Developing Meaningful Marine Ecosystem Indicators in the Face of a Changing Climate

Phillip S. Levin,I Maria Damon,II & Jameal F. SamhouriIII

Abstract Evidence that the earth’s climate is changing is overwhelming, and because climate affects temperature, patterns of circulation and chemistry of the ocean, marine ecosystems are changing as well. Effectively reducing climate-related threats requires management responses that move beyond disjointed efforts and that integrate diverse management actions with the goal of increasing adaptive capacity. The development of robust indicators—quantitative measurements that provide insight into the state of natural and socio-economic systems—is a necessary step toward these goals because indicators provide information that allows management strategies to be evaluated and refined. In this paper, we outline an approach to indicator selection that melds social and natural science. Our approach acknowledges that the value of specific indicators to policy makers and resource managers can diverge from the scientific value of these indicators. In addition, it is grounded in rigorous scientific analyses that meet widely accepted guidelines for ecosystem indicators. Our approach also recognizes that a suite of indicators is needed, and we argue that the optimal portfolio of indicators is one that ensures appropriate scientific information is captured while also maximizing the value of the indicators for policy makers. We contend that integrating natural and social science is crucial as we begin to recognize the potential consequences of climate change on marine ecosystems and seek ways to adapt existing management strategies to alternative futures.

I. INTRODUCTION...... 37 II. STEP 1: EMBRACE HUMAN PREFERENCES...... 39 III. STEP 2: EMBRACE ECOLOGY (AND OTHER NATURAL SCIENCES)...... 40 IV. STEP 3: INTEGRATE ECONOMICS AND ECOLOGY TO DEVELOP MEANINGFUL INDICATOR PORTFOLIOS...... 42 V. THE CASE OF PUGET SOUND...... 44 V. CONCLUSIONS...... 45

I Corresponding author. [email protected], 206-860-3473. NOAA Fisheries, Northwest Fisheries Science Center, Conservation Biology Division, 2725 Montlake Blvd. E., Seattle WA 98112 II New York University, Wagner School of Public Service New York, NY 10012 III NOAA Fisheries, Northwest Fisheries Science Center, Conservation Biology Division. The authors would like to thank the following: Mark Plummer and Todd Lee provided stimulating commentary on our ideas that helped sharpen our thinking about these topics. We greatly appreciate the efforts of the symposium organizers for providing an opportunity to exchange ideas on dealing with climate change. Finally, PSL thanks Jens Voigt for inspiration and insight.

37 STANFORD JOURNAL OF LAW, SCIENCE & POLICY Vol. 2

I. INTRODUCTION

Climate is changing. Evidence of the warming of the earth’s land, ocean and atmosphere is unequivocal,1 and marine ecosystems will certainly respond to changing climatic conditions. Temperature affects a range of physiological processes, and changes in temperature can negatively affect the performance and survival of many marine organisms.2 Warming temperatures are also resulting in changes in distribution of marine species—there have been poleward shifts in the distribution of algal, plankton and fish populations.3 Similarly, warming seawater is altering the phenology of species; migration timing, peak abundance and reproductive cycles are shifting in a variety of species.4 Changes in average wind speed and direction will influence patterns of dispersal of planktonic life stages,5 and alterations in extreme wind events will affect the magnitude and distribution of storm damage.6 Increasing acidification of the ocean is likely to impair functioning of a number of planktonic and benthic marine organisms, with potentially severe impacts on ecosystem functioning.7 The cumulative impact of these and other changes will be altered ecological interactions, as well as shifts in ecosystem structure and function, with virtually certain modifications in the goods and services humans obtain from the oceans.8 Importantly, the impacts of climate change on marine ecosystems do not occur in isolation of other human activity. Habitat destruction, pollution, energy production, mining, fisheries, aquaculture, and invasive species are all affecting marine ecosystems and may exacerbate the effects of climate change. Indeed, multiple stressors in marine ecosystems have the potential to act in concert with climate change and cause significant degradation to coastal ecology and associated economies.9 Given the disquieting future of marine ecosystems, we have several options. We could just do nothing. Humanity could conduct business as usual, and we would simply muddle through as best as possible in a changed world. A second option is to address the source of the climate problem. While reducing emissions of greenhouse gases and developing strategies for sequestering carbon may be crucial and seem obvious, warming and concomitant sea level rise

