Restoring agricultural watersheds often involves incentivizing private landowners to adopt conservation practices that have high public benefits but low or uncertain private benefits for farmers. In the United States, public and private institutions provide overlapping incentives to adopt conservation practices and most funding is governed by complex rules for eligibility and reimbursement. The burden on landowners of navigating such institutional complexity is often cited as a key barrier to their adoption of conservation practices. These barriers contribute to institutional misfit, or the misalignment of program designs and farmers' expectations of them. The rate of conservation practice adoption in the Chesapeake Bay watershed (CBW) is higher than the national average, and can provide insights into overcoming institutional misfit. Previous research with conservation practitioners (CPs) in the CBW suggested that much of their engagement with farmers centered on improving institutional fit. To better explore the role of CPs in enhancing institutional fit, we interviewed over 130 farmers in the CBW, representing diverse farm sizes and both direct-to-market and commodity producers, about their perceptions of, and experiences with, incentive programs. Using qualitative text analysis, we suggest that farmers' key programmatic concerns center on the application and funding process and the impact of programs on farm operation. Further, we argue that farmers evaluated the effectiveness of CPs based on their ability to share knowledge, understand the farmers' vision, and be professional. These expectations of CPs have statistically significant explanatory power in describing farmers' overall satisfaction with CPs. We also found preliminary evidence of a positive correlation between the number of conservation practices adopted by farmers and whether they met with, and were satisfied with the work of, CPs. Together these results suggest that, along with difficult and time-intensive redesigns of formal agricultural conservation assistance programs, the institutional fit of such programs can be enhanced via the relationships between CPs and farmers and the extent to which the former meets the latter's expectations. Additionally, CPs could further improve their work and possibly achieve more conservation adoption by learning more about the practicalities of farming, taking the time to understand farmers' visions for their land, and being professional.

Multivariate social vulnerability indices, used to compare communities' susceptibility to adverse disaster outcomes, cannot be combined with physical exposure risk estimates without double-counting some effects and potentially obscuring risk sources. Further, the techniques used to create the indices appear to have methodological concerns, including diluting the signal of poverty in defining overburdened communities, creating conflict with some federal and state policy definitions. This research examined ways to modify social vulnerability indices to isolate the residual social risk that could serve as a multiplier on flood or other quantitative risk assessments, and thereby create an equity-weighted risk metric. We advanced this concept by reviewing the social vulnerability studies that tested the explanatory power of sociodemographic indicators on disaster outcomes, when controlling for physical exposure risk. We then suggested a new type of vulnerability index, or Equity (E) Index, that isolated the indicators with the strongest evidence that they represented residual social risk and examined their potential magnitude as multipliers on physical exposure risk. We also used multiple decision science techniques to minimize some undesirable index construction issues. Whereas the literature provided mixed evidence for all indicators, poverty, disability, and old age had the highest confidence that they amplified physical risk. Other factors such as race, ethnicity, acculturation, mobility limitations, children under five, and female single parents had an intermediate level of support. Indicators of median home value and low education were less frequently tested, and gender and percentage of renters had ambiguous signs. An initial exploration of empirical models suggested that, on average, the E index approximately doubled the effect of physical harm when assessing outcomes for the most vulnerable groups, but further research and validation are required.

