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In the United States, greater attention has been given to developing water supplies and quantifying available waters than determining who uses water, how much they withdraw and consume, and how and where water use occurs. As water supplies are stressed due to an increasingly variable climate, changing land-use, and growing water needs, greater consideration of the demand side of the water balance equation is essential. Data about the spatial and temporal aspects of water use for different purposes are now critical to long-term water supply planning and resource management. We detail the current state of water-use data, the major stakeholders involved in their collection and applications, and the challenges in obtaining high-quality nationally consistent data applicable to a range of scales and purposes. Opportunities to improve access, use, and sharing of water-use data are outlined. We cast a vision for a world-class national water-use data product that is accessible, timely, and spatially detailed. Our vision will leverage the strengths of existing local, state, and federal agencies to facilitate rapid and informed decision-making, modeling, and science for water resources. To inform future decision-making regarding water supplies and uses, we must coordinate efforts to substantially improve our capacity to collect, model, and disseminate water-use data. U.S. Geological Survey (USGS); U.S. Geological Survey Grant/Cooperative Agreement [G20AP00002]; NSF/USDA [ACI-1639529]; NSF [CBET-2144169]; Water Foundation; Western States Water Council's Water Information Management Systems (WIMS) Published version This work was conducted as a part of the "Reanalyzing and predicting U.S. water use by economic history and forecast data; an experiment in short-range national hydroeconomic data synthesis" Working Group supported by the John Wesley Powell Center for Analysis and Synthesis, funded by the U.S. Geological Survey (USGS). U.S. Geological Survey Grant/Cooperative Agreement No. G20AP00002. NSF/USDA grant ACI-1639529 and NSF grant CBET-2144169 are also acknowledged. Any use of trade, firm, or product names is for descriptive purposes and does not imply endorsement by the U.S. Government. The Water Foundation provided funding that supported the Western States Water Council's Water Information Management Systems (WIMS) and USGS National Water Use Data Collaboration Workshop in Fort Collins, Colorado in 2019. The authors would like to acknowledge constructive reviews by Tony Willardson (Western States Water Council), Mindi Dalton (USGS), Natalie Latysh (USGS), and two anonymous reviewers that improved this manuscript.

Despite a growing number of national-scale ecosystem service (ES) assessments, few studies consider the impacts of ES use and consumption beyond national or regional boundaries. Interregional ES flows ecosystem services imported from and exported to other countries are rarely analyzed and their importance for global sustainability is little known. Here, we provide a first multi-ES quantification of a nation's use of ES from abroad. We focus on ES flows that benefit the population in Germany but are supplied outside German territory. We employ a conceptual framework recently developed to systematically quantify interregional ES flows. We address four types of interregional ES flows with: (i) biophysical flows of traded goods: cocoa import for consumption; (ii) flows mediated by migratory species: migration of birds providing pest control; (iii) passive biophysical flows: flood control along transboundary watersheds; and (iv) information flows: China's giant panda loan to the Berlin Zoo. We determined that: (i) Ivory Coast and Ghana alone supply around 53% of Germany's cocoa while major negative consequences for biodiversity occurred in Cameroon and Ecuador; (ii) Africa´s humid and sub-humid climate zones are important habitats for the majority of migratory bird species that provide natural pest control services in agricultural areas in Germany; (iii) Upstream watersheds outside the country add an additional 64% flood regulation services nationally, while Germany exports 40% of flood regulation services in neighboring, downstream countries; (iv) Information flows transported by the pandas were mainly related to political aspects and - contrary to our expectations - considerably less on biological and natural aspects. We discuss the implications of these results for international resource management policy and governance. (c) 2020 The Authors Thomas Kastner was supported by the Vienna Science and Technology Fund (WWTF), project no. ESR17-014. Laura Lopez-Hoffman acknowledges the support of the National Science Foundation (NSF) awards DEB-1118975 and DEB-1518359. Support for Liu's time was provided by US National Science Foundation and Michigan AgBioResearch. Javier Martínez-López acknowledges the support of the Spanish Government through María de Maeztu excellence accreditation 2018-2021 (Ref. MDM-2017-0714). Sarah Wolff was supported by the European Research Council grant GLOLAND (grant no. 311819)