1 Intergovernmental Panel on Climate Change (IPCC), Summary for Policymakers, in CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS. CONTRIBUTION OF WORKING GROUP I TO THE FOURTH ASSESSMENT REPORT OF THE INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE 1, 5 (Susan Solomon et al. eds., 2007), available at http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-spm.pdf. 2 Brian Helmuth et al., All Climate Change is Local: Understanding and Predicting the Effects of Climate Change from an Organism’s Point of View, 2 STAN. J. L. SCI. & POL’Y (forthcoming publication, 2010). 3 Martin Parry et al., Technical Summary, in CLIMATE CHANGE 2007: IMPACTS, ADAPTATION AND VULNERABILITY. CONTRIBUTION OF WORKING GROUP II TO THE FOURTH ASSESSMENT REPORT OF THE INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE 24, 28 (Martin Parry et al. eds., 2007), available at http://www.ipcc- wg2.gov/AR4/website/ts.pdf [hereinafter CLIMATE CHANGE 2007: IMPACTS, ADAPTATION AND VULNERABILITY]. 4 Graeme C. Hays et al., Climate Change and Marine Plankton, 20 TRENDS IN ECOLOGY & EVOLUTION 337, 340 (2005). 5 Christoper D. G. Harley et al., The Impacts of Climate Change in Coastal Marine Systems, 9 ECOLOGY LETTERS 228, 232 (2006). 6 Id. 7 Parry et al., supra note 3, at 28. 8 Id. 9 Robert J. Nicholls et al., Coastal Systems and Low-Lying Areas, in CLIMATE CHANGE 2007: IMPACTS, ADAPTATION & VULNERABILITY, supra note 3, at 316, 345, available at http://www.ipcc- wg2.gov/AR4/website/06.pdf. 2010 DEVELOPING MEANINGFUL MARINE ECOSYSTEM INDICATORS 38 are likely to continue for centuries because of climatic processes and feedbacks.10 Thus, this option is unlikely to yield short-term benefits. A third option is to adjust our human systems in response to existing or expected climatic changes, with the goal of reducing potential climate- related damages (i.e. adapt). In fact, the Intergovernmental Panel on Climate Change (IPCC) recently concluded that developing adaptive strategies to prepare for inevitable changes along with creating a portfolio of policy strategies that mitigate the causes of climate change can greatly diminish the risks associated with climate change.11 Effectively reducing climate-related threats thus requires a management response that moves beyond disjointed efforts and integrates ecosystem-based management (EBM) with the objective of increasing adaptive capacity. EBM is an integrated approach to management that considers the entire ecosystem with the goal of providing the full suite of ecosystem goods and services that humans want or need. Adaptation practices can include objectives such as increasing resilience, flexibility, and climate-resistant populations,12 all with the goal of ensuring the long-term delivery of ecosystem goods and services. Like many natural resource management issues, the desired outcome of management actions employing adaptation is a clear reduction of the climate-related risk to the ecosystem. However, the specific actions required to achieve effective adaptation to climate change are uncertain. Thus, in an increasingly dynamic world the implementation of management actions is best viewed as an iterative series of experiments with policy refinements enlightened by outcomes. In other words, when a new management approach is employed, common sense suggests that we check and see how well we are doing and alter the approach as we learn more about the system. Effectively doing so requires that we develop robust indicators— quantitative measurements that provide insight into the state of natural and socio-economic systems. Hundreds of indicators have been proposed as useful measures of ecosystem health. These include physical indices like temperature or air quality, the abundance of single species or groups of species, the size structure of the community, biomass ratios, indices of diversity, and various metrics of ecosystem function derived from models.13 There is no shortage of potential indicators of ecosystem status, but the difficulty is to select wisely from long lists of these candidates. Scientists have recently invested a great deal of effort in defining the desirable properties of indicators,14 and below we highlight some approaches for examining the ecological performance of these indicators. However, ecosystem indicators should do more than simply document changes in ecosystem health—they also must communicate information that is meaningful to resource managers and policy makers. Thus, the challenge is to identify indicators that are scientifically robust, but that also resonate in the arena of public policy—a challenge often not met.15 In this paper, we outline an approach to indicator selection that tackles this challenge and allows for flexibility in the face of Earth’s rapidly changing climate. While our paper is

