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Human domination of landscapes is a key driver of biodiversity loss, with the fingerprint of climate change becoming increasingly pronounced. Frameworks and tools for identifying threats to biodiversity are required to meet Post-2020 Global Biodiversity Framework targets for 2030 that call for, among other things, reducing or halting species extinction rates (1). Hence, we compiled a phylogenetic tree for terrestrial tetrapods, mapped hotspots of geographically restricted and evolutionarily distinct lineages, and identified which hotspots may simultaneously face the highest magnitudes of land use impacts and climate change. Across a quarter of Earth’s surface, hotspots contain the entire ranges of 45% of tetrapods, representing 39% of terrestrial tetrapod evolutionary heritage. By 2070, we estimate 8–13% of this heritage to occur entirely within hotspots highly exposed to climate change, with 13–29% of hotspots projected to experience high exposure to both stressors simultaneously. Most hotspots at highest risk occur in countries least able to take action. Our analysis highlights the need for global ambition and coordination to avoid catastrophic loss of tetrapod evolutionary heritage.

Climate refugia—areas that remain suitable for species during periods of climate disruption—have played an important role in species persistence over time. Identifying and protecting these refugia is a key climate change adaptation approach for conservation planning. To identify climate refugia for Australian tropical/sub-tropical rainforest flora, from the Last Glacial Maximum to 2070. Habitat suitability models were calibrated for 30 species using Maxent, and projected onto climate data for: Last Glacial Maximum (LGM, ~ 22,000 ybp); mid-Holocene (MH, ~ 6000 ybp); current period; and 2070. The intersection of suitable habitat over consecutive periods was assessed, identifying: current refugia (LGM–MH–Current); future refugia (Current–Future); and High Value Refugia (HVR, suitable over all four periods). Refugial hotspots (regions suitable for at least 15 species) were also identified. Suitable habitat was generally projected to span the greatest area in the current period. Four current refugial hotspots were identified: Wet Tropics, Central Mackay Coast, South Eastern Queensland, and North Coast (New South Wales). While suitable habitat for most species may decline in the future, HVRs will likely be retained for all species to at least 2070, although restricted in size. Future refugia was also projected in areas beyond species’ dispersal ranges. HVRs are highly important for the conservation of these rainforest species, given their generation times, limited dispersal capabilities and additional anthropogenic barriers to movement. This study assists in understanding long-term spatial shifts in rainforest flora in response to climate change and in designing future conservation strategies.

Urban forests (i.e. all vegetation present in urban areas), provide environmental and socio-economic benefits to more than half of the global population. Projected climate change threatens these benefits to society. Here, we assess vulnerability to climate change of 16,006 plant species present in the urban forests of 1,010 cities within 93 countries, using three vulnerability metrics: exposure, safety margin and risk. Exposure expresses the magnitude of projected changes in climate in a given area, safety margin measures species' sensitivity to climate change, and risk is the difference between exposure and safety margin. We identified 9,676 (60.5%) and 8,344 (52.1%) species exceeding their current climatic tolerance (i.e. safety margin) for mean annual temperature (MAT) and annual precipitation (AP), respectively. By 2050, 13,479 (84.2%) and 9,960 (62.2%) species are predicted to be at risk from projected changes in MAT and AP, respectively, with risk increasing in cities at lower latitudes. Our results can aid evaluation of the impacts of climate change on urban forests and identify the species most at risk. Considering future climates when selecting species for urban plantings will enhance the long-term societal benefits provided by urban forests, including their contribution to mitigating the magnitude and impacts of climate change.

Climate change presents a substantial threat to species unable to keep pace via migration or adaptation. In-situ climate refugia, areas currently occupied by a species and that remain suitable in the future, will be vital for species with dispersal limitations. Ex-situ refugia, areas beyond species' current ranges that remain suitable, may facilitate range shifts or provide options for translocation. Assessing both refugia is a conservation priority. Here, we identify refugia for 319 species threatened in New South Wales, using four plausible scenarios describing futures that are Warmer/Wetter, Warmer/Drier, Hotter/Wetter and Hotter/Little Precipitation change, relative to the present. Using Maxent, we identify (a) in-situ refugia for each species under each scenario; (b) regions of consensus – areas projected as in-situ refugia across all scenarios; (c) hotspots of in-situ refugia (regions suitable for >1 species); and (d) regions of consensus for ex-situ refugia. Species were categorised based on the extent of in- and ex-situ refugia. By 2070, refugia will likely be broadest, and narrowest, under the Warmer/Wetter and Hotter/Wetter scenarios, respectively. East coast regions currently suitable for multiple species are unlikely to remain as hotspots. Most species (65%) are projected to have limited regions of consensus for either refugia. Translocation should be explored for species with little-to-no in-situ refugia, but for which ex-situ refugia exist. Management of existing populations will be critical for species with in-situ refugia but limited ex-situ. We highlight how management decisions based on agreement across climate scenarios can be made, irrespective of uncertainty about the magnitude of climate change.