Rwanda, a small but rapidly developing central African nation, has undertaken development of natural capital accounts to better inform its economic development through the World Bank's Wealth Accounting and Valuation of Ecosystem Services (WAVES) Partnership. In this paper, we develop ecosystem service (ES) models to quantify ecosystem condition and physical supply components of ecosystem accounts in Rwanda from 1990 to 2015. We applied the InVEST carbon storage, sediment delivery ratio, nutrient delivery ratio, and annual and seasonal water yield models to map changes in potential ES supply nationwide. We also quantified flows of sediment, water and nutrients to 96 hydroelectric dam, irrigation dam and water treatment plant sites. Over a 25‐year period, we found declines in all ES, which were most strongly driven by conversion of forests to cropland. Declines were most pronounced from 1990 to 2000 and 2010 to 2015; ES were relatively stable from 2000 to 2010 (with the exception of nutrient exports to water bodies, which jumped most sharply from 2000 to 2010). From 2010 to 2015, over 42% of Rwanda's water‐use sites (representing 9% of the nation's hydroelectric generation capacity and 59% of its water treatment capacity) had upstream increases in sediment export and quick flow greater than the national average. Half of Rwanda's water treatment plants had upstream phosphorus exports greater than the national average. Our results quantify nation‐wide ES trends, their implications for key water‐dependent industries, and the importance of protected areas in safeguarding ES flows and potential supply in Rwanda. They also provide data that can be integrated with existing land, water and economic accounts for Rwanda, as well as a baseline to inform development strategies that better link economic and environmental goals. A free Plain Language Summary can be found within the Supporting Information of this article.

Semi-arid urban environments are undergoing an increase in both average air temperatures and in the frequency and intensity of extreme heat events. Within cities, different composition and densities of urban landcovers (ULC) influence local air temperatures, either mitigating or increasing heat. Currently, understanding how combinations of ULC influence air temperature at the block to neighborhood scale is necessary for heat mitigation plans, and yet limited due to the complexities integrating high-resolution ULC with spatial and temporally high-resolution microclimate data. We quantify how ULC influences air temperature at 60 m resolution for day and nighttime climate normals and extreme heat conditions by integrating microclimate sensor data sensor and high-resolution (1 m

Ecosystem services (ES) assessments commonly focus on a specific biophysical region or nation and take its geographic borders as the system boundary. Most geographical regions are, however, not closed systems but are open and telecoupled with other regions, such that the use of ES in one location is dependent on ecosystem processes and ecological management in other locations. Interregional ES flows often affect national economies and may trigger issues of national security and global equity. To date, however, methodologies for assessing interregional flows of ES have been published in dispersed literature. This paper provides a three-step guidance for how to assess four different types of interregional ES flows (traded goods, passive biophysical flows, species migration and dispersal as well as information flows). This guidance is intended to complement national and regional ecosystem assessments. The three steps are to (i) define the goal and scope of interregional ES flow assessments, (ii) quantify the interregional ES flows using a tiered approach and (iii) interpret results in terms of uncertainties, consequences and governance options. We compile different indicators for assessing interregional ES flows and evaluate their suitability for national and regional ES assessments. Finally, to assess the implications of interregional ES flows for environmental sustainability and human well-being, we relate our flow indicators to the Sustainable Development Goals. This guidance towards systematic assessment of interregional ES flows provides a first step to measure and quantify externalised environmental costs and can contribute to the development of indicators to address interregional imbalances in trade, foreign policy and beyond.

Using contingent valuation, we estimated willingness to pay (WTP) in Canada, Mexico, and the United States to protect habitat for Northern Pintails (hereafter pintails), a migratory waterfowl species that provides benefits to and requires habitat in the three countries. Our study contributes to research on spatial subsidies by measuring the value of migratory species habitat. While WTP to protect pintail habitat is highest in the household's own country, there also is substantial WTP to protect pintail habitat in the other two countries. Canadian households' annual WTP is US$12 (all dollar values are in 2016 US dollars) to stabilize the pintail population in Canada, US$4 in Mexico, and US$5 in the U.S. Mexican households would pay US$8 in Mexico, US$5 in the U.S., and US$5 in Canada. U.S. households would pay US$28 in the U.S., US$18 in Canada, and US$16 in Mexico. WTP is statistically significantly higher in all three countries to increase the pintail population. WTP as a percentage of household income is statistically significantly higher for respondents in Mexico. WTP is logically related to explanatory variables such as respondent income, interest in hunting waterfowl, and financial support of wildlife conservation organizations. This study has important implications for conducting economic analyses of habitat issues of transboundary migratory species' conservation and to more effectively and equitably achieve conservation goals.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Microsoft released a U.S.-wide vector building dataset in 2018. Although the vector building layers provide relatively accurate geometries, their use in large-extent geospatial analysis comes at a high computational cost. We used High-Performance Computing (HPC) to develop an algorithm that calculates six summary values for each cell in a raster representation of each U.S. state, excluding Alaska and Hawaii: (1) total footprint coverage, (2) number of unique buildings intersecting each cell, (3) number of building centroids falling inside each cell, and area of the (4) average, (5) smallest, and (6) largest area of buildings that intersect each cell. These values are represented as raster layers with 30 m cell size covering the 48 conterminous states. We also identify errors in the original building dataset. We evaluate precision and recall in the data for three large U.S. urban areas. Precision is high and comparable to results reported by Microsoft while recall is high for buildings with footprints larger than 200 m2 but lower for progressively smaller buildings., Measurement(s)building • building footprint • area • building countTechnology Type(s)computational modeling techniqueSample Characteristic - EnvironmentcitySample Characteristic - Locationcontiguous United States of America Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12444776