10 IPCC, supra note 1, at 16. 11 Parry et al., supra note 3, at 71. 12 Nicholls et al., supra note 9, at 342. 13 Elizabeth A. Fulton et al., Which Ecological Indicators Can Robustly Detect Effects of Fishing?, 62 ICES J. MARINE SCI. 540, 544 (2005). 14 See, e.g., Simon Jennings, Indicators to Support an Ecosystem Approach to Fisheries, 6 FISH AND FISHERIES 212 (2005). 15 Lisa A. Wainger & James W. Boyd, Valuing Ecosystem Services, in ECOSYSTEM-BASED MANAGEMENT FOR THE OCEANS 92, 100 (Karen McLeod & Heather Leslie eds., 2009). 39 STANFORD JOURNAL OF LAW, SCIENCE & POLICY Vol. 2 motivated by issues related to EBM in a shifting climate, the methods we present are generic and could be used in many applications. Our approach first acknowledges that the value of specific indicators to policy makers and resource managers can diverge from the scientific value of these indicators. In particular, the usefulness and importance of a particular indicator to decision makers depends not only on its ability to convey meaningful information to scientists, but also on the societal value of the direct information it conveys. As ecosystems provide direct benefits to human well being, measuring and quantifying these benefits in understandable terms is inherently valuable to policy makers. Moreover, the relative values that individual stakeholders place on direct knowledge of the status of specific species can be susceptible to the preferences, emotions, and personal experiences of those stakeholders.16 Secondly, our approach is grounded in rigorous scientific analyses that meet widely accepted guidelines for ecosystem indicators.17 Thirdly, we recognize that a suite of indicators is needed,18 and we argue that the most useful portfolio of indicators is one that ensures appropriate scientific information is captured while also maximizing the value of the indicators for policy makers. We illustrate these ideas using ecological indicators because that is our particular field of expertise; however, the approach we describe is easily adaptable to indicators developed for any other ecosystem component, including human well-being.

II. STEP 1: EMBRACE HUMAN PREFERENCES

The overall societal value of an ecosystem stems both from direct uses (e.g., food, shelter, extraction, eco-tourism, and other uses that entail direct physical interaction with parts of the ecosystem) and what economists term “passive uses” (i.e., the inherent values that people place on the existence and status of a species).19 Because people derive value from these passive uses, the overall value of information regarding ecosystem health will in part depend on human individual preferences for particular elements of the ecosystem; in other words, imperfect information about the health of a particular species will have a direct cost to any individual who cares about that species, as well as to policymakers attempting to maximize welfare among their constituents. If everyone perfectly understood the scientific information contained in each ecosystem indicator, and, for example, how it translated to the status of each species, then a scientifically robust set of indicators would be identically meaningful to all policy makers, resource managers, and citizens. But people generally do not have perfect information on or understanding of the scientific complexities involved with management decisions. Additionally, the field of psychology has taught us that the opinions of people are not always motivated by a fully accurate perception of their environment even when they have full information. Indeed, people can be impulsive, instinctive, and inclined to make assessments based on subjective experience. Taken together, all of these factors can lead to a divergence between the scientific informational quality of a set of ecosystem indicators and its direct value to managers and policy makers. In the context of developing ecosystem indicators for marine environments, it is important to recognize that a relationship between an individual and the ocean ecosystem is

16 See Amos Tversky & David Kahneman, The Framing of Decisions and the Psychology of Choice, 211 SCIENCE 453, 453 (1981). 17 Les Kaufman et al., Monitoring and Evaluation, in ECOSYSTEM-BASED MANAGEMENT FOR THE OCEANS 115, 119 (Karen McLeod & Heather Leslie eds., 2009). 18 E.g., Fulton et al., supra note 13, at 548. 19 See John V. Krutilla, Conservation Reconsidered, 57 AM. ECON. REV. 777 (1967). 2010 DEVELOPING MEANINGFUL MARINE ECOSYSTEM INDICATORS 40 molded by culture and society and develops over the course of an individual’s lifetime.20 Thus, people often develop remarkable affinity for some groups of organisms.21 For instance, people’s willingness to pay for conservation is positively correlated to eye-size of the conservation target.22 Thus, conservation values for whales and seals generally tend to be greater than for fish or invertebrates—and, direct information on the health of whales can, in turn, be of more direct value to the public than direct information on fish and invertebrates. One exception to this rule is Pacific salmon, an icon of the U.S. Pacific Northwest. Salmon provide the basis for the culture, economy and religion of the region’s indigenous people,23 and permeate public discourse on issues ranging from land use to generation of electricity to shipping.24 Thus, as residents of the U.S. Pacific Northwest evaluate the effects of climate change and adaptive management measures on the ecosystem, they will certainly demand information on the status and trends of salmon whether or not salmon are reflective of overall ecosystem health. As a result, we can expect some indicators to be selected because of their value to decision makers rather than their adherence to scientifically rigorous criteria. Although such choices might be labeled as “irrational” by some natural scientists, we contend that such indicators are consistent with rational decision-making in a policy environment with imperfect information. Moreover, these indicators are crucial in that they reflect the values of the population that management actions are meant to serve.25 We thus propose that the first step of indicator selection is to identify ecosystem components that hold high value to stakeholders and policy makers. In other words, in the context of monitoring and evaluating the effects of a changing climate, we propose that portfolios of indicators be built upon a foundation of ecosystem components that are most meaningful to people affected by climate change and the actions meant to mitigate its impacts. While explicit acknowledgement of the importance of charismatic species or habitats may cause some natural scientists to roll their eyes, we view this step as a critical one. We recognize that there are important limitations of a sole focus on such flagship ecosystem components,26 but we argue that it is more effective initially to embrace rather than deny the role of human preferences in indicator selection.

