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Feral cats (Felis catus) pose a significant global threat to biodiversity, primarily through predation, disease and competition. A key gap in parameterizing models for improving management decisions for feral cat control relates to factors that drive feral cat survival and movement in the wild. Our study objective was to conduct the first continental-scale analysis of survival rates and displacement distances for feral cats. We collated data on 528 feral cats from telemetry studies in naturally-vegetated landscapes across Australia. Using Cox-proportional hazards models, we investigated the effects of sex, presence of larger predators (dingoes, Canis familiaris and introduced foxes, Vulpes vulpes), presence of introduced prey (rabbits, Oryctolagus cuniculus), body mass, landscape productivity and feral cat density on feral cat survival. We also analysed the effects of sex, body mass and landscape productivity on feral cat displacement using linear mixed model analysis. Feral cat survival was positively associated with presence of dingoes and increasing body mass, whereas there was no clear association between feral cat survival and sex, presence of rabbits, or cat density. Presence of foxes had a strong negative effect on feral cat survival, but the hazard ratio was associated with considerable uncertainty. Net displacement of male feral cats was nearly two times further than that of females, and the proportion of feral cats making long-distance movements was greater in landscapes with low productivity. Increasing body mass of feral cats was positively related to net displacement, with heavier cats moving further. Analysis of metadata from telemetry studies can provide valuable insights into wildlife survival rates and movement behaviour. Our findings will help inform the development of effective management strategies and improve feral cat management for biodiversity conservation.

Feral cats (Felis catus) pose a significant global threat to biodiversity, primarily through predation, disease and competition. A key gap in parameterizing models for improving management decisions for feral cat control relates to factors that drive feral cat survival and movement in the wild. Our study objective was to conduct the first continental-scale analysis of survival rates and displacement distances for feral cats. We collated data on 528 feral cats from telemetry studies in naturally-vegetated landscapes across Australia. Using Cox-proportional hazards models, we investigated the effects of sex, presence of larger predators (dingoes, Canis familiaris and introduced foxes, Vulpes vulpes), presence of introduced prey (rabbits, Oryctolagus cuniculus), body mass, landscape productivity and feral cat density on feral cat survival. We also analysed the effects of sex, body mass and landscape productivity on feral cat displacement using linear mixed model analysis. Feral cat survival was positively associated with presence of dingoes and increasing body mass, whereas there was no clear association between feral cat survival and sex, presence of rabbits, or cat density. Presence of foxes had a strong negative effect on feral cat survival, but the hazard ratio was associated with considerable uncertainty. Net displacement of male feral cats was nearly two times further than that of females, and the proportion of feral cats making long-distance movements was greater in landscapes with low productivity. Increasing body mass of feral cats was positively related to net displacement, with heavier cats moving further. Analysis of metadata from telemetry studies can provide valuable insights into wildlife survival rates and movement behaviour. Our findings will help inform the development of effective management strategies and improve feral cat management for biodiversity conservation.

Feral cats (Felis catus) pose a significant global threat to biodiversity, primarily through predation, disease and competition. A key gap in parameterizing models for improving management decisions for feral cat control relates to factors that drive feral cat survival and movement in the wild. Our study objective was to conduct the first continental-scale analysis of survival rates and displacement distances for feral cats. We collated data on 528 feral cats from telemetry studies in naturally-vegetated landscapes across Australia. Using Cox-proportional hazards models, we investigated the effects of sex, presence of larger predators (dingoes, Canis familiaris and introduced foxes, Vulpes vulpes), presence of introduced prey (rabbits, Oryctolagus cuniculus), body mass, landscape productivity and feral cat density on feral cat survival. We also analysed the effects of sex, body mass and landscape productivity on feral cat displacement using linear mixed model analysis. Feral cat survival was positively associated with presence of dingoes and increasing body mass, whereas there was no clear association between feral cat survival and sex, presence of rabbits, or cat density. Presence of foxes had a strong negative effect on feral cat survival, but the hazard ratio was associated with considerable uncertainty. Net displacement of male feral cats was nearly two times further than that of females, and the proportion of feral cats making long-distance movements was greater in landscapes with low productivity. Increasing body mass of feral cats was positively related to net displacement, with heavier cats moving further. Analysis of metadata from telemetry studies can provide valuable insights into wildlife survival rates and movement behaviour. Our findings will help inform the development of effective management strategies and improve feral cat management for biodiversity conservation.

Feral cats (Felis catus) pose a significant global threat to biodiversity, primarily through predation, disease and competition. A key gap in parameterizing models for improving management decisions for feral cat control relates to factors that drive feral cat survival and movement in the wild. Our study objective was to conduct the first continental-scale analysis of survival rates and displacement distances for feral cats. We collated data on 528 feral cats from telemetry studies in naturally-vegetated landscapes across Australia. Using Cox-proportional hazards models, we investigated the effects of sex, presence of larger predators (dingoes, Canis familiaris and introduced foxes, Vulpes vulpes), presence of introduced prey (rabbits, Oryctolagus cuniculus), body mass, landscape productivity and feral cat density on feral cat survival. We also analysed the effects of sex, body mass and landscape productivity on feral cat displacement using linear mixed model analysis. Feral cat survival was positively associated with presence of dingoes and increasing body mass, whereas there was no clear association between feral cat survival and sex, presence of rabbits, or cat density. Presence of foxes had a strong negative effect on feral cat survival, but the hazard ratio was associated with considerable uncertainty. Net displacement of male feral cats was nearly two times further than that of females, and the proportion of feral cats making long-distance movements was greater in landscapes with low productivity. Increasing body mass of feral cats was positively related to net displacement, with heavier cats moving further. Analysis of metadata from telemetry studies can provide valuable insights into wildlife survival rates and movement behaviour. Our findings will help inform the development of effective management strategies and improve feral cat management for biodiversity conservation.

