Nonlinearity in interspecific interactions in response to climate change: Cod and haddock as an example

Climate change has profound ecological effects, yet our understanding of how trophic interactions among species are affected by climate change is still patchy. The sympatric Atlantic haddock and cod are co‐occurring across the North Atlantic. They compete for food at younger stages and thereafter the former is preyed by the latter. Climate change might affect the interaction and coexistence of these two species. Particularly, the increase in sea temperature (ST) has been shown to affect distribution, population growth and trophic interactions in marine systems. We used 33‐year long time series of haddock and cod abundances estimates from two data sources (acoustic and trawl survey) to analyse the dynamic effect of climate on the coexistence of these two sympatric species in the Arcto‐Boreal Barents Sea. Using a Bayesian state‐space threshold model, we demonstrated that long‐term climate variation, as expressed by changes of ST, affected species demography through different influences on density‐independent processes. The interaction between cod and haddock has shifted in the last two decades due to an increase in ST, altering the equilibrium abundances and the dynamics of the system. During warm years (ST over ca. 4°C), the increase in the cod abundance negatively affected haddock abundance while it did not during cold years. This change in interactions therefore changed the equilibrium population size with a higher population size during warm years. Our analyses show that long‐term climate change in the Arcto‐Boreal system can generate differences in the equilibrium conditions of species assemblages.     

Modelled spatial distribution of marine fish and projected modifications in the North Atlantic Ocean

The objectives of this work were to examine the past, current and potential influence of global climate change on the spatial distribution of some commercially exploited fish and to evaluate a recently proposed new ecological niche model (ENM) called nonparametric probabilistic ecological niche model (NPPEN). This new technique is based on a modified version of the test called Multiple Response Permutation Procedure (MRPP) using the generalized Mahalanobis distance. The technique was applied in the extratropical regions of the North Atlantic Ocean on eight commercially exploited fish species using three environmental parameters (sea surface temperature, bathymetry and sea surface salinity). The numerical procedure and the model allowed a better characterization of the niche (sensu Hutchinson) and an improved modelling of the spatial distribution of the species. Furthermore, the technique appeared to be robust to incomplete or bimodal training sets. Despite some potential limitations related to the choice of the climatic scenarios (A2 and B2), the type of physical model (ECHAM 4) and the absence of consideration of biotic interactions, modelled changes in species distribution explained some current observed shifts in dominance that occurred in the North Atlantic sector, and particularly in the North Sea. Although projected changes suggest a poleward movement of species, our results indicate that some species may not be able to track their climatic envelope and that climate change may have a prominent influence on fish distribution during this century. The phenomenon is likely to trigger locally major changes in the dominance of species with likely implications for socio‐economical systems. In this way, ENMs might provide a new management tool against which changes in the resource might be better anticipated.     

Can we project changes in fish abundance and distribution in response to climate?

Large‐scale and long‐term changes in fish abundance and distribution in response to climate change have been simulated using both statistical and process‐based models. However, national and regional fisheries management requires also shorter term projections on smaller spatial scales, and these need to be validated against fisheries data. A 26‐year time series of fish surveys with high spatial resolution in the North‐East Atlantic provides a unique opportunity to assess the ability of models to correctly simulate the changes in fish distribution and abundance that occurred in response to climate variability and change. We use a dynamic bioclimate envelope model forced by physical–biogeochemical output from eight ocean models to simulate changes in fish abundance and distribution at scales down to a spatial resolution of 0.5°. When comparing with these simulations with annual fish survey data, we found the largest differences at the 0.5° scale. Differences between fishery model runs driven by different biogeochemical models decrease dramatically when results are aggregated to larger scales (e.g. the whole North Sea), to total catches rather than individual species or when the ensemble mean instead of individual simulations are used. Recent improvements in the fidelity of biogeochemical models translate into lower error rates in the fisheries simulations. However, predictions based on different biogeochemical models are often more similar to each other than they are to the survey data, except for some pelagic species. We conclude that model results can be used to guide fisheries management at larger spatial scales, but more caution is needed at smaller scales.     