III. STEP 2: EMBRACE ECOLOGY (AND OTHER NATURAL SCIENCES)

Although we begin by embracing human preferences, it is clear that stopping there would produce an indicator set that is inadequate. For instance, returning to the example of the U.S. Pacific Northwest, a focus on iconic species like salmon and killer whales will not necessarily provide information on all components of ecosystem structure and function. Thus, the next step

20 Carol D. Saunders, The Emerging Field of Conservation Psychology, 10 HUM. ECOLOGY REV. 137, 143 (2003). 21 Mark A. Zacharias & John C. Roff, Use of Focal Species in Marine Conservation and Management: A Review and Critique, 11 AQUATIC CONSERVATION: MARINE & FRESHWATER ECOSYSTEMS 59, 71(2001). 22 Berta Martín-López, Valuation of Biodiversity Conservation: The Meaning of Numbers, 22 CONSERVATION BIOLOGY 624, 630 (2008). 23 Phillip Levin & Michael Schiewe, Preserving Salmon Biodiversity, 89 AM. SCIENTIST 220, 220 (2001). 24 Mary H. Ruckelshaus et al., The Pacific Salmon Wars: What Science Brings to the Challenge of Recovering Species, 33 ANN. REV. OF ECOLOGY & SYSTEMATICS 665, 666 (2002). 25 In other words, the notion that human preferences are irrational assumes that they hold the same objectives as scientists attempting to achieve particular ecosystem-based management objectives. Since individuals attach direct and often idiosyncratic values to elements of the ecosystem, indicators of highly valued species will directly provide useful information to policymakers attempting to maximize the overall benefits provided by the ecosystem. 26 Zacharias & Roff, supra note 21, at 71. 41 STANFORD JOURNAL OF LAW, SCIENCE & POLICY Vol. 2 in the creation of a meaningful portfolio of indicators is to ensure that all aspects of ecosystem structure and function intended by the term “ecosystem health” are fully represented. A number of fundamental ecosystem attributes have been identified as important features of ecosystem health, including diversity, resilience, primary or secondary productivity, energy recycling, and mean trophic level.27 Identifying reliable and empirically tractable proxies for such difficult-to-measure ecosystem attributes is the key to generating an ecologically meaningful indicator set. Rice and Rochet outline a useful framework for selecting a suite of informative indicators for ecosystem management.28 They argue that indicators must be directly observable, based on well-defined theory, cost effective to measure, supported by historical time series, sensitive and responsive to changes in ecosystem state, and specific to properties they are intended to measure. Generating a list of candidate indicators that meet many of these criteria is a challenging but attainable goal. However, rigorously evaluating the sensitivity, responsiveness or specificity of indicators, i.e., indicator performance, can be technically demanding. Determining the degree to which an indicator responds to changes in ecosystem attributes entails either rigorous empirical analyses or simulation modeling. Empirical evaluation of indicator performance requires extensive data as well as knowledge about the statistical properties of the indicators and processes structuring the ecosystem. For instance, Trenkel and Rochet examined the performance of a series of population and community-level indicators in the Celtic Sea fish assemblage.29 They used data from a groundfish survey to test hypotheses related to pre-selected reference points or of no change. Performance of indicators was evaluated using estimates of precision (e.g., coefficient of variation) and statistical power. This approach allowed the authors to establish which metrics were relatively precise indicators of population or community change and which ones provided very little information regarding the status of the community. Computer simulation provides an alternative approach for evaluating indicator performance in cases where extensive data are lacking. Samhouri and colleagues, for example, used seven northeast Pacific marine food web models to determine the degree to which potential indicators reflected changes in ecosystem properties.30 In this approach, an operating model (Ecopath with Ecosim in this case) is used to simulate the dynamics of the system over time. Biomass or number of individuals can be extracted from the model to generate time series of indicators. These indicators are then evaluated by their ability to detect or predict changes in “true” values of key ecosystem attributes (which are known from the operating model). Using this approach, Fulton31 showed that a portfolio of indicators that includes species with high turnover, groups targeted by fisheries, habitat-defining taxa, and species near the top of the food web (and with long generation times) provided a good overall view of the system. These and similar quantitative approaches can ensure that proposed indicators are ecologically meaningful, and such information is obviously critical in building a comprehensive,

27 See Jameal F. Samhouri et al., Quantitative Evaluation of Marine Ecosystem Indicator Performance Using Food Web Models, 12 ECOSYSTEMS 1283, 1286 (2009) (description of key marine ecosystem attributes). 28 Jake C. Rice & Marie-Joëlle Rochet, A Framework for Selecting a Suite of Indicators for Fisheries Management, 62 ICES J. OF MARINE SCI. 516, 527 (2005). 29 Verina M. Trenkel & Marie-Joëlle Rochet, Performance Indicators Derived from Abundance Estimates for Detecting the Impact of Fishing on a Fish Community, 60 CANADIAN J. OF FISHERIES AND AQUATIC SCI. 67, 67-85 (2003). 30 Samhouri et al., supra note 27, at 1286. 31 Fulton et al., supra note 13, at 548. 2010 DEVELOPING MEANINGFUL MARINE ECOSYSTEM INDICATORS 42 scientifically rigorous indicator portfolio. We next must address how to bring together indicators with high social and high ecological meaning.

