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Article Excerpt
Introduction
For many years experienced fisheries social scientists have discussed developing a fisheries model for social impact assessment (SIA) that would be more compatible with the approaches taken by fisheries biologists and economists when assessing potential effects of management actions. They suspected that fishery management council (FMC) members might see social impact assessments as more useful if those assessments were provided in a format analogous to fisheries economists' and fisheries biologists' formats.
This point was given further support by Sharp and Lach's (2003) survey of Federal and state fishery managers and decision makers in the Pacific Northwest. They were asked about their knowledge of how to incorporate the social values of fishing communities into planning and decision-making. The authors concluded that it is unlikely that community information can be used in fishery plan development or amendment processes when it is presented in a qualitative, descriptive format.
Stimulated by this discussion, the Office of Science and Technology of NOAA's National Marine Fisheries Service invited a group of marine fisheries social scientists with expertise in social science modeling, quantitative methods, and marine fisheries impact assessment to create a conceptual model for predicting the social impacts of fishery management action alternatives using a limited set of quantitative and qualitative indicators. The resulting model was to be suitable for social impact assessment, and it was to include a dependent measure or output that would be analogous to the economists' use of jobs, income, or total economic output in their models.
This paper presents the results of the first phase of this group's work. Well-being was selected as the dependent measure for marine fisheries social impact assessment in this model. While this model is not the only possible approach to social impact assessment, it does open a door to a room that is closer to those currently occupied by marine fisheries economists and their biologist counterparts.
Historical Background
Social impact assessment began as a field in the 1960's as people became more concerned with human impacts on the environment (Finsterbusch and Freudenberg, 2002:408). The National Environmental Policy Act (NEPA) of 1969 (1) called for analyzing the impact of human actions on the environment when designated changes were contemplated. Early NEPA guidelines emphasized environmental assessment and did not require SIA's. Few government agencies had yet invested in the social science expertise to do SIA's. Social scientists, however, continued to perfect SIA methodologies (Shields, 1974; Finsterbusch and Wolf, 1977; Finsterbusch et al., 1983; Burch and DeLuca, 1984; Freudenberg, 1986; Barrow, 1997; Becker 1997; Burdge, 1994, 2004; Vanclay, 2003; Taylor et al., 2004).
Preparation and passage of the Fishery Conservation and Management Act of 1976 (now the Magnuson-Stevens Fishery Conservation and Management Act or MSFCMA, also referred to as the MSA (2)) led to efforts to gather social data and to carry out impact analysis specifically for fisheries (OSU, 1978; Acheson et al., 1980). The National Marine Fisheries Service (NOAA-NMFS, 1994, 2001, 2006), in association with social scientists, has been developing SIA approaches since the 1980's. (3) SIA methods were also being developed in other areas of resource management (Kogut, 1976; USDOT, 1982; Bryan, 1984). (4)
The 1990's brought recognition that progress on environmental problems was neither rapid nor successful in part because social and cultural dimensions of resource management were not being given sufficient emphasis. The U.S. Forest Service gathered social scientists from many agencies to develop common SIA approaches (ICGPSIA, 1994). By 1997, SIA became required in many Federal programs. (5) The Interorganizational Committee on Guidelines and Principles for SIA published revised SIA guidelines and principles in 2003 (ICGPSIA, 2003).
In marine resource management, lack of success with fishery management led to changes in the fishery management process and passage of the Sustainable Fisheries Act (SFA) of 1996. National Standard 8 of the SFA requires explicit consideration and minimization of community impacts. The NMFS (1998) subsequently published National Standard 8 Guidelines (6) and has directed efforts toward community profiling to serve as an informed basis from which to begin SIA. While economists had been on NMFS staff since its incarnation as the Bureau of Commercial Fisheries in 1956 (Hobart, 1995), and one anthropologist or sociologist had been in Headquarters since 1974, NMFS hired its first regional social scientist (other than economists) in 1992. By 2005, each NMFS region except the Southwest had at least one such social scientist, signaling a new agency effort to develop its capability to meet its obligations to examine sociocultural regulatory impacts (Colburn et al., 2006).
