Estimating the benefits of stream water quality improvements in urbanizing watersheds: An ecological production function approach.

Streams in urbanizing watersheds are threatened by economic development that can lead to excessive sediment erosion and surface runoff. These anthropogenic stressors diminish valuable ecosystem services and result in pervasive degradation commonly referred to as "urban stream syndrome." Understanding how the public perceives and values improvements in stream conditions is necessary to support efforts to quantify the economic benefits of water quality improvements. We develop an ecological production framework that translates measurable indicators of stream water quality into ecological endpoints. Our interdisciplinary approach integrates a predictive hierarchical water quality model that is well suited for sparse data environments, an expert elicitation that translates measurable water quality indicators into ecological endpoints that focus group participants identified as most relevant, and a stated preference survey that elicits the public's willingness to pay for changes in these endpoints. To illustrate our methods, we develop an application to the Upper Neuse River Watershed located in the rapidly developing Triangle region of North Carolina (the United States). Our results suggest, for example, that residents are willing to pay roughly $127 per household and $54 million per year in aggregate (2021 US$) for water quality improvements resulting from a stylized intervention that increases stream bank canopy cover by 25% and decreases runoff from impervious surfaces, leading to improvements in water quality and ecological endpoints for local streams. Although the three components of our analysis are conducted with data from North Carolina, we discuss how our findings are generalizable to urban and urbanizing areas across the larger Piedmont ecoregion of the Eastern United States.

Projecting U.S. forest management, market, and carbon sequestration responses to a high-impact climate scenario.

The impact of climate change on forest ecosystems remains uncertain, with wide variation in potential climate impacts across different radiative forcing scenarios and global circulation models, as well as potential variation in forest productivity impacts across species and regions. This study uses an empirical forest composition model to estimate the impact of climate factors (temperature and precipitation) and other environmental parameters on forest productivity for 94 forest species across the conterminous United States. The composition model is linked to a dynamic optimization model of the U.S. forestry sector to quantify economic impacts of a high warming scenario (Representative Concentration Pathway 8.5) under six alternative climate projections and two socioeconomic scenarios. Results suggest that forest market impacts and consumer impacts could range from relatively large losses (-$2.6 billion) to moderate gain ($0.2 billion) per year across climate scenarios. Temperature-induced higher mortality and lower productivity for some forest types and scenarios, coupled with increasing economic demands for forest products, result in forest inventory losses by end of century relative to the current climate baseline (3%-23%). Lower inventories and reduced carbon sequestration capacity result in additional economic losses of up to approximately $4.1 billion per year. However, our results also highlight important adaptation mechanisms, such forest type changes and shifts in regional mill capacity that could reduce the impact of high impact climate scenarios.

Nitrogen deposition and climate change effects on tree species composition and ecosystem services for a forest cohort.

The composition of forests in the northeastern United States and the ecosystem services they provide to future generations will depend on several factors. In this paper, we isolate the effects of two environmental drivers, nitrogen (N) deposition and climate (temperature and precipitation) change, through an analysis of a single cohort of 24 dominant tree species. We assembled a tree database using data from U.S. Forest Service Forest Inventory and Analysis monitoring plots. Applying observed species-specific growth and survival responses, we simulated how forest stands in a 19-state study area would change from 2005 to 2100 under 12 different future N deposition-climate scenarios. We then estimated implications for three selected forest ecosystem services: merchantable timber, aboveground carbon sequestration, and tree diversity. Total tree biomass (for 24 species combined) was positively associated with both increased N deposition and temperatures; however, due to differences in the direction and magnitude of species-specific responses, forest composition varied across scenarios. For example, red maple (Acer rubrum) trees gained biomass under scenarios with more N deposition and more climate change, whereas biomass of yellow birch (Betula alleghaniensis) and red pine (Pinus resinosa) was negatively affected. Projections for ecosystem services also varied across scenarios. Carbon sequestration, which is positively associated with biomass accumulation, increased with N deposition and increasing climate change. Total timber values also increased with overall biomass; however, scenarios with increasing climate change tended to favor species with lower merchantable value, whereas more N deposition favored species with higher merchantable value. Tree species diversity was projected to decrease with greater changes in climate (warmer temperatures), especially in the northwestern, central, and southeastern portions of the study area. In contrast, the effects of N deposition on diversity varied greatly in magnitude and direction across the study area. This study highlights species-specific and regional effects of N deposition and climate change in northeastern U.S. forests, which can inform management decision for air quality and forests in the region, as well as climate policy. It also provides a foundation for future studies that may incorporate other important factors such as multiple cohorts, sulfur deposition, insects, and diseases.