Increasingly, environmental modelers are called upon to evaluate the sustainability and ecosystem health (EH) impacts of new policies and land management practices. This demand requires modelers to convert the normative, value-laden concept of EH into a measurable quantity. To solve this problem, many have turned to the ecosystem services (ES) framework, an established system for quantifying the benefits humans derive from their natural environment. ES include a wide range of environmental variables, allowing modelers to select diverse indicators for EH. But leaving indicator selection up to modelers’ individual judgment gives researchers substantial control over the discourse of EH, raising ethical questions about inclusivity and objectivity. This study aims to examine the ES used in published EH modeling studies, with the goal of generating insight into the ways modelers define EH through ES indicator selection. Through a Web of Science database search, we identified 310 journal articles that lay at the intersection of EH and ES research. Further screening narrowed our focus to 49 papers that employed ES as the sole indicator variables in an EH assessment. In our systematic review of these 49 ES/EH modeling research papers, we classified indicators systematically and collected quantitative data on the ES that appear frequently in EH research. The three most frequently studied ES in the review, appearing in more than 20 papers each, were water quality, water provisioning, and global climate regulation. Results suggested physical ecosystem goods are preferred EH indicators, while environmental processes that do not have direct benefits for humans tend to be less frequently chosen as indicators in ES modeling research. Textual analysis and interviews with modelers are needed to fully understand the EH values and beliefs that influence indicator selection, but this study is an initial step towards a clearer understanding of the patterns of ES indicator selection in modeling research that involves normative assessment of EH.

Shellfish aquaculture producers in coastal systems are facing uncertain future growing conditions as climate change alters weather patterns and raises sea level. We examined expected mid-century (2059-2068) changes in aquaculture profitability from recent conditions by integrating models of climate change, estuarine hydrodynamics and biogeochemistry, oyster growth, oyster mortality, and economics, using the Chesapeake Bay, USA as a case study. We developed an economic stochastic dynamic programming (SDP) approach that generates optimal grower behavior to maximize profits under uncertainty by dynamically choosing planting density, replanting and mitigation use, in response to changing oyster stock status and water quality conditions. Separate models were developed for bottom culture largely serving the cannery market, and container culture largely serving the half-shell market, to reflect different production costs, market prices, and oyster growth and survival. The coupled hydrodynamic-biogeochemical and oyster ecology models projected high spatial variability in oyster growth and mortality with the most favorable growing conditions in the lower north and upper mid bay, where mortality is lowest, and the upper south bay, where growth is highest. Climate change by late mid-century generated modest water quality changes and virtually no mortality rate changes. Nonetheless, our modeling revealed that even if growers made optimal management choices under uncertainty, the majority of modeled sites would see a decline in profitability under climate change, primarily due to potential reductions in food availability. Bottom culture was more resilient to the future climate at most sites, being less sensitive to small changes in growth than container culture. Information on how aquaculture conditions currently vary in space was more important for profitability than future climate forecasts. Our stochastic dynamic programming approach tailored grower behavior to each site and unfolding annual conditions, including highly targeted and cost-effective mitigation adjustments to boost oyster survival or growth.

Worldwide, enhancement of oyster populations is undertaken to achieve a variety of goals including support of food production, local economies, water quality, coastal habitat, biodiversity, and cultural heritage. Although numerous strategies for improving oyster stocks exist, enhancement efforts can be thwarted by long-standing conflict among community groups about which strategies to implement, where efforts should be focused, and how much funding should be allocated to each strategy. The objective of this paper is to compare two engagement approaches that resulted in recommendations for multi-benefit enhancements to oyster populations and the oyster industry in Maryland, U.S.A., using the Consensus Solutions process with collaborative simulation modeling. These recommendations were put forward by the OysterFutures Workgroup in 2018 and the Maryland Oyster Advisory Commission (OAC) in 2021. Notable similarities between the efforts were the basic principles of the Consensus Solutions process: neutral facilitation, a 75% agreement threshold, the presence of management agency leadership at the meetings, a scientific support team that created a management scenario model in collaboration with community group representatives, numerous opportunities for representatives to listen to each other, and a structured consensus building process for idea generation, rating, and approval of management options. To ensure meaningful representation by the most affected user groups, the goal for membership composition was 60% from industry and 40% from advocacy, agency, and academic groups in both processes. Important differences between the processes included the impetus for the process (a research program versus a legislatively-mandated process), the size of the groups, the structure of the meetings, and the clear and pervasive impact of the COVID-19 pandemic on the ability of OAC members to interact. Despite differences and challenges, both groups were able to agree on a package of recommendations, indicating that consensus-based processes with collaborative modeling offer viable paths toward coordinated cross-sector natural resource decisions with scientific basis and community support. In addition, collaborative modeling resulted in ‘myth busting’ findings that allowed participants to reassess and realign their thinking about how the coupled human-oyster system would respond to management changes.

