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Climate and land‐use change pose unprecedented threats to ecosystems, economies, and communities worldwide. To help mitigate the climate crisis, restoration is a rapidly growing industry used to offset carbon emissions. The most common approach is to plant fast‐growing monocultures with the aim of sequestering as much carbon as possible in the shortest time. However, there has been little economic analysis of planting options that explicitly address short and long‐term ecological risks such as fire, disease, and environmental change. Here we develop a method for quantifying ecological risks from fire to sequestration investments and show how these risks can be factored into an analysis of long‐term financial returns relative to opportunity costs. In the case study presented, we find that the apparent advantage of fast‐growing monoculture plantations is likely to be outweighed by the long‐term fire risks to the carbon stored in them. Our analytical framework provides a widely applicable approach to comparing planting options against each other and other land uses, considering key uncertainties. With climate change already manifesting through extreme weather events, rising sea levels, and shifting wildlife populations, our framework can be used to make informed decisions about the best solutions to increase carbon sequestration, reduce ecological risks, and reduce climate impacts with greater certainty. [ABSTRACT FROM AUTHOR]

Decision science emphasizes necessary elements required for robust decision‐making. By incorporating decision science principles, frameworks, and tools, it has been demonstrated that decision‐makers can increase the chances of achieving conservation aims. Setting measurable objectives, clearly documenting assumptions about the impact of available actions on a specific threat or problem, explicitly considering constraints, exploring and characterizing uncertainty, and structured deliberation on trade‐offs have been identified as key elements of successful decision‐making. We quantify the extent to which these five elements were utilized in published examples of decision making in conservation in both academic and conservation practice between 2009 and 2018. We found that less than 50% of identified examples included all five elements, with differences in the degree of decision science applied across five commonly used decision support approaches: adaptive management (AM), systematic conservation planning (SCP), structured decision making (SDM), multi‐criteria decision analysis, and cost‐effectiveness analysis. Example applications that utilized the SDM framework were limited in numbers but used on average more than 50% of the five key elements we considered. Although SCP and AM constituted the majority of examples, they were more prevalent in academic studies rather than management applications. SCP and AM examples were widespread in protected area planning, threat abatement, and restoration. Strong geographic bias exists in documented conservation activities that deploy all five decision science elements. [ABSTRACT FROM AUTHOR]

Understanding the constraints that dominant predators impose on subordinate species is important for predicting ecosystem dynamics and anticipating outcomes of predator management. Subordinate predators may avoid dominant predators in time or space, making it difficult to quantify antipredator behaviours unless joint spatiotemporal analyses are used. Here, we test whether an invasive dominant predator (red fox Vulpes vulpes) alters the spatiotemporal activity of an invasive subordinate predator (feral cat Felis catus). We collated records of both species from 3667 camera‐traps deployed experimentally across two regions of south‐eastern Australia with simplified predator guilds. Foxes were poison‐baited in some landscapes within each region. We used generalised additive models to quantify changes in predator spatiotemporal activity across geographic space, vegetation types, human footprints and (artificially manipulated) gradients of dominant predator activity. Foxes and cats had similar diel activity patterns when averaged across all sites, but there was important differentiation at a finer scale: cats did not reduce their spatial activity but shifted diel patterns when localised fox activity was high. Cats were crepuscular on average. However, across dry vegetation types of both regions (where foxes were nocturnal), cats shifted to diurnal behaviour with increasing fox activity. In contrast, fox activity was relatively consistent throughout the daily cycle in the wet forest; here cats avoided dawn when fox activity was high. Changes in cat diel activity patterns may facilitate spatial coexistence between these two invasive predators, potentially shifting feral cat impacts onto different native prey. While it is well‐appreciated that predator activity varies spatially and fluctuates throughout the daily cycle,our study demonstrates that diel activity patterns also vary across space, likely mediated by both landscape‐context and fear. Dominant predator avoidance in time also appears to be spatially dynamic – a key nuance overlooked when simply comparing the average activity overlap between two species. [ABSTRACT FROM AUTHOR]

