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This article highlights some ways in which scholarly work in environmental and natural resource economics may be affected by, and may unintentionally further, racial inequity. We discuss four channels through which these effects may occur. The first is prioritization of efficiency over distribution. The second is inattention to procedural justice. The third involves abstraction away from crucial historical or social contexts. The fourth is a narrow focus on problems that fit neatly within existing analytical and empirical frameworks. We follow these threads through three areas in which we offer examples of how environmental and natural resource economics work may further racial inequity. The first involves methods of evaluating and measuring human and social welfare. The second relates to policy modeling choices. The third centers on analysis of management of the commons. We document opportunities to improve the field by better considering how racial inequity may affect, and be affected by, environmental and natural resource economic analysis. Scholars in this field have tools that can mitigate systemic racism in access to natural resources and a clean environment, but work must be done before that potential is realized.

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

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.

The use of images in choice experiment surveys has been increasing over time. Research on the impact of complex graphical displays of information on respondent comprehension and the quality of preference estimates yields mixed results. We contribute to this literature by leveraging a split-sample design for a choice experiment concerning green roofs in Portland, Oregon, to investigate the effects of including high-quality static images in the survey instrument and in the choice cards. We find that respondents who completed the ‘image’ version of our survey had a significantly higher total willingness to pay (TWTP) to support a new green roof program than respondents who completed the ‘text only’ version of the survey. We explore the relationship between respondent characteristics and TWTP and find that respondents with little knowledge about green roofs who completed the image survey have a TWTP that is over three times larger than text survey respondents. Our findings support the trend in the literature of using images in choice experiments but also highlight the importance of paying attention to image quality in survey design, using focus groups with mixed previous knowledge for survey refinement, and gathering information in surveys themselves about respondents’ prior knowledge about the valuation scenario.

The rate and extent of anthropogenic alteration of the global nitrogen cycle over the past four decades has been extensive, resulting in cascading negative impacts on riverine and coastal water quality. In this paper, we investigate the individual effects of a set of management, technology, and policy mechanisms that alter total reactive nitrogen (TN) flux through rivers, using a modified, spatially detailed SPARROW TN model, between 1980 and 2019 in the Northeast (NE) and Midwest (MW) of the United States. Using the recalibrated model, we simulate and validate a historical baseline, to which we compare a set of climate and non-climate single factor experiments (SFEs) in which individual factors are held at 1980s levels while all other factors change dynamically. We evaluate SFE performance in terms of differences in TN flux and willingness to pay. The largest effect on TN flux are related to reduction in cropland area and atmospheric nitrogen deposition. Multi-factor experiments (MFEs) suggest that increasingly efficient corn cultivars had a larger influence than increasing fertilizer application rate, while population growth has a larger influence than wastewater treatment. Extreme climate SFEs suggest that persistent wet conditions increase TN flux throughout the study region. Meanwhile, persistent hot years result in reduced TN flux. The persistent dry climate SFE leads to increased TN flux in the NE and reduced TN flux in the MW. We find that the potential for TN removal through aquatic decay is greatest in MW, due to the role of long travel time of rivers draining into the Lower Mississippi River. This paper sheds light on how a geographically and climatologically diverse region would respond to a representative selection of management options.

Introduction: Recent work examining the impact of climate-change induced extremes on food-energy-water systems (FEWS) estimates the potential changes in physical flows of multiple elements of the systems. Climate adaptation decisions can involve tradeoffs between different system outcomes. Thus, it is important for decision makers to consider the potential changes in monetary value attributed to the observed changes in physical flows from these events, since the value to society of a unit change in an outcome varies widely between thing like food and energy production, water quality, and carbon sequestration. Methods: We develop a valuation tool (FEWSVT) that applies theoretically sound valuation techniques to estimates changes in value for four parameters within the food-energy-water nexus. We demonstrate the utility of the tool through the application of a case study that analyzes the monetary changes in value of a modelled heat wave scenario relative to historic (baseline) conditions in two study regions in the United States. Results: We find that food (corn and soybeans) comprises the majority (89%) of total changes in value, as heatwaves trigger physical changes in corn and soybeans yields. We also find that specifying overly simplified and incorrect valuation methods lead to monetary values that largely differ from FEWSVT results that use accepted valuation methods. Discussion: These results demonstrate the value in considering changes in monetary value instead of just physical flows when making decisions on how to distribute investments and address the many potential impacts of climate change-induced extremes.