Feral cats (Felis catus) pose a significant global threat to biodiversity, primarily through predation, disease and competition. A key gap in parameterizing models for improving management decisions for feral cat control relates to factors that drive feral cat survival and movement in the wild. Our study objective was to conduct the first continental-scale analysis of survival rates and displacement distances for feral cats. We collated data on 528 feral cats from telemetry studies in naturally-vegetated landscapes across Australia. Using Cox-proportional hazards models, we investigated the effects of sex, presence of larger predators (dingoes, Canis familiaris and introduced foxes, Vulpes vulpes), presence of introduced prey (rabbits, Oryctolagus cuniculus), body mass, landscape productivity and feral cat density on feral cat survival. We also analysed the effects of sex, body mass and landscape productivity on feral cat displacement using linear mixed model analysis. Feral cat survival was positively associated with presence of dingoes and increasing body mass, whereas there was no clear association between feral cat survival and sex, presence of rabbits, or cat density. Presence of foxes had a strong negative effect on feral cat survival, but the hazard ratio was associated with considerable uncertainty. Net displacement of male feral cats was nearly two times further than that of females, and the proportion of feral cats making long-distance movements was greater in landscapes with low productivity. Increasing body mass of feral cats was positively related to net displacement, with heavier cats moving further. Analysis of metadata from telemetry studies can provide valuable insights into wildlife survival rates and movement behaviour. Our findings will help inform the development of effective management strategies and improve feral cat management for biodiversity conservation.

Ecological models used to forecast range change (range change models; RCM) have recently diversified to account for a greater number of ecological and observational processes in pursuit of more accurate and realistic predictions. Theory suggests that process-explicit RCMs should generate more robust forecasts, particularly under novel environmental conditions. RCMs accounting for processes are generally more complex and data hungry, and so, require extra effort to build. Thus, it is necessary to understand when the effort of building a more realistic model is likely to generate more reliable forecasts. Here, we review the literature to explore whether process-explicit models have been tested through benchmarking their temporal predictive performance (i.e. their predictive performance when transferred in time) and model transferability (i.e. their ability to keep their predictive performance when transferred to generate predictions into a different time) against simpler models, and highlight the gaps between the rapid development of process-explicit RCMs and the testing of their potential improvements. We found that, out of five ecological processes (dispersal, demography, physiology, evolution, species interactions) and two observational processes (sampling bias, imperfect detection) that may influence reliability of forecasts, only the effects of dispersal, demography and imperfect detection have been benchmarked using temporally-independent datasets. Only nine out of twenty-nine process-explicit model types have been tested to assess whether accounting for processes improves temporal predictive performance. We found no benchmarks assessing model transferability. We discuss potential reasons for the lack of empirical validation of process-explicit models. Considering these findings, we propose an expanded research agenda to properly test the performance of process-explicit RCMs, and highlight some opportunities to fill the gaps by suggesting models to be benchmarke

Beef production represents a complex global sustainability challenge including reducing poverty and hunger and the need for climate action. Understanding the trade-offs between these goals at a global scale and at resolutions to inform land use is critical for a global transition towards sustainable beef. Here we optimize global beef production at fine spatial resolution and identify trade-offs between economic and environmental objectives interpretable to global sustainability ambitions. We reveal that shifting production areas, compositions of current feeds and informed land restoration enable large emissions reductions of 34–85% annually (612–1,506 MtCO2e yr−1) without increasing costs. Even further reductions are possible but come at a trade-off with costs of production. Critically our approach can help to identify such trade-offs among multiple sustainability goals, produces fine-resolution mapping to inform required land-use change and does so at the scale necessary to shift towards a globally sustainable industry for beef and to sectors beyond.

Quantifying species population trends is crucial for monitoring progress towards global conservation targets, justifying investments, planning targeted responses and raising awareness about threatened species. Many global indicators are slow in response and report on common species, not on those at greatest risk of extinction. Here we develop a Threatened Species Index as a dynamic tool for tracking annual changes in Australia's imperiled birds. Based on the Living Planet Index method and containing more than 17,000 time series for 65 bird taxa surveyed systematically, the index at its second iteration shows an average reduction of 59% between 1985 and 2016, and 44% between 2000 and 2016. Decreases seem most severe for shorebirds and terrestrial birds and least severe for seabirds. The index provides a potential means for measuring performance against the Convention on Biological Diversity's Aichi Target 12, enabling governments, agencies and the public to observe changes in threatened species.

There are many sources of uncertainty in scenarios and models of socio-ecological systems, and understanding these uncertainties is critical in supporting informed decision-making about the management of natural resources. Here, we review uncertainty across the steps needed to create socio-ecological scenarios, from narrative storylines to the representation of human and biological processes in models and the estimation of scenario and model parameters. We find that socio-ecological scenarios and models would benefit from moving away from “stylized” approaches that do not consider a wide range of direct drivers and their dependency on indirect drivers. Indeed, a greater focus on the social phenomena is fundamental in understanding the functioning of nature on a human-dominated planet. There is no panacea for dealing with uncertainty, but several approaches to evaluating uncertainty are still not routinely applied in scenario modeling, and this is becoming increasingly unacceptable. However, it is important to avoid uncertainties becoming an excuse for inaction in decision-making when facing environmental challenges.

Measuring, reporting and forecasting research impact beyond academia has become increasingly important to demonstrate and understand real-world benefits. This is arguably most important in crisis disciplines such as medicine, environmental sustainability and biodiversity conservation, where application of new knowledge is urgently needed to improve health and environmental outcomes. Increasing focus on impact has prompted the development of theoretical guidance and practical tools tailored to a range of disciplines, but commensurate development of tools for conservation is still needed. In the present article, we review available tools for evaluating research impact applicable to conservation research. From these, and via a survey of conservation professionals, we compiled and ranked a list of 96 impact indicators useful for conservation science. Our indicators apply to a logic chain of inputs, processes, outputs, outcomes, and impacts. We suggest the list can act as a clear guide to realize and measure potential impacts from conservation research within and beyond academia.

There are many sources of uncertainty in scenarios and models of socio-ecological systems, and understanding these uncertainties is critical in supporting informed decision-making about the management of natural resources. Here, we review uncertainty across the steps needed to create socio-ecological scenarios, from narrative storylines to the representation of human and biological processes in models and the estimation of scenario and model parameters. We find that socio-ecological scenarios and models would benefit from moving away from “stylized” approaches that do not consider a wide range of direct drivers and their dependency on indirect drivers. Indeed, a greater focus on the social phenomena is fundamental in understanding the functioning of nature on a human-dominated planet. There is no panacea for dealing with uncertainty, but several approaches to evaluating uncertainty are still not routinely applied in scenario modeling, and this is becoming increasingly unacceptable. However, it is important to avoid uncertainties becoming an excuse for inaction in decision-making when facing environmental challenges.