Offsetting policies have increased worldwide, utilizing a range of biodiversity metrics to compensate for development impacts. We conducted a global analysis of offset legislation by reviewing policies from 108 countries, which have voluntary offsets, or which require offsets by law. We sought to understand how well biodiversity metrics and offset currencies are documented in current policies. Where biodiversity metrics are documented we aimed to understand how metrics were scored, combined, and multiplied to create offset currencies. We found only 22 jurisdictions (from 14 countries) had guidelines documenting how biodiversity should be assessed during offsetting, representing a significant gap in the guidance available for offsets. Of the 22 guidelines, 14 (63%) documented use of aggregated currencies, eight (23%) did not aggregate biodiversity metrics into a single currency, and three (17%) did not specify either approach. Habitat type and condition, as well as area, were widely recommended across policies (>50%). Where species‐level metrics were considered, guidelines generally focused on habitat distributions rather than abundance or population metrics. The lack of consistent and clear guidance about how biodiversity should be measured in offsets reduces our ability to determine the effectiveness of offsets in compensating for development impacts long term. [ABSTRACT FROM AUTHOR]

Effective biodiversity conservation requires robust and transparent prioritization of management actions. However, this is often hampered by a lack of spatially‐explicit data on habitat variables and empirical data on the effect of management actions. Although approaches exist that integrate structured expert elicitation (SEE) with species distribution models (SDMs) to encode species responses across habitat gradients, difficulties remain in predicting management outcomes under different settings, at a region‐wide scale when key habitat covariates are not spatially explicit. Therefore, we developed an approach to integrate SDMs with SEE to capture expert understanding of likely outcomes of management actions for individual frog species, and use this to spatially predict the effect of management actions. We demonstrate our approach across approximately 4000 wetlands in greater Melbourne, Victoria, Australia. As a measure of management effectiveness, we used the change in predicted probability of occurrence of seven frog species at wetlands 10 years after conservation actions are implemented (or not implemented). Management effect was elicited from experts under six scenarios. Individual expert estimates were aggregated using generalized linear models that were then used to spatially predict expected management effects, and a measure of uncertainty in the prediction, at all wetlands. Predicted management effect was strongly influenced by species initial probability of occurrence, with enhancing aquatic and surrounding vegetation an effective action for most species. We discuss practical challenges and recommend solutions in the integration of SDMs and SEE for the spatial prediction of management effect. [ABSTRACT FROM AUTHOR]

1. The mesopredator release theory predicts that the density of subordinate predators will increase as dominant predators decline. Persistent debate around mesopredator release in part reflects the lack of robust, replicated experiments that test this theory, and the use of population indices that confound changes in mesopredator density and detectability. This uncertainty has immediate impacts for conservationists who are faced with managing sympatric invasive predators. 2. We used replicated experimental designs and spatially explicit models to examine whether mesopredator release of the feral cat Felis catus occurs in response to targeted control of the introduced red fox Vulpes vulpes. We surveyed three Control‐Impact paired landscapes in a region with long‐term fox control (1080 poison baiting) and conducted a Before‐After Control‐Impact Paired‐Series experiment in another region. We used fox occurrence as a simple metric of fox populations and estimated feral cat density with spatial mark–resight models. 3. Lethal fox control had varying effects on fox occurrence, consistent with variation in the duration and intensity of poison baiting. Correspondingly, responses in feral cat density ranged from negligible to a 3.7‐fold higher density in fox‐baited landscapes. At a fine spatial scale (200 m2), feral cat density was negatively associated with fox occurrence probability across both regions. These results were consistent with mesopredator release, although uncertainty was high in the region where fox control had only recently commenced. 4. Feral cat detectability also varied across the (artificially manipulated) gradients of fox occurrence probability. In one region, nonlinear models indicated that feral cats had lower detection and increased movement rates when foxes were uncommon, giving way to density suppression at high fox occurrence probabilities. 5. Synthesis and applications. Our study provides replicated, experimental evidence that dominant predator suppression can be associated with a higher mesopredator density. Mesopredator release can manifest as changes in both behaviour and density, distorting inference if these processes are not distinguished. Our results may help explain why fox control does not consistently improve native prey persistence, suggesting integrated pest management may be necessary to improve conservation outcomes. [ABSTRACT FROM AUTHOR]

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 benchmarked using existing historical datasets. [ABSTRACT FROM AUTHOR]