Excessive nitrogen (N) pollution in the Chesapeake Bay is threatening ecological health. This study presents a multilayer N flow network model where each network layer represents a stage in the production step from raw agricultural commodities such as corn to final products such as packaged meat. We use this model to assess the impacts of alternative future agricultural production and land use changes on multiple pathways of N pollution within the Chesapeake Bay Watershed (CBW). We analyzed N loss via all pathways under multiple future scenarios, considering crop-specific projections based on empirical data and US Department of Agriculture projections. We found two model parameters, fertilizer nitrogen application rate (FNAR) and feed conversion ratio (FCR), to be particularly important for seeing measurable N loss reductions in the Bay. Our results indicate a large increase in N loss under the business-as-usual trajectory in geographic locations with intensive agricultural production. We found that numerous management scenarios including improvements in FNAR and FCR, N losses fall short of the 25% total maximum daily load targets. Our work suggests that achieving the CBW N loss reduction goals will necessitate large deviations from business as usual. Our model also highlights substantial regional variations in nitrogen loss across the U.S., with central regions like the Corn Belt and Central Valley of California experiencing the highest losses from crop-related stages, while eastern areas such as the Chesapeake Bay exhibit major losses from live animal production, underscoring the need for region-specific management strategies. Thus, implementation of effective N management strategies, combined with improved crop residue management, remains pivotal in mitigating N pollution in the Chesapeake Bay.

Management decisions for the eastern oyster ( Crassostrea virginica) ) fishery in Maryland are made at a finer spatial scale than the spatial data resolution of the current stock assessment. This mismatch creates concerns that the consequences of management actions and fishing activities are not being adequately represented when assessing fishery status. To produce a model that could support a participatory modeling process intended to differentiate results of fine-scale management actions we developed a method for conditioning a down-scaled oyster stock assessment model to produce a spatially-explicit operating model at the scale of individual oyster bars for eastern oysters in Chesapeake Bay, Maryland. To ensure that parameter values of the operating model were consistent with data at multiple scales we fitted the model to bar-specific harvest data during 2004-2020 and regional abundance estimates from the current Maryland Oyster Stock Assessment during 1999-2020. The operating model can then predict effects of different management actions, such as planting hatchery-reared oysters, addition of substrate, or modifying fishing regulations, at a bar-specific scale and compare outcomes among different scenarios. Model outputs included a suite of management performance metrics, including but not limited to oyster abundance and fishery harvest, that were important to stakeholders. These bar-specific scenarios would not have been possible using an operating model with the same spatial resolution as the current Maryland Oyster Stock Assessment. Accounting for fine scale spatial processes can be important to engaging participants and our model provides an expedient option to develop an operating model that downscales stock assessment models.

Would-be adopters of ecosystem service analysis frameworks might ask, ‘Do such frameworks improve ecosystem service provision or social benefits sufficiently to compensate for any extra effort?’ Here we explore that question by retrospectively applying an ecosystem goods and services (EGS) analysis framework to a large river restoration case study conducted by the US Army Corps of Engineers (USACE) and comparing potential time costs and outcomes of traditional versus EGS-informed planning. USACE analytic methods can have a large influence on which river and wetland restoration projects are implemented in the United States because they affect which projects or project elements are eligible for federal cost-share funding. A new framework is designed for the USACE and is primarily distinguished from current procedures by adding explicit steps to document and compare tradeoffs and complementarity among all affected EGS, rather than the subset that falls within project purposes. Further, it applies economic concepts to transform ecological performance indicators into social benefit indicators, even if changes cannot be valued. We conclude that, for large multi-partner restoration projects like our case study, using the framework provides novel information on social outcomes that could be used to enhance project design, without substantially increasing scoping costs. The primary benefits of using the framework in the case study appeared to stem from early comprehensive identification of stakeholder interests that might have prevented project delays late in the process, and improving the communication of social benefits and how tradeoffs among EGS benefits were weighed during planning.