Monitoring of threatened species and threatened ecosystems is critical for determining population trends, identifying urgency of management responses, and assessing the efficacy of management interventions. Yet many threatened species and threatened ecosystems are not monitored and for those that are, the quality of the monitoring is often poor. Here we provide a checklist of factors that need to be considered for inclusion in robust monitoring programs for threatened species and threatened ecosystems. These factors can be grouped under four broad themes - the design of monitoring programs, the structure and governance of monitoring programs, data management and reporting, and appropriate funding and legislative support. We briefly discuss key attributes of our checklist under these themes. Key topics in our first theme of the design of monitoring programs include appropriate objective setting, identification of the most appropriate entities to be measured, consistency in methodology and protocols through time, ensuring monitoring is long-term, and embedding monitoring into management. Under our second theme which focuses on the structure and governance of monitoring programs for threatened species and ecosystems, we touch on the importance of adopting monitoring programs that: test the effectiveness of management interventions, produce results that are relevant to management, and engage with (and are accepted by) the community. Under Theme 3, we discuss why data management is critical and highlight that the costs of data curation, analysis and reporting need to be factored into budgets for monitoring programs. This requires that appropriate levels of funding are made available for monitoring programs, beyond just the cost of data collection - a key topic examined in Theme 4. We provide examples, often from Australia, to highlight the importance of each of the four themes. We recognize that these themes and topics in our checklist are often closely inter-related and

The World Economic Forum now ranks biodiversity loss as a top-five risk to the global economy, and the draft post-2020 Global Biodiversity Framework proposes an expansion of conservation areas to 30% of the earth’s surface by 2030 (hereafter the “30% target”), using protected areas (PAs) and other effective area-based conservation measures (OECMs). - Two immediate concerns are how much a 30% target might cost and whether it will cause economic losses to the agriculture, forestry and fisheries sectors. - Conservation areas also generate economic benefits (e.g. revenue from nature tourism and ecosystem services), making PAs/Nature an economic sector in their own right. - If some economic sectors benefit but others experience a loss, high-level policy makers need to know the net impact on the wider economy, as well as on individual sectors. [...]

Aim: Species distribution models based on breeding occurrence data allow for identifying both environmental drivers and geographic areas potentially relevant for breeding. However, the interpretation of model predictions in terms of reproductive performance should be further investigated, as this information is crucial for conservation planning. We evaluated the strengths and weaknesses of a correlative modelling approach based on breeding occurrence data (presence–absence) against another approach based on vital rates’ data (breeding success) for gaining insights on species persistence in the case of Great Bustards (Otis tarda). Location: Spain. Methods: Breeding occurrence and breeding success were independently modelled using generalized linear models and multimodel inference analyses. Sensitivities to the way in which the population parameter (breeding success) was defined were explored by building five versions of the dependent variable. We evaluated differences in model performance and identified areas of congruence for breeding occurrence and breeding success. Results: The agreement between the spatial predictions achieved by breeding occurrence and breeding success models differed substantially across databases, with the largest differences in occupied breeding areas. The deviance explained by the breeding occurrence model was 64.98% and ranged from 7.83% to 62.27% for the breeding success models. Model performance was higher for models calibrated within potential than within occupied breeding areas. Main conclusions: The combination of data on both breeding occurrence and breeding success into a species distribution modelling framework showed the limitations of breeding occurrence models for inferring reproductive parameters. The definition of the population parameter as dependent variable was a key factor that strongly affected the inference of vital rates’ models. The approach allowed for discriminating between areas and landscape attributes necessary for

Advancing technology represents an unprecedented opportunity to enhance our capacity to conserve the Earth's biodiversity. However, this great potential is failing to materialize and rarely endures. We contend that unleashing the power of technology for conservation requires an internationally coordinated strategy that connects the conservation community and policy-makers with technologists. We argue an international conservation technology entity could (1) provide vision and leadership, (2) coordinate and deliver key services necessary to ensure translation from innovation to effective deployment and use of technology for on-the-ground conservation across the planet, and (3) help integrate innovation into biodiversity conservation policy from local to global scales, providing tools to monitor outcomes of conservation action and progress towards national and international biodiversity targets. This proposed entity could take the shape of an international alliance of conservation institutions or a formal intergovernmental institution. Active and targeted uptake of emerging technology can help society achieve biodiversity conservation goals.

Monitoring is an essential component of adaptive management, and a carefully designed program is needed to ensure high-quality data and inferences over realistic time scales. Co-operation among agencies and incorporating citizen science may help enhance learning while reducing the financial costs of monitoring. We seek to realise this potential while conserving the Australian malleefowl (Leipoa ocellata). An established network of citizen scientists provide low-cost, sustainable annual monitoring data, yet the most effective actions for conserving malleefowl remain highly uncertain. The continent-wide species' distribution presents significant challenges, including multiple environmental strata to sample and numerous management jurisdictions. We outline an adaptive management framework that aims to unify malleefowl conservation priorities nationally, and target monitoring efforts. We elicited a model structure for the drivers of, and threats to, malleefowl persistence in a workshop with land managers and advocates. We parameterised 80 uncertain interactions within this structure using novel ensemble modelling techniques and identified the effectiveness of predator control as a critical uncertainty affecting malleefowl persistence. We developed a classical, spatially replicated experimental design to test whether malleefowl breed more frequently where predators are suppressed. The proposed monitoring design will rely on the contributions of several dozen land managers and 200–300 citizen scientists annually. We have developed a broad stakeholder base, a proactive communication strategy, and an agile approach to accessing resources to foster resilience and longevity in the monitoring program. If malleefowl conservation successfully adapts in response to monitoring outcomes, it will become one of the largest adaptive management programs on the planet.

