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Context The cane toad (Rhinella marina) is one of the most globally significant and well-studied invasive alien species, and the detrimental impacts of its invasions warrant the design and application of decision support tools. While many models have been developed for guiding policies addressing cane toad invasions, none reliably predict the species’ population dynamics at scales relevant to on-the-ground management. Objectives We describe virToad—an individual-based life-history simulator of the cane toad. We then illustrate virToad’s ability to forecast the cane toad’s spatiotemporal population dynamics at local- to landscape-scales, and its potential for improving management responses to cane toad invasions. Methods We designed virToad to make population dynamics an emergent consequence of the cane toad’s fitness-maximising behavioural responses to mechanistic constraints (e.g., water availability, kin selection), and to management actions. We used virToad to simulate cane toad population dynamics in the absence of management, and under alternative management strategies implemented across a spectrum of effort: hand-capturing and trapping of juveniles and adults, fencing waterbodies, and trapping and chemically suppressing tadpoles. Results virToad produced plausible predictions of cane toad population densities, detection probabilities, distributions, and spatial segregation. Simulation experiments indicated that the efficacy of competing management actions varied significantly, and that only moderate to high effort hand-capturing and trapping of juveniles and adults had the potential to suppress invasions. Conclusion virToad is an open-source, rigorous, and extensible decision support platform that will enable researchers and practitioners to defensibly forecast local- to landscape-scale cane toad spatiotemporal population dynamics and management outcomes.

Aim: The incidence of major fires is increasing globally, creating extraordinary challenges for governments, managers and conservation scientists. In 2019–2020, Australia experienced precedent-setting fires that burned over several months, affecting seven states and territories and causing massive biodiversity loss. Whilst the fires were still burning, the Australian Government convened a biodiversity Expert Panel to guide its bushfire response. A pressing need was to target emergency investment and management to reduce the chance of extinctions and maximise the chances of longer-term recovery. We describe the approach taken to rapidly prioritise fire-affected animal species. We use the experience to consider the organisational and data requirements for evidence-based responses to future ecological disasters. Location: Forested biomes of subtropical and temperate Australia, with lessons for other regions. Methods: We developed assessment frameworks to screen fire-affected species based on their pre-fire conservation status, the proportion of their distribution overlapping with fires, and their behavioural/ecological traits relating to fire vulnerability. Using formal and informal networks of scientists, government and non-government staff and managers, we collated expert input and data from multiple sources, undertook the analyses, and completed the assessments in 3 weeks for vertebrates and 8 weeks for invertebrates. Results: The assessments prioritised 92 vertebrate and 213 invertebrate species for urgent management response; another 147 invertebrate species were placed on a watchlist requiring further information. Conclusions: The priority species lists helped focus government and non-government investment, management and research effort, and communication to the public. Using multiple expert networks allowed the assessments to be completed rapidly using the best information available. However, the assessments highlighted substantial gaps in data availability and access, deficiencies in statutory threatened species listings, and the need for capacity-building across the conservation science and management sectors. We outline a flexible template for using evidence effectively in emergency responses for future ecological disasters.

Australia is in the midst of an extinction crisis, having already lost 10% of terrestrial mammal fauna since European settlement and with hundreds of other species at high risk of extinction. The decline of the nation's biota is a result of an array of threatening processes; however, a comprehensive taxon‐specific understanding of threats and their relative impacts remains undocumented nationally. Using expert consultation, we compile the first complete, validated, and consistent taxon‐specific threat and impact dataset for all nationally listed threatened taxa in Australia. We confined our analysis to 1,795 terrestrial and aquatic taxa listed as threatened (Vulnerable, Endangered, or Critically Endangered) under Australian Commonwealth law. We engaged taxonomic experts to generate taxon‐specific threat and threat impact information to consistently apply the IUCN Threat Classification Scheme and Threat Impact Scoring System, as well as eight broad‐level threats and 51 subcategory threats, for all 1,795 threatened terrestrial and aquatic threatened taxa. This compilation produced 4,877 unique taxon–threat–impact combinations with the most frequently listed threats being Habitat loss, fragmentation, and degradation (n = 1,210 taxa), and Invasive species and disease (n = 966 taxa). Yet when only high‐impact threats or medium‐impact threats are considered, Invasive species and disease become the most prevalent threats. This dataset provides critical information for conservation action planning, national legislation and policy, and prioritizing investments in threatened species management and recovery., Australia is in the midst of an extinction crisis as a result of an array of threatening processes; however, a comprehensive taxon‐specific understanding of threats and their relative impacts remains undocumented nationally. Using expert consultation, we compile the first complete, validated, and consistent taxon‐specific threat and impact dataset for all 1,796 nationally listed threatened taxa in Australia. This compilation produced 4,877 unique taxon–threat combinations with the most frequently listed threats being Habitat loss, fragmentation, and degradation (n = 1,210 taxa), and Invasive species and disease (n = 966 taxa).

