52,000 years of woolly rhinoceros population dynamics reveal extinction mechanisms.

The extinction of the woolly rhinoceros (Coelodonta antiquitatis) at the onset of the Holocene remains an enigma, with conflicting evidence regarding its cause and spatiotemporal dynamics. This partly reflects challenges in determining demographic responses of late Quaternary megafauna to climatic and anthropogenic causal drivers with available genetic and paleontological techniques. Here, we show that elucidating mechanisms of ancient extinctions can benefit from a detailed understanding of fine-scale metapopulation dynamics, operating over many millennia. Using an abundant fossil record, ancient DNA, and high-resolution simulation models, we untangle the ecological mechanisms and causal drivers that are likely to have been integral in the decline and later extinction of the woolly rhinoceros. Our 52,000-y reconstruction of distribution-wide metapopulation dynamics supports a pathway to extinction that began long before the Holocene, when the combination of cooling temperatures and low but sustained hunting by humans trapped woolly rhinoceroses in suboptimal habitats along the southern edge of their range. Modeling indicates that this ecological trap intensified after the end of the last ice age, preventing colonization of newly formed suitable habitats, weakening stabilizing metapopulation processes, triggering the extinction of the woolly rhinoceros in the early Holocene. Our findings suggest that fragmentation and resultant metapopulation dynamics should be explicitly considered in explanations of late Quaternary megafauna extinctions, sending a clarion call to the fragility of the remaining large-bodied grazers restricted to disjunct fragments of poor-quality habitat due to anthropogenic environmental change.

Combining mesocosms with models reveals effects of global warming and ocean acidification on a temperate marine ecosystem.

Ocean warming and species exploitation have already caused large-scale reorganization of biological communities across the world. Accurate projections of future biodiversity change require a comprehensive understanding of how entire communities respond to global change. We combined a time-dynamic integrated food web modeling approach (Ecosim) with previous data from community-level mesocosm experiments to determine the independent and combined effects of ocean warming, ocean acidification and fisheries exploitation on a well-managed temperate coastal ecosystem. The mesocosm parameters enabled important physiological and behavioral responses to climate stressors to be projected for trophic levels ranging from primary producers to top predators, including sharks. Through model simulations, we show that under sustainable rates of fisheries exploitation, near-future warming or ocean acidification in isolation could benefit species biomass at higher trophic levels (e.g., mammals, birds, and demersal finfish) in their current climate ranges, with the exception of small pelagic fishes. However, under warming and acidification combined, biomass increases at higher trophic levels will be lower or absent, while in the longer term reduced productivity of prey species is unlikely to support the increased biomass at the top of the food web. We also show that increases in exploitation will suppress any positive effects of human-driven climate change, causing individual species biomass to decrease at higher trophic levels. Nevertheless, total future potential biomass of some fisheries species in temperate areas might remain high, particularly under acidification, because unharvested opportunistic species will likely benefit from decreased competition and show an increase in biomass. Ecological indicators of species composition such as the Shannon diversity index decline under all climate change scenarios, suggesting a trade-off between biomass gain and functional diversity. By coupling parameters from multilevel mesocosm food web experiments with dynamic food web models, we were able to simulate the generative mechanisms that drive complex responses of temperate marine ecosystems to global change. This approach, which blends theory with experimental data, provides new prospects for forecasting climate-driven biodiversity change and its effects on ecosystem processes.

Millennial processes of population decline, range contraction and near extinction of the European bison.