In the last 30 years, islands and fenced exclosures free of introduced predators (collectively, havens) have become an increasingly used option for protecting Australian mammals imperiled by predation by introduced cats (Felis catus) and foxes (Vulpes vulpes). However, Australia's network of havens is not expanding in a manner that maximizes representation of all predator-susceptible taxa, because of continued emphasis on already-represented taxa. Future additions to the haven network will improve representation of mammals most efficiently if they fill gaps in under-represented predator-susceptible taxa, particularly rodents. A systematic approach to expansion could protect at least one population of every Australian predator-susceptible threatened mammal taxon by the addition of 12 new havens to the current network. Were the current haven network to be doubled in number in a systematic manner, it could protect three populations of every Australian predator-susceptible threatened mammal taxon.

Since European occupation of Australia, human activities have caused the dramatic decline and sometimes extinction of many of the continent's unique species. Here we provide a comprehensive review of threats to species listed as threatened under Australia's Environment Protection and Biodiversity Conservation Act 1999. Following accepted global categories of threat, we find that invasive species affect the largest number of listed species (1257 species, or 82% of all threatened species); ecosystem modifications (e.g. fire) (74% of listed species) and agricultural activity (57%) are also important. The ranking of threats was largely consistent across taxonomic groups and the degree of species' endangerment. These results were significantly different (P < 0.01) from recent analyses of threats to threatened species globally, which highlighted overexploitation, agriculture and urban development as major causes of decline. Australia is distinct not only in the biodiversity it contains but also in the extent and mixture of processes that threaten the survival of these species. Notably, the IUCN threat classification scheme separates the numerous threats (e.g. urban development, agriculture, mining) that cause habitat loss, fragmentation and degradation, hence further research is required to quantify the net impact of these types of habitat change. We provide feasible suggestions for a more coordinated national approach to threatened species conservation, which could provide decision makers and managers at all levels with improved resources and information on threats and management. Adequate policy, legislative support and funding are critical for ensuring that on-ground management is successful in halting the decline of Australia's threatened species.

Aim: Species distribution models based on breeding occurrence data allow for identifying both environmental drivers and geographic areas potentially relevant for breeding. However, the interpretation of model predictions in terms of reproductive performance should be further investigated, as this information is crucial for conservation planning. We evaluated the strengths and weaknesses of a correlative modelling approach based on breeding occurrence data (presence–absence) against another approach based on vital rates’ data (breeding success) for gaining insights on species persistence in the case of Great Bustards (Otis tarda). Location: Spain. Methods: Breeding occurrence and breeding success were independently modelled using generalized linear models and multimodel inference analyses. Sensitivities to the way in which the population parameter (breeding success) was defined were explored by building five versions of the dependent variable. We evaluated differences in model performance and identified areas of congruence for breeding occurrence and breeding success. Results: The agreement between the spatial predictions achieved by breeding occurrence and breeding success models differed substantially across databases, with the largest differences in occupied breeding areas. The deviance explained by the breeding occurrence model was 64.98% and ranged from 7.83% to 62.27% for the breeding success models. Model performance was higher for models calibrated within potential than within occupied breeding areas. Main conclusions: The combination of data on both breeding occurrence and breeding success into a species distribution modelling framework showed the limitations of breeding occurrence models for inferring reproductive parameters. The definition of the population parameter as dependent variable was a key factor that strongly affected the inference of vital rates’ models. The approach allowed for discriminating between areas and landscape attributes necessary for

For much of the twentieth century, many or most scholarly journals in biodiversity, ecology, biogeography and conservation were owned and published by scientific societies and made available to the broader scientific community at relatively low cost. However, the past several decades have seen a dominant process of commercialization of the publication process in this field, either by commercial publishing firms taking over publication of journals owned by a society (e.g., Evolution), or by commercial publishers starting new journals to fill “niches” that were until then empty in the scholarly publishing ecosystem. Diversity and Distributions is an example of this latter category of journals, having been created by Wiley Publishers in 1993 (as Biodiversity Letters). Being a journal owned by a commercial publisher, it has always been accessed by readers via subscription, but the publication process has been free to potential authors whose work has passed peer review.

Context: Many Australian mammal species are highly susceptible to predation by introduced domestic cats (Felis catus) and European red foxes (Vulpes vulpes). These predators have caused many extinctions and have driven large distributional and population declines for many more species. The serendipitous occurrence of, and deliberate translocations of mammals to, 'havens' (cat- A nd fox-free offshore islands, and mainland fenced exclosures capable of excluding cats and foxes) has helped avoid further extinction. Aims: The aim of this study was to conduct a stocktake of current island and fenced havens in Australia and assess the extent of their protection for threatened mammal taxa that are most susceptible to cat and fox predation. Methods: Information was collated from diverse sources to document (1) the locations of havens and (2) the occurrence of populations of predator-susceptible threatened mammals (naturally occurring or translocated) in those havens. The list of predator-susceptible taxa (67 taxa, 52 species) was based on consensus opinion from >25 mammal experts. Key results: Seventeen fenced and 101 island havens contain 188 populations of 38 predator-susceptible threatened mammal taxa (32 species). Island havens cover a larger cumulative area than fenced havens (2152 km2 versus 346 km2), and reach larger sizes (largest island 325 km2, with another island of 628 km2 becoming available from 2018; largest fence: 123 km2). Islands and fenced havens contain similar numbers of taxa (27 each), because fenced havens usually contain more taxa per haven. Populations within fences are mostly translocated (43 of 49; 88%). Islands contain translocated populations (30 of 139; 22%); but also protect in situ (109) threatened mammal populations. Conclusions: Havens are used increasingly to safeguard threatened predator-susceptible mammals. However, 15

Australia's northern savannas are one of the few remaining large and mostly intact natural areas on Earth. However, their biodiversity and ecosystem values could be threatened if proposed agricultural development proceeds. Through land-use change scenarios, we explored trade-offs and synergies among biodiversity conservation, carbon farming and agriculture production in northern Australia. We found that if all suitable soils were converted to agriculture, habitat at unique recorded locations of three species would disappear and 40 species and vegetation communities could lose more than 50% of their current distributions. Yet, strategically considering agriculture and biodiversity outcomes leads to zoning options that could yield >56,000 km2 of agricultural development with a significantly lower impact on biodiversity values and carbon farming. Our analysis provides a template for policy-makers and planners to identify areas of conflict between competing land-uses, places to protect in advance of impacts, and planning options that balance agricultural and conservation needs.

