Linking water quality and well-being for improved assessment and valuation of ecosystem services

Despite broad recognition of the value of the goods and services provided by nature, existing tools for assessing and valuing ecosystem services often fall short of the needs and expectations of decision makers. Here we address one of the most important missing components in the current ecosystem services toolbox: a comprehensive and generalizable framework for describing and valuing water quality-related services. Water quality is often misrepresented as a final ecosystem service. We argue that it is actually an important contributor to many different services, from recreation to human health. We present a valuation approach for water quality-related services that is sensitive to different actions that affect water quality, identifies aquatic endpoints where the consequences of changing water quality on human well-being are realized, and recognizes the unique groups of beneficiaries affected by those changes. We describe the multiple biophysical and economic pathways that link actions to changes in water quality-related ecosystem goods and services and provide guidance to researchers interested in valuing these changes. Finally, we present a valuation template that integrates biophysical and economic models, links actions to changes in service provision and value estimates, and considers multiple sources of water quality-related ecosystem service values without double counting.One of the fundamental challenges of mainstreaming ecosystem services into decision making involves linking ecosystem processes with changes in human well-being (1). This is especially true for water quality-related ecosystem goods and services. Water quality is highly valued by the public, and information on water quality values is increasingly demanded by decision makers. However, there is no generalizable framework for linking changes in water quality to changes in multiple ecosystem goods and services. This is problematic because limiting ecosystem service assessments to those services with direct use value and market prices systematically undervalues ecosystem services and fails to achieve a full accounting of all of the environmental and economic tradeoffs associated with decisions.Valuing water quality changes is particularly challenging relative to other ecosystem goods and services. Changing water quality affects many aspects of human well-being, and benefits and/or costs accrue to different groups of beneficiaries at varying spatial and temporal scales. This complexity contrasts with other ecosystem services, such as carbon sequestration, for which emissions are aggregated into a global atmospheric pool. Each unit increase in carbon emissions results in a more or less constant loss in value (i.e., costs associated with climate change). By contrast, each unit improvement in water quality may affect only a local area, the value of which varies widely with spatial context and may have strongly diminishing marginal benefits (e.g., additional reductions in nutrient pollution entering a clean lake generate minimal new benefits, and those benefits are further influenced by the condition and proximity to substitute lakes). Further, actions today can affect water quality far into the future, with the consequent challenge of predicting future values.High uncertainty and lack of appropriate data to populate biophysical and economic models are also barriers to comprehensive water quality valuation. Water quality affects people through numerous pathways, from drinking water to recreation to commercial fisheries. The consequences of decisions on the provision of water quality-related ecosystem services are often separated by space and time, modified by variation in baseline conditions, and characterized by nonlinearities and thresholds (2). The value of ecosystem services, especially for cultural and aesthetic values, is also likely to be highly uncertain.Previous work has made progress in identifying sources of water quality value and in developing nonmarket approaches to valuation, but most water quality valuation tools fall short of the needs and expectations of decision makers (3). First, few water quality valuation assessments account for the multiple costs and/or benefits of water quality-related changes. Recent assessments of the water quality impacts of bioenergy policy in the United States (e.g., refs. 4 and 5) focus solely on the contribution of fertilizer-derived nitrogen to hypoxia in the Gulf of Mexico, neglecting other potential consequences for drinking water treatment costs, human health, and diminished recreational opportunities. Failure to consider all of the water quality-related consequences for well-being can lead to a serious underestimate of the true value of changes in ecosystem services associated with a given action or decision.A second shortcoming of existing work on water quality valuation, and ecosystem services research in general, is that valuation assessments often are not linked with changes in management, land use, or other actions that lead to water quality change (1). Assessments of the total costs of eutrophication (e.g., ref. 6) or the total value of ecosystem services from an ecosystem or land cover type (e.g., refs. 7 and 8) do little to help a decision maker trying to assess the consequences of alternative actions. The value attributable to conserving wetlands for improved sediment retention, for example, needs to be assessed relative to a specified alternative land cover or management action (i.e., draining wetlands for agriculture or urban development). Decision makers need models that are sensitive to the variation in local ecological conditions that affect the provision of ecosystem services, as well as to variation in local social and economic conditions that affect the value of ecosystem services to beneficiaries. By failing to link valuation estimates with specific actions and subsequent changes in human well-being, researchers also risk double-counting of value (9).Finally, economic models for valuing water quality-related ecosystem services are often poorly integrated with ecological and hydrologic models. Biophysical and economic models are typically developed in isolation, without consideration of how the outputs of one model may feed into the next, making it challenging to integrate models and data. For example, the water quality metrics most commonly measured by scientists are not well connected with attributes the public actually values (e.g., people value the extent to which they can safely use and enjoy a lake; they do not directly value the concentration of phosphorus in the lake). Similarly, many economic models require inputs that are very different from the outputs of standard water quality models.