Geographic variation in projected US forest aboveground carbon responses to climate change and atmospheric deposition.

Forest composition and ecosystem services are sensitive to anthropogenic pressures like climate change and atmospheric deposition of nitrogen (N) and sulfur (S). Here we extend recent forest projections for the current cohort of trees in the contiguous US, characterizing potential changes in aboveground tree carbon at the county level in response to varying mean annual temperature, precipitation, and N and S deposition. We found that relative to a scenario with N and S deposition reduction and no climate change, greater climate change led generally to decreasing aboveground carbon (mean -7.5% under RCP4.5, -16% under RCP8.5). Keeping climate constant, reduced N deposition tended to lessen aboveground carbon (mean -7%), whereas reduced S deposition tended to increase aboveground carbon (+3%) by 2100. Through mid-century (2050), deposition was more important for predicting carbon responses except under the extreme climate scenarios (RCP8.5); but, by 2100, climate drivers generally outweighed deposition. While more than 70% of counties showed reductions in aboveground carbon relative to the reference scenario, these were not evenly distributed across the US. Counties in the Northwest and Northern Great Plains, and the northern parts of New England and the Midwest, primarily showed positive responses, while counties in the Southeast showed negative responses. Counties with greater initial biomass showed less negative responses to climate change while those which exhibited the greatest change in composition (>15%) had a 95% chance of losing carbon relative to a no-climate change scenario. This analysis highlights that declines in forest growth and survival due to increases in mean temperature and reductions in atmospheric N deposition are likely to outweigh positive impacts of reduced S deposition and potential increases in precipitation. These effects vary at the regional and county level, however, so forest managers must consider local rather than national dynamics to maximize forest carbon sinks in the future.

Climate change could negate U.S. forest ecosystem service benefits gained through reductions in nitrogen and sulfur deposition.

Climate change and atmospheric deposition of nitrogen (N) and sulfur (S) impact the health and productivity of forests. Here, we explored the potential impacts of these environmental stressors on ecosystem services provided by future forests in the contiguous U.S. We found that all stand-level services benefitted (+ 2.6 to 8.1%) from reductions in N+S deposition, largely attributable to positive responses to reduced S that offset the net negative effects of lower N levels. Sawtimber responded positively (+ 0.5 to 0.6%) to some climate change, but negatively (- 2.4 to - 3.8%) to the most extreme scenarios. Aboveground carbon (C) sequestration and forest diversity were negatively impacted by all modelled changes in climate. Notably, the most extreme climate scenario eliminated gains in all three services achieved through reduced deposition. As individual tree species responded differently to climate change and atmospheric deposition, associated services unique to each species increased or decreased under future scenarios. Our results suggest that climate change should be considered when evaluating the benefits of N and S air pollution policies on the services provided by U.S. forests.

Using ecosystem services to inform decisions on U.S. air quality standards.

The ecosystem services (ES) framework provides a link between changes in a natural system's structure and function and public welfare. This systematic integration of ecology and economics allows for more consistency and transparency in environmental decision making by enabling valuation of nature's goods and services in a manner that is understood by the public. This policy analysis (1) assesses the utility of the ES conceptual framework in the context of setting a secondary National Ambient Air Quality Standard (NAAQS), (2) describes how economic valuation was used to summarize changes in ES affected by NOx and SOx in the review, and (3) uses the secondary NOxSOx NAAQS review as a case study to highlight the advantages and challenges of quantifying air pollutant effects on ES in a decision making context. Using an ES framework can benefit the decision making process by accounting for environmental, ecological, and social elements in a holistic manner. As formal quantitative linkages are developed between ecosystem structure and function and ES, this framework will increasingly allow for a clearer, more transparent link between changes in air quality and public welfare.