Increasingly the importance of Indigenous participation is acknowledged as central to effective biodiversity conservation. Traditional management emphasizes the importance of a holistic, integrated approach to safeguard species and ecological communities of cultural significance. This is discordant with many instruments for biodiversity conservation. Indigenous Australians have consistently lobbied for domestic laws to be amended to establish comanagement as the preferred approach to managing significant species and ecological communities – an approach that aligns with international obligations such as the Convention on Biological Diversity and the United Nations Declaration on the Rights of Indigenous Peoples. We describe amendments to Australia's biodiversity legislation and the use of biocultural indicators that would support Traditional management of Culturally Significant Entities (species and ecological communities), and in turn, assist Australia to effectively conserve biodiversity and meet international obligations. The ongoing challenge will be in empowering Indigenous peoples and their governance structures to implement enduring change. [ABSTRACT FROM AUTHOR]

Aim: Megafire plays a crucial role in driving the distribution of biodiversity around the world. Long‐term monitoring is vital for understanding how species are impacted immediately by megafire and subsequently respond over time. However, monitoring should be designed with sufficient statistical power to detect impact and recovery. In this study, we developed a simulation framework for optimizing the design of biodiversity monitoring programmes to detect population recoveries after megafire. Location: Victoria, Australia. Time period: 2019–2020. Major taxa studied: Vertebrates. Methods: We collated species distribution models for 45 priority vertebrates most likely to respond to management after the 2019–2020 megafires in Victoria, Australia. We combined these models with fire severity maps to optimize the location of monitoring sites in and around the fire footprint. We simulated the impact of the megafires on species distributions and modelled plausible recoveries over the next 10 years. Using estimates of detectability for a suite of preferred sampling methods, we simulated monitoring at pairs of burnt and unburnt sites to evaluate the statistical power to detect the modelled recoveries. We tested the sensitivity of power to alternative monitoring designs, rates of recovery and monitoring budgets. Results: Priority regions to establish monitoring sites varied by taxonomic group. Power to detect population recoveries increased as the monitoring budget increased, as the recovery rate increased and when the proportion of sites in burnt compared with unburnt habitat increased. According to the optimal monitoring design, an AUD $9M budget could detect 90% of recoveries to pre‐fire levels in 40% of species with >80% power. Power was highest for mammals, followed by birds, reptiles and amphibians. Main conclusions: Our simulation approach allowed us to test the relative performance of alternative post‐fire monitoring designs ahead of time. Although we focused on megafire, our approach could easily be applied to detect population recoveries after any large‐scale catastrophic disturbance. [ABSTRACT FROM AUTHOR]

Many threatened species depend on climatic microrefugia, but places with harsh climates for predators may also play a refugial role. Feral cats threaten many native species in arid Australia. Although cats can persist in regions with no free water, their abundance should depend on the availability of microclimates that protect them from harsh environmental conditions. We developed a biophysical model of feral cat heat stress and used it to explore how behavior and microhabitat features influence water requirements and activity. Tests of model predictions against fine‐scale GPS and microclimate data highlight the importance of refuges, particularly rabbit burrows. Continent‐wide simulations show large but temporally varying areas of the arid zone that would be lethal for cats without access to deep or shaded burrows. Our approach can identify locations that may act as natural refuges for native prey, and where habitat management strategies may be effective in controlling cat abundance. [ABSTRACT FROM AUTHOR]

Several methods of measuring biodiversity in development‐offset trades exist. However, there is little consensus on which biodiversity metrics should be used for quantifying development impacts and assigning offsets.We simulated development impacts in a virtual landscape and offset these impacts using six biodiversity metrics: vegetation area, vegetation condition, habitat suitability, species abundance, metapopulation connectivity and rarity‐weighted richness. We tested long‐term impacts of metric choice during offsetting by combining simulated landscapes with population viability analyses.No net loss or net gains in habitat were achieved using all metrics except vegetation area and condition. Limited habitat and like‐for‐like requirements resulted in offsets exhausting available habitat in each vegetation class before offset requirements were met when using vegetation‐based metrics. We also found that impact avoidance was an important driver in how much compensation offsets could deliver. When impacts avoided high‐suitability habitats, all six metrics achieved no net loss or net gains for most species. However, when core habitats were developed, none of the metrics were able to consistently prevent population declines.Synthesis and application. When impacts on high‐quality habitat were avoided, and assuming the protection and restoration benefits can occur in practice, vegetation‐based metrics may produce offsets which deliver gains in species abundance equivalent to species‐specific metrics. However, species‐specific metrics outperformed vegetation‐based metrics when core habitats were lost. Applying avoidance measures as a first step to minimise biodiversity impacts during development will significantly improve offset outcomes for species and result in greater long‐term population benefits delivered through offsetting. [ABSTRACT FROM AUTHOR]

