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In late December 1973, the United States enacted what some would come to call "the pitbull of environmental laws." In the 50 years since, the formidable regulatory teeth of the Endangered Species Act (ESA) have been credited with considerable successes, obliging agencies to draw upon the best available science to protect species and habitats. Yet human pressures continue to push the planet toward extinctions on a massive scale. With that prospect looming, and with scientific understanding ever changing, Science invited experts to discuss how the ESA has evolved and what its future might hold. -Brad Wible.
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Land conservation efforts throughout the United States sustain ecological benefits while generating wealth in the housing market through capitalization of amenities. This paper estimates the benefits of conservation that are capitalized into proximate home values and quantifies how those benefits are distributed across demographic groups. Using detailed property and household-level data from Massachusetts, we estimate that new land conservation led to $62 million in new housing wealth equity. However, houses owned by low-income or Black or Hispanic households are less likely to be located near protected areas, and hence, these populations are less likely to benefit financially. Direct study of the distribution of this new wealth from capitalized conservation is highly unequal, with the richest quartile of households receiving 43%, White households receiving 91%, and the richest White households receiving 40%, which is nearly 140% more than would be expected under equal distribution. We extend our analysis using census data for the entire United States and observe parallel patterns. We estimate that recent land conservation generated $9.8 billion in wealth through the housing market and that wealthier and White households benefited disproportionately. These findings suggest regressive and racially disparate incidence of the wealth benefits of land conservation policy.
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Conservação dos Recursos Naturais , Status Econômico , Habitação , Humanos , Características da Família , Hispânico ou Latino , Pobreza , Estados Unidos , Negro ou Afro-Americano , BrancosRESUMO
The lives lost and economic costs of viral zoonotic pandemics have steadily increased over the past century. Prominent policymakers have promoted plans that argue the best ways to address future pandemic catastrophes should entail, "detecting and containing emerging zoonotic threats." In other words, we should take actions only after humans get sick. We sharply disagree. Humans have extensive contact with wildlife known to harbor vast numbers of viruses, many of which have not yet spilled into humans. We compute the annualized damages from emerging viral zoonoses. We explore three practical actions to minimize the impact of future pandemics: better surveillance of pathogen spillover and development of global databases of virus genomics and serology, better management of wildlife trade, and substantial reduction of deforestation. We find that these primary pandemic prevention actions cost less than 1/20th the value of lives lost each year to emerging viral zoonoses and have substantial cobenefits.
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We use the full administrative records from four leading agricultural economics journals to study the impacts of the COVID-19 pandemic on manuscript submission, editorial desk rejection and reviewer acceptance rates, and time to editorial decision. We also test for gender differences in these impacts. Manuscript submissions increased sharply and equi-proportionately by gender. Desk rejection rates remained stable, leading to increased demand for reviews. Female reviewers became eight percentage points more likely to decline a review invitation during the early stage of the pandemic. First editorial decisions for papers sent out for peer review occurred significantly faster after pandemic lockdowns began. Overall, the initial effects of the pandemic on journal editorial tasks and review patterns appear relatively modest, despite the increased number of submissions handled by editors and reviewers. We find no evidence in agricultural economics of a generalized disruption to near-term, peer-reviewed publication.
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Carbon storage by ecosystems is valuable for climate protection. Biodiversity conservation may help increase carbon storage, but the value of this influence has been difficult to assess. We use plant, soil, and ecosystem carbon storage data from two grassland biodiversity experiments to show that greater species richness increases economic value: Increasing species richness from 1 to 10 had twice the economic value of increasing species richness from 1 to 2. The marginal value of each additional species declined as species accumulated, reflecting the nonlinear relationship between species richness and plant biomass production. Our demonstration of the economic value of biodiversity for enhancing carbon storage provides a foundation for assessing the value of biodiversity for decisions about land management. Combining carbon storage with other ecosystem services affected by biodiversity may well enhance the economic arguments for conservation even further.
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Climate-change induced uncertainties in future spatial patterns of conservation-related outcomes make it difficult to implement standard conservation-planning paradigms. A recent study translates Markowitz's risk-diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However, this method is information intensive and requires a large number of forecasts of ecological outcomes associated with possible climate-change scenarios for carrying out fine-resolution conservation planning. We developed a technique for iterative, spatial portfolio analysis that can be used to allocate scarce conservation resources across a desired level of subregions in a planning landscape in the absence of a sufficient number of ecological forecasts. We applied our technique to the Prairie Pothole Region in central North America. A lack of sufficient future climate information prevented attainment of the most efficient risk-return conservation outcomes in the Prairie Pothole Region. The difference in expected conservation returns between conservation planning with limited climate-change information and full climate-change information was as large as 30% for the Prairie Pothole Region even when the most efficient iterative approach was used. However, our iterative approach allowed finer resolution portfolio allocation with limited climate-change forecasts such that the best possible risk-return combinations were obtained. With our most efficient iterative approach, the expected loss in conservation outcomes owing to limited climate-change information could be reduced by 17% relative to other iterative approaches.