Rocky environments host rich levels of biodiversity and provide vital habitat for specialised organisms, range-restricted species and a broad range of ectotherms adapted to saxicoline environments. In Australia, rock habitat is being destroyed during soil amelioration practices associated with agricultural intensification. Advances in rock crushing technology, developed to expand or increase crop yields and efficiency, pose an undocumented threat to global biodiversity, especially reptiles dependent on non-renewable rock habitat in agricultural landscapes. Rock removal is a legislated key threatening process in parts of Australia and will accelerate biodiversity loss if not mitigated. We estimated reptile species’ range overlap with dryland cropping and modified pastoral regions within the Australian wheat-sheep zone to assess the potential impacts of rock crushing practices. We examined species- and family-richness within the impact zone and across bioregions within the impact zone, to identify areas where rock removal has the greatest potential to impact terrestrial and fossorial squamates. Our analysis revealed that 159 potentially impacted reptile species occur within the study area, representing 16% of Australian terrestrial squamates. Fourteen of these species, including six threatened species, have more than 50% range overlap with areas of intensive agriculture, and include several endangered pygopodids, scincids and agamids. Bioregions rich in rock and burrow-dwelling reptiles include the Brigalow Belt South, Murray Darling Depression, Darling Riverine Plains, Eyre Yorke Block, Avon Wheatbelt, Nandewar, Flinders Lofty Block and New South Wales South Western Slopes. Synthesis and applications. The conservation of reptiles in agricultural landscapes requires appropriate management and retention of surface rocks. Potential yield increases from destroying rock habitat to intensify or expand cropland will not compensate for the net loss of reptile populations dependent on non-renewable resources. Financial incentives to prevent the expansion and transformation of non-arable landscapes to cropland are required to prevent the ongoing loss of biodiversity.

Environmental DNA (eDNA) sampling is a promising method for surveying aquatic fauna. Recent eDNA studies have investigated the likelihood of false negative errors in the laboratory and in the field, but the likelihood of false positives remains poorly studied. We investigated the likelihood of both types of errors in eDNA surveys of an Australian threatened freshwater fish (Galaxiella pusilla) using laboratory experiments, field surveys, and recent advances in hierarchical site occupancy‐detection modeling. Laboratory experiments revealed high primer/probe specificity; absence of sample contamination in extraction and qPCR blanks; and rapid accumulation and deterioration of eDNA in aquaria. Hierarchical site occupancy‐detection models fitted to pilot data collected at 13 wetlands revealed that two water samples, each with two qPCRs, would be required to achieve a cumulative detection probability >.95. A more comprehensive survey, in which we simultaneously used dip netting and eDNA sampling at 29 wetlands, revealed similar mean detection probabilities of the two sampling methods (trapping: 0.74 vs. eDNA: 0.68), and low probabilities of false positive errors at the water sample level (0.0080) and at the qPCR level (0.0039) for eDNA sampling. Collectively, our results illustrate that eDNA sampling can be a sensitive and specific method for monitoring the occurrence of freshwater fauna. Detection probabilities of eDNA sampling were comparable to those of a traditional sampling method, and probabilities of laboratory‐induced false positives were low. Future studies employing eDNA sampling should estimate, and properly account for, false positive errors in addition to false negatives.

Joint species distribution models (JSDMs) simultaneously model the distributions of multiple species, while accounting for residual co-occurrence patterns. Despite increasing adoption of JSDMs in the literature, the question of how to define and evaluate JSDM predictions has only begun to be explored. We define four different JSDM prediction types that correspond to different aspects of species distribution and community assemblage processes. Marginal predictions are environment-only predictions akin to predictions from single-species models; joint predictions simultaneously predict entire community assemblages; and conditional marginal and conditional joint predictions are made at the species or assemblage level, conditional on the known occurrence state of one or more species at a site. We define five different classes of metrics that can be used to evaluate these types of predictions: threshold-dependent, threshold-independent, community dissimilarity, species richness and likelihood metrics. We illustrate different prediction types and evaluation metrics using a case study in which we fit a JSDM to a frog occurrence dataset collected in Melbourne, Australia. Joint species distribution models present opportunities to investigate the facets of species distribution and community assemblage processes that are not possible to explore with single-species models. We show that there are a variety of different metrics available to evaluate JSDM predictions, and that choice of prediction type and evaluation metric should closely match the questions being investigated.

Environmental DNA (eDNA) sampling can provide accurate, cost-effective, landscape-level data on species distributions. Previous studies have compared the sensitivity of eDNA sampling to traditional sampling methods for single species, but similar comparative studies on multispecies eDNA metabarcoding are rare. Using hierarchical site occupancy detection models, we examined whether key choices associated with eDNA metabarcoding (primer selection, low-abundance read filtering and the number of positive water samples used to classify a species as present at a site) affect the sensitivity of metabarcoding, relative to backpack electrofishing for fish in freshwater streams. Under all scenarios (teleostei and vertebrate primers; 0%, 0.1% and 1% read filtering thresholds; one or two positive samples required to classify species as present), we found that eDNA metabarcoding is, on average, more sensitive than electrofishing. Combining vertebrate and teleostei markers resulted in higher detection probabilities relative to the use of either marker in isolation. Increasing the threshold used to filter low-abundance reads decreased species detection probabilities but did not change our overall finding that eDNA metabarcoding was more sensitive than electrofishing. Using a threshold of two positive water samples (out of five) to classify a species as present typically had negligible effects on detection probabilities compared to using one positive water sample. Our findings demonstrate that eDNA metabarcoding is generally more sensitive than electrofishing for conducting fish surveys in freshwater streams, and that this outcome is not sensitive to methodological decisions associated with metabarcoding.