Aims: Reconnaissance surveys followed by monitoring are needed to assess the impact and response of biodiversity to wildfire. However, post‐wildfire survey and monitoring design are challenging due to the infrequency and unpredictability of wildfire, an urgency to initiate surveys and uncertainty about how species respond. In this article, we discuss key design considerations and quantitative tools available to aid post‐wildfire survey design. Our motivation was to inform the design of rapid surveys for threatened species heavily impacted by the 2019–2020 fires in Australia. Location: Global. Methods: We discuss a set of best practice design considerations for post‐wildfire reconnaissance surveys across a range of survey objectives. We provide examples that illustrate key design considerations from post‐fire reconnaissance surveys and monitoring programmes from around the world. Results: We highlight how the objective of post‐fire surveys drastically influences design decisions (e.g. survey location and timing). We discuss how the unpredictability of wildfire and uncertainty in the response of biodiversity complicate survey design decisions. Main conclusions: Surveys should be conducted immediately following wildfire to assess the impact on biodiversity, to ground truth fire severity mapping and to provide a benchmark from which to assess recovery. Where possible, surveys should be conducted at burnt and unburnt sites in regions with historical data so that state variables of interest can be compared with baseline estimates (i.e. BACI design). This highlights the need to have long‐term monitoring programmes already in place and be prepared to modify their design when wildfires occur. There is opportunity to adopt tools from statistics (i.e. power analysis) and conservation planning (i.e. spatial prioritization) to improve survey design. We must anticipate wildfires rather than respond to them reactively as they will occur more frequently due to climate change. [ABSTRACT FROM AUTHOR]

Summary: Indigenous people are the custodians of knowledge systems that hold detailed awareness of the environment, including applications for monitoring and management to improve biodiversity and cultural outcomes. Indigenous communities are increasingly participating in programs to monitor populations of wildlife. There is a need for frameworks to guide how Indigenous priorities, aspirations and culture can be respected within monitoring programs, as well as case studies that demonstrate how Indigenous knowledge and practice can provide opportunities together with Western science practice to improve the rigour and outcomes of wildlife monitoring. Here, we describe the process of developing a monitoring program that was tailored to be carried out by Kanyirninpa Jukurrpa Indigenous ranger teams to assess the status, trend and response to the management of a threatened and culturally significant species Mankarr (Greater Bilby; Macrotis lagotis). We applied a collaborative two‐way approach, using iterative consultations, elicitations and field trials involving Indigenous and non‐Indigenous project partners to define monitoring objectives, record biocultural knowledge and tailor a sampling methodology to fit the requirements of Martu Traditional Owners. Our project focused on creating a method that would be engaging, accessible and useful for rangers who would carry out the program, and prioritized collection of relevant data for community decision‐making regarding management. We outline our key learnings for co‐design of wildlife monitoring programs on Indigenous lands. Our approach provides insights that will assist in designing other cross‐cultural or participatory monitoring programs. [ABSTRACT FROM AUTHOR]