European bison (Bison bonasus) were widespread throughout Europe during the late Pleistocene. However, the contributions of environmental change and humans to their near extinction have never been resolved. Using process-explicit models, fossils and ancient DNA, we disentangle the combinations of threatening processes that drove population declines and regional extinctions of European bison through space and across time. We show that the population size of European bison declined abruptly at the termination of the Pleistocene in response to rapid environmental change, hunting by humans and their interaction. Human activities prevented populations of European bison from rebounding in the Holocene, despite improved environmental conditions. Hunting caused range loss in the north and east of its distribution, while land use change was responsible for losses in the west and south. Advances in hunting technologies from 1500 CE were needed to simulate low abundances observed in 1870 CE. While our findings show that humans were an important driver of the extinction of the European bison in the wild, vast areas of its range vanished during the Pleistocene-Holocene transition because of post-glacial environmental change. These areas of its former range have been climatically unsuitable for millennia and should not be considered in reintroduction efforts.

Process-explicit models reveal pathway to extinction for woolly mammoth using pattern-oriented validation.

Pathways to extinction start long before the death of the last individual. However, causes of early stage population declines and the susceptibility of small residual populations to extirpation are typically studied in isolation. Using validated process-explicit models, we disentangle the ecological mechanisms and threats that were integral in the initial decline and later extinction of the woolly mammoth. We show that reconciling ancient DNA data on woolly mammoth population decline with fossil evidence of location and timing of extinction requires process-explicit models with specific demographic and niche constraints, and a constrained synergy of climatic change and human impacts. Validated models needed humans to hasten climate-driven population declines by many millennia, and to allow woolly mammoths to persist in mainland Arctic refugia until the mid-Holocene. Our results show that the role of humans in the extinction dynamics of woolly mammoth began well before the Holocene, exerting lasting effects on the spatial pattern and timing of its range-wide extinction.

Spatiotemporal influences of climate and humans on muskox range dynamics over multiple millennia.

Processes leading to range contractions and population declines of Arctic megafauna during the late Pleistocene and early Holocene are uncertain, with intense debate on the roles of human hunting, climatic change, and their synergy. Obstacles to a resolution have included an overreliance on correlative rather than process-explicit approaches for inferring drivers of distributional and demographic change. Here, we disentangle the ecological mechanisms and threats that were integral in the decline and extinction of the muskox (Ovibos moschatus) in Eurasia and in its expansion in North America using process-explicit macroecological models. The approach integrates modern and fossil occurrence records, ancient DNA, spatiotemporal reconstructions of past climatic change, species-specific population ecology, and the growth and spread of anatomically modern humans. We show that accurately reconstructing inferences of past demographic changes for muskox over the last 21,000 years require high dispersal abilities, large maximum densities, and a small Allee effect. Analyses of validated process-explicit projections indicate that climatic change was the primary driver of muskox distribution shifts and demographic changes across its previously extensive (circumpolar) range, with populations responding negatively to rapid warming events. Regional analyses show that the range collapse and extinction of the muskox in Europe (~13,000 years ago) was likely caused by humans operating in synergy with climatic warming. In Canada and Greenland, climatic change and human activities probably combined to drive recent population sizes. The impact of past climatic change on the range and extinction dynamics of muskox during the Pleistocene-Holocene transition signals a vulnerability of this species to future increased warming. By better establishing the ecological processes that shaped the distribution of the muskox through space and time, we show that process-explicit macroecological models have important applications for the future conservation and management of this iconic species in a warming Arctic.

Faster ocean warming threatens richest areas of marine biodiversity.

The vulnerability of marine biodiversity to accelerated rates of climatic change is poorly understood. By developing a new method for identifying extreme oceanic warming events during Earth's most recent deglaciation, and comparing these to 21st century projections, we show that future rates of ocean warming will disproportionately affect the most speciose marine communities, potentially threatening biodiversity in more than 70% of current-day global hotspots of marine species richness. The persistence of these richest areas of marine biodiversity will require many species to move well beyond the biogeographic realm where they are endemic, at rates of redistribution not previously seen. Our approach for quantifying exposure of biodiversity to past and future rates of oceanic warming provides new context and scalable information for deriving and strengthening conservation actions to safeguard marine biodiversity under climate change.

Climate change could drive marine food web collapse through altered trophic flows and cyanobacterial proliferation.