Reversing the ongoing degradation of the planet's ecosystems requires timely and detailed monitoring of ecosystem change and uses. Yet, the System of National Accounts (SNA), first developed in response to the economic crisis of the 1930s and used by statistical offices worldwide to record economic activity (for example, production, consumption, and asset accumulation), does not make explicit either inputs from the environment to the economy or the cost of environmental degradation (1, 2). Experimental Ecosystem Accounting (EEA), part of the System of Environmental-Economic Accounting (SEEA), has been developed to monitor and report on ecosystem change and use, using the same accounting approach, concepts, and classifications as the SNA (3). The EEA is part of the statistical community's response to move SNA measurement “beyond gross domestic product (GDP).” With the first generation of ecosystem accounts now published in 24 countries, and with a push to finalize a United Nations (UN) statistical standard for ecosystem accounting by 2021, we highlight key advances, challenges, and opportunities.

Many economic studies value birdwatching in general and often do not account for potential differences in viewers’ benefits from observing different species. But, how different are economic values ...

Conserving and managing global natural capital requires an understanding of the complexity of flows ofecosystem services across geographic boundaries. Failing to understand and to incorporate these flowsinto national and international ecosystem assessments leads to incomplete and potentially skewed conclusions,impairing society’s ability to identify sustainable management and policy choices. In this paper,we synthesise existing knowledge and develop a conceptual framework for analysing interregionalecosystem service flows. We synthesise the types of such flows, the characteristics of sending and receivingsocio-ecological systems, and the impacts of ecosystem service flows on interregional sustainability.Using four cases (trade of certified coffee, migration of northern pintails, flood protection in the Danubewatershed, and information on giant pandas), we test the conceptual framework and show how anenhanced understanding of interregional telecouplings in socio-ecological systems can inform ecosystemservice-based decision making and governance with respect to sustainability goals.&nbsp

Migratory species provide ecosystem goods and services throughout their annual cycles, often over long distances. Designing effective conservation solutions for migratory species requires knowledge of both species ecology and the socioeconomic context of their migrations. We present a framework built around the concept that migratory species act as carriers, delivering benefit flows to people throughout their annual cycle that are supported by the network of ecosystems upon which the species depend. We apply this framework to the monarch butterfly (Danaus plexippus) migration of eastern North America by calculating their spatial subsidies. Spatial subsidies are the net ecosystem service flows throughout a species’ range and a quantitative measure of the spatial mismatch between the locations where people receive most benefits and the locations of habitats that most support the species. Results indicate cultural benefits provided by monarchs in the U.S. and Canada are subsidized by migration and overwintering habitat in Mexico. At a finer scale, throughout the monarch range, habitat in rural landscapes subsidizes urban residents. Understanding the spatial distribution of benefits derived from and ecological support provided to monarchs and other migratory species offers a promising means of understanding the costs and benefits associated with conservation across jurisdictional borders.

Migratory species provide important benefits to society, but their cross-border conservation poses serious challenges. By quantifying the economic value of ecosystem services (ESs) provided across a species’ range and ecological data on a species’ habitat dependence, we estimate spatial subsidies—how different regions support ESs provided by a species across its range. We illustrate this method for migratory northern pintail ducks in North America. Pintails support over $101 million USD annually in recreational hunting and viewing and subsistence hunting in the U.S. and Canada. Pintail breeding regions provide nearly $30 million in subsidies to wintering regions, with the “Prairie Pothole” region supplying over $24 million in annual benefits to other regions. This information can be used to inform conservation funding allocation among migratory regions and nations on which the pintail depends. We thus illustrate a transferrable method to quantify migratory species-derived ESs and provide information to aid in their transboundary conservation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13280-018-1049-4) contains supplementary material, which is available to authorized users.

Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address these questions at national, provincial, and subwatershed scales in Rwanda. We compared results for carbon, water, and sediment as modeled using InVEST and WaSSI using (1) land cover data at 30 and 300 m resolution and (2) three different input land cover datasets. WaSSI and simpler InVEST models (carbon storage and annual water yield) were relatively insensitive to the choice of spatial resolution, but more complex InVEST models (seasonal water yield and sediment regulation) produced large differences when applied at differing resolution. Six out of nine ES metrics (InVEST annual and seasonal water yield and WaSSI) gave similar predictions for at least two different input land cover datasets. Despite differences in mean values when using different data sources and resolution, we found significant and highly correlated results when using Spearman's rank correlation, indicating consistent spatial patterns of high and low values. Our results confirm and extend conclusions of past studies, showing that in certain cases (e.g., simpler models and national-scale analyses), results can be robust to data and modeling choices. For more complex models, those with different output metrics, and subnational to site-based analyses in heterogeneous environments, data and model choices may strongly influence study findings.

The United States and European Union (EU) face common challenges in managing natural capital and balancing conservation and resource use with consumption of other forms of capital. This paper synthesizes findings from 11 individual application papers from a special issue of Ecosystem Services on natural capital accounting (NCA) and their application to the public and private sectors in the EU and U.S. NCA is inherently a data-integration centered exercise, aiming to draw new insights by realigning environmental and economic data into a consistent framework. Drawing primarily on papers from the special issue and other key NCA literature, we identify lessons learned and gaps remaining for NCA’s development and application to decision making. In doing so, we identify eight key similarities and three major differences in NCA development, status, and application between the U.S. and EU. NCA can be highly policy relevant: special issue papers address critical issues including agriculture, water, conservation/land-use planning, climate, and corporate decision making. In both the U.S. and EU, further application is needed to drive demand for the accounts’ production. Based on these experiences, the U.S. and EU can be important leaders in cross-sector, international collaboration toward next-generation environmental economic accounts that advance global NCA practice.

In spatial planning and management of protected areas, increased priority is being given to research that integrates social and ecological data. However, public viewpoints of the benefits provided by ecosystems are not easily quantified and often implicitly folded into natural resource management decisions. Drawing on a spatially explicit participatory mapping exercise and a Social Values for Ecosystem Services (SolVES) analysis tool, the present study empirically examined and integrated social values for ecosystem services and environmental conditions within Channel Islands National Park, California. Specifically, a social value indicator of perceived biodiversity was examined using on-site survey data collected from a sample of people who visited the park. This information was modeled alongside eight environmental conditions including faunal species richness for six taxa, vegetation density, categories of marine and terrestrial land cover, and distance to features relevant for decision-makers. Results showed that biodiversity value points assigned to places by the pooled sample of respondents were widely and unevenly mapped, which reflected the belief that biodiversity was embodied to varying degrees by multiple locations in the park. Models generated for two survey subgroups defined by their self-reported knowledge of the Channels Islands revealed distinct spatial patterns of these perceived values. Specifically, respondents with high knowledge valued large spaces that were publicly inaccessible and unlikely to contain on-ground biodiversity, whereas respondents with low knowledge valued places that were experienced first-hand. Accessibility and infrastructure were also important considerations for anticipating how and where people valued the protected land and seascapes of Channel Islands National Park.

Development from extracting oil and gas resources can have unintended effects on multiple ecosystem functions, with cascading effects on wildlife, ecosystem services, and local economies. Big-game hunting opportunities may be closely related to these effects, but empirical analyses of impacts of energy development on hunting are limited. We examined the influence of oil and gas development density on harvest efficiency, or harvest per unit of hunter effort, within all hunt areas in Wyoming, USA, from 2008 to 2014 for 3 big-game species: elk (Cervus canadensis), mule deer (Odocoileus hemionus), and pronghorn (Antilocapra americana). Using harvest/hunter day as the response variable, we compared linear mixed-effects models for each species that included total well density (i.e., all wells constructed up to the year of record), active well density (i.e., only those wells currently producing oil or gas in that year), or neither as a predictor variable. We used well densities as indicators of development in the absence of data specifying the locations of other oil and gas infrastructure (e.g., roads, well pads). Models also accounted for the fixed effects of road density, hunter density, proportion of the area that is public land with unrestricted hunter access, proportion of the area that is forested, year of observation, and random effects of variation among hunt areas nested within associated game herd units. Presence of oil and gas wells had a positive influence on harvest efficiency for elk and mule deer. Although there was no overall effect to pronghorn, there was a negative influence of wells on juvenile pronghorn harvest efficiency. Changes in harvest efficiency due to expanding oil and gas development could alter the time spent hunting by hunters and their chances of harvesting an animal. This could have subsequent impacts on hunter satisfaction, game populations, and economic revenue generated from recreational hunters. © 2016 The Wildlife Society.