Objectives
Building on previous government experience and an extensive literature on SIA, our effort takes SIA for marine resource management a step further. Our goals include making SIA more quantitative and useful. First, data derived through SIA should be amenable to comparison across space and time and should be cross-referenced with biophysical and economic data.
Biophysical and economic data are typically more quantitative than the social science data currently collected for SIA. The quantitative natures of biophysical and economic data facilitate the comparison of datasets collected in disparate spatial and temporal frames. To obtain quantitative social science data for comparative purposes that can be linked with biophysical and economic data, variables need to be identified, defined, and operationalized in a consistent way, and sufficient data must be gathered to make comparisons statistically and scientifically defensible. Operationalization means measuring variables in a way that is replicable, reliable, accurate, and valid. It means the measure is comprehensible to all researchers conducting SIA.
The approach presented here emphasizes the fact that humans are an important component of marine ecosystems. NMFS has committed itself to developing ecosystem-based approaches to marine resource management (7) (NMFS, 1999), an approach compatible with the approach presented here. The current NOAA working definition of an ecosystem is "... a geographically specified system of organisms (including humans), the environment, and the processes that control its dynamics". (8) Another goal is to develop an SIA model that is fully compatible with ecosystem-based approaches to fisheries management.
Well-Being, the Dependent Measure
The SIA model for marine resource management is designed to predict changes in well-being. Well-being refers to the degree to which an individual, family, or larger social grouping (e.g. firm, community) can be characterized as being healthy (sound and functional), happy, and prosperous.
One might argue that changes in economic welfare, such as changes in income or wealth are adequate measures of well-being. Social scientists, however, have shown that fishing and interaction with marine resources is much more than solely an economic activity (Acheson et al., 1980; Anderson, 1980; Smith, 1981; McCay et al., 1993; Bunce et al., 2000). Well-being is affected by a large number of sociocultural and economic variables that are impacted by management decisions, making it a suitable measure in this context (Colfer and Byron, 2001; Eckersley, et al., 2001; Gullone and Cummins, 2002; Suh and Deiner, 2003). There is a substantial literature on this widely used construct as well as on its operationalization at the individual, community, and national levels of analysis. It has the advantage that it can be measured in multiple ways using established and publicly available indicators for different levels of analysis (Sharpe, 1999; Ryan and Deci, 2001; Sirgy, 2002; Zumbo, 2002), and it can be related to the narrower economic measures of welfare.
SIA Procedure
The first step carried out by an analyst in an SIA is a scoping process to determine the sociocultural variables relevant to the management questions (NMFS, 2001). This can lead to initial sketches of the sociocultural system that may be affected by the management action. Management actions will affect a range of social entities including individuals, firms, families, and communities (9), and therefore the SIA must attend to these as distinct units of analysis.
Special attention should be given to social groups that may gain or lose from the management choices made. These populations may not always be readily visible at public hearings or on newspaper op-ed pages. Scoping, theretore, requires an assessment of each part of the sociocultural system that is likely to be affected, with specific attention to any marginalized populations because environmental justice issues may also be involved.
Of primary concern is measuring how the well-being of system participants will change. The objective is not to include every sociocultural element in the system: it is to do an initial assessment that identifies the critical populations that have a significant stake in the management action and the issues of concern to these populations that may increase or decrease their well-being.
The next step following the scoping process is to operationalize the relevant variables by defining the variables in a way that facilitates measurement. (10) A variety of instruments available for these assessments are given in the appendix. Limited financial resources, time constraints, and staff skill level might further limit the variables and measures chosen.