The Red List of Threatened Species, published by the International Union for Conservation of Nature (IUCN), is a crucial tool for conservation decision making. However, despite substantial effort, numerous species remain unassessed, or have insufficient data available to be assigned a Red List threat category. Moreover, the Red Listing process is subject to various sources of uncertainty and bias. The development of robust automated assessment methods could serve as an efficient and highly useful tool to accelerate the assessment process and offer provisional assessments. Here we aimed to: 1) present a machine learning based automated threat assessment method that can be used on less known species; 2) offer provisional assessments for all reptiles - the only major tetrapod group without a comprehensive Red List assessment; and 3) evaluate potential effects of human decision biases on the outcome of assessments. We use the method presented here to assess 4,369 reptile species that are currently unassessed or classified as Data Deficient by the IUCN. Our models range in accuracy from 88% to 93% for classifying species as threatened/non-threatened, and from 82% to 87% for predicting specific threat categories. Unassessed and Data Deficient reptiles were more likely to be threatened than assessed species, adding to mounting evidence that they should be considered threatened by default. The overall proportion of threatened species greatly increased when we included our provisional assessments. Assessor identities strongly affected prediction outcomes, suggesting that assessor effects need to be carefully considered in extinction risk assessments. Regions and taxa we identified as likely to be more threatened should be given increased attention in new assessments and conservation planning. Lastly, the method we present here can be easily implemented to help bridge the assessment gap on other less known taxa.

Smooth newts (Lissotriton vulgaris) established recently in Melbourne, Australia. Previously, the population's disease status was unknown. Samples from 34 adults and 78 larvae, collected 2011-16, were tested for two pathogens driving the global amphibian extinction crisis. The fungus Batrachochytrium dendrobatidis was identified (6.3% quantitative PCR positive); ranaviruses were not detected.

AimViviparity has evolved more times in squamates than in any other vertebrate group; therefore, squamates offer an excellent model system in which to study the patterns, drivers and implications of reproductive mode evolution. Based on current species distributions, we examined three selective forces hypothesized to drive the evolution of squamate viviparity (cold climate, variable climate and hypoxic conditions) and tested whether viviparity is associated with larger body size.LocationGlobal.Time periodPresent day.TaxonSquamata.MethodsWe compiled a dataset of 9061 squamate species, including their distributions, elevation, climate, body mass and reproductive modes. We applied species-level and assemblage-level approaches for predicting reproductive mode, both globally and within biogeographical realms. We tested the relationships of temperature, interannual and intra-annual climatic variation, elevation (as a proxy for hypoxic conditions) and body mass with reproductive mode, using path analyses to account for correlations among the environmental predictors.ResultsViviparity was strongly associated with cold climates at both species and assemblage levels, despite the prevalence of viviparity in some warm climates. Viviparity was not clearly correlated with climatic variability or elevation. The probability of being viviparous exhibited a weak positive correlation with body size.ConclusionsAlthough phylogenetic history is important, potentially explaining the occurrence of viviparous species in regions that are warm at present, current global squamate distribution is characterized by a higher relative abundance of viviparity in cold environments, supporting the prediction of the “cold-climate” hypothesis. The roles of climatic variation and hypoxia are less important and not straightforward. Elevation probably exerts various selective pressures and influences the prevalence of viviparity primarily through its effect on temperature rather than on oxygen concentration.

The Red List of Threatened Species, published by the International Union for Conservation of Nature (IUCN), is a crucial tool for conservation decision-making. However, despite substantial effort, numerous species remain unassessed or have insufficient data available to be assigned a Red List extinction risk category. Moreover, the Red Listing process is subject to various sources of uncertainty and bias. The development of robust automated assessment methods could serve as an efficient and highly useful tool to accelerate the assessment process and offer provisional assessments. Here, we aimed to (1) present a machine learning–based automated extinction risk assessment method that can be used on less known species; (2) offer provisional assessments for all reptiles—the only major tetrapod group without a comprehensive Red List assessment; and (3) evaluate potential effects of human decision biases on the outcome of assessments. We use the method presented here to assess 4,369 reptile species that are currently unassessed or classified as Data Deficient by the IUCN. The models used in our predictions were 90% accurate in classifying species as threatened/nonthreatened, and 84% accurate in predicting specific extinction risk categories. Unassessed and Data Deficient reptiles were considerably more likely to be threatened than assessed species, adding to mounting evidence that these species warrant more conservation attention. The overall proportion of threatened species greatly increased when we included our provisional assessments. Assessor identities strongly affected prediction outcomes, suggesting that assessor effects need to be carefully considered in extinction risk assessments. Regions and taxa we identified as likely to be more threatened should be given increased attention in new assessments and conservation planning. Lastly, the method we present here can be easily implemented to help bridge the assessment gap for other less known taxa.