Freshwater biodiversity is declining, despite national and international efforts to manage and protect freshwater ecosystems. Ecosystem-based management (EBM) has been proposed as an approach that could more efficiently and adaptively balance ecological and societal needs. However, this raises the question of how social and ecological objectives can be included in an integrated management plan. Here, we present a generic model-coupling framework tailored to address this question for freshwater ecosystems, using three components: biodiversity, ecosystem services (ESS), and a spatial prioritisation that aims to balance the spatial representation of biodiversity and ESS supply and demand. We illustrate this model-coupling approach within the Danube River Basin using the spatially explicit, potential distribution of (i) 85 fish species as a surrogate for biodiversity as modelled using hierarchical Bayesian models, and (ii) four estimated ESS layers produced by the Artificial Intelligence for Ecosystem Services (ARIES) platform (with ESS supply defined as carbon storage and flood regulation, and demand specified as recreation and water use). These are then used for (iii) a joint spatial prioritisation of biodiversity and ESS employing Marxan with Zones, laying out the spatial representation of multiple management zones. Given the transboundary setting of the Danube River Basin, we also run comparative analyses including the country-level purchasing power parity (PPP)-adjusted gross domestic product (GDP) and each country's percent cover of the total basin area as potential cost factors, illustrating a scheme for balancing the share of establishing specific zones among countries. We demonstrate how emphasizing various biodiversity or ESS targets in an EBM model-coupling framework can be used to cost-effectively test various spatially explicit management options across a multi-national case study. We further discuss possible limitations, future developments, and requirements for effectively managing a balance between biodiversity and ESS supply and demand in freshwater ecosystems. © 2018 The Authors This study was funded by the European Union's Horizon 2020 - Research and Innovation Framework Programme under grant agreement No. 642317 , granting funding to SD, SCJ, KK, SDL, JML, SB, FV, AF, TH, and FB. SDL has received additional funding from the European Union's Horizon 2020 - Research and Innovation Framework Programme under the Marie Skłodowska-Curie grant agreement No. 748625 , and SCJ from the German Federal Ministry of Education and Research (BMBF) for the “GLANCE” project (Global Change Effects in River Ecosystems; 01 LN1320A ). VH is funded by a Ramon y Cajal contract (RYC-2013-13979) supported by the Spanish Government. The U.S. Geological Survey Land Change Science Program under the Land Resources Mission Area supported KJB's contributions to this paper. We thank Van Bustic for constructive comments on an earlier draft of this manuscript.