Protected areas are the primary strategy for maintaining natural landscapes and separating biodiversity features from preventable anthropogenic threats. The Convention on Biological Diversity calls for the coverage of at least 17% of land by protected areas, and the strategic prioritization of important biodiversity areas. Using the spatially explicit reserve design software, Marxan, this study combines climate refugia modelled under future climates in the year 2070 and bioregions to identify priority sites for protected area expansion under climate change in the state of New South Wales (NSW), Australia. Priority sites for new protected areas that meet bioregion and climate refugia targets were identified in central-western, northeast and patches of southeast NSW. Seven existing parks, including Kosciuszko National Park, overlapped with regions identified repeatedly as climate refugia under 12 future climate scenarios. The recommendations from this study support policy-makers in prioritizing the protection of biodiversity under a changing and uncertain climate.

Trait-based invasiveness studies typically categorize exotic species as invasive or noninvasive, implicitly assuming species form two homogenous groups. However, species can become invasive in different ways (e.g., high abundance, fast spread), likely relying on different functional traits to do so. As such, binary classification may obscure traits associated with invasiveness. We tested whether (1) the way in which invasiveness is quantified influences its correlation with functional traits and (2) different demography-based metrics are related to different sets of traits. Using a case study of 251 herbs exotic to Victoria, Australia, we quantified species' invasiveness using 10 metrics: four continuous, demography-based dimensions of invasiveness (spread rate, local abundance, geographic and environmental range sizes) and six binary classifications of invasiveness (based on alternative sources and invasion criteria). We examined the correlation between species' invasiveness and a set of four traits known to relate to plant demography and invasion. Then, we examined whether different demographic dimensions of invasiveness were better explained by different sets of traits. We found that the way invasiveness was quantified was important: different traits were linked with different invasiveness metrics, and some traits showed opposite effects across metrics. Species with fast spread were either tall with small seeds (i.e., good colonizers), or had heavy, animal-dispersed seeds. Plants with a large environmental range had greater plasticity for some traits. Locally abundant plants had low SLA and heavy seeds (i.e., strong competitors). Animal dispersal was also key to reach a large geographic range. No traits were consistently related to the six binary classifications. Our results indicate that exotic plants are invasive in different ways and rely on different combinations of traits to be so. Some traits (e.g., seed mass) had complex relationships with invasion: they apparently promote, hampered, or had no influence on different dimensions of invasiveness. Our findings are consistent with the notion that plant species use strategies that may be near optimal under some, but not all, ecological conditions. Compared to binary classifications of invasiveness, the use of invasiveness dimensions advances clearer hypothesis testing in invasion science.

The ENMTools software package was introduced in 2008 as a platform for making measurements on environmental niche models (ENMs, frequently referred to as species distribution models or SDMs), and for using those measurements in the context of newly developed Monte Carlo tests to evaluate hypotheses regarding niche evolution. Additional functionality was later added for model selection and simulation from ENMs, and the software package has been quite widely used. ENMTools was initially implemented as a Perl script, which was also compiled into an executable file for various platforms. However, the package had a number of significant limitations; it was only designed to fit models using Maxent, it relied on a specific Perl distribution to function, and its internal structure made it difficult to maintain and expand. Subsequently, the R programming language became the platform of choice for most ENM studies, making ENMTools less usable for many practitioners. Here we introduce a new R version of ENMTools that implements much of the functionality of its predecessor as well as numerous additions that simplify the construction, comparison and evaluation of niche models. These additions include new metrics for model fit, methods of measuring ENM overlap, and methods for testing evolutionary hypotheses. The new version of ENMTools is also designed to work within the expanding universe of R tools for ecological biogeography, and as such includes greatly simplified interfaces for analyses from several other R packages., DLW was funded by ARC DECRA award # DE140101675 and supported by subsidy funding to OIST. NJM was funded by Marsden grants 16‐UOA‐277 and 18‐UOA‐034, and U. Auckland FRDF #3722433. JCP is funded by a doctoral fellowship supported by the Agencia Canaria de la Investigación, Innovación y Sociedad de la Información and the European Social Fund (Operational Programme of the Canary Islands 2014‐2020). MC acknowledges support from Australian Research Council Discovery Project DP110103168.