Framework for Water Quality Valuation.

We propose a unique framework for the assessment and valuation of water quality-related services that addresses many of the shortcomings of existing work. Our approach is comprehensive, integrates biophysical and economic research, is sensitive to alternative land use or management decisions, and avoids double-counting of costs or benefits. To maximize the potential utility for decision making, the framework links actions to a measured or modeled change in water quality and then to changes in the value of ecosystem goods and services (Fig. 1).Open in a separate windowFig. 1.Framework for linking actions to values for water quality-related ecosystem services.Biophysical models inform the linkage between actions or changes on the landscape and a change in water quality (Fig. 1A) as measured by changes in nutrient concentrations, sediment loading, or inputs of toxins or other chemicals. Models focusing on the characterization of changes in water quality include continuous daily time step models, such as the Soil and Water Assessment Tool (10), and less complex models, such as the Integrated Valuation of Ecosystem Services and Tradeoffs (11). These models have been used to estimate the water quality consequences of future land use scenarios (12) or the effectiveness of conservation policies (13). Outputs from the biophysical models may be expressed in terms of nutrient retention across a landscape or in loadings to specific aquatic endpoints.The second step in our framework (Fig. 1B) links changes in water quality to changes in the provision of ecosystem goods and services that directly affect human well-being. Lack of appropriate models or data to describe this link often limits the potential to successfully integrate biophysical and economic models. Ideally, biophysical models would translate water quality changes to valued goods and services, such as changes in catch per unit effort of fishes, frequency of beach closures, or the toxicity of harmful algal blooms. However, many of these relationships are either poorly understood, difficult to generalize, or we lack the data to quantify the relationships. Specificity is also an important part of this linkage: water quality affects many different aspects of human well-being, so a change in one water quality constituent may affect different beneficiaries at varying spatial and temporal scales.The final linkage in the framework (Fig. 1C) connects changes in ecosystem goods and services to changes in values. There are numerous approaches used by economists to place an economic value on water quality-related ecosystem services (14–17). In brief, economists can ask respondents directly how much they would be willing to pay for a given improvement in water quality (stated preference methods). Alternately, economists can indirectly estimate the value of changes in water quality through observations of human behavior, such as willingness to drive longer distances to visit areas of higher water quality or willingness to pay for property neighboring waters of higher quality (revealed preference methods). Other approaches include estimating the costs avoided by improving water quality (e.g., sediment dredging, drinking water treatment), or the costs associated with increased health risks due to contact or consumption of unsafe water. Some caution is needed in applying these cost-based approaches, to ensure that they represent measures of value (18). In addition, valuation methods typically generate estimates of value held by people today given current conditions and not a dynamic assessment of values of changes in the flow of ecosystem services through time. Reviews of economic approaches to water quality valuation are provided by Wilson and Carpenter (19), Brauman et al. (20), Olmstead (21), and Griffiths et al. (3).

Delineating the Multiple Ecosystem Services Associated with Water Quality.