Global warming and ocean acidification are forecast to exert significant impacts on marine ecosystems worldwide. However, most of these projections are based on ecological proxies or experiments on single species or simplified food webs. How energy fluxes are likely to change in marine food webs in response to future climates remains unclear, hampering forecasts of ecosystem functioning. Using a sophisticated mesocosm experiment, we model energy flows through a species-rich multilevel food web, with live habitats, natural abiotic variability, and the potential for intra- and intergenerational adaptation. We show experimentally that the combined stress of acidification and warming reduced energy flows from the first trophic level (primary producers and detritus) to the second (herbivores), and from the second to the third trophic level (carnivores). Warming in isolation also reduced the energy flow from herbivores to carnivores, the efficiency of energy transfer from primary producers and detritus to herbivores and detritivores, and the living biomass of detritivores, herbivores, and carnivores. Whilst warming and acidification jointly boosted primary producer biomass through an expansion of cyanobacteria, this biomass was converted to detritus rather than to biomass at higher trophic levels-i.e., production was constrained to the base of the food web. In contrast, ocean acidification affected the food web positively by enhancing trophic flow from detritus and primary producers to herbivores, and by increasing the biomass of carnivores. Our results show how future climate change can potentially weaken marine food webs through reduced energy flow to higher trophic levels and a shift towards a more detritus-based system, leading to food web simplification and altered producer-consumer dynamics, both of which have important implications for the structuring of benthic communities.

Models of spatiotemporal variation in rabbit abundance reveal management hot spots for an invasive species.

The European rabbit (Oryctolagus cuniculus) is a notorious economic and environmental pest species in its invasive range. To better understand the population and range dynamics of this species, 41 yr of abundance data have been collected from 116 unique sites across a broad range of climatic and environmental conditions in Australia. We analyzed this time series of abundance data to determine whether interannual variation in climatic conditions can be used to map historic, contemporary, and potential future fluctuations in rabbit abundance from regional to continental scales. We constructed a hierarchical Bayesian regression model of relative abundance that corrected for observation error and seasonal biases. The corrected abundances were regressed against environmental and disease variables in order to project high spatiotemporal resolution, continent-wide rabbit abundances. We show that rabbit abundance in Australia is highly variable in space and time, being driven primarily by internnual variation in temperature and precipitation in concert with the prevalence of a non-pathogenic virus. Moreover, we show that internnual variation in local spatial abundances can be mapped effectively at a continental scale using highly resolved spatiotemporal predictors, allowing "hot spots" of persistently high rabbit abundance to be identified. Importantly, cross-validated model performance was fair to excellent within and across distinct climate zones. Long-term monitoring data for invasive species can be used to map fine-scale spatiotemporal fluctuations in abundance patterns when accurately accounting for inherent sampling biases. Our analysis provides ecologists and pest managers with a clearer understanding of the determinants of rabbit abundance in Australia, offering an important new approach for predicting spatial abundance patterns of invasive species at the near-term temporal scales that are directly relevant to resource management.

Spatial resilience of the Great Barrier Reef under cumulative disturbance impacts.

In the face of increasing cumulative effects from human and natural disturbances, sustaining coral reefs will require a deeper understanding of the drivers of coral resilience in space and time. Here we develop a high-resolution, spatially explicit model of coral dynamics on Australia's Great Barrier Reef (GBR). Our model accounts for biological, ecological and environmental processes, as well as spatial variation in water quality and the cumulative effects of coral diseases, bleaching, outbreaks of crown-of-thorns starfish (Acanthaster cf. solaris), and tropical cyclones. Our projections reconstruct coral cover trajectories between 1996 and 2017 over a total reef area of 14,780 km2 , predicting a mean annual coral loss of -0.67%/year mostly due to the impact of cyclones, followed by starfish outbreaks and coral bleaching. Coral growth rate was the highest for outer shelf coral communities characterized by digitate and tabulate Acropora spp. and exposed to low seasonal variations in salinity and sea surface temperature, and the lowest for inner-shelf communities exposed to reduced water quality. We show that coral resilience (defined as the net effect of resistance and recovery following disturbance) was negatively related to the frequency of river plume conditions, and to reef accessibility to a lesser extent. Surprisingly, reef resilience was substantially lower within no-take marine protected areas, however this difference was mostly driven by the effect of water quality. Our model provides a new validated, spatially explicit platform for identifying the reefs that face the greatest risk of biodiversity loss, and those that have the highest chances to persist under increasing disturbance regimes.