Behavior-modifying drugs, such as antidepressants, are increasingly being detected in waterways and aquatic wildlife around the globe. Typically, behavioral effects of these contaminants are assessed using animals tested in social isolation. However, for group-living species, effects seen in isolation may not reflect those occurring in realistic social settings. Furthermore, interactions between chemical pollution and other stressors, such as predation risk, are seldom considered. This is true even though animals in the wild are rarely, if ever, confronted by chemical pollution as a single stressor. Here, in a 2 year multigenerational experiment, we tested for effects of the antidepressant fluoxetine (measured concentrations [±SD]: 42.27 ± 36.14 and 359.06 ± 262.65 ng/L) on shoaling behavior in guppies (Poecilia reticulata) across different social contexts and under varying levels of perceived predation risk. Shoaling propensity and shoal choice (choice of groups with different densities) were assessed in a Y-maze under the presence of a predatory or nonpredatory heterospecific, with guppies tested individually and in male-female pairs. When tested individually, no effect of fluoxetine was seen on shoaling behavior. However, in paired trials, high-fluoxetine-exposed fish exhibited a significantly greater shoaling propensity. Hence, effects of fluoxetine were mediated by social context, highlighting the importance of this fundamental but rarely considered factor when evaluating impacts of environmental pollution.

Species population dynamics are driven by spatial and temporal changes in the environment, anthropogenic activities and conservation management actions. Understanding how populations will change in response to these drivers is fundamental to a wide range of ecological applications, but there are few open-source software options accessible to researchers and managers that allow them to predict these changes in a flexible and transparent way. We introduce an open-source, multi-platform r package, steps, that models spatial changes in species populations as a function of drivers of distribution and abundance, such as climate, disturbance, landscape dynamics and species ecological and physiological requirements. To illustrate the functionality of steps, we model the population dynamics of the greater glider Petauroides volans, an arboreal Australian mammal. We demonstrate how steps can be used to simulate population responses of the glider to forest dynamics and management with the types of data commonly used in ecological analyses. steps expands on the features found in existing software packages, can easily incorporate a range of spatial layers (e.g. habitat suitability, vegetation dynamics and disturbances), facilitates integrated and transparent analyses within a single platform and produces interpretable outputs of changes in species' populations through space and time. Further, steps offers both ready-to-use, built-in functionality, as well as the ability for advanced users to define their own modules for custom analyses. Thus, we anticipate that steps will be of significant value to environment and wildlife managers and researchers from a broad range of disciplines.

Environmental DNA, or eDNA—DNA shed from organisms and extracted from environmental samples—is an emerging survey technique that has the potential to transform biodiversity monitoring in freshwater ecosystems. We provide a brief overview of the primary methodological aspects of eDNA sampling that ecologists should consider before taking environmental samples in the field. We outline five key methodological considerations: (i) targeting single species vs multiple species; (ii) where and when to sample; (iii) how much water to collect; (iv) how many samples to take; and (v) recognising potential sources of false positives. The need to account for false negatives and false positives in eDNA surveys, and the power of species occupancy detection models in accounting for imperfect detection, is also discussed.

Insights into the causal mechanisms that limit species distributions are likely to improve our ability to anticipate species range shifts in response to climate change. For species with complex life histories, a mechanistic understanding of how climate affects different lifecycle stages may be crucial for making accurate forecasts. Here, we use mechanistic niche modeling (NicheMapR) to derive "proximate" (mechanistic) variables for tadpole, juvenile, and adult Rana temporaria. We modeled the hydroperiod, and maximum and minimum temperatures of shallow (30 cm) ponds, as well as activity windows for juveniles and adults. We then used those ("proximate") variables in correlative ecological niche models (Maxent) to assess their role in limiting the species' current distribution, and to investigate the potential effects of climate change on R. temporaria across Europe. We further compared the results with a model based on commonly used macroclimatic ("distal") layers (i.e., bioclimatic layers from WorldClim). The maximum temperature of the warmest month (a macroclimatic variable) and maximum pond temperatures (a mechanistic variable) were the most important range-limiting factors, and maximum temperature thresholds were consistent with the observed upper thermal limit of R. temporaria tadpoles. We found that range shift forecasts in central Europe are far more pessimistic when using distal macroclimatic variables, compared to projections based on proximate mechanistic variables. However, both approaches predicted extensive decreases in climatic suitability in southern Europe, which harbors a significant fraction of the species' genetic diversity. We show how mechanistic modeling provides ways to depict gridded layers that directly reflect the microenvironments experienced by organisms at continental scales, and to reconstruct those predictors without extrapolation under novel future conditions. Furthermore, incorporating those predictors in correlative ecological niche models can help shed light on range-limiting processes, and can have substantial impacts on predictions of climate-induced range shifts.