Zach Ancona (U.S. Geological Survey, USGS) assisted with preparation of numerous datasets for use in ARIES. Support for Bagstad's time was provided by the USGS Land Change Science Program. Support for Voigt's time was provided by the USGS Sustaining Environmental Capital Initiative. We thank Lisa Mandle for constructive comments on an earlier draft of this paper. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Appendix A Scientists, stakeholders and decision makers face trade-offs between adopting simple or complex approaches when modeling ecosystem services (ES). Complex approaches may be time- and data-intensive, making them more challenging to implement and difficult to scale, but can produce more accurate and locally specific results. In contrast, simple approaches allow for faster assessments but may sacrifice accuracy and credibility. The ARtificial Intelligence for Ecosystem Services (ARIES) modeling platform has endeavored to provide a spectrum of simple to complex ES models that are readily accessible to a broad range of users. In this paper, we describe a series of five Tier 1 ES models that users can run anywhere in the world with no user input, while offering the option to easily customize models with context-specific data and parameters. This approach enables rapid ES quantification, as models are automatically adapted to the application context. We provide examples of customized ES assessments at three locations on different continents and demonstrate the use of ARIES' spatial multi-criteria analysis module, which enables spatial prioritization of ES for different beneficiary groups. The models described here use publicly available global- and continental-scale data as defaults. Advanced users can modify data input requirements, model parameters or entire model structures to capitalize on high-resolution data and context-specific model formulations. Data and methods contributed by the research community become part of a growing knowledge base, enabling faster and better ES assessment for users worldwide. By engaging with the ES modeling community to further develop and customize these models based on user needs, spatiotemporal contexts, and scale(s) of analysis, we aim to cover the full arc from simple to complex assessments, minimizing the additional cost to the user when increased complexity and accuracy are needed AQUACROSS - Knowledge, Assessment, and Management for AQUAtic Biodiversity and Ecosystem Services aCROSS EU policies (AQUACROSS) (642317) Zach Ancona (U.S. Geological Survey, USGS) assisted with preparation of numerous datasets for use in ARIES. Support for Bagstad's time was provided by the USGS Land Change Science Program. Support for Voigt's time was provided by the USGS Sustaining Environmental Capital Initiative. We thank Lisa Mandle for constructive comments on an earlier draft of this paper. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Large river-floodplain systems are hotspots of biodiversity and ecosystem services but are also used for multiple human activities, making them one of the most threatened ecosystems worldwide. There is wide evidence that reconnecting river channels with their floodplains is an effective measure to increase their multi-functionality, i.e., ecological integrity, habitats for multiple species and the multiple functions and services of river-floodplain systems, although, the selection of promising sites for restoration projects can be a demanding task. In the case of the Danube River in Europe, planning and implementation of restoration projects is substantially hampered by the complexity and heterogeneity of the environmental problems, lack of data and strong differences in socio-economic conditions as well as inconsistencies in legislation related to river management. We take a quantitative approach based on best-available data to assess biodiversity using selected species and three ecosystem services (flood regulation, crop pollination, and recreation), focused on the navigable main stem of the Danube River and its floodplains. We spatially prioritize river-floodplain segments for conservation and restoration based on (1) multi-functionality related to biodiversity and ecosystem services, (2) availability of remaining semi-natural areas and (3) reversibility as it relates to multiple human activities (e.g. flood protection, hydropower and navigation). Our approach can thus serve as a strategic planning tool for the Danube and provide a method for similar analyses in other large river-floodplain systems. © 2018 The Authors This work was funded by the projects AQUACROSS (Knowledge, Assessment and Management for AQUAtic Biodiversity and Ecosystem Services aCROSS EU policies, Contract no. 642317 ; http://aquacross.eu ). Support for Bagstad

In this study, we develop urban ecosystem accounts in the U.S., using the System of Environmental-Economic Accounting Experimental Ecosystem Accounting (SEEA EEA) framework. Most ecosystem accounts focus on regional and national scales, which are appropriate for many ecosystem services. However, ecosystems provide substantial services in cities, improving quality of life and contributing to resiliency for substantial parts of the population. Our models estimate energy savings for indoor cooling resulting from heat mitigated by trees and rainfall intercepted by trees. Both models cover major cities in the contiguous U.S. and report the results through physical supply and use tables for multiple accounting periods (2011 and 2016). Using conservative assumptions, urban trees provide substantial heat mitigation (4,098 and 4,229 GWh, valued at $523 and $539 million in 2011 and 2016, respectively) and rainfall interception (2,422 and 2,627 million m3, valued at $434 and $425 million for 2011 and 2016, respectively). Interannual differences largely reflect variations in weather patterns. Our work shows how Earth observation data can support urban ecosystem accounting. We provide model code within a public repository to facilitate model runs elsewhere, enabling the SEEA EEA and Earth observation user communities to reuse our models and provide feedback for improvement.

Land plays a critical role in both economic and environmental accounting. As an asset, it occupies a unique position at the intersection of the System of National Accounts (SNA), the System of Environmental-Economic Accounting Central Framework (SEEA-CF), and (as a spatial unit) SEEA Experimental Ecosystem Accounting (SEEA-EEA), making land a natural starting point for developing natural capital accounts more generally. We develop a pilot set of national and subnational land accounts for the United States that are consistent with the SEEA-CF and SNA principles, quantified in both physical and monetary terms. The physical accounts utilize detailed land use (National Land Use Database) and land cover (National Land Cover Database) datasets, which provide insights into how land cover in the U.S. is changing over time. To provide aggregate estimates of land values, we use a hedonic approach that exploits fine-grain microdata (“big data” from Zillow) that contains detailed information from hundreds of millions of property transactions and their corresponding physical characteristics covering much of the U.S. Methodologically, we show that it is feasible to produce monetary accounts for land that can be directly linked to and integrated with physical land cover/use. Overall, U.S. land cover has shown declines in forests, cropland, and pasture with increases in barren, scrub/shrub, and developed classes, which are particularly concentrated in the U.S. Southeast. Nominal land values in the U.S. fell about 28% ($7 trillion) from the boom to bust periods in the prior decade, albeit with substantial regional variation, and have subsequently experienced a nearly full recovery in recent years. We estimate private land in the contiguous 48 states to be worth approximately $25.1 trillion in 2016.

