• Energy Research

The causes of Sahul’s megafauna extinctions remain uncertain, although several interacting factors were likely responsible. To examine the relative support for hypotheses regarding plausible ecological mechanisms underlying these extinctions, we constructed the first stochastic, age-structured models for 13 extinct megafauna species from five functional/taxonomic groups, as well as 8 extant species within these groups for comparison. Perturbing specific demographic rates individually, we tested which species were more demographically susceptible to extinction, and then compared these relative sensitivities to the fossil-derived extinction chronology. Our models show that the macropodiformes were the least demographically susceptible to extinction, followed by carnivores, monotremes, vombatiform herbivores, and large birds. Five of the eight extant species were as or more susceptible than the extinct species. There was no clear relationship between extinction susceptibility and the extinction chronology for any perturbation scenario, while body mass and generation length explained much of the variation in relative risk. Our results reveal that the actual mechanisms leading to the observed extinction chronology were unlikely related to variation in demographic susceptibility per se, but were possibly driven instead by finer-scale variation in climate change and/or human prey choice and relative hunting success.

SummaryClimate refugia, locations where taxa survive periods of regionally adverse climate, are thought to be critical for maintaining biodiversity through the glacial–interglacial climate changes of the Quaternary. A critical research need is to better integrate and reconcile the three major lines of evidence used to infer the existence of past refugia – fossil records, species distribution models and phylogeographic surveys – in order to characterize the complex spatiotemporal trajectories of species and populations in and out of refugia. Here we review the complementary strengths, limitations and new advances for these three approaches. We provide case studies to illustrate their combined application, and point the way towards new opportunities for synthesizing these disparate lines of evidence. Case studies with European beech, Qinghai spruce and Douglas‐fir illustrate how the combination of these three approaches successfully resolves complex species histories not attainable from any one approach. Promising new statistical techniques can capitalize on the strengths of each method and provide a robust quantitative reconstruction of species history. Studying past refugia can help identify contemporary refugia and clarify their conservation significance, in particular by elucidating the fine‐scale processes and the particular geographic locations that buffer species against rapidly changing climate. Contents Summary 38 I. Climate refugia: biogeographical and conservation significance 38 II. Approaches for reconstructing refugia: strengths, limitations and recent advances 39 III. Climate refugia of the past: three case studies 46 IV. New integrative approaches to reconstructing refugia 47 V. How can historical refugia inform us about future refugia? 48 VI. Concluding thoughts 49 Acknowledgements 49 References 49

AbstractThe biosphere is changing rapidly due to human endeavour. Because ecological communities underlie networks of interacting species, changes that directly affect some species can have indirect effects on others. Accurate tools to predict these direct and indirect effects are therefore required to guide conservation strategies. However, most extinction‐risk studies only consider the direct effects of global change—such as predicting which species will breach their thermal limits under different warming scenarios—with predictions of trophic cascades and co‐extinction risks remaining mostly speculative. To predict the potential indirect effects of primary extinctions, data describing community interactions and network modelling can estimate how extinctions cascade through communities. While theoretical studies have demonstrated the usefulness of models in predicting how communities react to threats like climate change, few have applied such methods to real‐world communities. This gap partly reflects challenges in constructing trophic network models of real‐world food webs, highlighting the need to develop approaches for quantifying co‐extinction risk more accurately. We propose a framework for constructing ecological network models representing real‐world food webs in terrestrial ecosystems and subjecting these models to co‐extinction scenarios triggered by probable future environmental perturbations. Adopting our framework will improve estimates of how environmental perturbations affect whole ecological communities. Identifying species at risk of co‐extinction (or those that might trigger co‐extinctions) will also guide conservation interventions aiming to reduce the probability of co‐extinction cascades and additional species losses.

AbstractLate Quaternary megafauna extinctions impoverished mammalian diversity worldwide. The causes of these extinctions in Australia are most controversial but essential to resolve, because this continent-wide event presaged similar losses that occurred thousands of years later on other continents. Here we apply a rigorous metadata analysis and new ensemble-hindcasting approach to 659 Australian megafauna fossil ages. When coupled with analysis of several high-resolution climate records, we show that megafaunal extinctions were broadly synchronous among genera and independent of climate aridity and variability in Australia over the last 120,000 years. Our results reject climate change as the primary driver of megafauna extinctions in the world’s most controversial context, and instead estimate that the megafauna disappeared Australia-wide ∼13,500 years after human arrival, with shorter periods of coexistence in some regions. This is the first comprehensive approach to incorporate uncertainty in fossil ages, extinction timing and climatology, to quantify mechanisms of prehistorical extinctions.

Summary To conserve future biodiversity, a better understanding of the likely effects of climate and land‐use change on the geographical distributions of species and the persistence of ecological communities is needed. Recent advances have integrated population dynamic processes into species distribution models (SDMs), to reduce potential biases in predictions and to better reflect the demographic nuances of incremental range shifts. However, there is no clear framework for selecting the most appropriate demographic‐based model for a given data set or scientific question. We review the computer‐based modelling platforms currently used for the development of either population‐ or individual‐based species range dynamics models. We describe the features and requirements of 20 software platforms commonly used to generate simulations of species ranges and abundances. We classify the platforms according to particular capabilities or features that account for user requirements and constraints, such as (i) ability to simulate simple to complex population dynamics, (ii) organism specificity or (iii) their computational capacities. Using this classification, we develop a protocol for choosing the most appropriate framework for modelling species range dynamics based in data availability and research requirements. We find that the main differences between modelling platforms are related to the way in which they simulate population dynamics, the type of organisms they are able to model and the ecological processes they incorporate. We show that some platforms can be used as generic modelling software to investigate a broad range of ecological questions related to the range dynamics of most species, and how these are likely to change in the future in response to forecast climate and land‐use change. We argue that model predictions will be improved by reducing usage to a smaller number of highly flexible freeware platforms. Our approach provides ecologists and conservation biologists with a clear method for selecting the most appropriate software platform that meets their needs when developing SDMs coupled with population‐dynamic processes. We argue that informed tool choice will translate to better predictions of species responses to climate and land‐use change and improved conservation management.

AbstractThe 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.