Conservation strategies based on charismatic flagship species, such as tigers, lions, and elephants, successfully attract funding from individuals and corporate donors. However, critics of this species-focused approach argue it wastes resources and often does not benefit broader biodiversity. If true, then the best way of raising conservation funds excludes the best way of spending it. Here we show that this conundrum can be resolved, and that the flagship species approach does not impede cost-effective conservation. Through a tailored prioritization approach, we identify places containing flagship species while also maximizing global biodiversity representation (based on 19,616 terrestrial and freshwater species). We then compare these results to scenarios that only maximized biodiversity representation, and demonstrate that our flagship-based approach achieves 79−89% of our objective. This provides strong evidence that prudently selected flagships can both raise funds for conservation and help target where these resources are best spent to conserve biodiversity., Conservation actions focused on flagship species are effective at raising funds and awareness. Here, McGowan et al. show that prioritizing areas for conservation based on the presence of flagship species results in the selection of areas with ~ 79-89% of the total species that would be selected by maximizing biodiversity representation only.

Tephritid fruit flies are among the most destructive horticultural pests posing risks to Australia's multi-billion-dollar horticulture industry. Currently, there are 11 pest fruit fly species of economic concern in Australia. Of these, nine are native to this continent (Bactrocera aquilonis, B. bryoniae, B. halfordiae, B. jarvisi, B. kraussi, B. musae, B. neohumeralis, B. tryoni and Zeugodacus cucumis), while B. frauenfeldi and Ceratitis capitata are introduced. To varying degrees these species are costly to Australia's horticulture through in-farm management, monitoring to demonstrate pest freedom, quarantine and trade restrictions, and crop losses. Here, we used a common species distribution model, Maxent, to assess climate suitability for these 11 species under baseline (1960-1990) and future climate scenarios for Australia. Projections indicate that the Wet Tropics is likely to be vulnerable to all 11 species until at least 2070, with the east coast of Australia also likely to remain vulnerable to multiple species. While the Cape York Peninsula and Northern Territory are projected to have suitable climate for numerous species, extrapolation to novel climates in these areas decreases confidence in model projections. The climate suitability of major horticulture areas currently in eastern Queensland, southern-central New South Wales and southern Victoria to these pests may increase as climate changes. By highlighting areas at risk of pest range expansion in the future our study may guide Australia's horticulture industry in developing effective monitoring and management strategies.

International audience; Climate change threatens Earth's biodiversity, although its impacts are variable and depend on the capacity of species and ecosystems to cope with the magnitude and speed of change. Natural protected areas (NPAs) constitute potential refugia for species' persistence and for sustaining the provisioning of ecosystem services. Biosphere reserves are NPAs that are less altered by human actions and provide habitat to endemic, threatened or endangered species. Here, we aim to evaluate the threat imposed by climate change on the network of biosphere reserves in Mexico. Focusing on five bioclimatic variables, we computed the climatic space – measured as an n-dimensional hypervolume – of 40 NPAs. Increases in temperature are predicted for all NPAs by 2050, whereas decreases in annual rainfall are predicted for 30 NPAs. By 2050, 31 NPAs that provide habitat to 22,866 recorded species are predicted to lose 100% of their baseline climatic space, shifting to completely novel climates. On average, the other nine NPAs are predicted to lose 55.7% (SD = 26.7%) of their baseline climatic space, while 54.5% (SD = 32.5%) of the future climatic space will be novel. Seventeen NPAs may lose climate variability (homogenization), decreasing species' niches. The extent to which non-analogue conditions will remain within the tolerance of species and ecosystems is currently unknown. Finally, we propose a vulnerability index to categorise NPAs based on their loss of existing climatic space, total geographic area, species richness, and uniqueness of species composition, finding los Tuxtlas and Tiburon Ballena as the most and least vulnerable NPAs, respectively.