Biomass changes and trophic amplification of plankton in a warmer ocean

Ocean warming can modify the ecophysiology and distribution of marine organisms, and relationships between species, with nonlinear interactions between ecosystem components potentially resulting in trophic amplification. Trophic amplification (or attenuation) describe the propagation of a hydroclimatic signal up the food web, causing magnification (or depression) of biomass values along one or more trophic pathways. We have employed 3‐D coupled physical‐biogeochemical models to explore ecosystem responses to climate change with a focus on trophic amplification. The response of phytoplankton and zooplankton to global climate‐change projections, carried out with the IPSL Earth System Model by the end of the century, is analysed at global and regional basis, including European seas (NE Atlantic, Barents Sea, Baltic Sea, Black Sea, Bay of Biscay, Adriatic Sea, Aegean Sea) and the Eastern Boundary Upwelling System (Benguela). Results indicate that globally and in Atlantic Margin and North Sea, increased ocean stratification causes primary production and zooplankton biomass to decrease in response to a warming climate, whilst in the Barents, Baltic and Black Seas, primary production and zooplankton biomass increase. Projected warming characterized by an increase in sea surface temperature of 2.29 ± 0.05 °C leads to a reduction in zooplankton and phytoplankton biomasses of 11% and 6%, respectively. This suggests negative amplification of climate driven modifications of trophic level biomass through bottom‐up control, leading to a reduced capacity of oceans to regulate climate through the biological carbon pump. Simulations suggest negative amplification is the dominant response across 47% of the ocean surface and prevails in the tropical oceans; whilst positive trophic amplification prevails in the Arctic and Antarctic oceans. Trophic attenuation is projected in temperate seas. Uncertainties in ocean plankton projections, associated to the use of single global and regional models, imply the need for caution when extending these considerations into higher trophic levels.     

Predicting future coexistence in a North American ant community

Global climate change will remodel ecological communities worldwide. However, as a consequence of biotic interactions, communities may respond to climate change in idiosyncratic ways. This makes predictive models that incorporate biotic interactions necessary. We show how such models can be constructed based on empirical studies in combination with predictions or assumptions regarding the abiotic consequences of climate change. Specifically, we consider a well‐studied ant community in North America. First, we use historical data to parameterize a basic model for species coexistence. Using this model, we determine the importance of various factors, including thermal niches, food discovery rates, and food removal rates, to historical species coexistence. We then extend the model to predict how the community will restructure in response to several climate‐related changes, such as increased temperature, shifts in species phenology, and altered resource availability. Interestingly, our mechanistic model suggests that increased temperature and shifts in species phenology can have contrasting effects. Nevertheless, for almost all scenarios considered, we find that the most subordinate ant species suffers most as a result of climate change. More generally, our analysis shows that community composition can respond to climate warming in nonintuitive ways. For example, in the context of a community, it is not necessarily the most heat‐sensitive species that are most at risk. Our results demonstrate how models that account for niche partitioning and interspecific trade‐offs among species can be used to predict the likely idiosyncratic responses of local communities to climate change.     

Future climate‐driven shifts in distribution of Calanus finmarchicus

Calanus finmarchicus is a key‐structural species of the North Atlantic polar biome. The species plays an important trophic role in subpolar and polar ecosystems as a grazer of phytoplankton and as a prey for higher trophic levels such as the larval stages of many fish species. Here, we used a recently developed ecological niche model to assess the ecological niche (sensu Hutchinson) of C. finmarchicus and characterize its spatial distribution. This model explained about 65% of the total variance of the observed spatial distribution inferred from an independent dataset (data of the continuous plankton recorder survey). Comparisons with other types of models (structured population and ecophysiological models) revealed a clear similarity between modeled spatial distributions at the scale of the North Atlantic. Contemporary models coupled with future projections indicated a progressive reduction of the spatial habitat of the species at the southern edge and a more pronounced one in the Georges Bank, the Scotian Shelf and the North Sea and a potential increase in abundance at the northern edge of its spatial distribution, especially in the Barents Sea. These major changes will probably lead to a major alteration of the trophodynamics of North Atlantic ecosystems affecting the trophodynamics and the biological carbon pump.     

