Approaches to evaluating climate change impacts on species: a guide to initiating the adaptation planning process

An increase in management actions has compensated for past climate change effects on desert locust gregarization in western Africa

In response to high population density, the desert locust, Schistocerca gregaria, becomes gregarious and forms swarms that can cause significant damage to crops and pastures, threatening food security of human populations from western Africa to India. This switch from solitary to gregarious populations is highly dependent on favorable weather conditions. Climate change, which has been hypothesized to shift conditions towards increasing risks of gregarization, is therefore likely to have significant impacts on the spatial distribution and likelihood of outbreak events. However, the desert locust is intensely managed at large scales, which possibly counteracts any increased risk of outbreaks due to a more favorable climate. Consequently, understanding the changes in risks in the future involves teasing out the effects of climate change and management actions. Here we studied the dynamics of gregarization at the very early stages of potential outbreaks, in parallel with trends in climate and management, between 1985 and 2018 in western Africa. We used three different spatial scales, with the goal to have a better understanding of the potential effects of climate change per se while controlling for management. Our first approach was to look at a regional scale, where we observed an overall decrease in gregarization events. However, this scale includes very heterogeneous environments and management efforts. To consider this heterogeneity, we divided the area into a grid of 0.5° cells. For each cell, a climate analysis was performed for rainfall and temperature, with trends obtained by a harmonic decomposition model on monthly data. Analyses of gregarization showed only a few significant trends, both positive and negative, mainly found in western Mauritania where management effort has increased. To improve the statistical power, these cells were then grouped into larger homogeneous climatic clusters, i.e. groups of cells with similar climatic conditions and similar climatic trends over the study period. At this scale, gregarization events depend on the intersection between climate conditions and management efforts. The clusters where gregarization increased were also the ones with the highest increase of management. These results highlight the important effect of preventive management, which may counteract the positive effects of climate change on locust proliferation.

Assessment of Amphibians Vulnerability to Climate Change in China

Global climate change is considered to be one of the main threats to organisms. As poikilothermic animals, amphibians are in particular sensitive because they cannot adapt to the dramatic climate change through active physiological regulation. Using 104 representative species, the present study conducted an assessment of amphibians vulnerability to climate change in China through the combination of two approaches. Specifically, 18 vulnerability criteria belonging to five categories (i.e., thermal tolerance, individual reproductive, population diffusion and diversity, food and habitat, and climate conditions) were first selected and scored based on literatures and experts opinions. Species were then ranked into three levels of climate change vulnerability (i.e., high, moderate, and low) by calculating vulnerability scores and conducting natural breaks analyses, as well as performing a principal coordinate analysis (PCoA) and k-means cluster analyses, respectively. To integrate the two results, a matrix with the ranks from each result was developed to produce a final integrated list. Our results indicated that the 104 amphibian species were classified into three types by natural breaks, with 54 low vulnerable species, 41 moderately vulnerable species, and nine highly vulnerable species. Based on the results of PCoA and k-means cluster analyses, five species were highly vulnerable, 38 species were moderately vulnerable, and 61 species were low vulnerable. The combination of the two ranks suggested that 36 species such as Hyla tsinlingensis and Liangshantriton taliangensis were of low vulnerability, 54 species such as Echinotriton chinhaiensis and Hynobius chinensis were of moderate vulnerability, and 14 species such as Ichthyophis kohtaoensis and Zhangixalus prasinatus were of high vulnerability. Overall, our results indicated that climate change could have strong potential effects on amphibians in China. And the highly vulnerable species such as Ichthyophis kohtaoensis, Zhangixalus prasinatus, and Theloderma corticale should be the priority in future conservation activities.

Projected impacts of climate change on snow leopard habitat in Qinghai Province, China

Assessing species' vulnerability to climate change is a prerequisite for developing effective strategies to reduce emerging climate-related threats. We used the maximum entropy algorithm (MaxEnt model) to assess potential changes in suitable snow leopard (Panthera uncia) habitat in Qinghai Province, China, under a mild climate change scenario. Our results showed that the area of suitable snow leopard habitat in Qinghai Province was 302,821 km2 under current conditions and 228,997 km2 under the 2050s climatic scenario, with a mean upward shift in elevation of 90 m. At present, nature reserves protect 38.78% of currently suitable habitat and will protect 42.56% of future suitable habitat. Current areas of climate refugia amounted to 212,341 km2 and are mainly distributed in the Sanjiangyuan region, Qilian mountains, and surrounding areas. Our results provide valuable information for formulating strategies to meet future conservation challenges brought on by climate stress. We suggest that conservation efforts in Qinghai Province should focus on protecting areas of climate refugia and on maintaining or building corridors when planning for future species management.