Anthropogenic climate change is a major factor driving shifts in the distributions of pests and invasive species. The Queensland fruit fly, Bactrocera tryoni (Froggatt) (Qfly), is the most economically damaging insect pest of Australia’s horticultural industry, and its management is a key priority for plant protection and biosecurity. Identifying the extent to which climate change may alter the distribution of suitable habitat for Qfly is important for the development and continuation of effective monitoring programs, phytosanitary measures, and management strategies. We used Maxent, a species distribution model, to map suitable habitat for Qfly under current climate, and six climate scenarios for 2030, 2050 and 2070. Our results highlight that south-western Australia, northern regions of the Northern Territory, eastern Queensland, and much of south-eastern Australia are currently suitable for Qfly. This includes southern Victoria and eastern Tasmania, which are currently free of breeding populations. There is substantial agreement across future climate scenarios that most areas currently suitable will remain so until at least 2070. Our projections provide an initial estimate of the potential exposure of Australia’s horticultural industry to Qfly as climate changes, highlighting the need for long-term vigilance across southern Australia to prevent further range expansion of this species.

Species distribution models (SDMs) frequently project substantial declines in the spatial extent of climatically suitable habitat in response to scenarios of future climate change. Such projections are highly disconcerting. Yet, considerable variation can occur in the direction and magnitude of range changes projected by different SDM methods, even when predictive performance is similar. In this study, we assessed whether particular methods have a tendency to predict substantial loss or gain of suitable habitat. In particular, we asked, “are 14 SDM methods equally likely to predict extreme changes to the future extent of suitable habitat for 220 Australian mammal species?”. We defined five non-mutually exclusive categories of ‘extreme’ change, based on stability or loss of current habitat, or the dislocation of current and future habitat: a) no future habitat (range extinction); b) low stability of current habitat (≤10% remains); c) no gain of habitat in new locations; d) all future habitat is in new locations (i.e. completely displaced from current habitat); and e) substantial increase in size of habitat (future habitat is ≥100% larger than current). We found that some SDM methods were significantly more likely than others to predict extreme changes. In particular, distance-based models were significantly less likely than other methods to predict substantial increases in habitat size; Random Forest models and Surface Range Envelopes were significantly more likely to predict a complete loss of current habitat, and future range extinction. Generalised Additive Models and Generalised Linear Models rarely predicted range extinction; future habitat completely disjunct from current habitat was predicted more frequently than expected by Classification Tree Analysis and less frequently by Maxent. Random Forest generally predicted extreme range changes more frequently than other SDM methods. Our results identify trends among different methods with respect to tendency to predict extreme range changes. These are of significance for climate-impact assessments, with implications for transferability of models to novel environments. Our findings emphasise the need to explore and justify the use of different models and their parameterisations, and to develop approaches to assist with optimisation of models.

Globally, local governments are increasing investment in urban greening projects. However, there is little consideration of whether the species being planted will be resilient to climate change. We assessed the distribution of climatically suitable habitat, now and in the future, for 176 tree species native to Australia, commonly planted across Australia's Significant Urban Areas (SUAs) and currently grown by commercial nurseries. Species' occurrence records were obtained from inventories and herbaria, globally and across Australia, and combined with baseline climate data (WorldClim, 1960-1990) and six climate scenarios for 2030 and 2070 using climatic suitability models (CSMs). CSMs for each species were calibrated and projected onto baseline and future scenarios. We calculated changes in the size of climatically suitable habitat for each species across each SUA, and identified urban areas that are likely to have suitable climate for either fewer or more of our study species under future climate. By 2070, climatically suitable habitat in SUAs is predicted to decline for 73% of species assessed. For 18% of these species, climatically suitable area is predicted to be more than halved, relative to their baseline extent. Generally, for urban areas in cooler regions, climatically suitable habitat is predicted to increase. By contrast, for urban areas in warmer regions, a greater proportion of tree species may lose climatically suitable habitat. Our results highlight changing patterns of urban climatic space for commonly planted species, suggesting that local governments and the horticultural industry should take a proactive approach to identify new climate-ready species for urban plantings.