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Mudança Climática , Conservação dos Recursos Naturais , América Central , Clima , Previsões , Humanos , América do NorteRESUMO
Establishing nature reserves protects species from land cover conversion and the resulting loss of habitat. Even within a reserve, however, many factors such as fires and defoliating insects still threaten habitat and the survival of species. To address the risk to species survival after reserve establishment, reserve networks can be created that allow some redundancy of species coverage to maximize the expected number of species that survive in the presence of threats. In some regions, however, the threats to species within a reserve may be spatially correlated. As examples, fires, diseases, and pest infestations can spread from a starting point and threaten neighboring parcels' habitats, in addition to damage caused at the initial location. This paper develops a reserve site selection optimization framework that compares the optimal reserve networks in cases where risks do and do not reflect spatial correlation. By exploring the impact of spatially-correlated risk on reserve networks on a stylized landscape and on an Oregon landscape, this analysis demonstrates an appropriate and feasible method for incorporating such post-reserve establishment risks in the reserve site selection literature as an additional tool to be further developed for future conservation planning.
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Ecossistema , Modelos BiológicosRESUMO
Protected area networks are designed to restrict anthropogenic pressures in areas of high biodiversity. Resource users respond by seeking to replace some or all of the lost resources from locations elsewhere in the landscape. Protected area networks thereby perturb the pattern of human pressures by displacing extractive effort from within protected areas into the broader landscape, a process known as leakage. The negative effects of leakage on conservation outcomes have been empirically documented and modeled using homogeneous descriptions of conservation landscapes. Human resource use and biodiversity vary greatly in space, however, and a theory of leakage must describe how this heterogeneity affects the magnitude, pattern, and biodiversity impacts of leakage. We combined models of household utility, adaptive human foraging, and biodiversity conservation to provide a bioeconomic model of leakage that accounts for spatial heterogeneity. Leakage had strong and divergent impacts on the performance of protected area networks, undermining biodiversity benefits but mitigating the negative impacts on local resource users. When leakage was present, our model showed that poorly designed protected area networks resulted in a substantial net loss of biodiversity. However, the effects of leakage can be mitigated if they are incorporated ex-ante into the conservation planning process. If protected areas are coupled with nonreserve policy instruments such as market subsidies, our model shows that the trade-offs between biodiversity and human well-being can be further and more directly reduced.
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Biodiversidade , Conservação dos Recursos Naturais/métodos , Ecossistema , Modelos TeóricosAssuntos
Conservação dos Recursos Naturais/legislação & jurisprudência , Conservação dos Recursos Naturais/estatística & dados numéricos , Espécies em Perigo de Extinção/estatística & dados numéricos , Animais , Conservação dos Recursos Naturais/economia , Conservação dos Recursos Naturais/tendências , Ecossistema , Espécies em Perigo de Extinção/economia , Espécies em Perigo de Extinção/legislação & jurisprudência , Extinção Biológica , Modelos Biológicos , Modelos Econômicos , Estados UnidosRESUMO
Climate change is likely to alter the spatial distributions of species and habitat types but the nature of such change is uncertain. Thus, climate change makes it difficult to implement standard conservation planning paradigms. Previous work has suggested some approaches to cope with such uncertainty but has not harnessed all of the benefits of risk diversification. We adapt Modern Portfolio Theory (MPT) to optimal spatial targeting of conservation activity, using wetland habitat conservation in the Prairie Pothole Region (PPR) as an example. This approach finds the allocations of conservation activity among subregions of the planning area that maximize the expected conservation returns for a given level of uncertainty or minimize uncertainty for a given expected level of returns. We find that using MPT instead of simple diversification in the PPR can achieve a value of the conservation objective per dollar spent that is 15% higher for the same level of risk. MPT-based portfolios can also have 21% less uncertainty over benefits or 6% greater expected benefits than the current portfolio of PPR conservation. Total benefits from conservation investment are higher if returns are defined in terms of benefit-cost ratios rather than benefits alone. MPT-guided diversification can work to reduce the climate-change-induced uncertainty of future ecosystem-service benefits from many land policy and investment initiatives, especially when outcomes are negatively correlated between subregions of a planning area.
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Clima , Conservação dos Recursos Naturais , Incerteza , Estados Unidos , Áreas AlagadasRESUMO
The expense and inconvenience of enhanced-vehicle-emissions testing using the full 240-second dynamometer test has led states to search for ways to shorten the test process. In fact, all states that currently use the IM240 allow some type of fast-pass, usually as early in the test as second 31, and Arizona has allowed vehicles to fast-fail after second 93. While these shorter tests save states millions of dollars in inspection lanes and driver costs, there is a loss of information since test results are no longer comparable across vehicles. This paper presents a methodology for estimating full 240-second results from partial-test results for three pollutants: HC, CO, and NOx. If states can convert all tests to consistent IM240 readings, they will be able to better characterize fleet emissions and to evaluate the impact of inspection and maintenance and other programs on emissions over time. Using a random sample of vehicles in Arizona which received full 240-second tests, we use regression analysis to estimate the relationship between emissions at second 240 and emissions at earlier seconds in the test. We examine the influence of other variables such as age, model-year group, and the pollution level itself on this relationship. We also use the estimated coefficients in several applications. First, we try to shed light on the frequent assertion that the results of the dynamometer test provide guidance for vehicle repair of failing vehicles. Using a probit analysis, we find that the probability that a failing vehicle will pass the test on the first retest is greater the longer the test has progressed. Second, we test the accuracy of our estimates for forecasting fleet emissions from partial-test emissions results in Arizona. We find forecasted fleet average emissions to be very close to the actual fleet averages for light-duty vehicles, but not quite as good for trucks, particularly when NOx emissions are forecast.