Risk of short-term biodiversity loss under more persistent precipitation regimes

Recent findings indicate that atmospheric warming increases the persistence of weather patterns in the mid-latitudes, resulting in sequences of longer dry and wet periods compared to historic averages. The alternation of progressively longer dry and wet extremes could increasingly select for species with a broad environmental tolerance. As a consequence, biodiversity may decline. Here we explore the relationship between the persistence of summer precipitation regimes and plant diversity by subjecting experimental grassland mesocosms to a gradient of dry-wet alternation frequencies whilst keeping the total precipitation constant. The gradient varied the duration of consecutive wet and dry periods, from 1 up to 60 days with or without precipitation, over a total of 120 days. An alternation of longer dry and wet spells led to a severe loss of species richness (up to -75% relative to the current rainfall pattern in W-Europe) and functional diversity (enhanced dominance of grasses relative to nitrogen (N)-fixers and non-N-fixing forbs). Loss of N-fixers and non-N-fixing forbs in severe treatments was linked to lower baseline competitive success and higher physiological sensitivity to changes in soil moisture compared to grasses. The extent of diversity losses also strongly depended on the timing of the dry and wet periods. Regimes in which long droughts (≥20 days) coincided with above-average temperatures showed significantly more physiological plant stress over the experimental period, greater plant mortality, and impoverished communities by the end of the season. Across all regimes, the duration of the longest period below permanent wilting point was an accurate predictor of mortality across the communities, indicating that increasingly persistent precipitation regimes may reduce opportunities for drought stress alleviation. We conclude that without recruitment, which was precluded in this experiment, summer precipitation regimes with longer dry and wet spells will likely diminish plant diversity, at least in the short term.

Trait-based climate vulnerability assessments in data-rich systems: An application to eastern Bering Sea fish and invertebrate stocks

Trait-based climate vulnerability assessments based on expert evaluation have emerged as a rapid tool to assess biological vulnerability when detailed correlative or mechanistic studies are not feasible. Trait-based assessments typically view vulnerability as a combination of sensitivity and exposure to climate change. However, in some locations, a substantial amount of information may exist on system productivity and environmental conditions (both current and projected), with potential disparities in the information available for data-rich and data-poor stocks. Incorporating this level of detailed information poses challenges when conducting, and communicating uncertainty from, rapid vulnerability assessments. We applied a trait-based vulnerability assessment to 36 fish and invertebrate stocks in the eastern Bering Sea (EBS), a data-rich ecosystem. In recent years, the living marine resources of the EBS and Aleutian Islands have supported fisheries worth more than US $1 billion of annual ex-vessel value. Our vulnerability assessment uses projections (to 2039) from three downscaled climate models, and graphically characterizes the variation in climate projections between climate models and between seasons. Bootstrapping was used to characterize uncertainty in specific biological traits and environmental variables, and in the scores for sensitivity, exposure, and vulnerability. The sensitivity of EBS stocks to climate change ranged from "low" to "high," but vulnerability ranged between "low" and "moderate" due to limited exposure to climate change. Comparison with more detailed studies reveals that water temperature is an important variable for projecting climate impacts on stocks such as walleye pollock (Gadus chalcogrammus), and sensitivity analyses revealed that modifying the rule for determining vulnerability increased the vulnerability scores. This study demonstrates the importance of considering several uncertainties (e.g., climate projections, biological, and model structure) when conducting climate vulnerability assessments, and can be extended in future research to consider the vulnerability of user groups dependent on these stocks.

