As one of the main causes of habitat loss, agricultural cropland expansion is a major threat to biodiversity. We analyze past and anticipated future trends in population, per capita crop demand, and crop yield to estimate agricultural cropland requirements globally by 2050 and 2100, assuming moderate levels of climate change. According to a model of "business as usual," higher-income countries would be expected to show little or no net growth in cropland by the end of the century whereas cropland area could nearly double in lower-income countries. We consider two strategies to reduce global cropland expansion: decreasing per capita crop demand in higher-income countries by eating healthier diets, reducing food waste, and reducing biofuel production, and accelerating economic development in lower-income countries. Economic development in lower-income countries could reduce future cropland requirements via slower population growth, improved crop yield, and higher volumes of global crop trade, which could more than offset rising per capita crop demand. These impacts would far exceed reductions in cropland requirements from decreased crop demand in higher-income countries. Further, by combining accelerated economic development in lower-income countries with reduced crop demand in higher-income countries in tandem with reduced trade friction, global cropland requirements could shrink dramatically by the year 2100. Although economic growth is often considered to work in opposition to environmental conservation, accelerating economic development in lower-income countries would not only help alleviate poverty but could also confer benefits for biodiversity and global climate change.

We used the quasi- experimental difference - in - differences method to estimate the impact that the Endangered Species Act's critical habitat (CH) regulation had on developed and undeveloped parcel prices throughout the United States between 2000 and 2019. At the national level we find that, on average, the prices of parcels in CH areas were not statistically different from the prices of similar nearby parcels not in CH. However, limiting our analysis to specific subsets of CH areas, we find mixed results. Previous empirical estimates have consistently found that the regulation reduces parcel prices. We offer several potential explanations for our contradictory results. (JEL Q24, Q57)

The purchase and sale of assets such as housing will increasingly be affected by forces related to a changing climate. This article considers decisions over assets as a neurobiological process in which an associative memory with pattern completion informs choices. We develop these neuroeconomic explanations and analyze their implications for climate change-related shocks in asset markets, and discuss these effects in the context of both individual experiences as well as community-driven remembering. These neuroeconomic models provide mechanistic explanations for behavioral responses to more easily accessed information (the "representativeness " and "availability " heuristics, "framing " and "priming "). Understanding the links from neuroscience to economics is critical to building policies and institutions capable of coping with and adjusting to disasters affecting real assets that are increasing in frequency and scope due to climate change.

Using a dataset of more than 51,000 US lakes, we estimated the relationship between summertime lake visits, lake water clarity, landscape features, and other amenities, where visits were estimated with counts of geo-located photographs. Given the size and complexity of our dataset, we used a combination of machine learning techniques, imputation techniques, and a Poisson count model to estimate these relationships. We found that every additional meter of average summertime Secchi depth was associated with at least 7% more summertime lake visits, all else equal. Second, we found that lake amenities, such as beaches, boat launches, and public toilets, were more powerful predictors of visits than water clarity. Third, we found that visits to a lake were strongly influenced by the lake's accessibility and its distance to nearby lakes and the amenities the nearby lakes offered. Our research highlights the need for (1) a better understanding of how representative social media data are of actual recreational behavior, (2) the development of best practices to account for nonrandom patterns in missing natural feature data, and (3) a better understanding of the potential endogeneity in the lake visit-water quality relationships.

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.

Natural climate solutions (NCS) are recognized as an important tool for governments to reduce greenhouse gas emissions and remove atmospheric carbon dioxide. Using California as a globally relevant reference, we evaluate the magnitude of biological climate mitigation potential from NCS starting in 2020 under four climate change scenarios. By mid-century NCS implementation leads to a large increase in net carbon stored, flipping the state from a net source to a net sink in two scenarios. Forest and conservation land management strategies make up 85% of all NCS emissions reductions by 2050, with agricultural strategies accounting for the remaining 15%. The most severe climate change impacts on ecosystem carbon materialize in the latter half of the century with three scenarios resulting in California ecosystems becoming a net source of carbon emissions under a baseline trajectory. However, NCS provide a strong attenuating effect, reducing land carbon emissions 41-54% by 2100 with total costs of deployment of 752-777 million USD annually through 2050. Rapid implementation of a portfolio of NCS interventions provides long-term investment in protecting ecosystem carbon in the face of climate change driven disturbances. This open-source, spatially-explicit framework can help evaluate risks to NCS carbon storage stability, implementation costs, and overall mitigation potential for NCS at jurisdictional scales.