A Participatory Science Approach to Evaluating Factors Associated with the Occurrence of Metals and PFAS in Guatemala City Tap Water.

Limited information is available regarding chemical water quality at the tap in Guatemala City, preventing individuals, water utilities, and public health authorities from making data-driven decisions related to water quality. To address this need, 113 participants among households served by a range of water providers across the Guatemala City metropolitan area were recruited as participatory scientists to collect first-draw and flushed tap water samples at their residence. Samples were transported to the U.S. and analyzed for 20 metals and 25 per- and polyfluoroalkyl substances (PFAS). At least one metal exceeded the Guatemalan Maximum Permissible Limit (MPL) for drinking water in 63% of households (n = 71). Arsenic and lead exceeded the MPL in 33.6% (n = 38) and 8.9% (n = 10) of samples, respectively. Arsenic was strongly associated with groundwater while lead occurrence was not associated with location, water source, or provider. One or more PFAS were detected in 19% of samples (n = 21, range 2.1-64.2 ppt). PFAS were significantly associated with the use of plastic water storage tanks but not with location, water source, or provider. Overall, the high prevalence of arsenic above the MPL in Guatemala City tap water represents a potential health risk that current water treatment processes are not optimized to remove. Furthermore, potential contaminants from premise plumbing and storage, including lead and PFAS, represent additional risks requiring further investigation and public engagement.

Methods for the meta-analysis of willingness-to-pay data: an overview.

Given the policy relevance and growing volume of research measuring individuals' willingness to pay (WTP) for health-related goods and services, meta-analysis provides a potentially rich set of tools for answering key questions about this research area. In particular, when taken as a whole, what does the existing empirical literature tell us about health preferences, the effectiveness of health policies, and the demand for health-related goods and services? Although the application of meta-analysis techniques to health-related WTP data is fundamentally similar to other meta-analysis applications, it nonetheless presents a number of specific challenges. The purpose of this article is to describe some of the main features that distinguish WTP research and to discuss ways in which meta-analysis methods must be tailored to meet these challenges. One of the most notable features of this research area is its heterogeneity in terms of research methods, reporting practices and publication outlets. This article discusses the implications of this diversity for the methods used at various stages of meta-analysis, including problem formulation, data collection, data evaluation and abstraction, data preparation and data analysis. One central implication is a strong reliance on meta-regression and panel data approaches. Another key feature is the frequent objective of providing benefit estimates for economic evaluation. The implication for meta-analysis is that it is a powerful tool not only for synthesizing results and testing hypotheses, but also for predicting WTP and generating benefit estimates for a variety of scenarios. This article discusses what this role implies for how meta-analysis is conducted and how the results are reported.

Using a final ecosystem goods and services approach to support policy analysis.

Evaluating environmental policies requires estimating the impacts of policy-induced changes on ecological and human systems. Drawing connections between biophysical and economic models is complex due to the multidisciplinary nature of the task and the lack of data. Further, time and resource constraints typically limit our ability to conduct original valuation studies to fit the specific policy context. Policy analysts thus rely on methods to transfer and adapt value estimates from existing studies. To conduct end-to-end policy analysis, assumptions are needed to make the linkages between ecological and valuation models as well as to conduct benefit transfers. This paper discusses an approach that can potentially help a policy analyst to minimize assumptions and identify appropriate caveats. This approach focuses on what human beings truly value from ecosystems, or, in other words, metrics of Final Ecosystem Goods and Services (FEGS). our hypothesis is that the FEGS approach will help support policy analysis by drawing important linkages between ecological and economic models as well as by designing valuation studies that will be more conducive to benefit transfers. To examine this hypothesis, we use a selected set of existing valuation studies as case study examples, and we examine how the methods used in these studies compare with the FEGS approach. We find that the studies are not always consistent with the FEGS approach, in many cases due to data limitations. We illustrate ways in which using FEGS metrics can provide economists with a useful starting point for considering how the commodity can be defined and specified in the valuation study. Even if data limitations exist, a FEGS approach can help in determining whether the context in which the original study was conducted matches with the policy context. This can also help in determining the extent of uncertainty associated with the analysis and in providing transparent documentation that can be informative for policy makers.