IV. STEP 3: INTEGRATE ECONOMICS AND ECOLOGY TO DEVELOP MEANINGFUL INDICATOR PORTFOLIOS

Approaches such as those described above can provide a consistent and coherent suite of indicators that reflect the ecology of the system and are meaningful to stakeholders and the general public. In a world free of constraints, one could simply use all of these indicators in reports attempting to show how ecosystem health is shifting as a result of climate change or the efficacy of management actions meant to mitigate the effects of climate change. However, given limited resources to monitor indicators and the limited capacity or attention span of decision makers to grasp a profuse and diverse indicator set, most efforts are compelled to reduce a large number of candidate indicators to only a few. With such practical constraints, maximizing the value of a single set of indicators requires melding indicators that carry ecological information with those that resonate with the public. A useful first step in this integration is to ask what ecosystem attributes are adequately represented by indicators that have high social value (i.e., those important to the public). Because charismatic species often come from a few closely related taxa (e.g., marine mammals), when several species are proposed, we expect these indicators to map onto similar ecosystem attributes. That is, they will provide redundant ecological information. Likewise, we expect other ecosystem attributes to be poorly represented by such charismatic indicators. For instance, the long-generation time and low inherent productivity of marine mammals make them poor indicators of energy flow in an ecosystem.32 Such gaps can be filled with indicators emerging from ecological analyses of empirical data or ecosystem models. If we imagine that a governance structure wants to track seven indicators,33 the process described above would allow us to form multiple portfolios of indicators, each of which carries the same amount and type of information about ecosystem structure and function. How does one choose among these ecologically identical indicator sets? We suggest the best indicator portfolio is the one that resonates most with the public and decision makers. However, which collection of indicators is most meaningful to the public is not always obvious. Fortunately, economists have introduced a number of approaches that can be used to evaluate the relative value of indicator portfolios. Since the 1960's, several valuation methods have been developed in response to increasing awareness of the importance of estimating values of services that cannot readily be bought or sold, such as the inherent value of knowing a species of whale is viable. The most commonly used non-market valuation methodology is contingent valuation, a survey-based technique that provides respondents the opportunity to make an economic decision concerning the relevant non-market good.34 Values for the good are then inferred from the induced economic decision or stated preference.35

32 Samhouri et al., supra note 27, at app., tbl A1. 33 E.g., JOINT OCEAN COMM’N, U.S. OCEAN POLICY REPORT CARD (2007), available at http://www.jointocean commission.org/resource-center/2-Report-Cards/2008-02-27_2007_Ocean_Policy_Report_Card.pdf. 34 For a bibliography of over 2,000 contingent valuation papers and studies from over 40 countries, see RICHARD CARSON ET AL., A BIBLIOGRAPHY OF CONTINGENT VALUATION STUDIES AND PAPERS (Natural Resources Damages Assessment Inc. 1995). 35 For an overview of the theoretical and empirical issues involved in contingent valuation, see A. MYRICK FREEMAN, THE MEASUREMENT OF ENVIRONMENTAL AND RESOURCE VALUES: THEORY AND METHODS (1993). 43 STANFORD JOURNAL OF LAW, SCIENCE & POLICY Vol. 2

