Biodiversity and Conservation Assessments of species' vulnerability to climate change: from pseudo to science --Manuscript Draft-Manuscript Number: Full Title:
Assessments of species' vulnerability to climate change: from pseudo to science
Article Type:
Commentary
Keywords:
conservation; prioritization; rigor; uncertainty
Corresponding Author:
Alisa A. Wade, PhD Flathead Lake Biological Station Polson, MT UNITED STATES
Corresponding Author Secondary Information: Corresponding Author's Institution:
Flathead Lake Biological Station
Corresponding Author's Secondary Institution: First Author:
Alisa A. Wade, PhD
First Author Secondary Information: Order of Authors:
Alisa A. Wade, PhD Brian K. Hand Ryan P. Kovach Clint C. Muhlfeld Robin S. Waples Gordon Luikart
Order of Authors Secondary Information: Funding Information:
National Aeronautics and Space Administration (12-ECOF12-0055) National Science Foundation (-DEB 1258203) U.S. Department of the Interior
Dr. Gordon Luikart
U.S. Geological Survey
Dr. Ryan P. Kovach
Dr. Ryan P. Kovach Dr. Brian K. Hand
Abstract:
Climate change vulnerability assessments (CCVAs) are important tools to plan for and mitigate potential impacts of climate change. However, CCVAs often lack scientific rigor, which can ultimately lead to poor conservation prioritization and associated ecological and economic costs. We discuss the need to improve comparability and consistency of CCVAs and either validate their findings or improve assessment of CCVA uncertainty and sensitivity to methodological assumptions.
Suggested Reviewers:
Meredith McClure, PhD Center for Large Landscape Conservation
[email protected] Dr. McClure is a practitioner who has conducted several CCVA. Molly Cross, PhD Wildlife Conservation Society
[email protected] Dr.Cross is an expert in climate change impact assessments. Josh Lawler, PhD University of Washington
[email protected]
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Dr. Lawler has published numerous articles concerning species vulnerability and assessing climatic impacts to biodiversity. Erik Beever, PhD USGS
[email protected] Dr. Beever is the author or co-author on several recent articles highlighting the need to better consider the adaptive capacity of species when assessing risk from climate change.
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Assessments of species’ vulnerability to climate change: from pseudo to science Alisa A. Wade1*, Brian K. Hand1, Ryan P. Kovach1,2, Clint C. Muhlfeld1,2, Robin S. Waples3, Gordon Luikart1 1
Flathead Lake Biological Station Division of Biological Sciences University of Montana Polson, MT 59860 USA 2
United States Geological Survey Northern Rocky Mountain Science Center, Glacier National Park West Glacier, MT 59936 USA 3
NOAA Fisheries Northwest Fisheries Science Center Seattle, WA 98112 *Corresponding Author Alisa A. Wade Flathead Lake Biological Station Division of Biological Sciences University of Montana
[email protected] 406-233-9722 Abstract Climate change vulnerability assessments (CCVAs) are important tools to plan for and
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mitigate potential impacts of climate change. However, CCVAs often lack scientific rigor, which
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can ultimately lead to poor conservation prioritization and associated ecological and economic
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costs. We discuss the need to improve comparability and consistency of CCVAs and either
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validate their findings or improve assessment of CCVA uncertainty and sensitivity to
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methodological assumptions.
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Keywords: conservation, prioritization, rigor, uncertainty
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Acknowledgements
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This work was funded by a National Aeronautics and Space Administration ROSES grant
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12-ECOF12-0055. A US Geological Survey Mendenhall Fellowship partially supported RPK.
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GL and RPK were also partially supported by National Science Foundation-DEB 1258203. BKH
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received support from the Department of the Interior Northwest Climate Science Center. Any use
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of trade, firm, or product names is for descriptive purposes only and does not imply endorsement
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by the U.S. Government.
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Peer Review DISCLAIMER: This draft manuscript is distributed solely for purposes of scientific peer review. Its content is deliberative and predecisional, so it must not be disclosed or released by reviewers. Because the manuscript has not yet been approved for publication by the U.S. Geological Survey (USGS), it does not represent any official USGS finding or policy.
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Assessments of species’ vulnerability to climate change: from pseudo to science
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Introduction
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Use of climate change vulnerability assessments (CCVAs) to identify species and ecological
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systems at risk have increased exponentially in recent years (Tonmoy et al. 2014). CCVAs seek
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to quantify a systems’ “propensity to be adversely affected” (IPCC 2014) by climate change and
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to assist managers in prioritizing conservation actions, which, given limited resources, requires
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tradeoffs between species, populations, or locations. Lack of scientific rigor in CCVAs can lead
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to inefficient or inappropriate allocation of resources and associated ecological and economic
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costs.