Tephritid fruit flies are among the most destructive horticultural pests and pose risks to Australia’s multi-billion-dollar horticulture industry. Currently, there are 11 pest fruit fly species of economic concern present in various regions of Australia. Of these, nine are native to this continent (Bactrocera aquilonis, B. bryoniae, B. halfordiae, B. jarvisi, B. kraussi, B. musae, B. neohumeralis, B. tryoniandZeugodacus cucumis), whileB. frauenfeldiandCeratitis capitataare introduced. To varying degrees these species are costly to Australia’s horticulture through in-farm management, monitoring to demonstrate pest freedom, quarantine and trade restrictions, and crop losses. Here, we used a common species distribution modelling approach, Maxent, to assess habitat suitability for these 11 species under current and future climate scenarios. These projections indicate that the Wet Tropics is likely to be vulnerable to all 11 species. The east coast of Australia will likely remain vulnerable to multiple species until at least 2070. Both the Cape York Peninsula and Northern Territory are also likely to be vulnerable, however, extrapolation to novel climates in these areas decrease confidence in model projections. The climate suitability of current major horticulture regions in north-western Australia, the Northern Territory, southern-central regions of New South Wales and southern Victoria to these pests is projected to increase as climate changes. Our study highlights areas at risk of pest range expansion in the future, to guide Australia’s horticulture industry in developing effective monitoring and management strategies.

A definitive list of invasive species traits remains elusive, perhaps due to inconsistent ways of identifying invasive species. Invasive species are typically identified using one or more of four demographic criteria (local abundance, geographic range, environmental range, spread rate), referred to here as the demographic dimensions of invasiveness. In 112 studies comparing invasive and non-invasive plant traits, all 15 combinations of the four demographic dimensions were used to identify invasive species; 22% of studies identified invasive species solely by high abundance, while 25% ignored abundance. We used demographic data of 340 alien herbs classified as invasive or non-invasive in Victoria, Australia, to test whether the demographic dimensions are independent and which dimensions influence invasive species listing in practice. Species' abundances, spread rates and range sizes were independent. Relative abundance best explained the invasiveness classification. However, invasive and non-invasive species each spanned the full range of each demographic dimension, indicating that no dimension clearly separates invasive from non-invasive species. Graminoids with longer minimum residence times were more frequently classified as invasive, as were forbs occurring near edges of native vegetation fragments. Synthesis. Conflating multiple forms of invasiveness, by not distinguishing invasive species that are identified using different demographic criteria, may obscure traits possessed by particular subsets of invasive species. Traits promoting high abundance likely differ from those enabling fast spread and broad ranges. Examining traits linked with the four demographic dimensions of invasiveness will highlight species at risk of becoming dominant, spreading quickly or occupying large ranges.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Online access to species occurrence records has opened new windows into investigating biodiversity patterns across multiple scales. The value of these records for research depends on their spatial, temporal, and taxonomic quality. We assessed temporal patterns in records from the Australasian Virtual Herbarium, asking: (1) How temporally consistent has collecting been across Australia? (2) Which areas of Australia have the most reliable records, in terms of temporal consistency and inventory completeness? (3) Are there temporal trends in the completeness of attribute information associated with records? We undertook a multi-step filtering procedure, then estimated temporal consistency and inventory completeness for sampling units (SUs) of 50 km × 50 km. We found temporal bias in collecting, with 80% of records collected over the period 1970–1999. South-eastern Australia, the Wet Tropics in north-east Queensland, and parts of Western Australia have received the most consistent sampling effort over time, whereas much of central Australia has had low temporal consistency. Of the SUs, 18% have relatively complete inventories with high temporal consistency in sampling. We also determined that 25% of digitized records had missing attribute information. By identifying areas with low reliability, we can limit erroneous inferences about distribution patterns and identify priority areas for future sampling.

Motivation: Past sea level fluctuations have shaped island area and archipelago configuration. The availability of global high‐resolution data on bathymetry and past sea levels allows reconstruction of island palaeo‐geography. Studies on the role of palaeo‐area often consider only the Last Glacial Maximum, which neglects the dynamics of island fusion and fission resulting from cyclic sea level fluctuations throughout the Quaternary. Currently, no global database is available to test the role of changing island geographies driven by Quaternary sea level change on evolutionary, ecological and archaeological patterns. However, data on island palaeo‐environments is crucial for understanding insular biodiversity distributions and human settlement patterns. Here, we present the Palaeo‐Islands and Archipelago Configuration (PIAC) database, containing sea level‐driven palaeo‐geography changes over the late Quaternary of 178 islands in 27 archipelagos, and discuss its relevance, limitations and uncertainties. The R functions developed to create the PIAC database are provided to allow calculations for other islands, time steps, sea‐level curves and higher spatio‐temporal resolutions.Main types of variables contained: Polygon shapefiles with archipelago configuration and tables with palaeo‐area per island.Spatial location and grain: The database has a global representation, with 27 archipelagos being covered: Aldabra, Azores, Balearic Islands, California Channel Islands, Canary Islands, Cape Verde, Comoros, Cook Islands, Crozet Islands, Dutch Caribbean, Galápagos, Gulf of Guinea, Hawaii, Inner Seychelles, Juan Fernández, Kuril Islands, Madeira, Marianas, Marquesas, Mascarenes, Phoenix Islands, Pitcairn Islands, Prince Edward Islands, Revillagigedo, Samoan Islands, Society Islands and Tristan da Cunha. All data are at 1 km2 spatial resolution. Time period and grain: The focus of this paper is on the last 35 kyr; data for the last 140 kyr are also provided. The grain is 1 kyr temporal resolution.Level of measurement: Data are per island, grouped per archipelago.Software format: The data were produced in the R programming language.