Advances in contingent valuation have led to techniques that are increasingly robust to potential biases stemming from the hypothetical nature of stated preference surveys. For example, experimental techniques such as choice-based conjoint analysis can determine individual preferences based on the valuation of underlying attributes. Instead of directly stating their willingness to pay for a non-market good, respondents are asked to choose among alternate states of the environment, where each state is a set of characteristics and price. Researchers can then estimate how an individual weighs different attributes of the ecosystem and, consequently, the marginal willingness to trade off between attributes. If one attribute is monetary cost and one is, say, the population status of a particular species, then a researcher can estimate the willingness to pay for a marginal change in the condition of a species by looking at the marginal rate of substitution between cost and the attribute related to species abundance.36 If properly executed, non-market valuation techniques can help researchers develop more meaningful portfolios of ecosystem indicators, in that they can help scientists and policy makers choose among portfolios of indicators with high scientific value and varying societal value. For example, consider two hypothetical indicator portfolios: portfolio A includes orcas, rockfish, sea urchins, and sea grass; portfolio B includes harbor seals, salmon, mussels, and kelp. Imagine, also, that portfolios A and B confer identical information about the state of the food web. In other words, both portfolios hypothetically provide equal information about biodiversity, resistance to human disturbance, efficiency of energy transfer through the food web, etc. Because the individual species that make up these portfolios vary in their societal value,37 we expect that the total value of portfolio A and B may differ as well. Thus, with portfolio A versus B as our non-market good, we can use contingent valuation methodology to assess which portfolio has more value. To illustrate potential trade-offs between ecological information and societal value, we explored the relationship between the ecological meaning of an indicator and its potential societal value in the Strait of Georgia (Canada) food web. As mentioned above, people’s willingness to pay for conservation, and hence societal value, can be positively correlated to eye- size of the conservation target. For the sake of illustration, we thus used eye size as a proxy of societal value. We used results from Samhouri et al.38 to evaluate ecological meaning by testing the ability of eleven candidate indicator species to track two widely used attributes of ecosystem health: Shannon diversity and mean trophic level. In the case of Shannon diversity, the ecological information provided by an indicator declined as its putative societal value increased (see infra Fig. 1a). This result illustrates the point that selection of an appropriate indicator species will, at times, require operating along a trade-off between scientific and societal value. While some iconic species (e.g., orcas) captured little information about changes in Shannon diversity, others (e.g., Chinook salmon) contained a substantial amount of ecological information, though not as much as less-valued species (e.g., euphausiids, commonly referred to as krill). In the case of mean trophic level, a way of describing the relative numbers of apex predators, mid-level consumers, and primary producers, there was no monotonic relationship

36 The literature on these methods is large and growing, and is well summarized in Louviere et al., STATED CHOICE METHODS: ANALYSIS & APPLICATION (2000). 37 See generally John B. Loomis & Douglas S. White, Economic Benefits of Rare and Endangered Species: Summary and Meta-Analysis, 18 ECOLOGICAL ECON. 197, 197-206 (1996) (comprehensive review of studies valuing endangered species). 38 Samhouri et al., supra note 27, at 1287.

2010 DEVELOPING MEANINGFUL MARINE ECOSYSTEM INDICATORS 44 between an indicator’s ecological information content and its putative societal value (see infra Fig. 1b). For this attribute of the ecosystem, then, it is possible to select an indicator with both high scientific and societal value (e.g., transient orcas and pinnipeds such as seals and sea lions). Because human preferences for certain indicators may be context-dependent, some of the other non-market valuation techniques mentioned above can be used to decide which of the indicators with nearly equivalent societal and scientific value should be included in the assembly of a portfolio covering multiple aspects of ecosystem structure and function. We used individual species as indicators in this example because of the availability of eye-size as a proxy for public appeal. We expect the general result of this illustration to apply with many other, more complex indicators as well.

V. THE CASE OF PUGET SOUND

Ecosystem-based management in Puget Sound provides a compelling example for the need to adopt an approach that integrates natural and social science in the selection of ecosystem health indicators. EBM in Puget Sound is coordinated by the Puget Sound Partnership (PSP), a public-private partnership charged with restoring the natural and human components of the Puget Sound ecosystem by 2020. At the outset, the PSP conducted a systematic review of all existing indicators, which were then evaluated using expert judgment of regional scientists. A total of 657 indicators were initially identified. These candidate indicators were subjected to a screening process based on criteria developed by the Environmental Protection Agency that required indicators to be directly observable, based on well-defined theory, cost effective to measure, supported by historical time series, and relevant to management needs.39 After this vetting, 73 indicators were considered “good,” meaning they met the criteria described above and could be used immediately.40 Indeed, the set included some indicators that were considered useful gauges of ecosystem health. These included charismatic species such as seabirds, marine mammals, and salmon, fisheries targets including Pacific hake, herring, and rockfish, and a primary producer group, kelp.41 Do these indicators meet our ecological and social criteria for meaningful indicators? First, these indicators clearly have high social value in the Puget Sound region. In addition to high-value flagship species (e.g., salmon), the PSP indicator portfolio includes fisheries species that are valuable because of their usefulness to Puget Sound citizens.42 However, while these indicators provide information on some aspects of ecosystem health (food web structure, the total amount of primary production, and community-level respiration), a number of aspects of ecosystem health (e.g., resilience, diversity, mean trophic level) may not be adequately represented by this indicator set.43 In addition, there is considerable overlap in the ecological information conveyed by individual indicators.44