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Species’ CCVAs have differing methods depending on the ecological and management
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context, necessitating approaches tailored to specific conservation goals (Hinkel 2011). A wide
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variety of methods are available (reviewed in Rowland et al. 2011; Pacifici et al. 2015), with
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little consensus on the best approach (Preston et al. 2011; Costa and Kropp 2012). To clarify the
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complexity surrounding CCVA, efforts have been made to categorize vulnerability typologies
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(Adger 2006; Tonmoy et al. 2014), define key terms (Turner et al. 2003; Williams et al. 2008),
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and provide practitioner guidance in conducting CCVAs specific to species (e.g., Glick et al.
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2011).
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Nevertheless, many CCVAs lack rigor. CCVAs represent hypotheses about how species will
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respond to climatic perturbations. The scientific process requires hypotheses be tested or
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confronted with evidence and findings be replicable. Rigorous science, particularly for complex
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biological systems, requires a clear accounting of uncertainty when a hypothesis cannot be tested
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with a reductionist approach (Harmon et al. 2015). Thus, there are at least two critical
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considerations necessary to improve CCVA rigor: 1) improve consistency and comparability of 3
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CCVAs to provide multiple lines of evidence supporting a hypothesis and to illustrate
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replicability, and 2) validate CCVA findings, or assess their uncertainty when validation is not
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possible.
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Improve consistency and comparability
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Making methodologically-diverse CCVAs more comparable is necessary to embed CCVAs
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more firmly in the scientific process. Application of the term “vulnerability” to climate
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assessments should be judiciously applied only to studies meeting a standardized set of
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requirements. Although species CCVAs share features with traditional impact assessments
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(Rowland et al. 2011) and Population Viability Analyses (PVA; Akçakaya and Sjogren-Gulve
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2000), at least three essential characteristics distinguish CCVAs.
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First, CCVAs seek to understand the ecological processes linking climate change and
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impacts to ascertain conservation options (Füssel and Klein 2006). A study focused on outcome,
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without seeking opportunities for adaptation, such as an impact assessment, is not a CCVA.
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Second, CCVAs require consideration of three primary elements of vulnerability: 1) climate
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exposure, 2) sensitivity, and 3) adaptive capacity (IPCC 2007; Glick et al. 2011). Evaluating
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climate exposure – the magnitude or risk of changing conditions – generally requires a future
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climate scenario (Hinkel 2011). Projections of other stressors (e.g., habitat modification) can also
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be included (see Wilsey et al. 2013). Thus, a third characteristic is that CCVAs consider future
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conditions to project future outcomes. Many PVAs do not consider potential climatic changes,
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and estimates of future population abundance are largely based on current environmental
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conditions. Models focused only on exposure (e.g., bioclimatic niche) do not meet the definition
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of CCVA.
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“Vulnerability” is a theoretical concept, and therefore, cannot be directly measured (Adger
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2006). Instead, CCVAs rely on proxy metrics assumed to represent vulnerability elements.
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Because sensitivity and adaptive capacity often overlap, it can be difficult to identify which
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vulnerability element(s) a metric represents. Sensitivity metrics reflect a “dose-response”
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relationship between climate exposure and likelihood of adverse effects to a species or system.
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Metrics could include physiological tolerances, population vital rates, or habitat quality assuming
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organisms inhabiting poor habitat are more sensitive to additional climatic stress (e.g., Wade et
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al. 2013). Adaptive capacity metrics reflect the inherent potential for a species to adapt via range
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shifts, phenotypic and behavioral plasticity (trait changes in response to the environment, without
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requiring genetic change), or microevolution (changes in frequency of a specific gene within a
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population). Adaptive capacity can reduce species sensitivity, and the two are linked through
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interactions of ecological and evolutionary processes (Schoener 2011). Nevertheless, species
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with high sensitivity can also have high adaptive capacity, and CCVAs should include at least
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one metric that reflects each element independently.