Identifying potential refugia and corridors under climate change: A case study of endangered Sichuan golden monkey (Rhinopithecus roxellana) in Qinling Mountains, China

Climate change threatens endangered species and challenges current conservation strategies. Effective conservation requires vulnerability assessments for species susceptible to climate change and adaptive strategies to mitigate threats associated with climate. In this paper, we used the Maxent to model the impacts of climate change on habitat suitability of Sichuan golden monkey Rhinopithecus roxellana. Our results showed that (i) suitable habitat for Sichuan golden monkey was predicted to decrease by 37% in 2050s under climate change; (ii) the mean elevations of suitable habitat in the 2050s was estimated to shift 160 m higher; (iii) nature reserves protect 62% of current suitable habitat and 56% of future suitable habitat; and (iv) 49% of current suitable habitat was predicted to be vulnerable to future climate change. Given these results, we proposed conservation implications to mitigate the impacts of climate change on Sichuan golden monkey, including adjusting range of national park, establishing habitat corridors, and conducting long‐term monitoring.

Habitat Climate Change Vulnerability Index Applied to Major Vegetation Types of the Western Interior United States

We applied a framework to assess climate change vulnerability of 52 major vegetation types in the Western United States to provide a spatially explicit input to adaptive management decisions. The framework addressed climate exposure and ecosystem resilience; the latter derived from analyses of ecosystem sensitivity and adaptive capacity. Measures of climate change exposure used observed climate change (1981–2014) and then climate projections for the mid-21st century (2040–2069 RCP 4.5). Measures of resilience included (under ecosystem sensitivity) landscape intactness, invasive species, fire regime alteration, and forest insect and disease risk, and (under adaptive capacity), measures for topo-climate variability, diversity within functional species groups, and vulnerability of any keystone species. Outputs are generated per 100 km2 hexagonal area for each type. As of 2014, moderate climate change vulnerability was indicated for >50% of the area of 50 of 52 types. By the mid-21st century, all but 19 types face high or very high vulnerability with >50% of the area scoring in these categories. Measures for resilience explain most components of vulnerability as of 2014, with most targeted vegetation scoring low in adaptive capacity measures and variably for specific sensitivity measures. Elevated climate exposure explains increases in vulnerability between the current and mid-century time periods.

Using climate envelope models to identify potential ecological trajectories on the Kenai Peninsula, Alaska

Managers need information about the vulnerability of historical plant communities, and their potential future conditions, to respond appropriately to landscape change driven by global climate change. We model the climate envelopes of plant communities on the Kenai Peninsula in Southcentral Alaska and forecast to 2020, 2050, and 2080. We assess 6 model outputs representing downscaled climate data from 3 global climate model outputs and 2 representative concentration pathways. We use two lines of evidence, model convergence and empirically measured rates of change, to identify the following plausible ecological trajectories for the peninsula: (1.) alpine tundra and sub-alpine shrub decrease, (2.) perennial snow and ice decrease, (3.) forests remain on the Kenai Lowlands, (4.) the contiguous white-Lutz-Sitka spruce complex declines, and (5.) mixed conifer afforestation occurs along the Gulf of Alaska coast. We suggest that converging models in the context of other lines of evidence is a viable approach to increase certainty for adaptation planning. Extremely dynamic areas with multiple outcomes (i.e., disagreement) among models represent ecological risk, but may also represent opportunities for facilitated adaptation and other managerial approaches to help tip the balance one way or another. By reducing uncertainty, this eclectic approach can be used to inform expectations about the future.

Managing for climate change on protected areas: An adaptive management decision making framework

Current protected area management is becoming more challenging with advancing climate change and current park management techniques may not be adequate to adapt for effective management into the future. The framework presented here provides an adaptive management decision making process to assist protected area managers with adapting on-park management to climate change. The framework sets out a 4 step process. One, a good understanding of the park's context within climate change. Secondly, a thorough understanding of the park management systems including governance, planning and management systems. Thirdly, a series of management options set out as an accept/prevent change style structure, including a systematic assessment of those options. The adaptive approaches are defined as acceptance of anthropogenic climate change impact and attempt to adapt to a new climatic environment or prevention of change and attempt to maintain current systems under new climatic variations. Last, implementation and monitoring of long term trends in response to ecological responses to management interventions and assessing management effectiveness. The framework addresses many issues currently with park management in dealing with climate change including the considerable amount of research focussing on 'off-reserve' strategies, and threats and stress focused in situ park management.