39 Janis C. Kurtz et al., Strategies for Evaluating Indicators Based on Guidelines from the Environmental Protection Agency's Office of Research and Development, 1 ECOLOGICAL INDICATORS 49, 50 (2001). 40 Heather Tallis et al., The Many Faces of Ecosystem-based Management: Making the Process Work Today in Real Places, MARINE POL’Y (forthcoming Mar. 2010) (manuscript at 7). 41 SANDRA M. O’NEILL ET AL., ENVIRONMENTAL INDICATORS FOR THE PUGET SOUNDS PARTNERSHIP: A REGIONAL EFFORT TO SELECT PROVISIONAL INDICATORS (PHASE I) 27-29 (2008), available at http://www.psp.wa.gov/documents.php. 42 Martín-López et al., supra note 22, at 631. 43 Samhouri et al., supra note 27, at 1287-94. 44 Id. 45 STANFORD JOURNAL OF LAW, SCIENCE & POLICY Vol. 2

The process we propose would improve the situation in several ways. These PSP indicators were drawn from taxa with high social value, but because of time constraints, a careful examination of the ecological value of the indicators was not possible. Thus, the approach we propose would ensure that all aspects of food web health are represented, and that redundancy is minimized. In this way, the PSP could maximize the information content delivered by the indicators while minimizing the cost of monitoring indicator status. In ensuring full coverage of ecological processes, it will likely be necessary to include some indicators with lower social value in the indicator portfolio. There are, however, many choices of lower-value indicators that could be included. Consequently, assessing the value sets of indicators would make certain that total social value of the ecologically meaningful indicator package is maximized.

V. CONCLUSIONS

We take for granted we know the whole story We judge a book by its cover And read what we want Between selected lines. —Axl Rose45

It is tempting for natural scientists to advocate indicators that provide maximal information about ecosystem structure and function without consideration of societal values. This temptation is especially strong given the urgent need to adapt our management policies in the face of Earth’s rapidly changing climate. However, humans manage and conserve ecosystems for their own benefit, which can be quantified based on the direct and passive uses of an ecosystem’s components. And, as Rose commented,46 the value humans place on these components can be based on incomplete information, emotional response, and subjective inference. If indicators are chosen solely based on their scientific value, the societal value of those indicators may be less than it could be. We propose that advances in public policy and improvements in management outcomes are most likely if indicators both carry significant ecological information and resonate with the public for which the ecosystem is being managed. Since the same scientific value can be achieved with numerous different portfolios of indicators, we can maximize the value of the indicators themselves by making sure to include the ones that stakeholders care about the most. Our approach potentially raises several concerns. First, although we illustrated our approach with a focus on climate change and food web indicators, it is easily adaptable and can effectively accommodate water quality, oceanographic, habitat, or socio-economic indicators. Some may also perceive that assessing social value of indicators would exclude physical attributes of ecosystem health such as temperature or pH. However, in our approach, the science dictates which ecosystem attributes must be represented by indicators. If the science determines some ecosystem attribute must be included, then the question is not whether it should or should not be included, but rather, which indicator (if there is more than one) of that attribute resonates most with the public. An approach that is flexible with respect to ecosystem indicators and simply responds to societal trends could be in conflict with the need for long-term datasets that are comparable

45 GUNS N’ ROSES, Don’t Damn Me, on USE YOUR ILLUSION I (Geffen Records 1991). 46 Id. 2010 DEVELOPING MEANINGFUL MARINE ECOSYSTEM INDICATORS 46 through time. However, although the approach we propose is responsive to societal values, it also recognizes the need for scientifically robust indicators. Thus, a key characteristic of indicators in our framework is that they are supported by a historical time series and have known statistical properties.47 Additionally, there are numerous scientific reasons to generate long-term datasets outside of context we discuss here. Because constraints require that the number of indicators that are reported is limited, this should not preclude support for monitoring for other reasons. We have highlighted contingent valuation as an acceptable tool to assess societal value; however, a variety of other means of determining social value are available. For instance, Q methodology is a systematic statistical approach that reveals subjective structures, attitudes, and perspectives of participants in simple surveys.48 Even careful analysis of news media content can reveal the manifest and latent meaning, attitude, and intention of a community.49 It is not easy to predict whether tracking different aspects of ecosystem structure and function will require trade-offs between the scientific information content and societal value of indicators, or which portfolio of indicators will hold the most public appeal. This challenge is likely to become greater as climate change alters the relationships between ecosystem attributes and indicators and the societal value of indicator species. One of the main advantages of the approach for developing indicators we advocate here is that it can be used iteratively and adaptively as climate changes. Though the IPCC and other groups have sketched out a range of possible futures under alternative carbon emissions scenarios, efforts to scale down models from global to regional or local are only beginning to emerge. Such efforts will be particularly useful for highlighting indicators that hold scientific promise and testing whether currently robust ecosystem indicators will continue to be sensitive and responsive in the future. Similarly, it should be possible to compare historic and present-day ecosystem models to identify indicators that are consistently ecologically informative, and therefore likely to be instructive under future climate scenarios. Just as indicators carrying the most ecological meaning may change with Earth’s climate, the societal value of indicators will also shift. For instance, the broad appeal of polar bears as a flagship indicator for the impacts of climate change50 is a recent development. It is possible that the societal value of polar bears will decline in time as conservation efforts focused on them either succeed or fail. Indeed, at some point public empathy for polar bears will probably be replaced by other species or ecosystems in more urgent need of protection or with greater potential to respond to conservation efforts, such as penguins51 or corals.52 The three-step process we propose here of embracing human preferences, ecology, and non-market valuation is a flexible approach that can be repeated as often as needed in order to respond to shifting climate, ecosystem configurations, and societal values. In essence, the approach we outline limits the cost of information failure associated with choosing indicators that are not well understood by some direct users (and/or general observers) of the indicators. We argue that it is