Although implementing conservation practices on private farms and forests can produce substantial environmental benefits, these practices are not being adopted widely enough to result in measurable improvements at regional scales. Researchers have investigated the production and program factors influencing producer choices to voluntarily adopt these practices. However, the findings of reviews are inconsistent, raising questions about review methods, including the omission of relevant variables. Further, applying lessons from past work to promote adoption is difficult because many reviews investigated dispositional or demographic variables that practitioners and policy makers cannot directly observe or influence. We conducted a new review of 146 empirical studies that tested the effects of different interventions (e.g., financial incentives, outreach events, and nudges) on increasing the likelihood of producers adopting conservation practices. We conducted a metaregression of quantitative studies from diverse disciplines that filtered studies by quality (i.e., use of randomization and clear analysis reporting). We synthesized these results with a thematic analysis of qualitative studies on producer perspectives about conservation practices. Financial incentives had the strongest evidence of increasing producers’ likelihood of adopting conservation practices (odds ratio 1.86, p < 0.05). However, this effect was only apparent after filtering by study quality, which also improved model fit and identified significant regional differences (odds ratio –1.69, p < 0.01). The thematic review of qualitative studies revealed that peer groups may be successful in reinforcing adoption behaviors due to homophily effects and that financial incentives not only offset implementation costs but also mitigated perceived risks of adoption. Given the problems we encountered in testing hypotheses about the magnitude of variability explained by intervention types and practice characteristics, we recommend additional experimental and longitudinal work that accounts for financial incentives and pairs qualitative and quantitative data to clarify relationships between program design and practice adoption rates.

Chesapeake Bay oyster (Crassostrea virginica) management is often contentious due to differences in stakeholders' support for alternative strategies that aim to reverse historic declines in oyster harvests and abundance. The OysterFutures (OF) research program brought 16 stakeholders from the fishing industry, non-governmental organizations, and state and federal management agencies together to generate a consensus package of man-agement recommendations for the Choptank River basin (a tributary of the Chesapeake Bay). In this study, we looked for group effects on results by testing the consistency of the OF group-negotiated management recom-mendations with individual preferences, as evaluated through individual interviews and multi-criteria decision analysis methods (MCDA). We further tested the sensitivity of option rankings to stakeholder group composition, preference elicitation method, and MCDA analytic choices. We developed metrics of cost-effectiveness and eli-cited time preferences for outcomes, which were only used implicitly in the negotiated OF process. We found that group effects appeared minimal since the OF-derived set of preferred options generally ranked highly in the MCDA analysis. However, some of the recommended options were not found to be among the most cost-effective. The consistency of findings using individual vs group-derived preferences suggests that methods to elicit indi-vidual preferences outside of group meetings might complement and streamline consensus-seeking engagement processes by quickly identifying areas of agreement and disagreement to reduce the substantial time commit-ments of in-person meetings.