Defining water quality as multiple biophysical metrics that may influence the provision of many different “final” ecosystem services is critical for comprehensive valuation (9). In Fig. 2 we chart the potential interactions between changes in water quality and multiple ecosystem services. A single action that affects water quality may cause a change in another attribute, such as water clarity, or have a direct effect on the provision of various ecosystem services that affect different groups of beneficiaries. Fig. 2 builds the on the general framework introduced by the Millennium Ecosystem Assessment (22) that links ecosystem services to constituents of well-being, while adding specificity for water quality-related services.Open in a separate windowFig. 2.Relationships between water quality change, multiple ecosystem goods and services, and associated changes in values. Actions considered in the far left column include changing land use or land management as well as other drivers of water quality change, such as climate change, invasive species, and atmospheric deposition. Connections between columns are classified as primary or secondary, according to expert opinion. Although not representative of all possible water quality changes, pathways, and effects on well-being, the figure highlights the most important and often-measured services.Few water quality-related services are affected by just one action, and many services in combination cause changes in value (Fig. 2). For example, the value of lake fishing is affected by changes in fish abundance and species composition but may also be influenced by water clarity and/or the prevalence of toxins that lead to fish consumption advisories. Fish abundance, in turn, is driven by changes in phosphorus and is influenced by nitrogen, temperature, sediments, toxins, and interactions with other organisms. There may also be feedbacks among services such that a change in the provision of one service affects the provision of another service (e.g., a change in lake fishing may also affect the value of boating).Fig. 2 also illustrates how a single change in one water quality constituent can affect multiple ecosystem services and numerous sources of value. Changes in nitrate loading are most commonly associated with changes in the extent and duration of coastal hypoxia and with the health risks of methemoglobinemia, often called blue-baby syndrome (23, 24). However, changes in nitrate can also affect the prevalence of water-borne disease-causing organisms, and even low levels of nitrate in drinking water can lead to increased health risks (25). Therefore, the total value associated with a change in the quality of drinking water includes both the cost of removing nitrate from drinking water and any loss in value associated with increased health risks from consuming water with nitrate levels that are high but below the drinking water standard. Additional negative commercial or recreational consequences associated with hypoxia or harmful algal blooms would add to the lost value attributable to a single action (e.g., increased nitrogen fertilizer added upstream).

Template for the Assessment and Valuation of Water Quality-Related Services.

On the basis of the services and interactions mapped in Fig. 2, we present a template for integrated biophysical and economic modeling for comprehensive water quality valuation. For each constituent of water quality change (nitrogen, phosphorus, sediment, etc.), the template identifies the water quality attribute most commonly valued by people, the endpoint and beneficiaries to be measured or modeled, and appropriate economic valuation approaches (Fig. 3). Researchers interested in assessing water quality-related services and economic values can use the template to identify model requirements, key data needs, and existing tools and approaches for water quality valuation. There are five steps to using the template.Open in a separate windowFig. 3.Template for water quality valuation based on integrated biophysical and economic models. Each row in the table represents a water quality change that affects an endpoint and groups of beneficiaries in a unique way, such that there is no overlap in value. Value estimates generated by each row in the template can be summed for an estimate of the value generated or lost by a given action or scenario. For some service estimates (e.g., lake recreation), users will need to select a single valuation tool (e.g., hedonic model or recreation demand model) listed in the cell to avoid double-counting value because there may be overlap in the groups of beneficiaries if multiple approaches are applied to the same water quality change (e.g., lakeshore property owners may also be lake recreationists). The examples given in the template are not meant to be a complete enumeration of all services but rather are provided as illustrative examples of the steps involved in an integrated approach.

Step 1: Identify actions and beneficiaries of interest.

