**4. Differences in well-being by respondent or community type**

Effective measures of human well-being can be useful to decision making at the community level. Community decision-making is based on a shared commitment to achieving realizable improvements in family, child and neighborhood conditions in order to build accountability and capacity to achieve those results. This type of decision-making achieves the best results when it:


**D1 D2 D3 D4 D5 D6 D7 D8** D1 – −0.581\* −0.616\* −0.392\* 0.075 −0.438\* −0.499\* −0.703\* D2 – 0.415\* 0.407\* −0.088 0.334\* 0.326\* 0.346\* D3 – 0.642\* 0.004 0.120 0.605\* 0.407\* D4 – 0.157 0.202 0.680\* 0.159 D5 – −0.199\* −0.017 −0.206 D6 – 0.355\* 0.104 D7 – 0.387\* D8 –

**Figure 2.** Comparison of observed and predicted values from forecast models for well-being based on ecosystem.

D1 = Connection to nature; D2 = Cultural fulfillment; D3 = Education; D4 = Health; D5 = Leisure time; D6 = Living

**Table 3.** Correlations (Pearson product moment) among human well-being domains (\* = p < 0.0001; N = 561) (from [66]).

standards; D7 = Safety and security; D8 = Social cohesion.

Economic and social services (from [66]).

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These attributes can be accomplished through effective engagement with community stakeholders. Stakeholder engagement is a necessary process of evaluation because effective use of the HWBI as an assessment tool requires information on the relative importance of the domains of HWBI for any given community (i.e., their community value structure), as well as the baseline value of well-being against which we can measure change.

Using the Relative Valuation of Multiple Ecosystem Services method (RESVI), Jordan et al. [3] queried three respondent groups to determine their overall value judgments related to various ecosystem services. The RESVI method uses an assessment where respondents are (1) briefed about policy questions to be examined with regard to the extent and nature of the ecosystem(s) and services involved, (2) asked to assign relative values to a list of ecosystem services in terms of what proportional dollar value for one service versus another, (3) application of a dollar value based on literature or research for each service type, and (4) creation of an index for all services using reference and relative values determined by the respondents.

The RESVI was used with three respondent groups – programmatic regulators, research scientists, and community stakeholders. The results compared the relative values of eight ecosystem services (**Figure 3**) – habitat functions, water quality regulation, water supply, recreation, flood control, esthetics, biodiversity and climate regulation. The test groups valued

eight types, which differ both in their baseline HWBI scores and in the relative importance of the different domains of HWBI (**Figure 4**). The developed approach aids communities by defining meaningful changes in well-being across similar communities through the establishment of reference points that can provide information regarding investment in activities like

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The holistic suite of indicators used in the Human Well-Being Index (HWBI) represent a synergistic measure of the outcome of ecosystem good and services production and delivery [11, 19, 25]. However, measures of well-being and their constituents (e.g., civic engagement, social cohesion, connection to nature) are not always easily understood and are not a direct measure of the delivery of services. The key at a community level is linking these broader well-being measures to community-specific desires and values. Fulford et al. [62] took a comparative approach toward well-being points of references based on an ecosystem goods and servicesbased community topology and Bayesian model-based cluster analysis [80] The HWBI was compared among community cluster groups to detect patterns in well-being as a function of the ecosystem goods and services community types (**Figure 4**). The key differences among community groups were population density and composition, economic dependence on local resources (e.g., forestry, fishing, agriculture), and to some extent geography. Differences among coastal county groupings indicated both strong and weak similarities resulting in three major clusters among the eight topological types (**Figure 5**). Fulford et al. [62] determined that community decision makers could use the classification system to identify well-being values

**Figure 4.** Analytical comparison of human well-being among categorical groups of U.S. coastal counties based on a multivariate community topology (dashed arrows = data dependency; solid arrows = outcomes) (adapted from [62]).

conservation, restoration of natural capital and mitigation [77–79].

from which to gauge impact of decisions that could shift well-being.