Exploring mechanisms and origins of reduced dispersal in island Komodo dragons.

Loss of dispersal typifies island biotas, but the selective processes driving this phenomenon remain contentious. This is because selection via, both indirect (e.g. relaxed selection or island syndromes) and direct (e.g. natural selection or spatial sorting) processes may be involved, and no study has yet convincingly distinguished between these alternatives. Here, we combined observational and experimental analyses of an island lizard, the Komodo dragon (Varanus komodoensis, the world's largest lizard), to provide evidence for the actions of multiple processes that could contribute to island dispersal loss. In the Komodo dragon, concordant results from telemetry, simulations, experimental translocations, mark-recapture, and gene flow studies indicated that despite impressive physical and sensory capabilities for long-distance movement, Komodo dragons exhibited near complete dispersal restriction: individuals rarely moved beyond the valleys they were born/captured in. Importantly, lizard site-fidelity was insensitive to common agents of dispersal evolution (i.e. indices of risk for inbreeding, kin and intraspecific competition, and low habitat quality) that consequently reduced survival of resident individuals. We suggest that direct selection restricts movement capacity (e.g. via benefits of spatial philopatry and increased costs of dispersal) alongside use of dispersal-compensating traits (e.g. intraspecific niche partitioning) to constrain dispersal in island species.

Why decadal to century timescale palaeoclimate data are needed to explain present-day patterns of biological diversity and change.

The current distribution of species, environmental conditions and their interactions represent only one snapshot of a planet that is continuously changing, in part due to human influences. To distinguish human impacts from natural factors, the magnitude and pace of climate shifts, since the Last Glacial Maximum, are often used to determine whether patterns of diversity today are artefacts of past climate change. In the absence of high-temporal resolution palaeoclimate reconstructions, this is generally done by assuming that past climate change occurred at a linear pace between widely spaced (usually, ≥1,000 years) climate snapshots. We show here that this is a flawed assumption because regional climates have changed significantly across decades and centuries during glacial-interglacial cycles, likely causing rapid regional replacement of biota. We demonstrate how recent atmosphere-ocean general circulation model (AOGCM) simulations of the climate of the past 21,000 years can provide credible estimates of the details of climate change on decadal to centennial timescales, showing that these details differ radically from what might be inferred from longer timescale information. High-temporal resolution information can provide more meaningful estimates of the magnitude and pace of climate shifts, the location and timing of drivers of physiological stress, and the extent of novel climates. They also produce new opportunities to directly investigate whether short-term climate variability is more important in shaping biodiversity patterns rather than gradual changes in long-term climatic means. Together, these more accurate measures of past climate instability are likely to bring about a better understanding of the role of palaeoclimatic change and variability in shaping current macroecological patterns in many regions of the world.

How complex should models be? Comparing correlative and mechanistic range dynamics models.