Change to global climate, including both its progressive character and episodic extremes, constitutes a critical societal challenge. We apply here a framework to analyze Climate-induced Extremes on the Food, Energy, Water System Nexus (C-FEWS), with particular emphasis on the roles and sensitivities of traditionally-engineered (TEI) and nature-based (NBI) infrastructures. The rationale and technical specifications for the overall C-FEWS framework, its component models and supporting datasets are detailed in an accompanying paper (Vörösmarty et al., this issue). We report here on initial results produced by applying this framework in two important macro-regions of the United States (Northeast, NE; Midwest, MW), where major decisions affecting global food production, biofuels, energy security and pollution abatement require critical scientific support. We present the essential FEWS-related hypotheses that organize our work with an overview of the methodologies and experimental designs applied. We report on initial C-FEWS framework results using five emblematic studies that highlight how various combinations of climate sensitivities, TEI-NBI deployments, technology, and environmental management have determined regional FEWS performance over a historical time period (1980–2019). Despite their relative simplicity, these initial scenario experiments yielded important insights. We found that FEWS performance was impacted by climate stress, but the sensitivity was strongly modified by technology choices applied to both ecosystems (e.g., cropland production using new cultivars) and engineered systems (e.g., thermoelectricity from different fuels and cooling types). We tabulated strong legacy effects stemming from decisions on managing NBI (e.g., multi-decade land conversions that limit long-term carbon sequestration). The framework also enabled us to reveal how broad-scale policies aimed at a particular net benefit can result in unintended and potentially negative consequences. For example, tradeoff modeling experiments identified the regional importance of TEI in the form wastewater treatment and NBI via aquatic self-purification. This finding, in turn, could be used to guide potential investments in point and/or non-point source water pollution control. Another example used a reduced complexity model to demonstrate a FEWS tradeoff in the context of water supply, electricity production, and thermal pollution. Such results demonstrated the importance of TEI and NBI in jointly determining historical FEWS performance, their vulnerabilities, and their resilience to extreme climate events. These infrastructures, plus technology and environmental management, constitute the “policy levers” which can actively be engaged to mitigate the challenge of contemporary and future climate change.

Although many migratory species are of conservation concern, traditional conservation policies and economic analysis rarely address the unique characteristics of migratory species, limiting their impact. After a brief description of key attributes of migratory species, this paper explores how those features alter approaches to answering critical conservation policy questions: where, when, with what tools, and which migratory species to conserve? Because migratory species make movement decisions across space and time, migratory species conservation also considers the joint question of when and where to conserve. Policy analysis that considers the spatial–temporal actions of migratory species throughout their annual habitat and incorporates the use of near real-time information is of particular importance for migratory species conservation. Regression analysis of increasingly available spatial–temporal data about species movements could generate important insights about species responses to human-managed landscapes and provide inputs that simplify and empirically ground spatial–dynamic conservation policy analysis.

Widespread global grassland de-struction motivates restoration efforts. How-ever, little research on public preferences exists to inform restoration decisions, and reduced exposure to nature such as grass-lands could diminish public willingness to pay (WTP) for it. We conducted a choice exper-iment to estimate preferences over tallgrass prairie grassland restorations and quantify how those preferences are correlated with childhood experiences. We find that WTP for grassland restoration can be large, especially with recreational opportunities. Further, peo-ple who participated in outdoor activities or grew up near grasslands during their child-hood place a higher value on grassland res-toration than people who did not.

Climate change continues to challenge food, energy, and water systems (FEWS) across the globe and will figure prominently in shaping future decisions on how best to manage this nexus. In turn, traditionally engineered and natural infrastructures jointly support and hence determine FEWS performance, their vulnerabilities, and their resilience in light of extreme climate events. We present here a research framework to advance the modeling, data integration, and assessment capabilities that support hypothesis-driven research on FEWS dynamics cast at the macro-regional scale. The framework was developed to support studies on climate-induced extremes on food, energy, and water systems (C-FEWS) and designed to identify and evaluate response options to extreme climate events in the context of managing traditionally engineered (TEI) and nature-based infrastructures (NBI). This paper presents our strategy for a first stage of research using the framework to analyze contemporary FEWS and their sensitivity to climate drivers shaped by historical conditions (1980–2019). We offer a description of the computational framework, working definitions of the climate extremes analyzed, and example configurations of numerical experiments aimed at evaluating the importance of individual and combined driving variables. Single and multiple factor experiments involving the historical time series enable two categories of outputs to be analyzed: the first involving biogeophysical entities (e.g., crop production, carbon sequestered, nutrient and thermal pollution loads) and the second reflecting a portfolio of services provided by the region’s TEI and NBI, evaluated in economic terms. The framework is exercised in a series of companion papers in this special issue that focus on the Northeast and Midwest regions of the United States. Use of the C-FEWS framework to simulate historical conditions facilitates research to better identify existing FEWS linkages and how they function. The framework also enables a next stage of analysis to be pursued using future scenario pathways that will vary land use, technology deployments, regulatory objectives, and climate trends and extremes. It also supports a stakeholder engagement effort to co-design scenarios of interest beyond the research domain.