Land use and land management decisions, as well as factors such as climate change and invasive species, have the potential to affect the source and transport of many different types of water quality constituents or contaminants. Identifying the beneficiaries of interest and then working backward to determine the appropriate biophysical parameters that have the greatest potential to affect those groups provides focus for research efforts and can ensure that subsequent work captures the most important drivers and ecosystem service consequences. Alternatively, if water quality information is available from previous monitoring or modeling, then the template can be used to identify all of the potential services affected by a change in a given nutrient or pollutant. One goal of the template is to draw attention to all of the constituents, endpoints, beneficiaries, and ecosystem goods and services related to changes in water quality. Therefore, an approach that considers both upstream drivers and downstream beneficiaries will generate the most comprehensive valuation.

Step 2: Identify shared inputs/outputs of biophysical and economic models.

After selecting the key actions and ecosystem service changes, the next step is to identify the inputs and outputs that need to be included in a set of integrated biophysical and economic models. In Fig. 3 we use the term “valued attribute” to describe the aspect of water quality that can be measured or modeled in biophysical assessments and directly affects human well-being. For the service of clean drinking water, the valued attribute is the concentration of the nutrient or contaminant for which increased health risks are associated with increased exposure to nitrate or toxins. For other services, an additional biophysical model may be needed to translate the driver of water quality change into the valued attribute. For example, stream temperature has been identified as a principal driver of the distribution and abundance of trout (26, 27). Here, a functional relationship is needed to translate changes in stream temperature into changes in either the size and abundance of trout populations or the area of suitable habitat for each species. Warming water temperatures may also alter species composition, shifting angling value from that based on cold-water species to warm-water species (28). In some cases, there may be alternative choices of the valued attribute, and what should be chosen depends on biophysical understanding, links to human well-being, and data availability.

Step 3: Select appropriate biophysical models.

Applying the template requires the user to identify an appropriate biophysical model to capture the effects of an action on the valued attribute at a defined endpoint. Watershed water quality models estimate how changing land use or management resulting from alternative policies or future scenarios will affect nitrogen and phosphorus loading to downstream endpoints. To use these models in our framework, nutrient outputs need to be linked to a valued attribute from Fig. 3, such as changes in water clarity. Comprehensive valuation of water quality may require different biophysical models for each water quality constituent. For example, a groundwater model could be used for services associated with nitrate contamination of drinking water wells, and a basin-scale water quality model could be used to route nutrients downstream to predict consequences for coastal regions. Differing spatial and temporal lags for each service mean it is important to consider how the concentration of any given constituent changes across space and through time (29).

Step 4: Select appropriate economic models.

In addition to identifying an appropriate biophysical model, applying the framework requires linking valued attributes at particular endpoints with economic models that measure the value of these attributes to specific beneficiaries. For example, changes in the concentration of nitrate in groundwater affect human well-being where wells supply drinking water to residents. Economic models can be used to compare the well-being of people before and after a change in water quality. These models predict how changes in nitrate concentrations at drinking water sources will affect behavior, such as prompting the installation of treatment systems by municipal water treatment facilities or the purchase of bottled water by well owners. Although these costs can be used as proxies for economic values, it is important to distinguish the costs incurred through avoidance activities (the price of a new treatment system) from the true value associated with access to clean drinking water (difficult to measure but likely of much greater value).Economic models should measure change in value in terms of a common monetary metric. Where the valued attribute is a market good such as fish or shellfish, valuation is fairly straightforward. However, most water quality-related ecosystem services are not directly associated with market goods, so values must be estimated using nonmarket valuation techniques. Both market and nonmarket values are context dependent; they are influenced by the physical, economic, and regulatory settings in which the valuation takes place, as well as on social or cultural norms. For example, the amount that a user is willing to pay to engage in a recreational activity such as swimming varies by income level as well as by the availability of substitute recreational opportunities (30). There is also variability in perceptions of the way water quality affects the suitability or desirability of recreation in different locations. Surveys of water recreationists in Minnesota, for example, have found that the level of lake water clarity users rate as “suitable for swimming” ranges from just 0.5 m to at least 2.0 m, depending on the baseline water quality of the region (31).

Step 5: Consider existing models and data sources.