Contamination of aquatic habitats with pharmaceuticals is a major environmental concern. Recent studies have detected pharmaceutical pollutants in a wide array of ecosystems and organisms, with many of these contaminants being highly resistant to biodegradation and capable of eliciting sub-lethal effects in non-target species. One such pollutant is fluoxetine, a widely prescribed antidepressant, which is frequently detected in surface waters globally and can alter physiology and behaviour in aquatic organisms. Despite this, relatively little is known about the potential for fluoxetine to disrupt mechanisms of sexual selection. Here, we investigate the impacts of 30-day exposure to two environmentally realistic levels of fluoxetine (low and high) on mechanisms of pre- and post-copulatory sexual selection in the eastern mosquitofish (Gambusia holbrooki). We tested 1) male mating behaviour in the absence or presence of a competitor male, and 2) sperm quality and quantity. We found that high-fluoxetine exposure increased male copulatory behaviour in the absence of a competitor, while no effect was detected under male-male competition. Further, fluoxetine exposure at both concentrations increased total sperm count relative to males from the control group, while no significant change in sperm quality was observed. Lastly, low-fluoxetine males showed a significant reduction in condition index (mass relative to length). Our study is the first to show altered mechanisms of both pre- and post-copulatory sexual selection in an aquatic species resulting from environmentally realistic fluoxetine exposure, highlighting the capacity of pharmaceutical pollution to interfere with sensitive reproductive processes in wildlife.

Climate change directly affects the suitability of habitats for species, but also indirectly alters natural disturbances such as fire, which can negatively impact species’ persistence. Developing accurate predictions of climate change impacts requires estimates of the interactive effects of climate and disturbance regimes at both population and landscape scales. Here we couple a habitat suitability model with a population viability model to examine the interactive effects of climate change and altered fire regimes on a fire-responsive frog species across its geographic range in south-eastern Australia. By 2100, we predict expected minimum abundances (EMA) to decline by 66% (under GFDL-CM2 A1FI climate projections) or 87% (CSIRO Mk3.5 A1FI) in the absence of fire. Increased frequency of low-intensity fires reduced EMA by less than 5%, whereas increased frequency of high-intensity fires reduced EMA by up to 40% compared with the no-fire scenario. While shifts in fire regimes are predicted to impact metapopulation viability, these indirect effects of fire are far less severe than the direct impact of climate change on habitat suitability. Exploring the interactive impacts of climate change and altered disturbance regimes can help managers prioritize threats across space and time.

The ability of species to track their climate niche is dependent on their dispersal potential and the connectivity of the landscape matrix linking current and future suitable habitat. However, studies modeling climate-driven range shifts rarely address the movement of species across landscapes realistically, often assuming “unlimited” or “no” dispersal. Here, we incorporate dispersal rate and landscape connectivity with a species distribution model (Maxent) to assess the extent to which the Cunningham’s skink (Egernia cunninghami) may be capable of tracking spatial shifts in suitable habitat as climate changes. Our model was projected onto four contrasting, but equally plausible, scenarios describing futures that are (relative to now) hot/wet, warm/dry, hot/with similar precipitation and warm/wet, at six time horizons with decadal intervals (2020–2070) and at two spatial resolutions: 1 km and 250 m. The size of suitable habitat was projected to decline 23–63% at 1 km and 26–64% at 250 m, by 2070. Combining Maxent output with the dispersal rate of the species and connectivity of the intervening landscape matrix showed that most current populations in regions projected to become unsuitable in the medium to long term, will be unable to shift the distance necessary to reach suitable habitat. In particular, numerous populations currently inhabiting the trailing edge of the species’ range are highly unlikely to be able to disperse fast enough to track climate change. Unless these populations are capable of adaptation they are likely to be extirpated. We note, however, that the core of the species distribution remains suitable across the broad spectrum of climate scenarios considered. Our findings highlight challenges faced by philopatric species and the importance of adaptation for the persistence of peripheral populations under climate change.