Influence of adaptive capacity on the outcome of climate change vulnerability assessment

Climate change vulnerability assessment (CCVA) has become a mainstay conservation decision support tool. CCVAs are recommended to incorporate three elements of vulnerability – exposure, sensitivity and adaptive capacity – yet, lack of data frequently leads to the latter being excluded. Further, weighted or unweighted scoring schemes, based on expert opinion, may be applied. Comparisons of these approaches are rare. In a CCVA for 17 Australian lizard species, we show that membership within three vulnerability categories (low, medium and high) generally remained similar regardless of the framework or scoring scheme. There was one exception however, where, under the warm/dry scenario for 2070, including adaptive capacity lead to five fewer species being classified as highly vulnerable. Two species, Eulamprus leuraensis and E. kosciuskoi, were consistently ranked the most vulnerable, primarily due to projected losses in climatically suitable habitat, narrow thermal tolerance and specialist habitat requirements. Our findings provide relevant information for prioritizing target species for conservation and choosing appropriate conservation actions. We conclude that for the species included in this study, the framework and scoring scheme used had little impact on the identification of the most vulnerable species. We caution, however, that this outcome may not apply to other taxa or regions.

Dispersal and extrapolation on the accuracy of temporal predictions from distribution models for the Darwin's frog

Climate change is a major threat to biodiversity; the development of models that reliably predict its effects on species distributions is a priority for conservation biogeography. Two of the main issues for accurate temporal predictions from Species Distribution Models (SDM) are model extrapolation and unrealistic dispersal scenarios. We assessed the consequences of these issues on the accuracy of climate-driven SDM predictions for the dispersal-limited Darwin's frog Rhinoderma darwinii in South America. We calibrated models using historical data (1950-1975) and projected them across 40 yr to predict distribution under current climatic conditions, assessing predictive accuracy through the area under the ROC curve (AUC) and True Skill Statistics (TSS), contrasting binary model predictions against temporal-independent validation data set (i.e., current presences/absences). To assess the effects of incorporating dispersal processes we compared the predictive accuracy of dispersal constrained models with no dispersal limited SDMs; and to assess the effects of model extrapolation on the predictive accuracy of SDMs, we compared this between extrapolated and no extrapolated areas. The incorporation of dispersal processes enhanced predictive accuracy, mainly due to a decrease in the false presence rate of model predictions, which is consistent with discrimination of suitable but inaccessible habitat. This also had consequences on range size changes over time, which is the most used proxy for extinction risk from climate change. The area of current climatic conditions that was absent in the baseline conditions (i.e., extrapolated areas) represents 39% of the study area, leading to a significant decrease in predictive accuracy of model predictions for those areas. Our results highlight (1) incorporating dispersal processes can improve predictive accuracy of temporal transference of SDMs and reduce uncertainties of extinction risk assessments from global change; (2) as geographical areas subjected to novel climates are expected to arise, they must be reported as they show less accurate predictions under future climate scenarios. Consequently, environmental extrapolation and dispersal processes should be explicitly incorporated to report and reduce uncertainties in temporal predictions of SDMs, respectively. Doing so, we expect to improve the reliability of the information we provide for conservation decision makers under future climate change scenarios.

Assessing vulnerability of giant pandas to climate change in the Qinling Mountains of China

Climate change might pose an additional threat to the already vulnerable giant panda (Ailuropoda melanoleuca). Effective conservation efforts require projections of vulnerability of the giant panda in facing climate change and proactive strategies to reduce emerging climate-related threats. We used the maximum entropy model to assess the vulnerability of giant panda to climate change in the Qinling Mountains of China. The results of modeling included the following findings: (1) the area of suitable habitat for giant pandas was projected to decrease by 281 km² from climate change by the 2050s; (2) the mean elevation of suitable habitat of giant panda was predicted to shift 30 m higher due to climate change over this period; (3) the network of nature reserves protect 61.73% of current suitable habitat for the species, and 59.23% of future suitable habitat; (4) current suitable habitat mainly located in Chenggu, Taibai, and Yangxian counties (with a total area of 987 km²) was predicted to be vulnerable. Assessing the vulnerability of giant panda provided adaptive strategies for conservation programs and national park construction. We proposed adaptation strategies to ameliorate the predicted impacts of climate change on giant panda, including establishing and adjusting reserves, establishing habitat corridors, improving adaptive capacity to climate change, and strengthening monitoring of giant panda.

Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates

How climate constrains species' distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8-19% less habitat loss in response to annual temperature increases of ~3-5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate-imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans.

Binational climate change vulnerability assessment of migratory birds in the Great Lakes Basins: Tools and impediments

Climate change is a global concern, requiring international strategies to reduce emissions, however, climate change vulnerability assessments are often local in scope with assessment areas restricted to jurisdictional boundaries. In our study we explored tools and impediments to understanding and responding to the effects of climate change on vulnerability of migratory birds from a binational perspective. We apply and assess the utility of a Climate Change Vulnerability Index on 3 focal species using distribution or niche modeling frameworks. We use the distributional forecasts to explore possible changes to jurisdictional conservation responsibilities resulting from shifting distributions for: eastern meadowlark (Sturnella magna), wood thrush (Hylocichla mustelina), and hooded warbler (Setophaga citrina). We found the Climate Change Vulnerability Index to be a well-organized approach to integrating numerous lines of evidence concerning effects of climate change, and provided transparency to the final assessment of vulnerability. Under this framework, we identified that eastern meadowlark and wood thrush are highly vulnerable to climate change, but hooded warbler is less vulnerable. Our study revealed impediments to assessing and modeling vulnerability to climate change from a binational perspective, including gaps in data or modeling for climate exposure parameters. We recommend increased cross-border collaboration to enhance the availability and resources needed to improve vulnerability assessments and development of conservation strategies. We did not find evidence to suggest major shifts in jurisdictional responsibility for the 3 focal species, but results do indicate increasing responsibility for these birds in the Canadian Provinces. These Provinces should consider conservation planning to help ensure a future supply of necessary habitat for these species.

Impacts of Climate Change on the Global Invasion Potential of the African Clawed Frog Xenopus laevis

By altering or eliminating delicate ecological relationships, non-indigenous species are considered a major threat to biodiversity, as well as a driver of environmental change. Global climate change affects ecosystems and ecological communities, leading to changes in the phenology, geographic ranges, or population abundance of several species. Thus, predicting the impacts of global climate change on the current and future distribution of invasive species is an important subject in macroecological studies. The African clawed frog (Xenopus laevis), native to South Africa, possesses a strong invasion potential and populations have become established in numerous countries across four continents. The global invasion potential of X. laevis was assessed using correlative species distribution models (SDMs). SDMs were computed based on a comprehensive set of occurrence records covering South Africa, North America, South America and Europe and a set of nine environmental predictors. Models were built using both a maximum entropy model and an ensemble approach integrating eight algorithms. The future occurrence probabilities for X. laevis were subsequently computed using bioclimatic variables for 2070 following four different IPCC scenarios. Despite minor differences between the statistical approaches, both SDMs predict the future potential distribution of X. laevis, on a global scale, to decrease across all climate change scenarios. On a continental scale, both SDMs predict decreasing potential distributions in the species' native range in South Africa, as well as in the invaded areas in North and South America, and in Australia where the species has not been introduced. In contrast, both SDMs predict the potential range size to expand in Europe. Our results suggest that all probability classes will be equally affected by climate change. New regional conditions may promote new invasions or the spread of established invasive populations, especially in France and Great Britain.

Contemporary Drought and Future Effects of Climate Change on the Endangered Blunt-Nosed Leopard Lizard, Gambelia sila

Extreme weather events can provide unique opportunities for testing models that predict the effect of climate change. Droughts of increasing severity have been predicted under numerous models, thus contemporary droughts may allow us to test these models prior to the onset of the more extreme effects predicted with a changing climate. In the third year of an ongoing severe drought, surveys failed to detect neonate endangered blunt-nosed leopard lizards in a subset of previously surveyed populations where we expected to see them. By conducting surveys at a large number of sites across the range of the species over a short time span, we were able to establish a strong positive correlation between winter precipitation and the presence of neonate leopard lizards over geographic space. Our results are consistent with those of numerous longitudinal studies and are in accordance with predictive climate change models. We suggest that scientists can take immediate advantage of droughts while they are still in progress to test patterns of occurrence in other drought-sensitive species and thus provide for more robust models of climate change effects on biodiversity.