Summary: Increasingly scientists and policy makers are acknowledging the importance of Indigenous participation in effective biodiversity conservation. In Australia, the recognised Indigenous estate is vast, accounting for up to 57% of the continent and comprising some of the highest priority conservation lands, including 46% of the formal National Reserve System. The Environment Protection and Biodiversity Conservation Act1999 (the Act) is Commonwealth legislation designed to protect and manage nationally and internationally important species and ecological communities, which entails specific objectives to recognise Indigenous people. However, to date the involvement of Indigenous people in implementation of the Act has been inconsistent and inadequate, particularly in the protection of the Indigenous estate, understanding and supporting Indigenous people's aspirations for Country and culturally significant species, and respecting the traditional management of species and landscapes. In this article, we will explore the key barriers and opportunities for improving Indigenous participation in biodiversity conservation under the Act. We structure our exploration using the three connected themes: (1) meaningful Indigenous engagement and participation, (2) recognition of the Indigenous Estate and (3) strengthening Indigenous‐led governance. We find that there is a pressing need and an immediate opportunity to reform and strengthen the Act to protect Indigenous Knowledge, to recognise and report on the role of Indigenous Estate, and to realise the aspirations of Indigenous peoples for improved land and sea management that strengthens people, culture and Country. [ABSTRACT FROM AUTHOR]

Equilibrium models (EMs) are frequently employed to examine the potential impacts of economic, energy, and trade policies as well as form the foundation of most integrated assessment models. Despite their central role coupling economic and environmental systems, environmental scientists are largely unfamiliar with the structure and methodology underpinning EMs, which serves as a barrier to interdisciplinary collaboration and model improvement. In this study we systematically extract data from 10 years of published EMs with a focus on how these models have been extended beyond their economic origins to encompass environmentally relevant sectors of interest. The results indicate that there is far greater spatial coverage of high income countries compared to low income countries, with notable gaps in Central America, Africa, the Middle East, and Central Asia. We also find a high degree of aggregation within production inputs and sectoral outputs, particularly within the context of global socioeconomic scenarios. For example, we were unable to identify a single temporally dynamic study that distinguished between products arising from managed versus natural forest, or pastures relative to natural grasslands. Due to the necessary breadth and associated knowledge gaps within a model of the entire global economy, we see considerable potential for cross‐disciplinary innovation as natural scientists gain familiarity into the role these models play in bridging the nexus between socioeconomic systems and environmental change. Plain Language Summary: This analysis of studies using equilibrium models provides an introduction to how they have been employed across a wide range of disciplines with an emphasis on their application within environmental analyses. We find that many model components are represented in a highly aggregated form, hampering their usefulness in policy‐making. This problem is particularly acute in low income geographic areas as well as within key production inputs. Key Points: Heterogeneity in ecologically consequential production inputs are rarely represented in temporally dynamic studiesSpatial aggregation disproportionately affects low income countries, notably Central America, Africa, the Middle East, and Central AsiaKey socioeconomic drivers within global socioeconomic scenarios have largely not been implemented within equilibrium studies [ABSTRACT FROM AUTHOR]

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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. [ABSTRACT FROM AUTHOR]

Approaches to assess the impacts of landscape disturbance scenarios on species range from metrics based on patterns of occurrence or habitat to comprehensive models that explicitly include ecological processes. The choice of metrics and models affects how impacts are interpreted and conservation decisions. We explored the impacts of 3 realistic disturbance scenarios on 4 species with different ecological and taxonomic traits. We used progressively more complex models and metrics to evaluate relative impact and rank of scenarios on the species. Models ranged from species distribution models that relied on implicit assumptions about environmental factors and species presence to highly parameterized spatially explicit population models that explicitly included ecological processes and stochasticity. Metrics performed consistently in ranking different scenarios in order of severity primarily when variation in impact was driven by habitat amount. However, they differed in rank for cases where dispersal dynamics were critical in influencing metapopulation persistence. Impacts of scenarios on species with low dispersal ability were better characterized using models that explicitly captured these processes. Metapopulation capacity provided rank orders that most consistently correlated with those from highly parameterized and data‐rich models and incorporated information about dispersal with little additional computational and data cost. Our results highlight the importance of explicitly considering species' ecology, spatial configuration of habitat, and disturbance when choosing indicators of species persistence. We suggest using hybrid approaches that are a mixture of simple and complex models to improve multispecies assessments. Article impact statement: Not explicitly including ecological complexity in biodiversity metrics may result in misleading conclusions when assessing impacts. [ABSTRACT FROM AUTHOR]