Although there are few examples of integrated, comprehensive analyses of ecosystem services related to water quality, there is a wealth of useful information with which to build such an assessment. In SI Text we have assembled a comprehensive literature review of water quality valuation studies, added relevant biophysical models and case studies, and linked these references to each row in the valuation template presented in Fig. 3. In some cases, existing work is sufficient to translate biophysical outputs to changes in service provision and value. However, few generalizable models linking actions to changes in value exist for water quality-related services. In many instances, researchers will have to collect new data in their region of interest or make assumptions about how to adapt existing models developed in other contexts. Recent work has advanced the practice of value transfer by developing valuation relationships that can be parameterized by the user with local data (e.g., refs. 16 and 32).     

Evaluating the Prognostic Value of Positron‐Emission Tomography Myocardial Perfusion Imaging Using Automated Software to Calculate Perfusion Defect Size

Background:

Myocardial perfusion imaging by positron‐emission tomography (PET MPI) is regarded as a valid technique for the diagnosis of coronary artery disease (CAD), but the incremental prognostic value of PET MPI among individuals with known or suspected CAD is not firmly established.

Hypothesis:

Myocardial perfusion defect sizes as measured by PET MPI using automated software will provide incremental prognostic value for cardiac and all‐cause mortality.

Methods:

This study included 3739 individuals who underwent rest‐stress rubidium‐82 PET MPI for the evaluation of known or suspected CAD. Rest, stress, and stress‐induced myocardial perfusion defect sizes were determined objectively by automated computer software. Study participants were followed for a mean of 5.2 years for cardiac and all‐cause mortality. Cox proportional hazards models were developed to evaluate the incremental prognostic value of PET MPI.

Results:

A strong correlation was observed between perfusion defect sizes assessed visually and by automated software (r = 0.76). After adjusting for cardiac risk factors, known CAD, noncoronary vascular disease, and use of cardioprotective medications, stress perfusion defect size was strongly associated with cardiac death (P < 0.001). Rest perfusion defects demonstrated a stronger association with cardiac death (P < 0.001) than stress‐induced perfusion defects (P = 0.01), yet both were highly significant. Similar patterns held for all‐cause death.

Conclusions:

The current study is the largest to date demonstrating PET MPI provides incremental prognostic value among individuals with known or suspected CAD. Automated calculation of perfusion defect sizes may provide valuable supplementary information to visual assessment. This work was partially funded by a predoctoral fellowship grant awarded to the first author by the American Heart Association's Founders' Affiliate. Additional funding was provided by Niagara Falls Memorial Medical Center, Positron Corporation, the University at Buffalo, and Niagara University. The authors have no other funding, financial relationships, or conflicts of interest to disclose.     

Craniofacial and orbital dermoids in children

Dermoid cysts are congenital lesions that commonly arise from nondisjunction of surface ectoderm from deeper neuroectodermal structures. They tend to be found along planes of embryonic closure. Classification by site is helpful for diagnostic planning and surgical treatment. A distinction can be made between frontotemporal, orbital, frontoethmoidal, and calvarial lesions. The risk of extension into deeper tissues must be determined before surgical intervention. Simple lesions are amenable to direct excision. Deeper lesions often require a coordinated surgical approach between a neurosurgeon and craniofacial surgeon after thorough radiographic imaging. Follow-up through the developmental years is recommended for complex dermoid lesions.     

Elderly Norms for the Hopkins Verbal Learning Test-Revised

The present study evaluates the effects of age, education, and gender in a representative sample of older adults and provides normative data for community-dwelling elderly. Age and gender had significant effects on HVLT-R performance. We provide age- and gender-adjusted normative data. Surprisingly, education level did not affect HVLT-R performance, indicating that education-adjusted norms are not necessary for this measure within this age range. We evaluated a subsample of subjects census-matched on age, education, and gender. These subjects did not differ in overall performance from our entire sample. Therefore, the normative data provided in this paper can be considered to be census-comparable for age, education, and gender.