Use of the NatureServe Climate Change Vulnerability Index as an Assessment Tool for Reptiles and Amphibians: Lessons Learned

Climate change threatens biodiversity globally, yet it can be challenging to predict which species may be most vulnerable. Given the scope of the problem, it is imperative to rapidly assess vulnerability and identify actions to decrease risk. Although a variety of tools have been developed to assess climate change vulnerability, few have been evaluated with regard to their suitability for certain taxonomic groups. Due to their ectothermic physiology, low vagility, and strong association with temporary wetlands, reptiles and amphibians may be particularly vulnerable relative to other groups. Here, we evaluate use of the NatureServe Climate Change Vulnerability Index (CCVI) to assess a large suite of herpetofauna from the Sand Hills Ecoregion of the southeastern United States. Although data were frequently lacking for certain variables (e.g., phenological response to climate change, genetic variation), sufficient data were available to evaluate all 117 species. Sensitivity analyses indicated that results were highly dependent on size of assessment area and climate scenario selection. In addition, several ecological traits common in, but relatively unique to, herpetofauna are likely to contribute to their vulnerability and need special consideration during the scoring process. Despite some limitations, the NatureServe CCVI was a useful tool for screening large numbers of reptile and amphibian species. We provide general recommendations as to how the CCVI tool's application to herpetofauna can be improved through more specific guidance to the user regarding how to incorporate unique physiological and behavioral traits into scoring existing sensitivity factors and through modification to the assessment tool itself.

Conservation Status of North American Birds in the Face of Future Climate Change

Human-induced climate change is increasingly recognized as a fundamental driver of biological processes and patterns. Historic climate change is known to have caused shifts in the geographic ranges of many taxa and future climate change is expected to result in even greater redistributions of species. As a result, predicting the impact of climate change on future patterns of biodiversity will greatly aid conservation planning. Using the North American Breeding Bird Survey and Audubon Christmas Bird Count, two of the most comprehensive continental datasets of vertebrates in the world, and correlative distribution modeling, we assessed geographic range shifts for 588 North American bird species during both the breeding and non-breeding seasons under a range of future emission scenarios (SRES A2, A1B, B2) through the end of the century. Here we show that 314 species (53%) are projected to lose more than half of their current geographic range across three scenarios of climate change through the end of the century. For 126 species, loss occurs without concomitant range expansion; whereas for 188 species, loss is coupled with potential to colonize new replacement range. We found no strong associations between projected climate sensitivities and existing conservation prioritizations. Moreover, species responses were not clearly associated with habitat affinities, migration strategies, or climate change scenarios. Our results demonstrate the need to include climate sensitivity into current conservation planning and to develop adaptive management strategies that accommodate shrinking and shifting geographic ranges. The persistence of many North American birds will depend on their ability to colonize climatically suitable areas outside of current ranges and management actions that target climate adaptation.

Water temperature and fish growth: otoliths predict growth patterns of a marine fish in a changing climate

Ecological modeling shows that even small, gradual changes in body size in a fish population can have large effects on natural mortality, biomass, and catch. However, efforts to model the impact of climate change on fish growth have been hampered by a lack of long-term (multidecadal) data needed to understand the effects of temperature on growth rates in natural environments. We used a combination of dendrochronology techniques and additive mixed-effects modeling to examine the sensitivity of growth in a long-lived (up to 70 years), endemic marine fish, the western blue groper (Achoerodus gouldii), to changes in water temperature. A multi-decadal biochronology (1952-2003) of growth was constructed from the otoliths of 56 fish collected off the southwestern coast of Western Australia, and we tested for correlations between the mean index chronology and a range of potential environmental drivers. The chronology was significantly correlated with sea surface temperature in the region, but common variance among individuals was low. This suggests that this species has been relatively insensitive to past variations in climate. Growth increment and age data were also used in an additive mixed model to predict otolith growth and body size later this century. Although growth was relatively insensitive to changes in temperature, the model results suggested that a fish aged 20 in 2099 would have an otolith about 10% larger and a body size about 5% larger than a fish aged 20 in 1977. Our study shows that species or populations regarded as relatively insensitive to climate change could still undergo significant changes in growth rate and body size that are likely to have important effects on the productivity and yield of fisheries.