Understanding the conditions under which small native Australian mammals can persist in the presence of introduced predators remains a key challenge to conservation ecologists. Bettong‐specific one‐way gates were used at a predator‐free reserve in South Australia to allow the burrowing bettong (Bettongia lesueur) – a small potoroid, listed as 'vulnerable' nationally – to disperse out of the reserve. We conducted a field experiment to explore the conditions affecting residence time of bettongs that left the reserve. We monitored bettong and mammalian predator activity outside the fence using track surveys across 18 sites over two seasons. We examined the effect of supplementary feeding as a strategy for increasing residence time, as well as the influence of predator presence and habitat quality, using linear mixed models. Bettong activity was positively associated with supplementary feeding, midstorey vegetation cover and shelter availability. After gates were closed, bettong activity near gates declined to almost zero the following weeks, likely either due to death from predation or due to movement away from the sites. To a small extent, mammalian predators were more likely to be present at sites with high bettong activity. Further research on conditions to support persistence of burrowing bettongs and other small mammals, including understanding minimum necessary predator control effort, is required before successful establishment of populations outside of fences can occur. [ABSTRACT FROM AUTHOR]

Trophic interactions and disturbance events can shape the structure and function of ecosystems. However, the effects of drivers such as predation, fire and climatic variables on species distributions are rarely considered concurrently. We used a replicated landscape‐scale predator management experiment to compare the effects of red fox Vulpes vulpes control, time‐since‐fire, vegetation type and other environmental variables on native herbivore distributions. Occurrence data for four native herbivores and an invasive predator – the red fox – were collected from 240 sites across three baited (for lethal fox control) and three unbaited forest blocks (4659–9750 ha) in south‐western Victoria, Australia, and used to build species distribution models. The herbivore taxa were as follows: red‐necked wallaby Macropus rufogriseus, black wallaby Wallabia bicolour, grey kangaroo Macropus fuligenosus and Macropus giganteus and common brushtail possum Trichosurus vulpecula. Fox control and fire had little effect on herbivore occurrence, despite the literature suggesting it can influence abundance, while climate, proximity to farmland and topography were more influential. This may be because the region's high productivity and agricultural pastures subsidise food resources for both predators and prey within the forest blocks and so dampen trophic interactions. Alternatively, these drivers may affect herbivore abundance, but not herbivore occurrence. Understanding the drivers of herbivore distributions is an important step in predicting the effects of herbivory on other species, particularly after management interventions such as predator control and prescribed burns. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Innovation has the potential to enable conservation science and practice to keep pace with the escalating threats to global biodiversity, but this potential will only be realized if such innovations are designed and developed to fulfill specific needs and solve well‐defined conservation problems. We propose that business‐world strategies for assessing the practicality of innovation can be applied to assess the viability of innovations, such as new technology, for addressing biodiversity conservation challenges. Here, we outline a five‐step, "lean start‐up" based approach for considering conservation innovation from a business‐planning perspective. Then, using three prominent conservation initiatives – Marxan (software), Conservation Drones (technology support), and Mataki (wildlife‐tracking devices) – as case studies, we show how considering proposed initiatives from the perspective of a conceptual business model can support innovative technologies in achieving desired conservation outcomes. [ABSTRACT FROM AUTHOR]

Knowing where species occur is fundamental to many ecological and environmental applications. Species distribution models (SDMs) are typically based on correlations between species occurrence data and environmental predictors, with ecological processes captured only implicitly. However, there is a growing interest in approaches that explicitly model processes such as physiology, dispersal, demography and biotic interactions. These models are believed to offer more robust predictions, particularly when extrapolating to novel conditions. Many process–explicit approaches are now available, but it is not clear how we can best draw on this expanded modelling toolbox to address ecological problems and inform management decisions. Here, we review a range of process–explicit models to determine their strengths and limitations, as well as their current use. Focusing on four common applications of SDMs – regulatory planning, extinction risk, climate refugia and invasive species – we then explore which models best meet management needs. We identify barriers to more widespread and effective use of process‐explicit models and outline how these might be overcome. As well as technical and data challenges, there is a pressing need for more thorough evaluation of model predictions to guide investment in method development and ensure the promise of these new approaches is fully realised. [ABSTRACT FROM AUTHOR]