Data for biophysically modeled and Public Participatory GIS (PPGIS)-derived cultural ecosystem services have potential to identify natural resource management synergies and conflicts, but have rarely been combined. Ecosystem service hot/coldspots generated using different methods vary in their spatial extent and connectivity, with important implications. We map biophysically modeled and PPGIS-derived cultural services for six U.S. national forests using six hot/coldspot delineation methods. We evaluate the implications of hotspot methods for management within and outside of designated wilderness areas. We used the ARIES and SolVES modeling tools to quantify four biophysically modeled and 11 largely cultural ecosystem services for six national forests in Colorado and Wyoming, USA. We mapped hot/coldspots using two quantile methods (top and bottom 10 and 33 % of values), two area-based methods (top and bottom 10 and 33 % of area), and two statistical methods (Getis-Ord Gi* at α = 0.05 and 0.10 significance level) and compare results within and outside wilderness areas. Delineation methods vary in their degree of conservatism for hot/coldspot extents and spatial clustering. Hotspots were more common in wilderness areas in national forests near the more densely populated Colorado Front Range, while coldspots were more common in wilderness areas in more urban-distant forests in northwest Wyoming. Statistical hotspot methods of intermediate conservatism (i.e., Getis-Ord Gi*, α = 0.10 significance) may be most useful for ecosystem service hot/coldspot mapping to inform landscape scale planning. We also found spatially explicit evidence in support of past findings about public attitudes toward wilderness areas.

Urban expansion and its associated landscape modifications are important drivers of changes in ecosystem service (ES). This study examined the effects of two alternative land use-change development scenarios in the Puget Sound region of Washington State on natural capital stocks and ES flows. Land-use change model outputs served as inputs to five ES models developed using the Artificial Intelligence for Ecosystem Services (ARIES) platform. While natural capital stocks declined under managed (1.3–5.8%) and unmanaged (2.8–11.8%) development scenarios, ES flows increased by 18.5–56% and 23.2–55.7%, respectively. Human development of natural landscapes reduced their capacity for service provision, while simultaneously adding beneficiaries, particularly along the urban fringe. Using global and local Moran’s I, we identified three distinct patterns of change in ES due to projected landuse change. For services with location-dependent beneficiaries – open space proximity, viewsheds, and flood regulation – urbanization led to increased clustering and hot-spot intensities. ES flows were greatest in the managed land-use change scenario for open space proximity and flood regulation, and in the unmanaged land-use change scenario for viewsheds—a consequence of the differing ES flow mechanisms underpinning these services. We observed a third pattern – general declines in service provision – for carbon storage and sediment retention, where beneficiaries in our analysis were not location dependent. Contrary to past authors’ finding of ES declines under urbanization, a more nuanced analysis that maps and quantifies ES provision, beneficiaries, and flows better identifies gains and losses for specific ES beneficiaries as urban areas expand.

Coastal zones are popular recreational areas that substantially contribute to social welfare. Managers can use information about specific environmental features that people value, and how these might change under different management scenarios, to spatially target actions to areas of high current or potential value. We explored how snorkelers' experience would be affected by separate and combined land and marine management actions in West Maui, Hawaiʻi, using a Bayesian belief network (BBN) and a spatially explicit ecosystem services model. The BBN simulates the attractiveness of a site for recreation by combining snorkeler preferences for coastal features with expert opinions on ecological dynamics, snorkeler behavior, and management actions. A choice experiment with snorkelers elucidated their preferences for sites with better ecological and water-quality conditions. Linking the economic elicitation to the spatially explicit BBN to evaluate land-sea management scenarios provides specific guidance on where and how to act in West Maui to maximize ecosystem service returns. Improving coastal water quality through sediment runoff and cesspool effluent reductions (land management), and enhancing coral reef ecosystem conditions (marine management) positively affected overall snorkeling attractiveness across the study area, but with differential results at specific sites. The highest improvements were attained through joint land-sea management, driven by strong efforts to increase fish abundance and reduce sediment; however, the effects of management at individual beaches varied.