1. Ecosystem-based management requires predictive models of ecosystem dynamics. There are typically insufficient empirical data available to parameterise these complex models, and so decision-makers commonly rely on beliefs elicited from experts. However, such expert beliefs are necessarily limited because (i) only a small proportion of ecosystem components and dynamics have been observed; (ii) uncertainty about ecosystem dynamics can result in contradictory expert judgements and (iii) elicitation time and resources are limited. 2. We use an ensemble of dynamic ecosystem models to extrapolate a limited set of stated expert beliefs into a wider range of revealed beliefs about how the ecosystem will respond to perturbations and management. Importantly, the method captures the expert uncertainty and propagates it through to predictions. We demonstrate this process and its potential value by applying it to the conservation of the threatened malleefowl (Leipoa ocellata) in the Murray mallee ecosystems of southern Australia. 3. In two workshops, we asked experts to construct a qualitative ecosystem interaction network and to describe their beliefs about how the ecosystem will respond to particular perturbations. We used this information to constrain an ensemble of 10(9) community models, leaving a subset that could reproduce stated expert beliefs. We then interrogated this ensemble of models to reveal experts' implicit beliefs about management scenarios that were not a part of the initial elicitation exercises. 4. Our method uses straightforward questions to efficiently elicit expert beliefs, and then applies a flexible modelling approach to reveal those experts' beliefs about the dynamics of the entire ecosystem. It allows rapid planning of ecosystem-based management informed by expert judgement, and provides a basis for value-of-information analyses and adaptive management.

Conservation fences are an increasingly common management action, particularly for species threatened by invasive predators. However, unlike many conservation actions, fence networks are expanding in an unsystematic manner, generally as a reaction to local funding opportunities or threats. We conducted a gap analysis of Australia's large predator-exclusion fence network by examining translocation of Australian mammals relative to their extinction risk. To address gaps identified in species representation, we devised a systematic prioritization method for expanding the conservation fence network that explicitly incorporated population viability analysis and minimized expected species' extinctions. The approach was applied to New South Wales, Australia, where the state government intends to expand the existing conservation fence network. Existing protection of species in fenced areas was highly uneven; 67% of predator-sensitive species were unrepresented in the fence network. Our systematic prioritization yielded substantial efficiencies in that it reduced expected number of species extinctions up to 17 times more effectively than ad hoc approaches. The outcome illustrates the importance of governance in coordinating management action when multiple projects have similar objectives and rely on systematic methods rather than expanding networks opportunistically.

Australia's northern savannas are one of the few remaining large and mostly intact natural areas on Earth. However, their biodiversity and ecosystem values could be threatened if proposed agricultural development proceeds. Through land-use change scenarios, we explored trade-offs and synergies among biodiversity conservation, carbon farming and agriculture production in northern Australia. We found that if all suitable soils were converted to agriculture, habitat at unique recorded locations of three species would disappear and 40 species and vegetation communities could lose more than 50% of their current distributions. Yet, strategically considering agriculture and biodiversity outcomes leads to zoning options that could yield >56,000 km2 of agricultural development with a significantly lower impact on biodiversity values and carbon farming. Our analysis provides a template for policy-makers and planners to identify areas of conflict between competing land-uses, places to protect in advance of impacts, and planning options that balance agricultural and conservation needs. Copyright and Photocopying: © 2016 The Authors. Conservation Letters published by Wiley Periodicals, Inc.

[Aim]: Species distribution models based on breeding occurrence data allow for identifying both environmental drivers and geographic areas potentially relevant for breeding. However, the interpretation of model predictions in terms of reproductive performance should be further investigated, as this information is crucial for conservation planning. We evaluated the strengths and weaknesses of a correlative modelling approach based on breeding occurrence data (presence–absence) against another approach based on vital rates’ data (breeding success) for gaining insights on species persistence in the case of Great Bustards (Otis tarda)., [Location]: Spain., [Methods]: Breeding occurrence and breeding success were independently modelled using generalized linear models and multimodel inference analyses. Sensitivities to the way in which the population parameter (breeding success) was defined were explored by building five versions of the dependent variable. We evaluated differences in model performance and identified areas of congruence for breeding occurrence and breeding success., [Results]: The agreement between the spatial predictions achieved by breeding occurrence and breeding success models differed substantially across databases, with the largest differences in occupied breeding areas. The deviance explained by the breeding occurrence model was 64.98% and ranged from 7.83% to 62.27% for the breeding success models. Model performance was higher for models calibrated within potential than within occupied breeding areas., [Main conclusions]: The combination of data on both breeding occurrence and breeding success into a species distribution modelling framework showed the limitations of breeding occurrence models for inferring reproductive parameters. The definition of the population parameter as dependent variable was a key factor that strongly affected the inference of vital rates’ models. The approach allowed for discriminating between areas and landscape attributes necessary for the long-term species persistence from others that may be relevant, but not so much for reproductive performance.

Disentangling the relative influence of the environment and biotic interactions in determining species coexistence patterns is a major challenge in ecology. The zonation occurring along elevation gradients, or at bioclimatic contact zones, offers a good opportunity to improve such understanding because the small scale at which the partitioning occurs facilitates inference based on experiments and ecological modelling. We studied the influence of abiotic gradients, habitat types, and interspecific competition in determining the spatial turnover between two pipit and two bunting species in NW Spain. We explored two independent lines of evidence to draw inference about the relative importance of environment and biotic interactions in driving range partitioning along elevation, latitude, and longitude. We combined occurrence data with environmental data to develop joint species distribution models (JSDM), in order to attribute co‐occurrence (or exclusion) to shared (or divergent) environmental responses and to interactions (attraction or exclusion). In the same region, we tested for interference competition by means of playback experiments in the contact zone. The JSDMs highlighted different responses for the two species pairs, although we did not find direct evidence of interspecific aggressiveness in our playback experiments. In pipits, partitioning was explained by divergent climate and habitat requirements and also by the negative correlations between species not explained by the environment. This significant residual correlation may reflect forms of competition others than direct interference, although we could not completely exclude the influence of unmeasured environmental predictors. When bunting species co‐occurred, it was because of shared habitat preferences, and a possible limitation to dispersal might cause their partitioning. Our results indicate that no single mechanism dominates in driving the distribution of our study species, but rather distributions a