Shellfish hatcheries have become an increasingly important component of aquaculture production in the United States. Although the industry has been advancing technologically over time to stabilize production and supply, many hatcheries suffer regularly from bouts of stalled or failed production, termed crashes. Crashes are widely acknowledged to occur and are considered a persistent problem in the industry but also an understudied phenomenon in the field of shellfish aquaculture that warrants greater investigation. Furthermore, there are few thorough reports on production variability from established hatcheries. To help fill the data gap and initiate a broader discussion on the causes of hatchery crashes, we provide testimonials from research hatchery managers across the Atlantic Coast about their experiences with crashes. As a case study, we report on long-term production trends (2011−2020) at Horn Point Laboratory's oyster hatchery, which included persistent production failure during the 2019 season. During the 2019 season, larval assays were conducted to determine drivers of production failure; however, no clear culprits were identified. Machine learning was used to help characterize production variability and hindcast the specific conditions when the hatchery's production was most efficient. Microbial community structure of larval associated microorganisms was shown to differ between a crash and non-crash time-point. We highlight the ubiquity of hatchery crashes along the Atlantic Coast of the US, the range of severity at which crashes can occur, and the difficulty of identifying the underlying causes of crashes, even at world-class research facilities. Collectively, we conclude that more research, data sharing, and cross-institution collaboration are needed to prevent crashes, and to develop mitigation strategies to maintain high levels of consistent shellfish aquaculture production.

The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States providing crucial habitat and natural resources for culturally and economically important species. Pressures from human population growth and associated development and agricultural intensification have led to excessive nutrient and sediment inputs entering the Bay, negatively affecting the health of the Bay ecosystem and the economic services it provides. The Chesapeake Bay Program (CBP) is a unique program formally created in 1983 as a multi-stakeholder partnership to guide and foster restoration of the Chesapeake Bay and its watershed. Since its inception, the CBP Partnership has been developing, updating, and applying a complex linked modeling system of watershed, airshed, and estuary models as a planning tool to inform strategic management decisions and Bay restoration efforts. This paper provides a description of the 2017 CBP Modeling System and the higher trophic level models developed by the NOAA Chesapeake Bay Office, along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. Recom-mendations highlight the need for simulation of watershed inputs, conditions, processes, and practices at higher resolution to provide improved information to guide local nutrient and sediment management plans. More explicit and extensive modeling of connectivity between watershed landforms and estuary sub-areas, estuarine hydrodynamics, watershed and estuarine water quality, the estuarine-watershed socioecological system, and living resources will be important to broaden and improve characterization of responses to targeted nutrient and sediment load reductions. Finally, the value and importance of maintaining effective collaborations among jurisdictional managers, scientists, modelers, support staff, and stakeholder communities is emphasized. An open collaborative and transparent process has been a key element of successes to date and is vitally important as the CBP Partnership moves forward with modeling system improvements that help stakeholders evolve new knowledge, improve management strategies, and better communicate outcomes.

Background Outreach events such as trainings, demonstrations, and workshops are important opportunities for encouraging private land operators to adopt voluntary conservation practices. However, the ability to understand the effectiveness of such events at influencing conservation behavior is confounded by the likelihood that attendees are already interested in conservation and may already be adopters. Understanding characteristics of events that draw non-adopters can aid in designing events and messaging that are better able to reach beyond those already interested in conservation. Methods For this study, we interviewed 101 operators of private agricultural lands in Maryland, USA, and used descriptive statistics and qualitative comparative analysis to investigate differences between the kinds of outreach events that adopters and non-adopters attended. Results Our results suggested that non-adopters, as compared to adopters, attended events that provided production-relevant information and were logistically easy to attend. Further, non-adopters were more selective when reading advertisements, generally preferring simplicity. Future research and outreach can build on these findings by experimentally testing the effectiveness of messages that are simple and relevant to farmers’ production priorities.