Invasive alien species are repeatedly shown to be amongst the top threats to biodiversity globally. Robust indicators for measuring the status and trends of biological invasions are lacking, but essential for monitoring biological invasions and the effectiveness of interventions. Here, we formulate and demonstrate three such indicators that capture the key dimensions of species invasions, each a significant and necessary advance to inform invasive alien species policy targets: 1) Rate of Invasive Alien Species Spread, which provides modelled rates of ongoing introductions of species based on invasion discovery and reporting. 2) Impact Risk, that estimates invasive alien species impacts on the environment in space and time and provides a basis for nationally targeted prioritization of where best to invest in management efforts. 3) Status Information on invasive alien species, that tracks improvement in the essential dimensions of information needed to guide relevant policy and data collection and in support of assessing invasive alien species spread and impact. We show how proximal, model-informed status and trend indicators on invasive alien species can provide more effective global (and national) reporting on biological invasions, and how countries can contribute to supporting these indicators.

Our knowledge of the conservation status of reptiles, the most diverse class of terrestrial vertebrates, has improved dramatically over the past decade, but still lags behind that of the other tetrapod groups. Here, we conduct the first comprehensive evaluation (~92% of the world’s ~1,714 described species) of the conservation status of skinks (Scincidae), a speciose reptile family with a worldwide distribution. Using International Union for Conservation of Nature (IUCN) criteria, we report that ~20% of species are threatened with extinction, and nine species are Extinct or Extinct in the Wild. The highest levels of threat are evident in Madagascar and the Neotropics, and in the subfamilies Mabuyinae, Eugongylinae and Scincinae. The vast majority of threatened skink species were listed based primarily on their small geographic ranges (Criterion B, 83%; Criterion D2, 13%). Although the population trend of 42% of species was stable, 14% have declining populations. The key threats to skinks are habitat loss due to agriculture, invasive species, and biological resource use (e.g., hunting, timber harvesting). The distributions of 61% of species do not overlap with protected areas. Despite our improved knowledge of the conservation status of the world’s skinks, 8% of species remain to be assessed, and 14% are listed as Data Deficient. The conservation status of almost a quarter of the world’s skink species thus remains unknown. We use our updated knowledge of the conservation status of the group to develop and outline the priorities for the conservation assessment and management of the world’s skink species.

Niche shifts and environmental non-equilibrium in invading alien species undermine niche-based predictions of alien species’ potential distributions and, consequently, their usefulness for invasion risk assessments. Here, we compared the realized climatic niches of four alien amphibian species (Hylarana erythraea, Rhinella marina, Hoplobatrachus rugulosus, and Kaloula pulchra) in their native and Philippine-invaded ranges to investigate niche changes that have unfolded during their invasion and, with this, assessed the extent of niche conservatism and environmental equilibrium. We investigated how niche changes affected reciprocal transferability of ecological niche models (ENMs) calibrated using data from the species’ native and Philippine-invaded ranges, and both ranges combined. We found varying levels of niche change across the species’ realized climatic niches in the Philippines: climatic niche shift for H. rugulosus; niche conservatism for R. marina and K. pulchra; environmental non-equilibrium in the Philippine-invaded range for all species; and environmental non-equilibrium in the native range or adaptive changes post-introduction for all species except H. erythraea. Niche changes undermined the reciprocal transferability of ENMs calibrated using native and Philippine-invaded range data. Our paper highlights the difficulty of predicting potential distributions given niche shifts and environmental non-equilibrium; we suggest calibrating ENMs with data from species’ combined native and invaded ranges, and to regularly reassess niche changes and recalibrate ENMs as species’ invasions progress.

Cities tend to be built in areas of high biodiversity, and the accelerating pace of urbanization threatens the persistence of many species and ecological communities globally. However, urban environments also offer unique prospects for biological conservation, with multiple benefits for humans and other species. We present seven ecological principles to conserve and increase the biodiversity of cities, using metaphors to bridge the gap between the languages of built-environment and conservation professionals. We draw upon John Ruskin's famous essay on the seven lamps of architecture, but more generally on the thinking of built-environment pioneers such as Patrick Geddes (1854–1932) who proposed a synoptic view of the urban environment that included humans and non-humans alike. To explain each principle or ‘lamp’ of urban biodiversity, we use an understanding from the built-environment disciplines as a base and demonstrate through metaphor that planning for the more-than-human does not require a conceptual leap. We conclude our discussion with ten practical strategies for turning on these lamps in cities. Urban planners, architects, landscape architects, engineers and other built-environmental professionals have a key role to play in a paradigm shift to plan for the more-than-human, because of their direct influence on the evolving urban environment. This essay is intended to increase dialogue between ecologists and members of these professions, and thus increase the biodiversity of cities around the world.