Trees provide critical contributions to human well-being. They sequester and store greenhouse gasses, filter air pollutants, provide wood, food, and other products, among other benefits. These benefits are threatened by climate change, fires, pests and pathogens. To quantify the current value of the flow of ecosystem services from U.S. trees, and the threats they face, we combine macroevolutionary and economic valuation approaches using spatially explicit data about tree species and lineages. We find that the value of five key ecosystem services with adequate data generated by US trees is $114 billion per annum (low: $85 B; high: $137 B; 2010 USD). The non-market value of trees from carbon storage and air pollution removal far exceed their commercial value from wood products and food crops. Two lineages—pines and oaks—account for 42% of the value of these services. The majority of species face threats from climate change, many face increasing fire risk, and known pests and pathogens threaten 40% of total woody biomass. The most valuable US tree species and lineages are among those most threatened by known pests and pathogens, with species most valuable for carbon storage most at risk from increasing fire threat. High turnover of tree species across the continent results in a diverse set of species distributed across the tree of life contributing to ecosystem services in the U.S. The high diversity of taxa across U.S. forests may be important in buffering ecosystem service losses if and when the most valuable lineages are compromised.

Context Urban-rural gradients are useful tools when examining the influence of human disturbances on ecological, social and coupled systems, yet the most commonly used gradient definitions are based on single broad measures such as housing density or percent forest cover that fail to capture landscape patterns important for conservation. Objectives We present an approach to defining urban–rural gradients that integrates multiple landscape pattern metrics related to ecosystem processes important for natural resources and wildlife sustainability. Methods We develop a set of land cover composition and configuration metrics and then use them as inputs to a cluster analysis process that, in addition to grouping towns with similar attributes, identifies exemplar towns for each group. We compare the outcome of the cluster-based urban-rural gradient typology to outcomes for four commonly-used rule-based typologies and discuss implications for resource management and conservation. Results The resulting cluster-based typology defines five town types (urban, suburban, exurban, rural, and agricultural) and notably identifies a bifurcation along the gradient distinguishing among rural forested and agricultural towns. Landscape patterns (e.g., core and islet forests) influence where individual towns fall along the gradient. Designations of town type differ substantially among the five different typologies, particularly along the middle of the gradient. Conclusions Understanding where a town occurs along the urban-rural gradient could aid local decision-makers in prioritizing and balancing between development and conservation scenarios. Variations in outcomes among the different urban-rural gradient typologies raise concerns that broad-measure classifications do not adequately account for important landscape patterns. We suggest future urban-rural gradient studies utilize more robust classification approaches.

Glaeser et al. (2008) argue that the relative distribution of poor and rich households (HHs) in American cities is “strongly” explained by the spatial location of the cities’ public transportation (PT) networks. Among their claims: 1) The broad distribution of poor and rich HHs in the typical American city is consistent with a basic monocentric city model that includes commute technology speeds; 2) Poor commuters will overwhelmingly transition from commuting by PT to car if they experience a substantial increase in their HH’s income; 3) areas in American cities that receive new PT infrastructure become poorer over time. Using 2017 data I find empirical evidence that partially or wholly contradicts these three claims. First, as of 2017, the observed concentration of poor HHs in the inner city and rich HHs in the suburbs of the US’ smaller cities cannot be explained by monocentric model that includes commute speeds. Second, as of 2017, significant increases in poor HHs’ incomes were not expected to lead to a “massive shift” towards car commuting in these HHs; most of these poor workers commute by car already. Third, using data from four cities that expanded their light-rail and rapid-bus network in the early 2000s, I find that neighborhoods surrounding new light-rail or rapid-bus stations either saw little change in their income patterns or became slightly richer after station opening. In conclusion, as of 2017, the spatial distribution of HH incomes within American urban areas is not as intricately linked to the location of PT networks as Glaeser et al. (2008) would have us believe. As an addendum to the analysis I add some thoughts on how the COVID19 pandemic might affect commuting behavior and income distributions within urban areas over the next decade.

Voluntary sustainability standards (VSS) are stakeholder-derived principles with measurable and enforceable criteria to promote sustainable production outcomes. While institutional commitments to use VSS to meet sustainable procurement policies have grown rapidly over the past decade, we still have relatively little understanding of the (i) direct environmental benefits of large-scale VSS adoption; (ii) potential perverse indirect impacts of adoption; and (iii) implementation pathways. Here, we illustrate and address these knowledge gaps using an ecosystem service modeling and scenario analysis of Bonsucro, the leading VSS for sugarcane. We find that global compliance with the Bonsucro environmental standards would reduce current sugarcane production area (-24%), net tonnage (-11%), irrigation water use (-65%), nutrient loading (-34%), and greenhouse gas emissions from cultivation (-51%). Under a scenario of doubled global sugarcane production, Bonsucro adoption would further limit water use and greenhouse gas emissions by preventing sugarcane expansion into water-stressed and high-carbon stock ecosystems. This outcome was achieved via expansion largely on existing agricultural lands. However, displacement of other crops could drive detrimental impacts from indirect land use. We find that over half of the potential direct environmental benefits of Bonsucro standards under the doubling scenario could be achieved by targeting adoption in just 10% of global sugarcane production areas. However, designing policy that generates the most environmentally beneficial Bonsucro adoption pathway requires a better understanding of the economic and social costs of VSS adoption. Finally, we suggest research directions to advance sustainable consumption and production.