The rising popularity of biodiversity offsetting as a tool for balancing biodiversity losses from development with equivalent gains elsewhere has sparked debate on many fronts. The fundamental questions are the following: Is offsetting good, bad, or at least better than the status quo for biodiversity conservation outcomes, and what do we need to know to decide? We present a concise synthesis of the most contentious issues related to biodiversity offsetting, categorized as ethical, social, technical, or governance challenges. In each case, we discuss avenues for reducing disagreement over these issues and identify those that are likely to remain unresolved. We argue that there are many risks associated with the unscrutinized expansion of offset policy. Nevertheless, governments are increasingly adopting offset policies, so working rapidly to clarify and-where possible-to resolve these issues is essential., The rising popularity of biodiversity offsetting as a tool for balancing biodiversity losses from development with equivalent gains elsewhere has sparked debate on many fronts. The fundamental questions are the following: Is offsetting good, bad, or at least better than the status quo for biodiversity conservation outcomes, and what do we need to know to decide? We present a concise synthesis of the most contentious issues related to biodiversity offsetting, categorized as ethical, social, technical, or governance challenges. In each case, we discuss avenues for reducing disagreement over these issues and identify those that are likely to remain unresolved. We argue that there are many risks associated with the unscrutinized expansion of offset policy. Nevertheless, governments are increasingly adopting offset policies, so working rapidly to clarify and-where possible-to resolve these issues is essential.

Population modeling is now widely used in threatened species management and for predicting the impacts and benefits of competing management options. However, some argue that the results of models must be used with caution, particularly when data are limited. This is important, as even the simplest models would generally require more data (and knowledge) than are available in order to have complete confidence in model predictions. In particular, population models often suffer from a lack of data on demographic rates, spatial distribution, dispersal, management responses, habitat correlations and the magnitude of temporal variations. A number of authors identify behavioral and physiological responses of animals to anthropogenic noise. Assessing population level impacts of noise on cetacean populations is essential to understanding how noise impacts on the future viability of marine mammal populations. This assessment will be particularly challenging due to the difficulties associated with identifying a clear link between behavioral responses of animals and physiological impacts, observing and measuring changes in cetacean population parameters and the long lag-times over which population changes manifest in long-lived species. The urgency of the conservation situation for many of these socially important species demands immediate action, despite pervasive uncertainty. Adaptive management provides a coherent framework for action and continuous improvement under uncertainty. I review the elements of adaptive management and discuss the role of population modeling in that context. I discuss Bayesian approaches to enhancing inferential power and reducing uncertainty in model parameter estimation. I then review approaches to characterizing irreducible uncertainty with Monte Carlo methods and sensitivity analysis and conclude with a brief discussion of formal decision tools available to assist with decision making under severe uncertainty. I propose that urgently needed acti

Population modeling is now widely used in threatened species management and for predicting the impacts and benefits of competing management options. However, some argue that the results of models must be used with caution, particularly when data are limited. This is important, as even the simplest models would generally require more data (and knowledge) than are available in order to have complete confidence in model predictions. In particular, population models often suffer from a lack of data on demographic rates, spatial distribution, dispersal, management responses, habitat correlations and the magnitude of temporal variations. A number of authors identify behavioral and physiological responses of animals to anthropogenic noise. Assessing population level impacts of noise on cetacean populations is essential to understanding how noise impacts on the future viability of marine mammal populations. This assessment will be particularly challenging due to the difficulties associated with identifying a clear link between behavioral responses of animals and physiological impacts, observing and measuring changes in cetacean population parameters and the long lag-times over which population changes manifest in long-lived species. The urgency of the conservation situation for many of these socially important species demands immediate action, despite pervasive uncertainty. Adaptive management provides a coherent framework for action and continuous improvement under uncertainty. I review the elements of adaptive management and discuss the role of population modeling in that context. I discuss Bayesian approaches to enhancing inferential power and reducing uncertainty in model parameter estimation. I then review approaches to characterizing irreducible uncertainty with Monte Carlo methods and sensitivity analysis and conclude with a brief discussion of formal decision tools available to assist with decision making under severe uncertainty. I propose that urgently needed acti

A range of mathematical models has been developed to infer whether a species is extinct based on a sighting record. Although observations have variable reliability, current methods for detecting extinction do not differentiate observation qualities. A more suitable approach would consider certain and uncertain sightings throughout the sighting period. We consider a small population system, meaning we assume sighting rates are constant and the population is not declining. Based on such an assumption, we develop a Bayesian method that assumes that certain and uncertain sightings occur independently and at uniform rates. These two types of sightings are connected by a common extinction date. Several rates of false sightings can be calculated to differentiate between observation types. Prior rates of false and true sightings, as well as a prior probability that the species is extant, are included. The model is implemented in OpenBugs, which uses Markov chain Monte Carlo (MCMC). Based on records of variable reliability, we estimate the probability that the following species are extinct: Caribbean seal Monachus tropicalis, grey, black-footed ferret Mustela nigripes, Audubon & Bachman, greater stick-nest rat Leporillus conditor, Sturt, and lesser stick-nest rat Leporillus apicalis, Gould. As further examples, Birdlife International provided the sighting records for the Alaotra grebe Tachybaptus rufolavatus, Delacour, Jamaica petrel Pterodroma caribbaea, Carte, and Pohnpei mountain starling Aplonis pelzelni, Finsch, with prior probabilities for extinction. The results are compared with existing methods, which ignore uncertain sightings. We find that including uncertain sightings can considerably change the probability that the species is extant, in either direction. However, in our examples, including the quality of the uncertain sighting made little difference. When we ignore uncertain sightings, our results agree with existing methods, especially when the last sightin