1. Joint species distribution models (JSDMs) account for biotic interactions and missing environmental predictors in correlative species distribution models. Several different JSDMs have been proposed in the literature, but the use of different or conflicting nomenclature and statistical notation potentially obscures similarities and differences among them. Furthermore, new JSDM implementations have been illustrated with different case studies, preventing direct comparisons of computational and statistical performance. 2. We aim to resolve these outstanding issues by (a) highlighting similarities among seven presence–absence JSDMs using a clearly defined, singular notation; and (b) evaluating the computational and statistical performance of each JSDM using six datasets that vary widely in numbers of sites, species, and environmental covariates considered. 3. Our singular notation shows that many of the JSDMs are very similar, and in turn parameter estimates of different JSDMs are moderate to strongly, positively correlated. In contrast, the different JSDMs clearly differ in computational efficiency and memory limitations. 4. Our framework will allow ecologists to make educated decisions about the JSDM that best suits their objective, and enable wider uptake of JSDM methods among the ecological community.

Containing the spread of established invasive species is critical for minimizing their ecological impact. Effective containment requires sensitive sampling methods capable of detecting new introductions when invaders are at low density. Here we explore whether environmental DNA (eDNA) sampling could be used as a surveillance tool to detect new incursions of aquatic invasive species on offshore islands. We develop an eDNA molecular assay for invasive cane toads (Rhinella marina) in Australia, validate our assay on the mainland, and apply it to an offshore island (Moreton Island) that is a target of ongoing cane toad surveillance. Our eDNA assay correctly identified four mainland sites at which cane toads were observed, as well as a fifth site within 1 km of known populations. Five additional sites outside the cane toad’s current distribution tested negative for cane toad eDNA. Site occupancy detection models indicated that two water samples and three qPCR replicates were sufficient to achieve a cumulate detection probability > 0.95. Applying our eDNA assay to samples from 19 sites on an offshore island over a 2-year period revealed the absence of cane toad eDNA, in line with our current understanding of cane toad distribution. Our results suggest that eDNA sampling could be strategically applied to meet the Australian Commonwealth’s objective of maintaining cane toad-free offshore islands.

Environmental DNA (eDNA) sampling is a promising tool for monitoring cryptic species. Numerous studies have demonstrated that eDNA sampling can achieve higher detection rates than traditional monitoring techniques, such as trapping; however, the consequences of that sensitivity for survey design requirements and resulting survey costs have not been investigated. We demonstrate how site occupancy detection models and optimal survey design methods can be used to evaluate the cost-efficiency of eDNA sampling vs. traditional survey methods. We apply these approaches to two datasets—one in which eDNA sampling and trapping were conducted simultaneously (paired dataset), and another in which sampling methods were independently deployed (unpaired dataset)—to assess the cost-efficiency of eDNA sampling for detecting a freshwater mammal: the platypus Ornithorhynchus anatinus. Conditional probabilities of platypus eDNA being captured in a single water sample (paired dataset: 0.838, unpaired: 0.879), and detected in a single water sample by qPCR (paired: 0.892, unpaired: 0.858), were higher than the conditional probability of detecting a platypus with a single trapping visit (paired: 0.470, unpaired: 0.219). eDNA sampling was more cost-efficient than trapping, regardless of whether the management objective was to (1) minimize the survey budget needed to achieve a particular asymptotic variance of the occupancy estimator, or (2) minimize the survey budget needed to detect a change in occupancy over time. Site occupancy detection models coupled with optimal survey design methods provide a powerful means with which to compare the sensitivity and cost-efficiency of eDNA sampling vs. traditional sampling methods.

The number of alien species transported as stowaways is steadily increasing, and new approaches are urgently needed to tackle this emerging invasion pathway. We introduce a general framework for identifying high-risk transport pathways and receiving sites for alien species that are unintentionally transported via goods and services. This approach combines the probability of species arrival at transport hubs with the likelihood that the environment in the new region can sustain populations of that species. We illustrate our approach using a case study of the Asian black-spined toad (Duttaphrynus melanostictus) in Australia, a species that is of significant biosecurity concern in Australasia, Indonesia, and Madagascar. A correlative model fitted to occurrence data from the native geographic range of D. melanostictus predicted high environmental suitability at locations where the species has established alien populations globally. Applying the model to Australia revealed that transport hubs with the highest numbers of border interceptions and on-shore detections of D. melanostictus were environmentally similar to locations within the species’ native range. Numbers of D. melanostictus interceptions and detections in Australia increased over time, but were unrelated to indices of air and maritime trade volume. Instead, numbers of interceptions and detections were determined by the country of origin of airplanes (Thailand) and ships (Indonesia). Thus, the common assumption that transport pressure is correlated with invasion risk does not hold in all cases. Our work builds on previous efforts to integrate transport pressure data and species distribution models, by jointly modelling the number of intercepted and detected stowaways, while incorporating imperfect detection and the environmental suitability of receiving hubs. The approach presented here can be applied to any system for which historical biosecurity data are available, and provides an efficient means to allocate quarantine and surveillance efforts to reduce the probability of alien species establishment. This article is protected by copyright. All rights reserved.