Assessing Effects of Variation in Global Climate Data Sets on Spatial Predictions from Climate Envelope Models

Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.

The value of a multi-faceted climate change vulnerability assessment to managing protected lands: lessons from a case study in Point Reyes National Seashore

Managing protected areas in the face of an uncertain future climate poses serious challenges. There are currently a variety of predictive and analytical methods for assessing future climates and biological responses to the changes, but an assessment produced by any one of these methods is necessarily limited in scope. When making management decisions, therefore, it is beneficial to have information from a variety of sources and analytical methods, and to compare the agreements and discrepancies among them. Based on existing climate change vulnerability assessment frameworks in the literature, we developed a multi-faceted climate change vulnerability assessment at the biological community level comprised of: a) expert judgment, b) predictive vegetation mapping, c) predictive geophysical mapping, and d) species-specific evaluations. We wrote a climate change vulnerability assessment for Point Reyes National Seashore and evaluated the usefulness of each facet, alone and in concert. We found that the facets were complementary and that each one was useful to inform some management goals; we also found that expert judgment was the most widely applicable and flexible assessment method. We believe that this multi-faceted framework can be employed in other protected areas to facilitate management decisions under a changing and uncertain future climate.

Assessing insect responses to climate change: What are we testing for? Where should we be heading?

To understand how researchers are tackling globally important issues, it is crucial to identify whether current research is comprehensive enough to make substantive predictions about general responses. We examined how research on climate change affecting insects is being assessed, what factors are being tested and the localities of studies, from 1703 papers published between 1985 and August 2012. Most published research (64%) is generated from Europe and North America and being dedicated to core data analysis, with 29% of the studies analysed dedicated to Lepidoptera and 22% Diptera: which are well above their contribution to the currently identified insect species richness (estimated at 13% and 17% respectively). Research publications on Coleoptera fall well short of their proportional contribution (19% of publications but 39% of insect species identified), and to a lesser extent so do Hemiptera, and Hymenoptera. Species specific responses to changes in temperature by assessing distribution/range shifts or changes in abundance were the most commonly used methods of assessing the impact of climate change on insects. Research on insects and climate change to date is dominated by manuscripts assessing butterflies in Europe, insects of economic and/or environmental concern in forestry, agriculture, and model organisms. The research on understanding how insects will respond to a rapidly changing climate is still in its infancy, but the current trends of publications give a good basis for how we are attempting to assess insect responses. In particular, there is a crucial need for broader studies of ecological, behavioural, physiological and life history responses to be addressed across a greater range of geographic locations, particularly Asia, Africa and Australasia, and in areas of high human population growth and habitat modification. It is still too early in our understanding of taxa responses to climate change to know if charismatic taxa, such as butterflies, or disease vectors, including Diptera, can be used as keystone taxa to generalise other insect responses to climate change. This is critical as the basic biology of most species is still poorly known, and dominant, well studied taxa may show variable responses to climate change across their distribution due to regional biotic and abiotic influences. Indeed identifying if insect responses to climate change can be generalised using phylogeny, functional traits, or functional groups, or will populations and species exhibit idiosyncratic responses, should be a key priority for future research.

A risk-based approach to evaluating wildlife demographics for management in a changing climate: a case study of the Lewis's Woodpecker

Given the projected threat that climate change poses to biodiversity, the need for proactive response efforts is clear. However, integrating uncertain climate change information into conservation planning is challenging, and more explicit guidance is needed. To this end, this article provides a specific example of how a risk-based approach can be used to incorporate a species' response to climate into conservation decisions. This is shown by taking advantage of species' response (i.e., impact) models that have been developed for a well-studied bird species of conservation concern. Specifically, we examine the current and potential impact of climate on nest survival of the Lewis's Woodpecker (Melanerpes lewis) in two different habitats. To address climate uncertainty, climate scenarios are developed by manipulating historical weather observations to create ensembles (i.e., multiple sequences of daily weather) that reflect historical variability and potential climate change. These ensembles allow for a probabilistic evaluation of the risk posed to Lewis's Woodpecker nest survival and are used in two demographic analyses. First, the relative value of each habitat is compared in terms of nest survival, and second, the likelihood of exceeding a critical population threshold is examined. By embedding the analyses in a risk framework, we show how management choices can be made to be commensurate with a defined level of acceptable risk. The results can be used to inform habitat prioritization and are discussed in the context of an economic framework for evaluating trade-offs between management alternatives.