**Figure 3.** Overall mean relative values for three respondent groups using to RESVI to ascertain relative values of ecosystem services (from [3]).

habitat functions and water quality regulation more than the other ecosystem services by a wide margin. However, some differences were observed among the respondent types with regard to their valuation systems. Regulators tended to more heavily value regulatory services while researchers tended to place higher values on ecosystems functions. Finally, general community stakeholders tended to value services that impacted landscapes.

Similarly, Fulford et al. [62] found that different community types could reflect different attitudes with regard to the relative importance of domains of well-being and the services that drive that well-being. There is an increasing understanding that decisions made by local communities can have significant impacts on community well-being and require a degree of understanding regarding local impact as well as cumulative impact across multiple communities [73–76]. All communities have unique characteristics resulting in the potential for varying views regarding the importance of different ecosystem services as well as the components of well-being. Similarly, different communities can have beliefs and value systems in common. Using a community typology approach, Fulford et al. [62] developed a system to inform decision makers about sustainable decision outcomes based on the similarities and differences of communities' priorities, belief systems, and values. Communities can be divided into one of eight types, which differ both in their baseline HWBI scores and in the relative importance of the different domains of HWBI (**Figure 4**). The developed approach aids communities by defining meaningful changes in well-being across similar communities through the establishment of reference points that can provide information regarding investment in activities like conservation, restoration of natural capital and mitigation [77–79].

The holistic suite of indicators used in the Human Well-Being Index (HWBI) represent a synergistic measure of the outcome of ecosystem good and services production and delivery [11, 19, 25]. However, measures of well-being and their constituents (e.g., civic engagement, social cohesion, connection to nature) are not always easily understood and are not a direct measure of the delivery of services. The key at a community level is linking these broader well-being measures to community-specific desires and values. Fulford et al. [62] took a comparative approach toward well-being points of references based on an ecosystem goods and servicesbased community topology and Bayesian model-based cluster analysis [80] The HWBI was compared among community cluster groups to detect patterns in well-being as a function of the ecosystem goods and services community types (**Figure 4**). The key differences among community groups were population density and composition, economic dependence on local resources (e.g., forestry, fishing, agriculture), and to some extent geography. Differences among coastal county groupings indicated both strong and weak similarities resulting in three major clusters among the eight topological types (**Figure 5**). Fulford et al. [62] determined that community decision makers could use the classification system to identify well-being values from which to gauge impact of decisions that could shift well-being.

habitat functions and water quality regulation more than the other ecosystem services by a wide margin. However, some differences were observed among the respondent types with regard to their valuation systems. Regulators tended to more heavily value regulatory services while researchers tended to place higher values on ecosystems functions. Finally, gen-

**Figure 3.** Overall mean relative values for three respondent groups using to RESVI to ascertain relative values of

Similarly, Fulford et al. [62] found that different community types could reflect different attitudes with regard to the relative importance of domains of well-being and the services that drive that well-being. There is an increasing understanding that decisions made by local communities can have significant impacts on community well-being and require a degree of understanding regarding local impact as well as cumulative impact across multiple communities [73–76]. All communities have unique characteristics resulting in the potential for varying views regarding the importance of different ecosystem services as well as the components of well-being. Similarly, different communities can have beliefs and value systems in common. Using a community typology approach, Fulford et al. [62] developed a system to inform decision makers about sustainable decision outcomes based on the similarities and differences of communities' priorities, belief systems, and values. Communities can be divided into one of

eral community stakeholders tended to value services that impacted landscapes.

ecosystem services (from [3]).

154 Ecosystem Services and Global Ecology

**Figure 4.** Analytical comparison of human well-being among categorical groups of U.S. coastal counties based on a multivariate community topology (dashed arrows = data dependency; solid arrows = outcomes) (adapted from [62]).