Biotic interactions influence the projected distribution of a specialist mammal under climate change

Aim

To measure the effects of including biotic interactions on climate‐based species distribution models (SDMs) used to predict distribution shifts under climate change. We evaluated the performance of distribution models for an endangered marsupial, the northern bettong (Bettongia tropica), comparing models that used only climate variables with models that also took into account biotic interactions.

Location

North‐east Queensland, Australia.

Methods

We developed separate climate‐based distribution models for the northern bettong, its two main resources and a competitor species. We then constructed models for the northern bettong by including climate suitability estimates for the resources and competitor as additional predictor variables to make climate + resource and climate + resource + competition models. We projected these models onto seven future climate scenarios and compared predictions of northern bettong distribution made by these differently structured models, using a ‘global’ metric, the I similarity statistic, to measure overlap in distribution and a ‘local’ metric to identify where predictions differed significantly.

Results

Inclusion of food resource biotic interactions improved model performance. Over moderate climate changes, up to 3.0 °C of warming, the climate‐only model for the northern bettong gave similar predictions of distribution to the more complex models including interactions, with differences only at the margins of predicted distributions. For climate changes beyond 3.0 °C, model predictions diverged significantly. The interactive model predicted less contraction of distribution than the simpler climate‐only model.

Main conclusions

Distribution models that account for interactions with other species, in particular direct resources, improve model predictions in the present‐day climate. For larger climate changes, shifts in distribution of interacting species cause predictions of interactive models to diverge from climate‐only models. Incorporating interactions with other species in SDMs may be needed for long‐term prediction of changes in distribution of species under climate change, particularly for specialized species strongly dependent on a small number of biotic interactions.     

Idiosyncratic species effects confound size-based predictions of responses to climate change

Understanding and predicting the consequences of warming for complex ecosystems and indeed individual species remains a major ecological challenge. Here, we investigated the effect of increased seawater temperatures on the metabolic and consumption rates of five distinct marine species. The experimental species reflected different trophic positions within a typical benthic East Atlantic food web, and included a herbivorous gastropod, a scavenging decapod, a predatory echinoderm, a decapod and a benthic-feeding fish. We examined the metabolism–body mass and consumption–body mass scaling for each species, and assessed changes in their consumption efficiencies. Our results indicate that body mass and temperature effects on metabolism were inconsistent across species and that some species were unable to meet metabolic demand at higher temperatures, thus highlighting the vulnerability of individual species to warming. While body size explains a large proportion of the variation in species'' physiological responses to warming, it is clear that idiosyncratic species responses, irrespective of body size, complicate predictions of population and ecosystem level response to future scenarios of climate change.     

From projected species distribution to food‐web structure under climate change

Climate change is inducing deep modifications in species geographic ranges worldwide. However, the consequences of such changes on community structure are still poorly understood, particularly the impacts on food‐web properties. Here, we propose a new framework, coupling species distribution and trophic models, to predict climate change impacts on food‐web structure across the Mediterranean Sea. Sea surface temperature was used to determine the fish climate niches and their future distributions. Body size was used to infer trophic interactions between fish species. Our projections reveal that 54 fish species of 256 endemic and native species included in our analysis would disappear by 2080–2099 from the Mediterranean continental shelf. The number of feeding links between fish species would decrease on 73.4% of the continental shelf. However, the connectance of the overall fish web would increase on average, from 0.26 to 0.29, mainly due to a differential loss rate of feeding links and species richness. This result masks a systematic decrease in predator generality, estimated here as the number of prey species, from 30.0 to 25.4. Therefore, our study highlights large‐scale impacts of climate change on marine food‐web structure with potential deep consequences on ecosystem functioning. However, these impacts will likely be highly heterogeneous in space, challenging our current understanding of climate change impact on local marine ecosystems.     