BackgroundShrubs play a key role in biogeochemical cycles, prevent soil and water erosion, provide forage for livestock, and are a source of food, wood and non-wood products. However, despite their ecological and societal importance, the influence of different environmental variables on shrub distributions remains unclear. We evaluated the influence of climate and soil characteristics, and whether including soil variables improved the performance of a species distribution model (SDM), Maxent.MethodsThis study assessed variation in predictions of environmental suitability for 29 Australian shrub species (representing dominant members of six shrubland classes) due to the use of alternative sets of predictor variables. Models were calibrated with (1) climate variables only, (2) climate and soil variables, and (3) soil variables only.ResultsThe predictive power of SDMs differed substantially across species, but generally models calibrated with both climate and soil data performed better than those calibrated only with climate variables. Models calibrated solely with soil variables were the least accurate. We found regional differences in potential shrub species richness across Australia due to the use of different sets of variables.ConclusionsOur study provides evidence that predicted patterns of species richness may be sensitive to the choice of predictor set when multiple, plausible alternatives exist, and demonstrates the importance of considering soil properties when modeling availability of habitat for plants.

Anthropogenic climate change is a key threat to global biodiversity. To inform strategic actions aimed at conserving biodiversity as climate changes, conservation planners need early warning of the risks faced by different species. The IUCN Red List criteria for threatened species are widely acknowledged as useful risk assessment tools for informing conservation under constraints imposed by limited data. However, doubts have been expressed about the ability of the criteria to detect risks imposed by potentially slow-acting threats such as climate change, particularly because criteria addressing rates of population decline are assessed over time scales as short as 10 years. We used spatially explicit stochastic population models and dynamic species distribution models projected to future climates to determine how long before extinction a species would become eligible for listing as threatened based on the IUCN Red List criteria. We focused on a short-lived frog species (Assa darlingtoni) chosen specifically to represent potential weaknesses in the criteria to allow detailed consideration of the analytical issues and to develop an approach for wider application. The criteria were more sensitive to climate change than previously anticipated; lead times between initial listing in a threatened category and predicted extinction varied from 40 to 80 years, depending on data availability. We attributed this sensitivity primarily to the ensemble properties of the criteria that assess contrasting symptoms of extinction risk. Nevertheless, we recommend the robustness of the criteria warrants further investigation across species with contrasting life histories and patterns of decline. The adequacy of these lead times for early warning depends on practicalities of environmental policy and management, bureaucratic or political inertia, and the anticipated species response times to management actions.

Aim: Population viability analysis (PVA) is used to quantify the risks faced by species under alternative management regimes. Bayesian PVAs allow uncertainty in the parameters of the underlying population model to be easily propagated through to the predictions. We developed a Bayesian stochastic patch occupancy model (SPOM) and used this model to assess the viability of a metapopulation of the growling grass frog (Litoria raniformis) under different urbanization scenarios. Location: Melbourne, Victoria, Australia. Methods: We fitted a Bayesian model that accounted for imperfect detection to a multiseason occupancy dataset for L. raniformis collected across northern Melbourne. The probability of extinction was modelled as a function of effective wetland area, aquatic vegetation cover and connectivity, using logistic regression. The probability of colonization was modelled as a function of connectivity alone. We then simulated the dynamics of a metapopulation of L. raniformis subject to differing levels of urbanization and compensatory wetland creation. Uncertainty was propagated by conducting simulations for 5000 estimates of the parameters of the models for extinction and colonization. Results: There was considerable uncertainty in both the probability of quasi-extinction and the minimum number of occupied wetlands under most urbanization scenarios. Uncertainty around the change in quasi-extinction risk and minimum metapopulation size increased with increasing habitat loss. For our focal metapopulation, the analysis revealed that significant investment in new wetlands may be required to offset the impacts of urbanization. Main conclusions: Bayesian approaches to PVA allow parametric uncertainty to be propagated and considered in management decisions. They also provide means of identifying parameters that represent critical uncertainties, and, through the use of informative priors, can easily assimilate new data to reduce parametric uncertainty. These advantages, and the ready availability of software to run Bayesian analyses, will ensure that Bayesian approaches are used increasingly for PVAs. © 2013 John Wiley & Sons Ltd.