Weber MA, Wainger LA, Harms NE, Nesslage GM. 2020. The economic value of research in managing invasive hydrilla in Florida public lakes. Lake Reserv Manage. XX:XX-XX. Decisions on how to allocate research funds can be informed by evaluating the benefits of research, yet past spending is rarely analyzed to gain insights for effective research allocation. We used a case study to evaluate whether research into nonnative invasive plants improved management of herbicide-resistant hydrilla (Hydrilla verticillata) in the Kissimmee Chain of Lakes (KCOL), Florida, USA. We applied a retrospective benefit-cost analysis to quantify the net economic benefits of invasive control informed by government-supported research, relative to a scenario without research funding. Using conservative assumptions, we estimated net benefits of 11 yr of research (1999-2009) and 5 yr of improved hydrilla management as $19.5 million (2017 dollars) with a benefit-cost ratio of 3.8, including avoided ecosystem service losses to angler and nonangler lake users. These benefits were about 2.2 times the annual value of recreational fishing in the KCOL. Sensitivity analysis indicated that positive net benefits were generally robust to uncertainty regarding the hydrilla intrinsic growth rate and treatment costs in the absence of research-informed protocols. We have likely underestimated research benefits because we lumped costs from multiple programs and did not measure benefits accruing to nonusers of lakes. To enable future retrospective economic analyses, we suggest some improvements in record keeping. Our findings of positive net benefits of research may be representative of cases where relatively modest research investment in invasive species control is likely to protect widely appreciated ecosystem services.

Hennig Brandt's discovery of phosphorus (P) occurred during the early European colonization of the Chesapeake Bay region. Today, P, an essential nutrient on land and water alike, is one of the principal threats to the health of the bay. Despite widespread implementation of best management practices across the Chesapeake Bay watershed following the implementation in 2010 of a total maximum daily load (TMDL) to improve the health of the bay, P load reductions across the bay's 166,000-km watershed have been uneven, and dissolved P loads have increased in a number of the bay's tributaries. As the midpoint of the 15-yr TMDL process has now passed, some of the more stubborn sources of P must now be tackled. For nonpoint agricultural sources, strategies that not only address particulate P but also mitigate dissolved P losses are essential. Lingering concerns include legacy P stored in soils and reservoir sediments, mitigation of P in artificial drainage and stormwater from hotspots and converted farmland, manure management and animal heavy use areas, and critical source areas of P in agricultural landscapes. While opportunities exist to curtail transport of all forms of P, greater attention is required toward adapting P management to new hydrologic regimes and transport pathways imposed by climate change.

Following their memorialization as protected landscapes, battlefield parks can provide a blend of cultural and other ecosystem services. Among the many threats to providing these services are non-native invasive plants. In this chapter, we assess the threats imposed by biological invasions of non-native plants in battlefield parks and discuss management strategies. We use evidence from the scientific and economic literature and the expert judgment of biologists, economists, and park managers to identify the harms caused by invasives and to characterize their effects on park ecosystem services. Based on this evidence, we propose four generic stressor-response relationships to describe the relationships between invasion extent and ecological endpoints such as park vegetation structure and diversity. Using Antietam National Battlefield as a case study, we tailor the general stressor-response curves to four specific species representing different functional groups of invasive plants: trees, shrubs, vines, and herbaceous forbs. We next link the ecological response of changes in vegetation structure and diversity to relevant ecosystem service impacts using interviews with national park service personnel and the economic literature. We identify four broad categories of parks users who might be affected by these losses of services: causal visitors, avid recreationalists, park neighbors, and non-use beneficiaries. Our findings reveal a general lack of experimental evidence quantifying the ecosystem service impacts of invasive plants. This lack of evidence, combined with the likely non-linear effects of non-native plant invasions on ecological endpoints, could catch managers unaware of dangerous thresholds in long-term resource management of battlefield landscapes.

Ecosystem service analysis aims to expand the accounting of human values for nature, yet frequently ignores or obfuscates a category of human values with potentially large magnitude, namely nonuse or passive use values. These values represent the satisfaction derived from the protection or restoration of species, habitats and wilderness areas, even if people never use them in any tangible way. The shunting of nonuse values to the background of ecosystem service analysis appears, in part, to be an attempt to avoid the perceived elitism of environmental values. To examine whether such values are the purview of the elite, we explore three types of evidence of who holds nonuse values. We find that when people are asked to 1) commit money via stated preference instruments, 2) respond to tweets, or 3) express opinions via surveys they demonstrate a significant willingness to protect and restore natural resources, regardless of their own use of those resources. Such values are represented in all socio-demographic groups that encompass race, ethnicity, immigration status, income, political affiliation, geographic location, age or gender, although the magnitude can vary among groups. The implications are that omitting nonuse values in ecosystem service analysis will tend to underestimate values, particularly for remote sites with limited use, and fail to represent important tradeoffs.