Policy documents advocate that managers should keep their options open while planning to protect coastal ecosystems from climate-change impacts. However, the actual costs and benefits of maintaining flexibility remain largely unexplored, and alternative approaches for decision making under uncertainty may lead to better joint outcomes for conservation and other societal goals. For example, keeping options open for coastal ecosystems incurs opportunity costs for developers. We devised a decision framework that integrates these costs and benefits with probabilistic forecasts for the extent of sea-level rise to find a balance between coastal ecosystem protection and moderate coastal development. Here, we suggest that instead of keeping their options open managers should incorporate uncertain sea-level rise predictions into a decision-making framework that evaluates the benefits and costs of conservation and development. In our example, based on plausible scenarios for sea-level rise and assuming a risk-neutral decision maker, we found that substantial development could be accommodated with negligible loss of environmental assets. Characterization of the Pareto efficiency of conservation and development outcomes provides valuable insight into the intensity of trade-offs between development and conservation. However, additional work is required to improve understanding of the consequences of alternative spatial plans and the value judgments and risk preferences of decision makers and stakeholders. Minimizando el Costo de Mantener Opciones Abiertas para la Conservacion en un Clima Cambiante Resumen Los documentos de politica abogan que los administradores deben mantener sus opciones abiertas mientras planean proteger a los ecosistemas costeros de los impactos del cambio climatico. Sin embargo, el beneficio de mantener la flexibilidad permanece en su mayoria sin explorar y los acercamientos alternativos para la toma de decisiones bajo incertidumbre pueden llevar a mejores

Decisions affecting the management of natural resources in agricultural landscapes are influenced by both social and ecological factors. Models that integrate these factors are likely to better predict the outcomes of natural resource management decisions

In a recent paper, Welsh, Lindenmayer and Donnelly (WLD) question the usefulness of models that estimate species occupancy while accounting for detectability. WLD claim that these models are difficult to fit and argue that disregarding detectability can be better than trying to adjust for it. We think that this conclusion and subsequent recommendations are not well founded and may negatively impact the quality of statistical inference in ecology and related management decisions. Here we respond to WLD's claims, evaluating in detail their arguments, using simulations and/or theory to support our points. In particular, WLD argue that both disregarding and accounting for imperfect detection lead to the same estimator performance regardless of sample size when detectability is a function of abundance. We show that this, the key result of their paper, only holds for cases of extreme heterogeneity like the single scenario they considered. Our results illustrate the dangers of disregarding imperfect detection. When ignored, occupancy and detection are confounded: the same naïve occupancy estimates can be obtained for very different true levels of occupancy so the size of the bias is unknowable. Hierarchical occupancy models separate occupancy and detection, and imprecise estimates simply indicate that more data are required for robust inference about the system in question. As for any statistical method, when underlying assumptions of simple hierarchical models are violated, their reliability is reduced. Resorting in those instances where hierarchical occupancy models do no perform well to the naïve occupancy estimator does not provide a satisfactory solution. The aim should instead be to achieve better estimation, by minimizing the effect of these issues during design, data collection and analysis, ensuring that the right amount of data is collected and model assumptions are met, considering model extensions where appropriate.

[Aim] Species often remain undetected at sites where they are present. However, the impact of imperfect detection on species distribution models (SDMs) is not fully appreciated. In this paper we evaluate the influence of imperfect detection on the calibration and discrimination capacity of SDMs. We compare the performance of three types of SDMs: (1) a technique based on presence–absence data, (2) a technique based on presence–background data, and (3) a technique based on detection/non-detection data that accounts for imperfect detection., [Innovation] We use simulations to evaluate the impacts of imperfect detection in SDMs. This allows us to assess model performance with respect to the true objective of the models: the estimation of species distributions. We study a range of scenarios of occupancy and detection based on ecologically plausible environmental relationships and identify the circumstances in which imperfect detection affects model calibration and discrimination. We show that imperfect detection can substantially reduce the inferential and predictive accuracy of presence–absence and presence–background methods that do not account for detectability. While calibration is always affected, the influence on discrimination depends on the relationship of detectability and environmental variables., [Main conclusions] The performance of a model should be assessed with respect to its objectives. Comparative studies that intend to assess the performance of an SDM by evaluating its ability to predict detections rather than presences fail to reveal the benefits of accounting for detectability. Disregarding imperfect detection can have severe consequences for SDM performance, and hence for the estimation of species distributions. To date, this issue has been largely ignored in the SDM literature. Simultaneously modelling occupancy and detection does not necessarily require a greater sampling effort, but rather that data are collected so that they are informative about detectability. We recommend that consideration of imperfect detection become standard practice for species distribution modelling.

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.

Population viability analyses (PVAs) contribute to conservation theory, policy, and management. Most PVAs focus on single species within a given landscape and address a specific problem. This specificity often is reflected in the organization of published PVA descriptions. Many lack structure, making them difficult to understand, assess, repeat, or use for drawing generalizations across PVA studies. In an assessment comparing published PVAs and existing guidelines, we found that model selection was rarely justified; important parameters remained neglected or their implementation was described vaguely; limited details were given on parameter ranges, sensitivity analysis, and scenarios; and results were often reported too inconsistently to enable repeatability and comparability. Although many guidelines exist on how to design and implement reliable PVAs and standards exist for documenting and communicating ecological models in general, there is a lack of organized guidelines for designing, applying, and communicating PVAs that account for their diversity of structures and contents. To fill this gap, we integrated published guidelines and recommendations for PVA design and application, protocols for documenting ecological models in general and individual-based models in particular, and our collective experience in developing, applying, and reviewing PVAs. We devised a comprehensive protocol for the design, application, and communication of PVAs (DAC-PVA), which has 3 primary elements. The first defines what a useful PVA is; the second element provides a workflow for the design and application of a useful PVA and highlights important aspects that need to be considered during these processes; and the third element focuses on communication of PVAs to ensure clarity, comprehensiveness, repeatability, and comparability. Thereby, DAC-PVA should strengthen the credibility and relevance of PVAs for policy and management, and improve the capacity to generalize PVA findings acro

Summary for Policy Makers Australia’s biodiversity is threatened by climate change, but we currently know little about the scale of the threat or how to deploy on ground conservation actions to protect biodiversity against the changes expected. In this project we predict the impacts of climate change for threatened species and delineate the best options for climate adaptation for all these species collectively via protecting and restoring their habitat. For 504 of Australia’s currently threatened species we predict their distributional responses to climate change, under three climate change scenarios of increasing severity: early mitigation, delayed mitigation and business-as-usual. We then simulate the optimal placement of new protected areas and where necessary, restoration of critical habitat for those species most affected by a changing climate, taking into account variation in the costs and benefits of taking action in different places. We measured the benefits of protecting and restoring habitat by considering the long-term availability and quality of habitat for threatened species as climate changes. We undertook a state-of-the-art multi-action optimisation that accounts for spatial and temporal habitat connectivity under climate change. The scale of the prioritisation analysis implemented here is unprecedented in the conservation literature, and is only possible because of recent advances in software sophistication and parallel computer processing power.