47 Rice & Rochet, supra note 28, at 517. 48 See Steven R. Brown, Q Methodology and Qualitative Research, 6 QUALITATIVE HEALTH RES. 561, 561-67 (1996). 49 KIMBERLEY A. NEUENDORF, THE CONTENT ANALYSIS GUIDEBOOK 23-25 (2002). 50 E.g., Polar Bears, http://www.savebiogems.org/polar/ (last visited Dec 28, 2009). 51 Matthew Knight, Climate Changing ‘Faster, Stronger, Sooner’, Cable News Network, Oct. 20, 2008, http://www.cnn.com/2008/TECH/science/10/20/wwf.climate.report/index.html. 52 Richard Harris, Can Corals Survive in a Warming World? (National Public Radio, Aug. 11, 2009), http://www.npr.org/templates/story/story.php?storyId=111757927. 47 STANFORD JOURNAL OF LAW, SCIENCE & POLICY Vol. 2 possible to simultaneously maximize the value of the indicators for such users by prioritizing the ecosystem components they directly care about most, while maintaining the overall scientific value that allows fully informed management. We have argued that the integration of scientific information with societal preferences and values is an efficient way to adapt public policy of the oceans to climate change or other ecosystem stressors. In some respects, our approach is similar to other generic behavioral approaches that seek to nudge public policy in directions that society generally considers to be beneficial.53 Similarly, our method provides tools that policy makers can use to promote policies that allow effective adaptation to climate change; however, it is important to note that a set of indicators that resonates with the public does not tell policy makers what to do. Instead, a "meaningful" indicator set simply provides relevant information to society that allows policy makers to better reach goals that emerge from public policy processes. Significant advances in adapting to climate change require that we understand both how the ecosystem is responding and how to effectively implement appropriate management responses. Our approach to indicator selection simultaneously informs both of these elements. Indeed, we contend that melding natural and social science is crucial as we begin to travel from a state of alarm about climate change and start to consider what is possible for our future.

53 For a wide ranging discussion of how behavioral economics and related fields could be used to affect societal welfare, see RICHARD H. THALER & CASS R. SUNSTEIN, NUDGE: IMPROVING DECISIONS ABOUT HEALTH, WEALTH, AND HAPPINESS (2008). 2010 DEVELOPING MEANINGFUL MARINE ECOSYSTEM INDICATORS 48

Figures

Figure 1. Relationship between the ecological information content of eleven candidate indicator species and eye size--a proxy for public appeal.54 Ecological information content was assessed by testing for correlations (Spearman rank) between the candidate indicators and two widely used metrics of ecosystem health: a) Shannon diversity, and b) mean trophic level, using an Ecopath with Ecosim model of the Strait of Georgia (Canada) marine food web.55 A range of values for the indicators, Shannon diversity, and mean trophic level was generated by simulating a range of fishing pressures.56 Eye-size was extracted from Howland et al.57 and Hiller-Adams and Case.58

54 Martín-López et al., supra note 22, at 630. 55 Steven J.D. Martell et al., Simulating Fisheries Management Strategies in the Strait of Georgia Ecosystem Using Ecopath and Ecosim, UCB Fish. Centre Res. Rep. 16, 17-18 (2002), available at http://www2.fisheries.com/archive/publications/reports/10-2.pdf. 56 Samhouri et al., supra note 27, at 1285. 57 Howard C. Howland et al., The Allometry and Scaling of the Size of Vertebrate Eyes, 44 VISION RES. 2043, 2047 (2004). 58 Page Hiller-Adams & James F. Case, Optical Parameters of Euphausiid Eyes as a Function of Habitat Depth, 154 J. COMP. PHYSIOLOGY A: NEUROETHOLOGY, SENSORY, NEURAL, AND BEHAVIORAL PHYSIOLOGY 307, 309 (1984