Identifying and assessing the application of ecosystem services approaches in environmental policies and decision making.

The presumption is that ecosystem services (ES) approaches provide a better basis for environmental decision making than do other approaches because they make explicit the connection between human well-being and ecosystem structures and processes. However, the existing literature does not provide a precise description of ES approaches for environmental policy and decision making, nor does it assess whether these applications will make a difference in terms of changing decisions and improving outcomes. We describe 3 criteria that can be used to identify whether and to what extent ES approaches are being applied: 1) connect impacts all the way from ecosystem changes to human well-being, 2) consider all relevant ES affected by the decision, and 3) consider and compare the changes in well-being of different stakeholders. As a demonstration, we then analyze retrospectively whether and how the criteria were met in different decision-making contexts. For this assessment, we have developed an analysis format that describes the type of policy, the relevant scales, the decisions or questions, the decision maker, and the underlying documents. This format includes a general judgment of how far the 3 ES criteria have been applied. It shows that the criteria can be applied to many different decision-making processes, ranging from the supranational to the local scale and to different parts of decision-making processes. In conclusion we suggest these criteria could be used for assessments of the extent to which ES approaches have been and should be applied, what benefits and challenges arise, and whether using ES approaches made a difference in the decision-making process, decisions made, or outcomes of those decisions. Results from such studies could inform future use and development of ES approaches, draw attention to where the greatest benefits and challenges are, and help to target integration of ES approaches into policies, where they can be most effective. Integr Environ Assess Manag 2017;13:41-51. © 2016 SETAC.

Terrestrial acidification and ecosystem services: effects of acid rain on bunnies, baseball, and Christmas trees.

Often termed "acid rain," combined nitrogen and sulfur deposition can directly and indirectly impact the condition and health of forest ecosystems. Researchers use critical loads (CLs) to describe response thresholds, and recent studies on acid-sensitive biological indicators show that forests continue to be at risk from terrestrial acidification. However, rarely are impacts translated into changes in "ecosystem services" that impact human well-being. Further, the relevance of this research to the general public is seldom communicated in terms that can motivate action to protect valuable resources. To understand how changes in biological indicators affect human well-being, we used the STEPS (Stressor-Ecological Production function-final ecosystem Services) Framework to quantitatively and qualitatively link CL exceedances to ecosystem service impacts. We specified the cause-and-effect ecological processes linking changes in biological indicators to final ecosystem services. The Final Ecosystem Goods and Services Classification System (FEGS-CS) was used within the STEPS Framework to classify the ecosystem component and the beneficiary class that uses or values the component. We analyzed two acid-sensitive tree species, balsam fir (Abies balsamea) and white ash (Fraxinus americana), that are common in northeastern USA. These well-known species provide habitat for animals and popular forest products that are relatable to a broad audience. We identified 160 chains with 10 classes of human beneficiaries for balsam fir and white ash combined, concluding that there are resources at risk that the public may value. Two stories resulting from these explorations into the cascading effects of acid rain on terrestrial resources are ideal for effective science communication: the relationship between (1) balsam fir as a popular Christmas tree and habitat for the snowshoe hare, a favorite of wildlife viewers, and (2) white ash because it is used for half of all baseball bats, fine wood products, and musical instruments. Thus, rather than focusing on biological indicators that may only be understood or appreciated by specific stakeholders or experts, this approach extends the analysis to include impacts on FEGS and humans. It also lays the foundation for developing stakeholder-specific narratives, quantitative measures of endpoints, and for conducting demand-based valuations of affected ecosystem services.