Criticism has been levelled at climate-change-induced forecasts of species range shifts that do not account explicitly for complex population dynamics. The relative importance of such dynamics under climate change is, however, undetermined because direct tests comparing the performance of demographic models vs. simpler ecological niche models are still lacking owing to difficulties in evaluating forecasts using real-world data. We provide the first comparison of the skill of coupled ecological-niche-population models and ecological niche models in predicting documented shifts in the ranges of 20 British breeding bird species across a 40-year period. Forecasts from models calibrated with data centred on 1970 were evaluated using data centred on 2010. We found that more complex coupled ecological-niche-population models (that account for dispersal and metapopulation dynamics) tend to have higher predictive accuracy in forecasting species range shifts than structurally simpler models that only account for variation in climate. However, these better forecasts are achieved only if ecological responses to climate change are simulated without static snapshots of historic land use, taken at a single point in time. In contrast, including both static land use and dynamic climate variables in simpler ecological niche models improve forecasts of observed range shifts. Despite being less skilful at predicting range changes at the grid-cell level, ecological niche models do as well, or better, than more complex models at predicting the magnitude of relative change in range size. Therefore, ecological niche models can provide a reasonable first approximation of the magnitude of species' potential range shifts, especially when more detailed data are lacking on dispersal dynamics, demographic processes underpinning population performance, and change in land cover.

Mesocosms Reveal Ecological Surprises from Climate Change.

Understanding, predicting, and mitigating the impacts of climate change on biodiversity poses one of the most crucial challenges this century. Currently, we know more about how future climates are likely to shift across the globe than about how species will respond to these changes. Two recent studies show how mesocosm experiments can hasten understanding of the ecological consequences of climate change on species' extinction risk, community structure, and ecosystem functions. Using a large-scale terrestrial warming experiment, Bestion et al. provide the first direct evidence that future global warming can increase extinction risk for temperate ectotherms. Using aquatic mesocosms, Yvon-Durocher et al. show that human-induced climate change could, in some cases, actually enhance the diversity of local communities, increasing productivity. Blending these theoretical and empirical results with computational models will improve forecasts of biodiversity loss and altered ecosystem processes due to climate change.

Disentangling synergistic disease dynamics: Implications for the viral biocontrol of rabbits.

European rabbits (Oryctolagus cuniculus) have been exposed to rabbit haemorrhagic disease virus (RHDV) and myxoma virus (MYXV) in their native and invasive ranges for decades. Yet, the long-term effects of these viruses on rabbit population dynamics remain poorly understood. In this context, we analysed 17 years of detailed capture-mark-recapture data (2000-2016) from Turretfield, South Australia, using a probabilistic state-space hierarchical modelling framework to estimate rabbit survival and epidemiological dynamics. While RHDV infection and disease-induced death were most prominent during annual epidemics in winter and spring, we found evidence for continuous infection of susceptible individuals with RHDV throughout the year. RHDV-susceptible rabbits had, on average, 25% lower monthly survival rates compared to immune individuals, while the average monthly force of infection in winter and spring was ~38%. These combined to result in an average infection-induced mortality rate of 69% in winter and spring. Individuals susceptible to MYXV and immune to RHDV had similar survival probabilities to those having survived infections from both viruses, whereas individuals susceptible to both RHDV and MYXV had higher survival probabilities than those susceptible to RHDV and immune to MYXV. This suggests that MYXV may reduce the future survival rates of individuals that endure initial MYXV infection. There was no evidence for long-term changes in disease-induced mortality and infection rates for either RHDV or MYXV. We conclude that continuous, year-round virus perpetuation (and perhaps heterogeneity in modes of transmission and infectious doses during and after epidemics) acts to reduce the efficiency of RHDV and MYXV as biocontrol agents of rabbits in their invasive range. However, if virulence can be maintained as relatively constant through time, RHDV and MYXV will likely continue realizing strong benefits as biocontrol agents.

Tick exposure and extreme climate events impact survival and threaten the persistence of a long-lived lizard.