Summary Accurate knowledge of species occurrence is fundamental to a wide variety of ecological, evolutionary and conservation applications. Assessing the presence or absence of species at sites is often complicated by imperfect detection, with different mechanisms potentially contributing to false-negative and/or false-positive errors at different sampling stages. Ambiguities in the data mean that estimation of relevant parameters might be confounded unless additional information is available to resolve those uncertainties. Here, we consider the analysis of species detection data with false-positive and false-negative errors at multiple levels. We develop and examine a two-stage occupancy-detection model for this purpose. We use profile likelihoods for identifiability analysis and estimation, and study the types of additional data required for reliable estimation. We test the model with simulated data, and then analyse data from environmental DNA (eDNA) surveys of four Australian frog species. In our case study, we consider that false positives may arise due to contamination at the water sample and quantitative PCR-sample levels, whereas false negatives may arise due to eDNA not being captured in a field sample, or due to the sensitivity of laboratory tests. We augment our eDNA survey data with data from aural surveys and laboratory calibration experiments. We demonstrate that the two-stage model with false-positive and false-negative errors is not identifiable if only survey data prone to false positives are available. At least two sources of extra information are required for reliable estimation (e.g. records from a survey method with unambiguous detections, and a calibration experiment). Alternatively, identifiability can be achieved by setting plausible bounds on false detection rates as prior information in a Bayesian setting. The results of our case study matched our simulations with respect to data requirements, and revealed false-positive rates greater than zero for all species. We provide statistical modelling tools to account for uncertainties in species occurrence survey data when false negatives and false positives could occur at multiple sampling stages. Such data are often needed to support management and policy decisions. Dealing with these uncertainties is relevant for traditional survey methods, but also for promising new techniques, such as eDNA sampling.

The vulnerability of species to climate change is jointly influenced by geographic phenotypic variation, acclimation and behavioural thermoregulation. The importance of interactions between these factors, however, remains poorly understood. We demonstrate how advances in mechanistic niche modelling can be used to integrate and assess the influence of these sources of uncertainty in forecasts of climate change impacts. We explored geographic variation in thermal tolerance (i.e. maximum and minimum thermal limits) and its potential for acclimation in juvenile European common frogs Rana temporaria along elevational gradients. Furthermore, we employed a mechanistic niche model (NicheMapR) to assess the relative contributions of phenotypic variation, acclimation and thermoregulation in determining the impacts of climate change on thermal safety margins and activity windows. Our analyses revealed that high-elevation populations had slightly wider tolerance ranges driven by increases in heat tolerance but lower potential for acclimation. Plausibly, wider thermal fluctuations at high elevations favour more tolerant but less plastic phenotypes, thus reducing the risk of encountering stressful temperatures during unpredictable extreme events. Biophysical models of thermal exposure indicated that observed phenotypic and plastic differences provide limited protection from changing climates. Indeed, the risk of reaching body temperatures beyond the species' thermal tolerance range was similar across elevations. In contrast, the ability to seek cooler retreat sites through behavioural adjustments played an essential role in buffering populations from thermal extremes predicted under climate change. Predicted climate change also altered current activity windows, but high-elevation populations were predicted to remain more temporally constrained than lowland populations. Our results demonstrate that elevational variation in thermal tolerances and acclimation capacity might be insufficient to buffer temperate amphibians from predicted climate change; instead, behavioural thermoregulation may be the only effective mechanism to avoid thermal stress under future climates.

Reptiles are the most species-rich group of terrestrial vertebrates, yet we lack a comprehensive understanding of their extinction risk. Only 45% of described reptile species have been assessed by IUCN to date (4648 of 10,400 species); of these, 20% (945 species) are threatened with extinction, and 19% (867 species) are Data Deficient. The goal of this special issue is to improve our understanding of reptile conservation needs and extinction risk by (i) investigating patterns and drivers of extinction risk and data deficiency at a global scale; (ii) identifying and addressing taxonomic and regional gaps in our understanding of extinction risk and data deficiency; and (iii) drawing upon detailed case studies to highlight conservation approaches to mitigate extinction. By doing so, the special issue will guide future conservation efforts toward the taxa and regions in greatest need of assessment, and toward risks requiring immediate mitigation. We conclude with potential avenues for future research, including the need to address regional knowledge gaps, conduct macroecological and retrospective analyses of extinction risk, and implement targeted monitoring of conservation intervention outcomes.

Understanding the locations of potential invasion hotspots and the extent to which they overlap with biodiversity hotspots is crucial for prioritizing efforts to reduce the impacts of alien species on global biodiversity. Using ensembles of species distribution models based on climate, anthropogenic predictors, vegetation, and water resources, we predict global potential invasion hotspots for alien herpetofauna (reptiles and amphibians). On average, when subjected to current and future climate scenarios, potential richness of alien herpetofauna per grid cell (the minimum unit of our spatial variables for modeling and projecting) in biodiversity hotspots is nearly 1.4 times higher than in other regions. Furthermore, potential invasion hotspots are projected to occupy a large proportion of the total area within biodiversity hotspots. These results suggest that biodiversity hotspots are at greater risk from alien herpetofaunal invasions than are other regions. Our results provide key information for globally targeting early detection and rapid-response programs to help prevent or mitigate future impacts of alien herpetofauna on biodiversity.