A framework to quantify the strength of ecological links between an environmental stressor and final ecosystem services.

Anthropogenic stressors such as climate change, increased fire frequency, and pollution drive shifts in ecosystem function and resilience. Scientists generally rely on biological indicators of these stressors to signal that ecosystem conditions have been altered. However, these biological indicators are not always capable of being directly related to ecosystem components that provide benefits to humans and/or can be used to evaluate the cost-benefit of a change in health of the component (ecosystem services). Therefore, we developed the STEPS (STressor - Ecological Production function - final ecosystem Services) Framework to link changes in a biological indicator of a stressor to final ecosystem services. The STEPS framework produces "chains" of ecological components that explore the breadth of impacts resulting from the change of a stressor. Chains are comprised of the biological indicator, the ecological production function (EPF; which uses ecological components to link the biological indicator to a final ecosystem service), and the user group who directly uses, appreciates, or values the component. The framework uses a qualitative score (High, Medium, Low) to describe the Strength of Science (SOS) for the relationship between each component in the EPF. We tested the STEPS Framework within a workshop setting using the exceedance of critical loads of air pollution as a model stressor and the Final Ecosystem Goods and Services Classification System (FEGS-CS) to describe final ecosystem services. We identified chains for four modes of ecological response to deposition: aquatic acidification, aquatic eutrophication, terrestrial acidification, and terrestrial eutrophication. The workshop participants identified 183 unique EPFs linking a change in a biological indicator to a FEGS; and when accounting for the multiple beneficiaries, we ended with 1104 chains. The SOS scores were effective in identifying chains with the highest confidence ranking as well as those where more research is needed. The STEPS framework could be adapted to any system in which a stressor is modifying a biological component. The results of the analysis can be used by the social science community to apply valuation measures to multiple or selected chains, providing a comprehensive analysis of the effects of anthropogenic stressors on measures of human well-being.

Eliciting benefit-risk preferences and probability-weighted utility using choice-format conjoint analysis.

This study applies conjoint analysis to estimate health-related benefit-risk tradeoffs in a non-expected-utility framework. We demonstrate how this method can be used to test for and estimate nonlinear weighting of adverse-event probabilities and we explore the implications of nonlinear weighting on maximum acceptable risk (MAR) measures of risk tolerance. We obtained preference data from 570 Crohn's disease patients using a web-enabled conjoint survey. Respondents were presented with choice tasks involving treatment options that involve different efficacy benefits and different mortality risks for 3 possible side effects. Using conditional logit maximum likelihood estimation, we estimate preference parameters using 3 models that allow for nonlinear preference weighting of risks--a categorical model, a simple-weighting model, and a rank dependent utility (RDU) model. For the second 2 models we specify and jointly estimate 1- and 2-parameter probability weighting functions. Although the 2-parameter functions are more flexible, estimation of the 1-parameter functions generally performed better. Despite well-known conceptual limitations, the simple-weighting model allows us to estimate weighting function parameters that vary across 3 risk types, and we find some evidence of statistically significant differences across risks. The parameter estimates from RDU model with the single-parameter weighting function provide the most robust estimates of MAR. For an improvement in Crohn's symptom severity from moderate and mild, we estimate maximum 10-year mortality risk tolerances ranging from 2.6% to 7.1%. Our results provide further the evidence that quantitative benefit-risk analysis used to evaluate medical interventions should account explicitly for the nonlinear probability weighting of preferences.

Rates and costs of respiratory illness in coal mining: a cross-industry comparative analysis.