Analysis of phenotypic change in relation to climatic drivers in a population of Soay sheep Ovis aries

Climatic change has frequently been identified as a key driver of change in biological communities. These changes can take the form of alterations to population dynamics, phenotypic characters, genetics and the life history of organisms and can have impacts on entire ecosystems. This study presents a novel investigation of how changes in a large scale climatic index, the North Atlantic Oscillation (NAO) can influence population dynamics and phenotypic characters in a population of ungulates. We use an integral projection model combined with actual climate change predictions to project future body size distributions for a population of Soay sheep Ovis aries. The climate change predictions used to direct our model projections were taken from published results of climate models, covering a range of different emissions scenarios. Our model results showed that for positive changes in the mean NAO large population declines occurred simultaneously with increases in mean body weight. The exact direction and magnitude of changes to population dynamics and character distributions were dependent on the greenhouse gas emissions scenario and model used to predict the NAO. This study has demonstrated how integral projection models can use outputs of climate models to direct projections of population dynamics and phenotypic character distributions. This approach allows the results of this study to be placed within current climate change research. The nature of integral projection models means that this methodology can be easily applied to other populations. The model can also be easily updated when new climate change predictions become available, making it a useful tool for understanding potential population level responses to climatic change. Synthesis Understanding how changes in climate affect biological communities is a key component in predicting the future form of populations. Utilising a novel approach that incorporates climatic drivers (in this instance the winter North Atlantic Oscillation) into an integral projection model framework, we predict future Soay sheep dynamics under specific climate change scenarios. Tracking quantitative trait distributions and life history metrics, our results predict declining population size and increasing body weight for an increasingly positive winter North Atlantic Oscillation index, as predicted by climate models. This has important implications for future wildlife management strategies and linking demographic responses to climate change.     

Warming shelf seas drive the subtropicalization of European pelagic fish communities

Pelagic fishes are among the most ecologically and economically important fish species in European seas. In principle, these pelagic fishes have potential to demonstrate rapid abundance and distribution shifts in response to climatic variability due to their high adult motility, planktonic larval stages, and low dependence on benthic habitat for food or shelter during their life histories. Here, we provide evidence of substantial climate‐driven changes to the structure of pelagic fish communities in European shelf seas. We investigated the patterns of species‐level change using catch records from 57 870 fisheries‐independent survey trawls from across European continental shelf region between 1965 and 2012. We analysed changes in the distribution and rate of occurrence of the six most common species, and observed a strong subtropicalization of the North Sea and Baltic Sea assemblages. These areas have shifted away from cold‐water assemblages typically characterized by Atlantic herring and European sprat from the 1960s to 1980s, to warmer‐water assemblages including Atlantic mackerel, Atlantic horse mackerel, European pilchard and European anchovy from the 1990s onwards. We next investigated if warming sea temperatures have forced these changes using temporally comprehensive data from the North Sea region. Our models indicated the primary driver of change in these species has been sea surface temperatures in all cases. Together, these analyses highlight how individual species responses have combined to result in a dramatic subtropicalization of the pelagic fish assemblage of the European continental shelf.     

How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability

Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America. We then use relationships between model performance and climate novelty derived from the fossil pollen record from eastern North America to estimate the expected decrease in predictive skill of ecological forecasting models as future climate novelty increases. We show that, in the high emissions scenario (RCP 8.5) and by late 21st century, future climate novelty is similar to or higher than peak levels of climate novelty over the last 21,000 years. The accuracy of ecological forecasting models is projected to decline steadily over the coming decades in response to increasing climate novelty, although models that incorporate co‐occurrences among species may retain somewhat higher predictive skill. In addition to quantifying future climate novelty in the context of late Quaternary climate change, this work underscores the challenges of making reliable forecasts to an increasingly novel future, while highlighting the need to assess potential avenues for improvement, such as increased reliance on geological analogs for future novel climates and improving existing models by pooling data through time and incorporating assemblage‐level information.     