Invasive species management can be a victim of its own success when decades of effective control cause memories of past harm to fade and raise questions of whether programs should continue. Economic analysis can be used to assess the efficiency of investing in invasive species control by comparing ecosystem service benefits to program costs, but only if appropriate data exist. We used a case study of water hyacinth (Eichhornia crassipes (Mart.) Solms), a nuisance floating aquatic plant, in Louisiana to demonstrate how comprehensive record-keeping supports economic analysis. Using long-term data sets, we developed empirical and spatio-temporal simulation models of intermediate complexity to project invasive species growth for control and no-control scenarios. For Louisiana, we estimated that peak plant cover would have been 76% higher without the growth rate suppression that appeared due primarily to biological control agents. Our economic analysis revealed that combined biological and herbicide control programs, monitored over an unusually long time period (1975-2013), generated a benefit-cost ratio of about 34:1 based on benefits to anglers, waterfowl hunters, boating-dependent businesses, and water treatment facilities. This work adds to the literature by 1) providing evidence of the effectiveness of water hyacinth biological control; 2) demonstrating use of parsimonious spatio-temporal models to estimate benefits of invasive control; and 3) incorporating substitutability into economic benefit transfer to avoid overstating benefits. Our study suggests that robust and cost-effective economic analysis is enabled by good record keeping and generalizable models that can demonstrate management effectiveness and promote social efficiency of invasive species control.

A qualitative ranking method, Q methodology, was used to assess stakeholder priorities for socioecological services derived from coastal marshes and communities. The goal was to reveal strength of concerns for and tradeoffs among effects of coastal resilience strategies. Factor analysis identified three perspectives that formed a spectrum from high to low priorities on intangible services. Academic and government stakeholders were more likely than local residents to prioritize intangible services, but stakeholder views were diverse. A collaborative learning process promoted some alignment of views and academics showed the most movement – towards residents’ perspectives. Q-sort appeared effective at efficiently synthesizing broad concerns.

There is a growing movement in government, environmental non -governmental organizations and the private sector to include ecosystem services in decision making. Adding ecosystem services into assessments implies measuring how much a change in ecological conditions affects people, social benefit, or value to society. Despite consensus around the general merit of accounting for ecosystem services, systematic guidance on what to measure and how is lacking. Current ecosystem services assessments often resort to biophysical proxies (e.g., area of wetland in a floodplain) or even disregard services that seem difficult to measure. Valuation, an important tool for assessing trade-offs and comparing outcomes, is also frequently omitted due to lack of data on social preferences, lack of expertise with valuation methods, or mistrust of valuation methods for non-market services. To address these shortcomings, we propose the use of a new type of indicator that explicitly reflects an ecosystem's capacity to provide benefits to society, ensuring that ecosystem services assessments measure outcomes that are demonstrably and directly relevant to human welfare. We call these Benefit-relevant indicators (BRIs) and describe a process for developing them using causal chains that link management decisions through ecological responses to effects on human well-being. BRIs identify what is valued and by whom, but stop short of valuation. A BRI for the ability of wetlands to ameliorate flooding would connect measures of the quantity and quality of wetland in a floodplain, as affected by wetlands management decisions, to the number of people or properties downstream that are vulnerable to flooding. BRIs can support monetary or non-monetary valuation, but are particularly useful when valuation will not be conducted; in such cases they serve as stand-alone measures of "what is valued" by particular beneficiaries. BRIs are valid measures of ecosystem services in that they are directly linked to human well-being. Flexibility in the development of BRIs helps to ensure that they are broadly applicable across practitioner and stakeholder communities and decision contexts.