Assessing the impacts of multiple, often synergistic, stressors on the population dynamics of long-lived species is becoming increasingly important due to recent and future global change. Tiliqua rugosa (sleepy lizard) is a long-lived skink (>30 years) that is adapted to survive in semi-arid environments with varying levels of parasite exposure and highly seasonal food availability. We used an exhaustive database of 30 years of capture-mark-recapture records to quantify the impacts of both parasite exposure and environmental conditions on the lizard's survival rates and long-term population dynamics. Lizard abundance was relatively stable throughout the study period; however, there were changing patterns in adult and juvenile apparent survival rates, driven by spatial and temporal variation in levels of tick exposure and temporal variation in environmental conditions. Extreme weather events during the winter and spring seasons were identified as important environmental drivers of survival. Climate models predict a dramatic increase in the frequency of extreme hot and dry winter and spring seasons in our South Australian study region; from a contemporary probability of 0.17 up to 0.47-0.83 in 2080 depending on the emissions scenario. Our stochastic population model projections showed that these future climatic conditions will induce a decline in the abundance of this long-lived reptile of up to 67% within 30 years from 2080, under worst case scenario modelling. The results have broad implications for future work investigating the drivers of population dynamics and persistence. We highlight the importance of long-term data sets and accounting for synergistic impacts between multiple stressors. We show that predicted increases in the frequency of extreme climate events have the potential to considerably and negatively influence a long-lived species, which might previously have been assumed to be resilient to environmental perturbations.

Extinction debt from climate change for frogs in the wet tropics.

The effect of twenty-first-century climate change on biodiversity is commonly forecast based on modelled shifts in species ranges, linked to habitat suitability. These projections have been coupled with species-area relationships (SAR) to infer extinction rates indirectly as a result of the loss of climatically suitable areas and associated habitat. This approach does not model population dynamics explicitly, and so accepts that extinctions might occur after substantial (but unknown) delays-an extinction debt. Here we explicitly couple bioclimatic envelope models of climate and habitat suitability with generic life-history models for 24 species of frogs found in the Australian Wet Tropics (AWT). We show that (i) as many as four species of frogs face imminent extinction by 2080, due primarily to climate change; (ii) three frogs face delayed extinctions; and (iii) this extinction debt will take at least a century to be realized in full. Furthermore, we find congruence between forecast rates of extinction using SARs, and demographic models with an extinction lag of 120 years. We conclude that SAR approaches can provide useful advice to conservation on climate change impacts, provided there is a good understanding of the time lags over which delayed extinctions are likely to occur.

Environmental effects and individual body condition drive seasonal fecundity of rabbits: identifying acute and lagged processes.

The reproduction of many species is determined by seasonally-driven resource supply. But it is difficult to quantify whether the fecundity is sensitive to short- or long-term exposure to environmental conditions such as rainfall that drive resource supply. Using 25 years of data on individual fecundity of European female rabbits, Oryctolagus cuniculus, from semiarid Australia, we investigate the role of individual body condition, rainfall and temperature as drivers of seasonal and long-term and population-level changes in fecundity (breeding probability, ovulation rate, embryo survival). We built distributed lag models in a hierarchical Bayesian framework to account for both immediate and time-lagged effects of climate and other environmental drivers, and possible shifts in reproduction over consecutive seasons. We show that rainfall during summer, when rabbits typically breed only rarely, increased breeding probability immediately and with time lags of up to 10 weeks. However, an earlier onset of the yearly breeding period did not result in more overall reproductive output. Better body condition was associated with an earlier onset of breeding and higher embryo survival. Breeding probability in the main breeding season declined with increased breeding activity in the preceding season and only individuals in good body condition were able to breed late in the season. Higher temperatures reduce breeding success across seasons. We conclude that a better understanding of seasonal dynamics and plasticity (and their interplay) in reproduction will provide crucial insights into how lagomorphs are likely to respond and potentially adapt to the influence of future climate and other environmental change.

Predictors of contraction and expansion of area of occupancy for British birds.