Summary 1.Active engagement with practitioners is a crucial component of model-based decision-making in conservation management; it can assist with data acquisition, improve models, and help narrow the ‘knowing-doing’ gap. 2.We worked with practitioners of one of the worst invasive species in Australia, the cane toad Rhinella marina, to revise a model that estimates the effectiveness of landscape barriers to contain spread. The original model predicted that the invasion could be contained by managing artificial watering points on pastoral properties, but was initially met with scepticism by practitioners, in part due to a lack of engagement during model development. 3.We held a workshop with practitioners and experts in cane toad biology. Using structured decision-making, we elicited concerns about the original model, revised its structure, updated relevant input data, added an economic component and found the most cost-effective location for a barrier across a range of fixed budgets and management scenarios. We then conducted scenario analyses to test the sensitivity of management decisions to model revisions. 4.We found that toad spread could be contained for all of the scenarios tested. Our modelling suggests a barrier could cost $4.5M (2015 AUD) over 50 years for the most likely landscape scenario. The incorporation of practitioner knowledge into the model was crucial. As well as improving engagement, when we incorporated practitioner concerns (particularly regarding the effects of irrigation and dwellings on toad spread), we found a different location for the optimal barrier compared to a previously published study (Tingley et al. 2013). 5.Synthesis and applications. Through engagement with practitioners, we turned an academic modelling exercise into a decision-support tool that integrated local information, and considered more realistic scenarios and constraints. Active engagement with practitioners led to productive revisions of a model that estimates the effectiveness of a landscape barrier to contain spread of the invasive cane toad Rhinella marina. Benefits also include greater confidence in model predictions, improving our assessment of the cost and feasibility of containing the spread of toads. This article is protected by copyright. All rights reserved.

Limited conservation resources mean that management decisions are often made on the basis of scarce biological information. Species distribution models (SDMs) are increasingly proposed as a way to improve the representation of biodiversity features in conservation planning, but the extent to which SDMs are used in conservation planning is unclear. We reviewed the peer-reviewed and grey conservation planning literature to explore if and how SDMs are used in conservation prioritisations. We use text mining to analyse 641 peer-reviewed conservation prioritisation articles published between 2006 and 2012 and find that only 10% of articles specifically mention SDMs in the abstract, title, and/or keywords. We use topic modelling of all peer-reviewed articles plus a detailed review of a random sample of 40 peer-reviewed and grey literature plans to evaluate factors that might influence whether decision-makers use SDMs to inform prioritisations. Our results reveal that habitat maps, expert-elicited species distributions, or metrics representing landscape processes (e.g. connectivity surfaces) are used more often than SDMs as biodiversity surrogates in prioritisations. We find four main reasons for using such alternatives in place of SDMs: (i) insufficient species occurrence data (particularly for threatened species); (ii) lack of biologically-meaningful predictor data relevant to the spatial scale of planning; (iii) low concern about uncertainty in biodiversity data; and (iv) a focus on accounting for ecological, evolutionary, and cumulative threatening processes that requires alternative data to be collected. Our results suggest that SDMs are perceived as best-suited to dealing with traditional reserve selection objectives and accounting for uncertainties such as future climate change or mapping accuracy. The majority of planners in both the grey and peer-reviewed literature appear to trade off the benefits of using SDMs for the benefits of including information on multiple threats and processes. We suggest that increasing the complexity of species distribution modelling methods might have little impact on their use in conservation planning without a corresponding increase in research aiming at better incorporation of a range of ecological, evolutionary, and threatening processes.

Aim The ‘two sides of the same coin’ hypothesis posits that biological traits that predispose species to extinction and invasion lie on opposite ends of a continuum. Conversely, anthropogenic factors may have similar effects on extinction and invasion risk. We test these two hypotheses using data on more than 1000 reptile species. Location Global. Methods We used hierarchical Bayesian models to determine whether biological traits and anthropogenic factors were correlated with whether a species was: (1) listed as Threatened versus Least Concern on the IUCN Red List, and (2) successful versus unsuccessful at establishing a viable population once introduced outside of its native geographical range. The ‘two sides of the same coin’ hypothesis predicts that model coefficients for each trait should be opposite in sign between these two models. Results Seventy-three per cent of model coefficients describing 10 aspects of a species’ life history, ecology, biogeography and environmental niche breadth were opposite in sign between the two groups; however, most effect sizes for variables that showed contrasting relationships were small and/or uncertain. The only exception was body size: larger-bodied species were more likely to be threatened, whereas smaller-bodied species were more likely to be invasive. As predicted, human population density across a species’ native geographical range was positively correlated with both threat and invasion probabilities. Other anthropogenic variables did not have strong analogous effects. Main conclusions The assumption that threatened and invasive species lie on opposite ends of a continuum, while consistent with life-history theory, appears to be an oversimplification. Our results do suggest, however, that anthropogenic variables can be important predictors of a species’ fate, and should be more routinely incorporated in trait-based analyses of extinction and invasion risk.