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More important than simply identifying variables, however, is discerning the relationships among them. This is because the impact on one variable or variable set may be transmitted to another linked variable or variable set through cumulative processes, feedback loops, and other systematic relationships. These relationships can exist both within single levels of analysis (e.g. the community) and across levels of analysis (e.g. the individual, the family, and the community). Some of these relationships are explored in the following sections.
General Fishery SIA Model
The general marine resource SIA model presented in Figure 1 depicts the sociocultural system, showing that external forces influence management strategies, which, in turn, influence human activities with regard to marine resources. These changes in activities impact satisfaction with the activities, and this influences aspects of individuals and the communities in which they live, as illustrated by the individual and social attributes (Fig. 1). The arrows in this figure reflect interrelationships (cause-effect, resonance, cumulative impacts) between these classes of variables that will be explained below as the general model is developed for commercial, subsistence, and recreational fisheries.
SIA in Three Types of Fisheries
Although there are many ways to classify U.S. fisheries, fishery managers identify three categories: commercial, subsistence, and recreational fisheries, and their subtypes. We consider how SIA can be conducted for each of these three kinds of fisheries. The examples that follow build from descriptions of the general ecosystem and illustrate relationships among variables that impact well-being. In the most general of formulations, a fishery is a system in which humans are linked to "fish."
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Commercial Fisheries
First, we will examine potential impacts of management on commercial fishermen (11) and shore side entities that constitute the commercial sector (e.g. processors and dealers, ice houses, etc.), as well as the commercial sector of the marine recreational fishery, including charter boat operators, party boat operators, guides, marina operators, bait and tackle dealers, and other entities appropriate to the SIA.
The simplified model (Fig. 1) presents some rather obvious relationships, and Figure 2 identifies for illustrative purposes a few of the specific variables included in each of the general categories in Figure 1. A more comprehensive list of variables can be found in the appendix. We argue that external forces, such as population pressure, declining fish stocks, environmental activism, and climate change influence the management of fisheries. In turn, management, which can impact fishing targets, times, techniques, numbers of fishermen, and other variables (the appendix lists activity attributes) has an influence on various attributes of the occupation of fishing.
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Impacts of the changes will vary according to attributes of the impacted fishery, fishermen, and community--some are more resilient (see glossary) than others. Smith et al. (2003), for example, discuss some factors influencing differential resilience of fishing families impacted by the Florida net fishing ban, and Gilden et al. (1999) discuss Oregon fishing communities' differential ability to cope in the face of complex regional changes. Individual and social resilience are complicated variables that represent an ability to cope with change, and they are related to other social and psychological variables including social support systems (both familial and external), self-esteem, and perceived control (Mederer, 1999). Additionally, Mederer (1999) notes that resilience is not a fixed attribute, but results from interaction between family and individual attributes and external circumstances.
Individual fishermen accustomed to a fishery with one set of attributes must then become accustomed to changes, some of which may impact their level of activity satisfaction and ultimately their well-being. In the instance of an occupation like commercial fishing we will refer to the activity satisfaction of individuals as job satisfaction, which is more commonly used in the literature. A great deal of research (Apostle et al., 1985; Pollnac and Poggie, 1988; Gatewood and McCay, 1990; Binkley, 1995; Pollnac et al., 2001) has linked job satisfaction to 1) individual attributes such as mental health and longevity, and 2) social problems such as family violence, absenteeism, and job performance (Fig. 3 gives a more complete list of impacts (12)).
While job satisfaction is an important aspect of all occupations, it is especially significant with regard to a fishery--including both commercial fishermen and commercial sectors of the recreational fishing industry (e.g. charter boat operators and fishing guides). The structure of job satisfaction among these groups manifests a common component (13) that is not always found in other occupations--a self-actualization component that includes "adventure" and "challenge" (Smith, 1981; Apostle et al., 1985; Pollnac and Poggie, 1988; Gatewood and McCay, 1990; Binkley, 1995; Pollnac, et al., 2001; Pollnac and Poggie, 2006).
These concepts have been described by fishermen as including the thrill of...
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