OBJECTIVE: To estimate the prevalence and costs of respiratory illness for workers in coal mining, compared with other US industries. METHODS: Using 5 years of insurance claims data for an annual average of 96,240 adult males, we model the probability and costs of respiratory illness as a function of workers' industry and other factors. RESULTS: Controlling for nonindustry factors, workers in coal mining had significantly higher rates of respiratory illness claims (by 2.1% to 3.3% points) compared with other mining, agriculture, construction, and manufacturing. For coal mining workers with respiratory illness, annual medical care costs for these claims were also significantly higher (by $111 to $289). Surprisingly, drug costs were mostly lower (by $17 to $268). CONCLUSIONS: Our findings underscore the continued importance and potential cost effectiveness of measures to protect miners from harmful occupational exposures, particularly to coal dust.

Multiple sclerosis patients' benefit-risk preferences: serious adverse event risks versus treatment efficacy.

OBJECTIVE: The aim of this study is to estimate the willingness of multiple sclerosis (MS) patients to accept life-threatening adverse event risks in exchange for improvements in their MS related health outcomes. METHODS: MS patients completed a survey questionnaire that included a series of choice-format conjoint tradeoff tasks. Patients chose hypothetical treatments from pairs of treatment alternatives with varying levels of clinical efficacy and associated risks. RESULTS: Among the 651 patients who completed the survey, delay in years to disability progression was the most important factor in treatment preferences. In return for decreases in relapse rates from 4 to 1 and increases in delay in progression from 3 to 5 years, patients were willing to accept a 0.38% annual risk of death or disability from PML, a 0.39% annual risk of death from liver failure or a 0.48% annual risk of death from leukemia. CONCLUSIONS: Medical interventions carry risks of adverse outcomes that must be evaluated against their clinical benefits. Most MS patients indicated they are willing to accept risks in exchange for clinical efficacy. Patient preferences for potential benefits and risks can assist in decision-making.

Valuing avoided morbidity using meta-regression analysis: what can health status measures and QALYs tell us about WTP?

Many economists argue that willingness-to-pay (WTP) measures are most appropriate for assessing the welfare effects of health changes. Nevertheless, the health evaluation literature is still dominated by studies estimating nonmonetary health status measures (HSMs), which are often used to assess changes in quality-adjusted life years (QALYs). Using meta-regression analysis, this paper combines results from both WTP and HSM studies applied to acute morbidity, and it tests whether a systematic relationship exists between HSM and WTP estimates. We analyze over 230 WTP estimates from 17 different studies and find evidence that QALY-based estimates of illness severity--as measured by the Quality of Well-Being (QWB) Scale--are significant factors in explaining variation in WTP, as are changes in the duration of illness and the average income and age of the study populations. In addition, we test and reject the assumption of a constant WTP per QALY gain. We also demonstrate how the estimated meta-regression equations can serve as benefit transfer functions for policy analysis. By specifying the change in duration and severity of the acute illness and the characteristics of the affected population, we apply the regression functions to predict average WTP per case avoided.

Private demand for a HIV/AIDS vaccine: evidence from Guadalajara, Mexico.

The private demand for a hypothetical vaccine that would provide lifetime protection against HIV/AIDS to an uninfected adult was measured in Guadalajara, Mexico, using the concept of willingness to pay (WTP). A 91-question survey instrument was administered by trained enumerators employing contingent valuation techniques to 234 adults, aged 18-60. Our estimates of private demand indicate that individuals anticipate sizable personal benefits from such a vaccine, and that they would be willing to allocate a substantial portion of their income to be protected in this way from HIV infection. A conservative estimate of the mean WTP of adults in the Guadalajara sample is 6358 pesos (669 US dollars) and the median is 3000 pesos (316 US dollars). A multivariate statistical analysis of the determinants of individuals' WTP shows that individuals with higher incomes, with spouses or partners, and with higher perceived risks of becoming infected with HIV are willing to pay more for the vaccine. Older respondents are willing to pay less. These results suggest that there is likely to be a potentially large private market for a HIV/AIDS vaccine in the middle-income developing countries such as Mexico. These findings have important implications both for the level of R&D effort that is devoted to a vaccine and, assuming these efforts are successful, for future policies to make the vaccine available to the public.