Environmental factors may affect chemical communication between individuals by limiting their ability to detect and respond to these signals. One such factor, high humidity, has been shown to interfere with the normal response of some invertebrate species to their attractant pheromones. The effect of humidity on the response of the five-spined bark beetle, Ips grandicollis, to a synthetic form of the aggregation pheromone component ipsenol, was tested in an experimental chamber in the laboratory. The response was measured as both the number of beetles to reach the pheromone source and the time taken, and was tested under high (>80% relative humidity) and low (30–40% relative humidity) conditions of humidity. There was no significant difference in response of beetles between the two treatments although there was a reduction in response in the high-humidity treatment when relative humidity levels were in excess of 90%. These findings suggest that atmospheric humidity does not influence bark beetles response to synthetic pheromone, except perhaps in unlikely conditions of excessive humidity.

Chemical pollution is a pervasive and insidious agent of environmental change. One class of chemical pollutant threatening ecosystems globally is the endocrine disrupting chemicals (EDCs). The capacity of EDCs to disrupt development and reproduction is well established, but their effects on behaviour have received far less attention. Here, we investigate the impact of a widespread androgenic EDC on reproductive behaviour in the guppy, Poecilia reticulata. We found that short-term exposure of male guppies to an environmentally relevant concentration of 17β-trenbolone-a common environmental pollutant associated with livestock production-influenced the amount of male courtship and forced copulatory behaviour (sneaking) performed toward females, as well as the receptivity of females toward exposed males. Exposure to 17β-trenbolone was also associated with greater male mass. However, no effect of female exposure to 17β-trenbolone was detected on female reproductive behaviour, indicating sex-specific vulnerability at this dosage. Our study is the first to show altered male reproductive behaviour following exposure to an environmentally realistic concentration of 17β-trenbolone, demonstrating the possibility of widespread disruption of mating systems of aquatic organisms by common agricultural contaminants.

Anthropogenic climate change is a key threat to global biodiversity. To inform strategic actions aimed at conserving biodiversity as climate changes, conservation planners need early warning of the risks faced by different species. The IUCN Red List criteria for threatened species are widely acknowledged as useful risk assessment tools for informing conservation under constraints imposed by limited data. However, doubts have been expressed about the ability of the criteria to detect risks imposed by potentially slow-acting threats such as climate change, particularly because criteria addressing rates of population decline are assessed over time scales as short as 10 years. We used spatially explicit stochastic population models and dynamic species distribution models projected to future climates to determine how long before extinction a species would become eligible for listing as threatened based on the IUCN Red List criteria. We focused on a short-lived frog species (Assa darlingtoni) chosen specifically to represent potential weaknesses in the criteria to allow detailed consideration of the analytical issues and to develop an approach for wider application. The criteria were more sensitive to climate change than previously anticipated; lead times between initial listing in a threatened category and predicted extinction varied from 40 to 80 years, depending on data availability. We attributed this sensitivity primarily to the ensemble properties of the criteria that assess contrasting symptoms of extinction risk. Nevertheless, we recommend the robustness of the criteria warrants further investigation across species with contrasting life histories and patterns of decline. The adequacy of these lead times for early warning depends on practicalities of environmental policy and management, bureaucratic or political inertia, and the anticipated species response times to management actions.

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on‐ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision‐making contexts when used within a structured and transparent decision‐making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision‐making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes. AG's stay in Brisbane, Australia, was supported by the CSIRO McMaster Foundation. The three workshops (held on December 2011, April and May 2012) that led to this publication were organised with financial support and within the framework of the Australian Research Council Centre of Excellence for Environmental Decisions (CEED; http://www.ceed.edu.au) led by HPP. AG benefitted from insights from a project on applying SDMs to invasive management in Switzerland granted by the Swiss Federal Office of the Environment (FOEN) and the National Centre for Competence in Research (NCCR) ‘Plant Survival’ in Neuchâtel. LB benefitted from support from the Catalan Government (CARTOBIO and 2010‐BE‐272 projects) and the EU‐FP7 SCALES (#226852) to attend the workshops.