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.

Conservation monitoring programs are critical for identifying many elements of species ecology and for detecting changes in populations. However, without articulating how monitoring information will trigger relevant conservation actions, programs that mon

A range of mathematical models has been developed to infer whether a species is extinct based on a sighting record. Although observations have variable reliability, current methods for detecting extinction do not differentiate observation qualities. A more suitable approach would consider certain and uncertain sightings throughout the sighting period. We consider a small population system, meaning we assume sighting rates are constant and the population is not declining. Based on such an assumption, we develop a Bayesian method that assumes that certain and uncertain sightings occur independently and at uniform rates. These two types of sightings are connected by a common extinction date. Several rates of false sightings can be calculated to differentiate between observation types. Prior rates of false and true sightings, as well as a prior probability that the species is extant, are included. The model is implemented in OpenBugs, which uses Markov chain Monte Carlo (MCMC). Based on records of variable reliability, we estimate the probability that the following species are extinct: Caribbean seal Monachus tropicalis, grey, black-footed ferret Mustela nigripes, Audubon & Bachman, greater stick-nest rat Leporillus conditor, Sturt, and lesser stick-nest rat Leporillus apicalis, Gould. As further examples, Birdlife International provided the sighting records for the Alaotra grebe Tachybaptus rufolavatus, Delacour, Jamaica petrel Pterodroma caribbaea, Carte, and Pohnpei mountain starling Aplonis pelzelni, Finsch, with prior probabilities for extinction. The results are compared with existing methods, which ignore uncertain sightings. We find that including uncertain sightings can considerably change the probability that the species is extant, in either direction. However, in our examples, including the quality of the uncertain sighting made little difference. When we ignore uncertain sightings, our results agree with existing methods, especially when the last sighting wa

The extinction of a species can be inferred from a record of its sightings. Existing methods for doing so assume that all sightings in the record are valid. Often,however,there are sightings of uncertain validity. To date,uncertain sightings have been treated in an ad hoc way, either excluding them from the record or including them as if they were certain. We developed a Bayesian method that formally accounts for such uncertain sightings. The method assumes that valid and invalid sightings follow independent Poisson processes and use noninformative prior distributions for the rate of valid sightings and for a measure of the quality of uncertain sightings. We applied the method to a recently published record of sightings of the Ivory-billed Woodpecker(Campephilus principalis).This record covers the period 1897-2010 and contains 39 sightings classified as certain and 29 classified as uncertain. The Bayes factor in favor of extinction was 4.03,which constitutes substantial support for extinction. The posterior distribution of the time of extinction has 3 main modes in 1944,1952,and 1988. The method can be applied to sighting records of other purportedly extinct species. © 2011 Society for Conservation Biology.

Substantial investment in climate change research has led to dire predictions of the impacts and risks to biodiversity. The Intergovernmental Panel on Climate Change fourth assessment report1 cites 28,586 studies demonstrating significant biological changes in terrestrial systems2. Already high extinction rates, driven primarily by habitat loss, are predicted to increase under climate change3, 4, 5, 6. Yet there is little specific advice or precedent in the literature to guide climate adaptation investment for conserving biodiversity within realistic economic constraints7. Here we present a systematic ecological and economic analysis of a climate adaptation problem in one of the world’s most species-rich and threatened ecosystems: the South African fynbos. We discover a counterintuitive optimal investment strategy that switches twice between options as the available adaptation budget increases. We demonstrate that optimal investment is nonlinearly dependent on available resources, making the choice of how much to invest as important as determining where to invest and what actions to take. Our study emphasizes the importance of a sound analytical framework for prioritizing adaptation investments4. Integrating ecological predictions in an economic decision framework will help support complex choices between adaptation options under severe uncertainty. Our prioritization method can be applied at any scale to minimize species loss and to evaluate the robustness of decisions to uncertainty about key assumptions.

Prioritizing management actions for wildlife conservation is a difficult task due to the large number of problems relative to available conservation resources and uncertainty about the benefits arising from numerous potential management actions. In this study we use a cost-efficiency protocol to evaluate and prioritize eight different management actions for waterbird community in wetlands throughout southeastern Spain. The protocol generated an action priority ranking based on the costs and predicted benefits of the actions in terms of waterbird carrying capacity. Action prioritization outcomes were also evaluated using population viability analysis models for two of the study species. Removal of dead bird carcasses to prevent disease outbreaks was identified as the most cost efficient action. Removing lead pel- lets from the sediment was the least efficient strategy. Our approach highlights the role of detailed risk assessment as a form of quality control on the simpler prioritization protocols. We recommend a two- step prioritization protocol based on (i) a rapid, usually simpler prioritization approach for the bulk of species or values being managed, and (ii) a more sophisticated risk assessment for a subset of the species of interest for which detailed risk assessments are tractable. This process strikes a balance between sophistication and practicality.

Barriers are used to achieve diverse objectives in conservation and biosecurity. In conservation management, fences are often erected to exclude introduced predators and to contain diseased animals or invasive species. Planning an efficient conservation fence involves a number of decisions, including the size and design of the enclosure. We formulated the first general framework for building a fence that minimizes long-term management costs by balancing the expense of constructing a more secure barrier against the costs of coping with more frequent failures. The approach systematically considers the range of potential solutions to a well-defined fencing problem and results in a solution that maximizes conservation return on investment. We illustrated this method by designing efficient fences to address two different conservation goals: exclusion of invasive predators from populations of threatened eastern barred bandicoots (Perameles gunnii) and maintenance of isolated populations of healthy Tasmanian devils (Sarcophilus harrisii). A systematic approach to conservation fencing allows the best fence design to be chosen quantitatively and defensibly. It also facilitates conservation decisions at a strategic level by allowing fencing to be compared transparently with alternative conservation management actions.