growth uncertainty in a local community. Our study is the first to explore how risk of uncertain economic growth affects cost of protected area acquisition using real estate values at the parcel level, enabling us to estimate the site-specific opportunity cost of carbon storage. The Pareto optimal trade-off frontier between the expected carbon storage benefit and its variance provides a continuum of risk-return combinations. The pattern of the trade-off relationship implies that risk mitigation is less costly in terms of foregone expected benefit when risk is higher than when it is lower. Our results also find that the difference in cluster-specific budget allocations between the strong economic growth scenario and the weak economic growth scenario subsequently decreases between the point of expected benefit maximization and the point of variance minimization. Our findings of optimal hectares of land for protected area acquisition for carbon storage and corresponding benefits and costs serve as an empirically informed knowledge base to help a local community prioritize acquisition of potential protected areas for carbon storage under economic growth uncertainty.
Forest carbon sequestration plays an important role in reducing the build-up of greenhouse gases that are known to contribute to global climate change. However, private landowners will supply less carbon sequestration than would be socially desirable if they are unable to capture the economic value of sequestration. We examine the viability of offering landowners property tax subsidies for forest carbon sequestration (referred to as a ‘tax-based subsidy approach’). Waiving property taxes on forestland provides incentives for landowners to afforest non-forested land and/or sustain forests that are at risk of deforestation. We focus on 17 Tennessee counties and one Kentucky county, constituting one of 179 Bureau of Economic Analysis areas in the United States, as a case study. Higher forestland net return from waiving property taxes increases the share of forestland in the 18 counties, which in turn increases the accumulation of carbon in the forest ecosystem, suggesting that this is a viable approach. The annualized county-level cost of supplying forest carbon sequestration using a tax-based subsidy ranges between US$15.56 and US$563.58 per carbon tonne across the 18 counties. Relevant government agencies can use these estimates to target selected counties for more cost-effective adoption of the county-level tax-based subsidy approach.
This study uses locally weighted regression to identify county-level characteristics that serve as drivers of creative employment throughout the southern United States. We found that higher per capita income, greater infrastructure investments, and the rural nature of a county tended to promote creative employment density, while higher scores on a natural amenity index had the opposite effect. We were also able to identify and map clusters of rural counties where the marginal effects of these variables on creative employment density were greatest. These findings should help rural communities to promote creative employment growth as a means of furthering rural economic development.
A two-stage multinomial logit selection model is used to model the relationship between demographic characteristics and housing density across Tennessee's six metropolitan statistical areas. The study finds that there is both spatial correlation and heterogeneity in the spatial distribution of housing both within and across the six areas. For example, Memphis, the most densely populated area, has the least amount of spatial correlation among housing density at the neighborhood level, while Johnson City, which has the lowest overall housing density, has the highest degree of spatial correlation.
This study estimates the effects of an urban growth boundary (UGB) on land development decisions in Knox County, TN, using a heteroscedastic probit model. With combined effects of increased land development within the city boundary and decreased development within the UGB and the neighboring town of Farragut after the implementation of UGB, the UGB of Knox County has been successful in urban revitalization within the city boundary and discouraging urban sprawl. These UGB impacts may be related to the city government having the right to annex land parcels within the UGB without consent of land owners.
This study evaluated the impacts of earlier traumatic events on the mental health of older adults, in terms of mental disorders and mental well-being, according to sociodemographic variables, trauma-related characteristics, and personality traits in a nationally representative sample of older Koreans.
A total of 1,621 subjects aged 60 to 74 years from a Korean national epidemiological survey of mental disorders responded face-to-face interviews. The Korean Composite International Diagnostic Interview was used to investigate lifetime trauma exposure (LTE) and psychiatric diagnoses. The EuroQol health classification system and life satisfaction scale were used to assess quality of life (QoL), and the Big Five Inventory-10 (BFI-10) to measure personality traits.
Five-hundred and seventy-seven subjects (35.6%) reported a history of LTE (mean age at trauma, 30.8 years old). Current mental disorders were more prevalent in elderly people with LTE, while better current QoL was more frequent in those without LTE. Among older people with LTE, lower extraversion and higher neuroticism increased the risk of current mood or anxiety disorders, whereas higher extraversion increased the probability of experiencing mental well-being after adjusting for sociodemographic and trauma-related variables.
Personality traits, especially extraversion, and neuroticism, may be useful for predicting the mental health outcomes of LTE in older adults. Further longitudinal studies investigating the relationship between traumatic events and mental health outcomes are needed.
The impact of an urban growth boundary (UGB) on land development in Knox County, TN is estimated via two-stage probit and neural-network models. The insignificance of UGB variable in the two-stage probit model and more visible development patterns in the western part of Knoxville and the neighboring town of Farragut during the post-UGB period in both models suggest that the UGB has not curtailed urban sprawl. Although the network model is found to be a viable alternative to more conventional discrete choice approach for improving the predictability of land development, it is at the cost of evaluating marginal effects.
This study compares an ordered probit model and a Tobit model with selection to take into account both true zero and protest zero bids while estimating the willingness to pay (WTP) for conservation easements in Macon County, NC. By comparing the two models, the ordered/unordered selection issue of the protest responses is analyzed to demonstrate how the treatment of protest responses can significantly influence WTP models. Both models consistently show that income and knowledge are positive and significant factors, while distance to poorer quality streams and duration of residency are negative and significant factors on WTP.
We have conducted low-temperature flip-chip bonding for both optical interconnect and microwave applications. Flip-chip bonding of vertical-cavity surface-emitting laser (VCSEL) arrays was performed on a fused silica substrate that provides propagation paths of laser beams and also supports a polymeric waveguide. To avoid thermal damage of the polymeric waveguide during the flip-chip bonding, indium bumps were used and the bonding condition of the flip-chip was determined as a heating temperature of 150 °C and a pressure of 500 gf. Experimentally, a thin silver (Ag) layer coated on the indium bump was very effective to enhance the adhesion strength between the indium bump and the VCSEL chip pads. In addition, the microwave characteristic of coplanar waveguide (CPW) package was slightly improved by the Ag coating.
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