Urgent calls for actions to slow climate change have stimulated new interest in actions to harness the potential for carbon sequestration on agricultural lands. The private sector has established corporate goals for reducing contributions to climate change and there has been much decentralized market activity to develop voluntary markets for agricultural soil carbon sequestration to meet this demand from companies and consumers wishing to offset emissions. This brief conducts a critical assessment of the nature of the market opportunity today for farmers and for those who would benefit from the opportunity to incentivize real increases in net carbon sequestered in agricultural lands of the U.S. We discuss how the potential success of these markets is currently limited by important factors related to contract design and land tenure, with suggestions for how to address the challenges and unlock the opportunities.

Green roofs are being incorporated into stormwater management programs around the world. While numerous studies have estimated the private benefits to the owners and residents of buildings with green roofs, the value of the multiple public benefits received by non-building residents are less well known. We use a choice experiment survey to estimate the public benefits for a proposed green roof program in Portland, Oregon, USA. These benefits include reduced combined sewer overflows, reduced urban heat island effects, and an increase in pollinators such as birds, bees and butterflies. Past investments in stormwater infrastructure have exposed some residents to poor water quality and urban flooding, so we also explore if respondents’ willingness to pay varies based on where new green roofs are located. Across models, the largest estimated benefit in our study area is from a reduction in combined sewer overflows. Model results also show that respondents prefer to not fully concentrate new green roofs in Portland’s Central City area, which is where most green roofs are currently located. Total willingness to pay estimates for the 1-year program range from around $202 to $442 per household, or $54.4 to $116.8 million for the city of Portland, Oregon, depending on program characteristics.

Economic research and frameworks, comprehensively synthesized in “The Economics of Biodiversity: The Dasgupta Review” (Dasgupta 2021), can do much to help stem global biodiversity loss. However, ingrained features of economics as a discipline often produce explanations and solutions for environmental problems that advantage wealthy and powerful entities in our global society rather than those who are poor or otherwise marginalized. This paper highlights two dimensions of economic research related to biodiversity where disciplinary bias can lead to ineffective and inequitable work: biodiversity valuation, and targeting causes of biodiversity loss to be changed. First, it shows how valuation approaches can best be used to inform actions that capture both use and non-use values and include the perspectives and needs of people who are typically marginalized in governance processes. Second, it discusses how global action to preserve biodiversity will be cost-ineffective and inequitable unless we take at least some steps to identify and correct actions taken by wealthy countries and large-scale producers that contribute much to the biodiversity crisis, rather than focusing policy primarily on the behavior of low-income individuals and households.

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.

Homeowner buyout programs promote climate adaptation efforts by removing homes from floodplains. We estimate homeowner willingness to pay (WTP) for a novel agreement in which they precommit to relocating if a flood severely damages their home in exchange for an expedited buyout process. We find nearly all respondents identified positive WTP to enroll in this program, with average WTP about $600. Factors like flood risk and expectation of neighbors’ responses significantly affect WTP. If the pre-flood agreement is available only if the homeowner has flood insurance, only 68% of homeowners were willing to accept the agreement.

Bison is an important and iconic mammal in the U.S. that is being reintroduced in many places after being driven nearly to extinction. This paper provides a nationwide assessment of the local economic impacts of bison reintroduction so that rural communities can take economic well-being into account when considering decisions regarding future bison restorations. We estimate the causal impacts of bison herd establishment on county-level income, employment, and population growth using staggered difference-in-difference and the synthetic control approaches. The simple positive correlation between local per capita income and bison herds might lead planners to think that bison reintroduction is good for the local economy. However, none of the causal inference analyses find statistically significant effects of bison reintroduction.

Nonmarket natural capital provides crucial inputs across the economy. We use land rental market data to calculate the welfare impacts of a change in an unpriced natural capital while accounting for spatial spillovers. We apply the welfare analysis to examine the cost of white-nose syndrome (WNS) in bats, which provide pest control services to agricultural producers. WNS, a disease that decimates bat populations, arrived in the United States in the mid-2000s. Leveraging the exogenous change in bat populations, we find that the loss of bats in a county causes land rental rates to fall by $2.84 per acre plus $1.50 per acre per neighboring county with WNS. Agricultural land falls by 1,102 acres plus 582 acres per neighboring county with WNS. As of 2017, agricultural losses from WNS were between $426 and $495 million per year. These estimates of ecosystem service values can inform public management of society’s natural capital.

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.