Climate change and commercial fishing practices codetermine survival of a long-lived seabird

Understanding the environmental mechanisms that govern population change is a fundamental objective in ecology. Although the determination of how top-down and bottom-up drivers affect demography is important, it is often equally critical to understand the extent to which, environmental conditions that underpin these drivers fluctuate across time. For example, associations between climate and both food availability and predation risk may suggest the presence of trophic interactions that may influence inferences made from patterns in ecological data. Analytical tools have been developed to account for these correlations, while providing opportunities to ask novel questions regarding how populations change across space and time. Here, we combine two modeling disciplines—path analysis and mark-recapture-recovery models—to explore whether shifts in sea-surface temperatures (SSTs) influenced top-down (entanglement in fishing equipment) or bottom-up (forage fish production) population constraints over 60 years, and the extent to which these covarying processes shaped the survival of a long-lived seabird, the Royal tern. We found that hemispheric trends in SST were associated with variation in the amount of fish harvested along the Atlantic coast of North America and in the Caribbean, whereas reductions in forage fish production were mostly driven by shifts in the amount of fish harvested by commercial fisheries throughout the North Atlantic the year prior. Although the indirect (i.e., stock depletion) and direct (i.e., entanglement) impacts of commercial fishing on Royal tern mortality has declined over the last 60 years, increased SSTs during this time period has resulted in a comparable increase in mortality risk, which disproportionately impacted the survival of the youngest age-classes of Royal terns. Given climate projections for the North Atlantic, our results indicate that threats to Royal tern population persistence in the Mid-Atlantic will most likely be driven by failures to recruit juveniles into the breeding population.     

Climate variability and the timing of spring raptor migration in eastern North America

Many birds have advanced their spring migration and breeding phenology in response to climate change, yet some long‐distance migrants appear constrained in their adjustments. In addition, bird species with long generation times and those in higher trophic positions may also be less able to track climate‐induced shifts in food availability. Migratory birds of prey may therefore be particularly vulnerable to climate change because: 1) most are long‐lived and have relatively low reproductive capacity, 2) many feed predominately on insectivorous passerines, and 3) several undertake annual migrations totaling tens of thousands of kilometers. Using multi‐decadal datasets for 14 raptor species observed at six sites across the Great Lakes region of North America, we detected phenological shifts in spring migration consistent with decadal climatic oscillations and global climate change. While the North Atlantic and El Niño Southern Oscillations exerted heterogeneous effects on the phenology of a few species, arrival dates more generally advanced by 1.18 d per decade, a pattern consistent with the effects of global climate change. After accounting for heterogeneity across observation sites, five of the 10 most abundant species advanced the bulk of their spring migration phenology. Contrary to expectations, we found that long‐distance migrants and birds with longer generation times tended to make the greatest advancements to their spring migration. Such results may indicate that phenotypic plasticity can facilitate climatic responses among these long‐lived predators.     

Conceptualizing ecosystem tipping points within a physiological framework

Connecting the nonlinear and often counterintuitive physiological effects of multiple environmental drivers to the emergent impacts on ecosystems is a fundamental challenge. Unfortunately, the disconnect between the way “stressors” (e.g., warming) is considered in organismal (physiological) and ecological (community) contexts continues to hamper progress. Environmental drivers typically elicit biphasic physiological responses, where performance declines at levels above and below some optimum. It is also well understood that species exhibit highly variable response surfaces to these changes so that the optimum level of any environmental driver can vary among interacting species. Thus, species interactions are unlikely to go unaltered under environmental change. However, while these nonlinear, species‐specific physiological relationships between environment and performance appear to be general, rarely are they incorporated into predictions of ecological tipping points. Instead, most ecosystem‐level studies focus on varying levels of “stress” and frequently assume that any deviation from “normal” environmental conditions has similar effects, albeit with different magnitudes, on all of the species within a community. We consider a framework that realigns the positive and negative physiological effects of changes in climatic and nonclimatic drivers with indirect ecological responses. Using a series of simple models based on direct physiological responses to temperature and ocean pCO₂, we explore how variation in environment‐performance relationships among primary producers and consumers translates into community‐level effects via trophic interactions. These models show that even in the absence of direct mortality, mismatched responses resulting from often subtle changes in the physical environment can lead to substantial ecosystem‐level change.     