**5. Examples of linking ecosystem services to well-being and public** 

Ecosystem goods and services (EGS) are the result of processes that can contribute to social welfare [82]. Social welfare can easily be translated into elements of human well-being as defined by Summers et al. [19, 20]; particularly, health, social cohesion and cultural fulfillment. Over 50 recent reviews relating human health and ecosystem services [83] showcase the focus of connecting ecosystem goods and services (EGS) with this aspect of well-being. However, fewer studies exist directly linking physical or mental health to natural systems via ecosystem goods and services, tracing the full pathways from ecosystem structure and function to EGS to health [83]. One recent review uses causal criteria analysis (CCA) to link health

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Causal criteria analysis was developed in epidemiology to support health decision making often based on weak but independent information [85, 86]. One study [84] conducted a CCA focusing on the effects of EGS provided by greenspaces on human disease (**Figure 6**). Green spaces included any vegetation with an environment dominated by humans [87] – urban trees, wetlands, and green roofs. The health endpoints included gastro-intestinal disease, respiratory illness, cardiovascular disease, and heat morbidity. Simply put, green spaces can abate floods and storm surge hazards by reducing runoff through natural percolation or physically limiting the influence of waves and storm surge [88]. This type of mitigation can lower human exposure to contaminated flood waters potentially reducing gastrointestinal diseases and reducing conditions that can lead to asthma through mold growth [89]. Green spaces potentially remove toxicants, reduce the prevalence of gastrointestinal disease, trap contaminants and mitigate extreme temperatures [90–94]. CCA results showed sufficient evidence for causality for all tested greenspace-EGS pairings (heat hazard mitigation, clean air, water hazard mitigation and clean water), three of six EGS-health pairings (heat hazard-heat morbidities, water hazard mitigation-gastrointestinal disease and clean water-gastrointestinal disease) and two of four direct greenspace-health pairings (heat morbidities and cardiovascular disease). This work indicates that most current literature supports intermediate pathway connections between ecosystems and ecosystem goods and services as well as ecosystem goods and services and health. However, very few studies support a direct connection between the presence of ecosystems and health outcomes. Of those studies that exist, few simultaneously

As a specific example, ongoing studies in the San Juan Bay Estuary, Puerto Rico are evaluating the role of wetlands on Dengue fever by means of ecosystem services (e.g., biological control, clean water, and heat hazard mitigation) [95] (**Figure 7**). Ecosystem goods and services associated with heat hazard mitigation may help reduce mosquito biting, oviposition rate, and viral load. Clean surface water provides habitat for wildlife and healthier ecosystems, favoring bio-control of mosquitoes [96–99]. Preliminary findings suggest that wetlands and wetland services are negatively associated with Dengue cases even after controlling for potentially confounding variables (**Figure 8**). Wetlands and wetland services were also found to help reduce temperature which is an environmental driver of Dengue transmission [98]. These findings help support a connection between an important ecosystem in the San Juan Bay area,

measure the mediation by ecosystem goods and services (**Figure 6**).

**health**

and EGS [1, 84].

**Figure 5.** Map showing example of Gulf of Mexico coastal counties separated into eight classification types and bar chart indicating differences in unweighted HWBI composite scores average (SE) by classification group. See [62] for more information on HWBI calculations and group delineations. Community types are represented by 1 = Urban/Suburban, 2 = Rural manufacturing, 3 = Rural farms, 4 = Rural high ethnic diversity, 5 = Rural balance of natural resource dependence and manufacturing, 6 = Rural dependence on natural resources, 7 = Older suburban, 8 = Suburban industrial.

Similarly, Fulford et al. [81] used a keyword-based approach to determine common terminology used by 97 counties in three regions of the U.S. (Gulf of Mexico, western Great Lakes and Northwest) to refer to community fundamental objectives closely aligned with the domains of HWBI. They analyzed strategic planning documents using the eight domains of human wellbeing described by Summers et al. [19] and listed in **Table 2**. Living Standards and Safety and Security were the most common well-being domains referred to in community strategic plans. Health and Cultural Fulfillment were the least commonly addressed domains in these documents. Major community type (same typology as used in Fulford et al. [62] differences were largely between urban and rural areas with urban community types focusing on Living Standards and Education while rural communities tended toward Leisure Time and Social Cohesion.