Abstract Since 2011, the private ride-hailing (RH) app companies Uber and Lyft have expanded into more and more US urban areas. We use a dynamic entry event study to examine the impact of Uber and Lyft’s entry on public transportation (PT) use in the United States’ largest urban areas. In most cases, entry into urban areas was staggered: Uber entered first, followed several months later by Lyft. We generally find that PT use increased in the representative urban area, all else equal, immediately following first RH app company entry. However, this spike in PT use largely disappeared following the entry of the second RH app company. Slightly different RH app company–PT use relationships emerge when we estimate the PT use model over various subsets of urban areas and PT modes.

[This corrects the article DOI: 10.1371/journal.pone.0211199.].

a Conservation Science Program, World Wildlife Fund, 1250 24th St. NW, Washington D.C. 20037, United States b Department of Soil, Water and Climate, University of Minnesota, 1991 Upper Buford Circle, St. Paul, MN 55108, United States c Department of Economics, Bowdoin College, 9700 College Station, Brunswick, ME 04011, United States d Department of Applied Economics, University of Minnesota, 1994 Buford Ave, St. Paul, MN, 55108, United States e Institute on the Environment, University of Minnesota, 1954 Buford Ave, St. Paul, MN, 55108, United States

We determine the effect of the US Endangered Species Act’s Critical Habitat designation on land use change from 1992 to 2011. We find that the rate of change in developed land (constructed material) and agricultural land is not significantly affected by Critical Habitat designation. Therefore, Sections 7 and 9 of the Endangered Species Act do not appear to be more heavily applied in lands designated as Critical Habitat areas versus lands within listed species’ ranges, but without critical habitat designation. Further, there does not appear to be any extraordinary conservation activity in critical habitat areas; for example, environmental non-profits and land trusts do not appear to be concentrating activity in these areas. Before we conclude that the opportunity cost of Critical Habitat designation is negligible we need to examine the land management impacts of designation.

Small natural features (SNFs), landscape elements that influence species persistence and ecological functioning on a much larger scale than one would expect from their size, can also offer a greater rate of return on conservation investment compared to that of larger natural features or more broad-based conservation. However, their size and perceived lack of significance also makes them more vulnerable to threats and destruction. We examine the management of SNFs and conservation of the associated ecosystem services they generate from an economics perspective. Using the economic concept of market failure, we identify three key themes that explain prevailing threats to SNFs and characterize impediments to and opportunities for SNF management: (1) the degree to which benefits derived from the feature spillover, beyond the feature itself (spatially and temporally); (2) the availability and quality of information about the feature and those who most directly influence its management; and (3) the existence and enforcement of property rights and legal standing of the feature. We argue that the efficacy of alternative SNF management approaches is highly case dependent and relies on four key components: (1) the specific ecosystem services of interest; (2) the amount of redundancy of the SNF on the landscape and the level of connectivity required by the SNF in order to provide ecosystem services; (3) the particular market failures that need correcting and their scope and extent; and (4) the magnitude and distribution of management costs.

Improving water quality and other ecosystem services in agriculturally dominated watersheds is an important policy objective in many regions of the world. A major challenge is overcoming the associated costs to agricultural producers. We integrate spatially-explicit models of ecosystem processes with agricultural commodity production models to analyze the biophysical and economic consequences of alternative land use and land management patterns to achieve Total Maximum Daily Loads targets in a proto-typical agricultural watershed. We apply these models to find patterns that maximize water quality objectives for given levels of foregone agricultural profit. We find it is possible to reduce baseline watershed phosphorus loads by ~20% and sediment loads by ~18% without any reduction in agricultural profits. Our results indicate that meeting more stringent targets will result in substantial economic loss. However, when we add the social benefits from water quality improvement and carbon sequestration to private agricultural net returns we find that water quality improvements up to 50% can be obtained at no loss to societal returns. The cost of meeting water quality targets will vary over time as commodity and ecosystem service prices fluctuate. If crop prices drop or the value of ecosystem services increase, then achieving higher water quality goals will be less costly.

Small Natural Features (SNFs) are analogous to keystone species in that they have ecological importance that is disproportionate to their size. Thus the recognition and management of SNFs can be an efficient way to conserve biodiversity and ecosystem services. In particular, while the size of SNFs can engender threats (e.g., they are often overlooked and are relatively vulnerable to complete destruction), small size also leads to special conservation opportunities (e.g., integration with resource uses such as forestry or fisheries). Commonly, SNF conservation begins with education and inventory to form a foundation for appropriate, targeted protection and/or sustainable management. However, in cases of severe degradation or loss, more intensive activities such as restoration or creation may be required. Diverse approaches to conservation action are possible. For example, sometimes SNF conservation is undertaken incidentally to other efforts or on a voluntary basis; sometimes it involves substantial economic incentives or restrictive regulations. In general, the required investment for SNF conservation is likely to be smaller than that for larger areas, with disproportionate benefits given the substantial spatio-temporal influence of these features. In practice, conservation of SNFs should be complementary to traditional, larger-scale, forms of conservation by fostering creative, constructive efforts to conserve some seemingly minor features; features that have previously unknown or unappreciated roles critical to their broader ecosystems and to biodiversity.