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Notably, the vast majority of recent biophysical CCVAs have not incorporated adaptive
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capacity metrics (Thompson et al. 2015). Although there is limited empirical understanding of
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how phenotypic plasticity and evolutionary potential influence adaptive capacity on
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contemporary time-scales (Hendry 2016; DeBiasse and Kelly 2016), it is clear that plasticity
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plays a major role in organismal response and potential population resilience to climate change
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(Gienapp et al. 2008; Vedder et al. 2013; Seebacher et al. 2015). Evidence is also increasing that
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adaptive microevolution can occur rapidly and potentially rescue populations from decline
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(Carlson et al. 2014). Recent works by Nicotra et al. (2015) and Beever et al. (2015) highlight
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the importance of adaptive capacity for species’ CCVA and outline possible ways forward. 5
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Beginning a CCVA with a conceptual model can also improve rigor. Conceptual models
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provide a visual depiction of the proxy metrics considered and how they are assumed to
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represent vulnerability elements, improving comparability (Fig. 1). Further, conceptual models
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provide a structured expression of hypotheses about system function, allowing formal testing of
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assumed causal linkages and virtual testing of ecological scenarios when field experimentation is
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not possible (Parysow and Gertner 1997; Manley et al. 2004). Conceptual models also help
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identify data gaps and incorporate new data into existing analyses (McClure et al. 2013).
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Explicitly consider uncertainty, assess sensitivity of results, and validate as possible
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The operationalization of a CCVA defines the multiple hypothesized relationships between
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climate exposure and species’ responses, influences findings, and has substantial implications for
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conservation planning decisions (Summers et al. 2012; Game et al. 2013). Yet, fewer than a
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quarter of recent CCVAs explicitly considered many of the uncertainties inherent to CCVA
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operationalization (Tonmoy et al. 2014). Pacifici et al. (2015) summarize sources of uncertainty
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associated with various climate-related impact assessments, including climatic, algorithmic, and
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biotic uncertainties.
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Uncertainty inherent to climate models is often ignored in empirical CCVA application.
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Uncertainty is propagated throughout the many steps involved in running and using a Global
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Circulation Model (GCM). Strategies exist for managing uncertainty (Jones 2000) or choosing a
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robust subset of climate model outputs (Snover et al. 2013), but some amount of irreducible
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uncertainty will remain. To account for this, CCVAs should consider a spectrum of potential
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impacts (e.g., best to worst-case scenarios) and communicate these uncertainties to managers
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(Deser et al. 2012).
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Sensitivity analyses should also be conducted to identify the relative influence of various
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assumptions and methods on estimated vulnerability. Results are highly sensitive to the metrics
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chosen (e.g., Summers et al. 2012; Lee et al. 2015; Wade et al. 2016). Differing CCVA
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algorithms applied to the same species can result in substantially different rankings (Lankford et
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al. 2014).
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Ultimately, hypothesized relationships in CCVAs require validation to cement CCVAs in the
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scientific process (Weeks et al. 2013). Because CCVAs represent scenarios, internal validation
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approaches, such as using subsetted or independent data sets, are not generally applicable.
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Instead, validation requires confronting the CCVA hypothesis with empirical data. Time-series
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monitoring data provide the best opportunity for retrospective validation, comparing
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hypothesized vulnerability to actual trends in species vigor or distribution. Unfortunately, these
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data are seldom available, and a combination of multiple pseudo-validation approaches is most
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appropriate. Comparisons can be made between CCVAs and other modeling approaches, or
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between multiple CCVAs for the same species or location. Dawson et al. (2011) suggest that the
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elements of vulnerability (exposure, sensitivity, and adaptive capacity) can be tested and
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analyzed independently with a breadth of data, including from ecophysiological, population, and
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bioclimatic models, paleoecological records, experimental manipulations, or direct observations.
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Emerging ancient DNA and paleo-genetic tools can also provide comparative evidence
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(Fordham et al. 2014). Studies quantitatively linking biotic variables (e.g., abundance,
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recruitment, genetic diversity) to climatic variation (Elith and Leathwick 2009; Harrisson et al.
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2016) provide ecological and evolutionary evidence for hypothesized relationships within the
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CCVA.
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Conclusion CCVAs can help prioritize species, populations, and locations that are most vulnerable to
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climate change. Alternatively, CCVAs can illuminate opportunities for protecting strongholds
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where species may be relatively invulnerable. To avoid misplaced conservation resources,
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CCVAs should be conducted with greater rigor. Increased comparability and consideration of
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uncertainty, an array of biophysical responses – including adaptive capacity, and multiple
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scenarios combined with on-going monitoring of species’ responses to climatic change will
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forward this goal. Nonetheless, conservation or restoration of a particular geographic area,
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population, or species will seldom be sufficient to maintain biodiversity. Uncertainty of climate
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change impacts demands consideration of how physical and biological processes affect
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ecological and evolutionary trajectories of populations and ecosystems over the long-term.
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Figure Captions
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Fig. 1 An example conceptual model detailing the hypothesized stressors to bull trout, Salvelinus
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confluentus, under a changing climate and the metrics used to operationalize the climate change
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vulnerability assessment (adapted from Wade et al. 2016)
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Figure 1
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