Uncertainty in predictions of range dynamics: black grouse climbing the Swiss Alps

Empirical species distribution models (SDMs) constitute often the tool of choice for the assessment of rapid climate change effects on species’ vulnerability. Conclusions regarding extinction risks might be misleading, however, because SDMs do not explicitly incorporate dispersal or other demographic processes. Here, we supplement SDMs with a dynamic population model 1) to predict climate‐induced range dynamics for black grouse in Switzerland, 2) to compare direct and indirect measures of extinction risks, and 3) to quantify uncertainty in predictions as well as the sources of that uncertainty. To this end, we linked models of habitat suitability to a spatially explicit, individual‐based model. In an extensive sensitivity analysis, we quantified uncertainty in various model outputs introduced by different SDM algorithms, by different climate scenarios and by demographic model parameters. Potentially suitable habitats were predicted to shift uphill and eastwards. By the end of the 21st century, abrupt habitat losses were predicted in the western Prealps for some climate scenarios. In contrast, population size and occupied area were primarily controlled by currently negative population growth and gradually declined from the beginning of the century across all climate scenarios and SDM algorithms. However, predictions of population dynamic features were highly variable across simulations. Results indicate that inferring extinction probabilities simply from the quantity of suitable habitat may underestimate extinction risks because this may ignore important interactions between life history traits and available habitat. Also, in dynamic range predictions uncertainty in SDM algorithms and climate scenarios can become secondary to uncertainty in dynamic model components. Our study emphasises the need for principal evaluation tools like sensitivity analysis in order to assess uncertainty and robustness in dynamic range predictions. A more direct benefit of such robustness analysis is an improved mechanistic understanding of dynamic species’ responses to climate change.     

Humpback whale diets respond to variance in ocean climate and ecosystem conditions in the California Current

Large, migratory predators are often cited as sentinel species for ecosystem processes and climate‐related changes, but their utility as indicators is dependent upon an understanding of their response to environmental variability. Documentation of the links between climate variability, ecosystem change and predator dynamics is absent for most top predators. Identifying species that may be useful indicators and elucidating these mechanistic links provides insight into current ecological dynamics and may inform predictions of future ecosystem responses to climatic change. We examine humpback whale response to environmental variability through stable isotope analysis of diet over a dynamic 20‐year period (1993–2012) in the California Current System (CCS). Humpback whale diets captured two major shifts in oceanographic and ecological conditions in the CCS. Isotopic signatures reflect a diet dominated by krill during periods characterized by positive phases of the North Pacific Gyre Oscillation (NPGO), cool sea surface temperature (SST), strong upwelling and high krill biomass. In contrast, humpback whale diets are dominated by schooling fish when the NPGO is negative, SST is warmer, seasonal upwelling is delayed and anchovy and sardine populations display increased biomass and range expansion. These findings demonstrate that humpback whales trophically respond to ecosystem shifts, and as a result, their foraging behavior is a synoptic indicator of oceanographic and ecological conditions across the CCS. Multi‐decadal examination of these sentinel species thus provides insight into biological consequences of interannual climate fluctuations, fundamental to advancing ecosystem predictions related to global climate change.     