Water management increasingly involves tradeoffs, making its accounting highly relevant in our interconnected world. Physical and economic data about water in many nations are becoming more widely integrated through application of the System of Environmental-Economic Accounts for Water (SEEA-Water), which enables the tracking of linkages between water and the economy. We present the first national and subnational SEEA-Water accounts for the United States. We compile accounts for water: (1) physical supply and use, (2) productivity, (3) quality, and (4) emissions for roughly the years 2000 to 2015. Total U.S. water use declined by 22% from 2000 to 2015, falling in 44 states though groundwater use increased in 21 states. Water-use reductions, combined with economic growth, led to increases in water productivity for the overall national economy (65%), mining (99%), and agriculture (68%). Surface-water quality trends were most evident at regional levels, and differed by water-quality constituent and region. This work provides (1) a baseline of recent historical water resource trends and their value in the U.S., and (2) a roadmap for the completion of future accounts for water, a critical ecosystem service. Our work also aids in the interpretation of ecosystem accounts in the context of long-term water resources trends.

We develop and link the Integrated Economic-Environmental Modeling (IEEM) Platform to ecosystem services modeling (ESM). The IEEM+ESM Platform is an innovative decision-making framework for exploring complex public policy goals and elucidating synergies and trade-offs between alternative policy portfolios. The IEEM+ESM approach is powerful in its ability to shed light on (i) change in land use and ecosystem services driven by public policy and the supply and demand responses of businesses and households; and (ii) impacts on standard economic indicators of concern to Ministries of Finance such as gross domestic product and employment, as well as changes in wealth and ecosystem services. The IEEM+ESM approach is being adopted rapidly and by the end of 2020, IEEM+ESM Platforms will be implemented for about 25 countries. To demonstrate the insights generated by the IEEM+ESM approach, we apply it to the analysis of alternative green growth strategies in Rwanda, a country that has made strong progress in reducing poverty and enhancing economic growth in the last 15 years. The case of Rwanda is particularly compelling as it faces intense pressure on its natural capital base and ecosystem services, already with the highest population density in Africa, which is projected to double by 2050. In applying IEEM+ESM and comparing the outcomes of Rwanda's green growth policies, increasing fertilization of agricultural crops shows the largest economic gains but also trade-offs in environmental quality reflected through higher nutrient export and reduced water quality. Combining crop fertilization with forest plantations better balances critical ecosystem services and their role in underpinning economic development as Rwanda progresses toward its target of middle-income status by 2035. This application to Rwanda's green growth strategy demonstrates the value-added of the IEEM+ESM approach in generating results that speak to both economic outcomes and impacts on market and non-market ecosystem services.

Ecosystem accounts, as formalized by the System of Environmental-Economic Accounting Experimental Ecosystem Accounts (SEEA EEA), have been compiled in a number of countries, yet there have been few attempts to develop them for the U.S. We explore the potential for U.S. ecosystem accounting by compiling ecosystem extent, condition, and ecosystem services supply and use accounts for a 10-state region in the Southeast. The pilot accounts address air quality, water quality, biodiversity, carbon storage, recreation, and pollination for selected years from 2001 to 2015. Results illustrate how information from ecosystem accounts can contribute to policy and decision making. Using an example from Atlanta, we also show how ecosystem accounts can be considered alongside other SEEA accounts to give a more complete picture of a local area’s environmental-economic trends. The process by which we determined where to place metrics within the accounting framework, which was strongly informed by the National Ecosystem Services Classification System (NESCS), can provide guidance for future ecosystem accounts in the U.S. and other countries. Finally, we identify knowledge gaps that limit the inclusion of certain ecosystem services in the accounts and suggest future research that can close these gaps and improve future U.S. ecosystem accounts.

Investment in conservation and ecological restoration depends on various socioeconomic factors and the social license for these activities. Our study demonstrates a method for targeting management of ecosystem services based on social values, identified by respondents through a collection of social survey data. We applied the Social Values for Ecosystem Services (SolVES) geographic information systems (GIS)-based tool in the Sonoita Creek watershed, Arizona, to map social values across the watershed. The survey focused on how respondents engage with the landscape, including through their ranking of 12 social values (eg, recreational, economic, or aesthetic value) and their placement of points on a map to identify their associations with the landscape. Additional information was elicited regarding how respondents engaged with water and various land uses, as well as their familiarity with restoration terminology. Results show how respondents perceive benefits from the natural environment. Specifically, maps of social values on the landscape show high social value along streamlines. Life-sustaining services, biological diversity, and aesthetics were the respondents’ highest rated social values. Land surrounding National Forest and private lands had lower values than conservation-based and state-owned areas, which we associate with landscape features. Results can inform watershed management by allowing managers to consider social values when prioritizing restoration or conservation investments.