Geographical range dynamics are driven by the joint effects of abiotic factors, human ecosystem modifications, biotic interactions and the intrinsic organismal responses to these. However, the relative contribution of each component remains largely unknown. Here, we compare the contribution of life-history attributes, broad-scale gradients in climate and geographical context of species' historical ranges, as predictors of recent changes in area of occupancy for 116 terrestrial British breeding birds (74 contractors, 42 expanders) between the early 1970s and late 1990 s. Regional threat classifications demonstrated that the species of highest conservation concern showed both the largest contractions and the smallest expansions. Species responded differently to climate depending on geographical distribution-northern species changed their area of occupancy (expansion or contraction) more in warmer and drier regions, whereas southern species changed more in colder and wetter environments. Species with slow life history (larger body size) tended to have a lower probability of changing their area of occupancy than species with faster life history, whereas species with greater natal dispersal capacity resisted contraction and, counterintuitively, expansion. Higher geographical fragmentation of species' range also increased expansion probability, possibly indicating a release from a previously limiting condition, for example through agricultural abandonment since the 1970s. After accounting statistically for the complexity and nonlinearity of the data, our results demonstrate two key aspects of changing area of occupancy for British birds: (i) climate is the dominant driver of change, but direction of effect depends on geographical context, and (ii) all of our predictors generally had a similar effect regardless of the direction of the change (contraction versus expansion). Although we caution applying results from Britain's highly modified and well-studied bird community to other biogeographic regions, our results do indicate that a species' propensity to change area of occupancy over decadal scales can be explained partially by a combination of simple allometric predictors of life-history pace, average climate conditions and geographical context.

Predicting current and future global distributions of whale sharks.

The Vulnerable (IUCN) whale shark spans warm and temperate waters around the globe. However, their present-day and possible future global distribution has never been predicted. Using 30 years (1980-2010) of whale shark observations recorded by tuna purse-seiners fishing in the Atlantic, Indian and Pacific Oceans, we applied generalized linear mixed-effects models to test the hypothesis that similar environmental covariates predict whale shark occurrence in all major ocean basins. We derived global predictors from satellite images for chlorophyll a and sea surface temperature, and bathymetric charts for depth, bottom slope and distance to shore. We randomly generated pseudo-absences within the area covered by the fisheries, and included fishing effort as an offset to account for potential sampling bias. We predicted sea surface temperatures for 2070 using an ensemble of five global circulation models under a no climate-policy reference scenario, and used these to predict changes in distribution. The full model (excluding standard deviation of sea surface temperature) had the highest relative statistical support (wAICc  = 0.99) and explained ca. 60% of the deviance. Habitat suitability was mainly driven by spatial variation in bathymetry and sea surface temperature among oceans, although these effects differed slightly among oceans. Predicted changes in sea surface temperature resulted in a slight shift of suitable habitat towards the poles in both the Atlantic and Indian Oceans (ca. 5°N and 3-8°S, respectively) accompanied by an overall range contraction (2.5-7.4% and 1.1-6.3%, respectively). Predicted changes in the Pacific Ocean were small. Assuming that whale shark environmental requirements and human disturbances (i.e. no stabilization of greenhouse gas emissions) remain similar, we show that warming sea surface temperatures might promote a net retreat from current aggregation areas and an overall redistribution of the species.

How interactions between animal movement and landscape processes modify local range dynamics and extinction risk.

Forecasts of range dynamics now incorporate many of the mechanisms and interactions that drive species distributions. However, connectivity continues to be simulated using overly simple distance-based dispersal models with little consideration of how the individual behaviour of dispersing organisms interacts with landscape structure (functional connectivity). Here, we link an individual-based model to a niche-population model to test the implications of this omission. We apply this novel approach to a turtle species inhabiting wetlands which are patchily distributed across a tropical savannah, and whose persistence is threatened by two important synergistic drivers of global change: predation by invasive species and overexploitation. We show that projections of local range dynamics in this study system change substantially when functional connectivity is modelled explicitly. Accounting for functional connectivity in model simulations causes the estimate of extinction risk to increase, and predictions of range contraction to slow. We conclude that models of range dynamics that simulate functional connectivity can reduce an important source of bias in predictions of shifts in species distributions and abundances, especially for organisms whose dispersal behaviours are strongly affected by landscape structure.