Climate‐based empirical models show biased predictions of butterfly communities along environmental gradients

A better understanding of the factors that mould ecological community structure is required to accurately predict community composition and to anticipate threats to ecosystems due to global changes. We tested how well stacked climate‐based species distribution models (S‐SDMs) could predict butterfly communities in a mountain region. It has been suggested that climate is the main force driving butterfly distribution and community structure in mountain environments, and that, as a consequence, climate‐based S‐SDMs should yield unbiased predictions. In contrast to this expectation, at lower altitudes, climate‐based S‐SDMs overpredicted butterfly species richness at sites with low plant species richness and underpredicted species richness at sites with high plant species richness. According to two indices of composition accuracy, the Sorensen index and a matching coefficient considering both absences and presences, S‐SDMs were more accurate in plant‐rich grasslands. Butterflies display strong and often specialised trophic interactions with plants. At lower altitudes, where land use is more intense, considering climate alone without accounting for land use influences on grassland plant richness leads to erroneous predictions of butterfly presences and absences. In contrast, at higher altitudes, where climate is the main force filtering communities, there were fewer differences between observed and predicted butterfly richness. At high altitudes, even if stochastic processes decrease the accuracy of predictions of presence, climate‐based S‐SDMs are able to better filter out butterfly species that are unable to cope with severe climatic conditions, providing more accurate predictions of absences. Our results suggest that predictions should account for plants in disturbed habitats at lower altitudes but that stochastic processes and heterogeneity at high altitudes may limit prediction success of climate‐based S‐SDMs.     

Population dynamics can be more important than physiological limits for determining range shifts under climate change

Evidence is accumulating that species' responses to climate changes are best predicted by modelling the interaction of physiological limits, biotic processes and the effects of dispersal‐limitation. Using commercially harvested blacklip (Haliotis rubra) and greenlip abalone (Haliotis laevigata) as case studies, we determine the relative importance of accounting for interactions among physiology, metapopulation dynamics and exploitation in predictions of range (geographical occupancy) and abundance (spatially explicit density) under various climate change scenarios. Traditional correlative ecological niche models (ENM) predict that climate change will benefit the commercial exploitation of abalone by promoting increased abundances without any reduction in range size. However, models that account simultaneously for demographic processes and physiological responses to climate‐related factors result in future (and present) estimates of area of occupancy (AOO) and abundance that differ from those generated by ENMs alone. Range expansion and population growth are unlikely for blacklip abalone because of important interactions between climate‐dependent mortality and metapopulation processes; in contrast, greenlip abalone should increase in abundance despite a contraction in AOO. The strongly non‐linear relationship between abalone population size and AOO has important ramifications for the use of ENM predictions that rely on metrics describing change in habitat area as proxies for extinction risk. These results show that predicting species' responses to climate change often require physiological information to understand climatic range determinants, and a metapopulation model that can make full use of this data to more realistically account for processes such as local extirpation, demographic rescue, source‐sink dynamics and dispersal‐limitation.     

Range position and climate sensitivity: The structure of among‐population demographic responses to climatic variation

Species’ distributions will respond to climate change based on the relationship between local demographic processes and climate and how this relationship varies based on range position. A rarely tested demographic prediction is that populations at the extremes of a species’ climate envelope (e.g., populations in areas with the highest mean annual temperature) will be most sensitive to local shifts in climate (i.e., warming). We tested this prediction using a dynamic species distribution model linking demographic rates to variation in temperature and precipitation for wood frogs (Lithobates sylvaticus) in North America. Using long‐term monitoring data from 746 populations in 27 study areas, we determined how climatic variation affected population growth rates and how these relationships varied with respect to long‐term climate. Some models supported the predicted pattern, with negative effects of extreme summer temperatures in hotter areas and positive effects on recruitment for summer water availability in drier areas. We also found evidence of interacting temperature and precipitation influencing population size, such as extreme heat having less of a negative effect in wetter areas. Other results were contrary to predictions, such as positive effects of summer water availability in wetter parts of the range and positive responses to winter warming especially in milder areas. In general, we found wood frogs were more sensitive to changes in temperature or temperature interacting with precipitation than to changes in precipitation alone. Our results suggest that sensitivity to changes in climate cannot be predicted simply by knowing locations within the species’ climate envelope. Many climate processes did not affect population growth rates in the predicted direction based on range position. Processes such as species‐interactions, local adaptation, and interactions with the physical landscape likely affect the responses we observed. Our work highlights the need to measure demographic responses to changing climate.