The Adaptation for Conservation Targets (ACT) framework: a tool for incorporating climate change into natural resource management

As natural resource management agencies and conservation organizations seek guidance on responding to climate change, myriad potential actions and strategies have been proposed for increasing the long-term viability of some attributes of natural systems. Managers need practical tools for selecting among these actions and strategies to develop a tailored management approach for specific targets at a given location. We developed and present one such tool, the participatory Adaptation for Conservation Targets (ACT) framework, which considers the effects of climate change in the development of management actions for particular species, ecosystems and ecological functions. Our framework is based on the premise that effective adaptation of management to climate change can rely on local knowledge of an ecosystem and does not necessarily require detailed projections of climate change or its effects. We illustrate the ACT framework by applying it to an ecological function in the Greater Yellowstone Ecosystem (Montana, Wyoming, and Idaho, USA)--water flows in the upper Yellowstone River. We suggest that the ACT framework is a practical tool for initiating adaptation planning, and for generating and communicating specific management interventions given an increasingly altered, yet uncertain, climate.

Integrating mechanistic organism–environment interactions into the basic theory of community and evolutionary ecology

This paper presents an overview of how mechanistic knowledge of organism–environment interactions, including biomechanical interactions of heat, mass and momentum transfer, can be integrated into basic theoretical population biology through mechanistic functional responses that quantitatively describe how organisms respond to their physical environment. Integrating such functional responses into simple community and microevolutionary models allows scaling up of the organism-level understanding from biomechanics both ecologically and temporally. For community models, Holling-type functional responses for predator–prey interactions provide a classic example of the functional response affecting qualitative model dynamics, and recent efforts are expanding analogous models to incorporate environmental influences such as temperature. For evolutionary models, mechanistic functional responses dependent on the environment can serve as fitness functions in both quantitative genetic and game theoretic frameworks, especially those concerning function-valued traits. I present a novel comparison of a mechanistic fitness function based on thermal performance curves to a commonly used generic fitness function, which quantitatively differ in their predictions for response to environmental change. A variety of examples illustrate how mechanistic functional responses enhance model connections to biologically relevant traits and processes as well as environmental conditions and therefore have the potential to link theoretical and empirical studies. Sensitivity analysis of such models can provide biologically relevant insight into which parameters and processes are important to community and evolutionary responses to environmental change such as climate change, which can inform conservation management aimed at protecting response capacity. Overall, the distillation of detailed knowledge or organism–environment interactions into mechanistic functional responses in simple population biology models provides a framework for integrating biomechanics and ecology that allows both tractability and generality.

A climate change vulnerability assessment of California's at-risk birds

Conservationists must develop new strategies and adapt existing tools to address the consequences of anthropogenic climate change. To support statewide climate change adaptation, we developed a framework for assessing climate change vulnerability of California's at-risk birds and integrating it into the existing California Bird Species of Special Concern list. We defined climate vulnerability as the amount of evidence that climate change will negatively impact a population. We quantified climate vulnerability by scoring sensitivity (intrinsic characteristics of an organism that make it vulnerable) and exposure (the magnitude of climate change expected) for each taxon. Using the combined sensitivity and exposure scores as an index, we ranked 358 avian taxa, and classified 128 as vulnerable to climate change. Birds associated with wetlands had the largest representation on the list relative to other habitat groups. Of the 29 state or federally listed taxa, 21 were also classified as climate vulnerable, further raising their conservation concern. Integrating climate vulnerability and California's Bird Species of Special Concern list resulted in the addition of five taxa and an increase in priority rank for ten. Our process illustrates a simple, immediate action that can be taken to inform climate change adaptation strategies for wildlife.