Invasive predators are a key driver of biodiversity decline, and effective predator management is an important conservation issue globally. The red fox (Vulpes vulpes) poses a significant threat to wildlife, livestock and human health across Eurasia, North America and Australia. Despite worldwide investment in red fox management, decision makers still lack flexible tools for predicting control efficacy.We have developed FoxNet, a spatially explicit, individual‐based model (IBM) framework that can be customised to predict red fox population dynamics, including responses to control and landscape productivity. High‐resolution models can be run across northern and southern hemisphere landscapes. We present four case‐study models to verify FoxNet outputs, explore key sensitivities and demonstrate the framework's utility as a management planning tool.FoxNet models were largely successful in reproducing the demographic structure of two red fox populations in highly contrasting landscapes. They also accurately generated the relationship between home‐range size and fox‐family density for home‐range sizes between 1.0 and 9.6 km2, and captured the rapid decline and seasonally driven recovery of a red fox population following poison‐baiting.An exploration of alternative poison‐baiting scenarios for a conservation reserve predicted that current management suppresses red fox density by ~70% and showed that frequent baiting is required to combat recolonisation. Baiting at higher densities or establishing a baited buffer would further reduce red fox density. Predictions were sensitive to home‐range and litter size assumptions, illustrating the value of region‐specific data on red fox movement and biology.Synthesis and applications. We have developed a versatile individual‐based model framework to guide management of the red fox, a globally significant invasive predator. Our framework, FoxNet, can be customised to generate realistic predictions of red fox population dynamics in diverse landscapes, making it immediately applicable to the design and optimisation of predator control programmes at scales relevant to management. Future extensions could explore competitor and prey responses to red fox control and the effects of habitat disturbance on predator population dynamics. We have developed a versatile individual‐based model framework to guide management of the red fox, a globally significant invasive predator. Our framework, FoxNet, can be customised to generate realistic predictions of red fox population dynamics in diverse landscapes, making it immediately applicable to the design and optimisation of predator control programmes at scales relevant to management. Future extensions could explore competitor and prey responses to red fox control and the effects of habitat disturbance on predator population dynamics. [ABSTRACT FROM AUTHOR]

Aim: Identifying hosts and regions susceptible to invasion by an emerged pathogen is vital to inform early risk assessments. We here show how differences between a pathogen's native and invasive observed niche and their underlying environments affect this process, using the recent emergence of Batrachochytrium salamandrivorans (Bsal) as a critical, empirical example. Location: Palaearctic. Methods: To quantify observed niches, we first gathered occurrences from the native Asian and invasive European distribution of Bsal. Through ordination in PCA‐bound environmental space, we then applied overlap tests to compare native and invasive Bsal niches with those of 56 putative Western Palaearctic host species. At last, we ensembled bivariate niche models (ESMs) for each Bsal niche to assess how differences in observed niches influenced suitability predictions. Results: The observed invasive Bsal niche is a conservative, partially filled subset of its wider native niche. Pathogen–host overlap measured using the narrow invasive niche was nevertheless found to be significantly higher than that of the native niche, which is partly situated in subtropical conditions absent from the Western Palaearctic. ESMs created using the native niche predict high suitability for Bsal throughout Europe. Conversely, a more restricted range was predicted using the invasive niche, which coincides with the presence of oceanic climates in north‐western Europe and several Mediterranean mountain ranges. Main conclusions: Unequal relative availability of environments in native and invasive ranges may lead to underestimation of observed niche overlap between native pathogen populations and putative hosts in the invasive range. The existence of partially filled niches may add uncertainty to overlap measurements, and predictions of potential further spread. Results based on the invasive niche therefore provide a conservative estimate; yet demonstrate, in our case, that Bsal is already present in conditions shared by numerous host species. Further niche filling may accordingly increase risk of salamander diversity across the Western Palaearctic. [ABSTRACT FROM AUTHOR]

In ecology, the true causal structure for a given problem is often not known, and several plausible models and thus model predictions exist. It has been claimed that using weighted averages of these models can reduce prediction error, as well as better reflect model selection uncertainty. These claims, however, are often demonstrated by isolated examples. Analysts must better understand under which conditions model averaging can improve predictions and their uncertainty estimates. Moreover, a large range of different model averaging methods exists, raising the question of how they differ in their behaviour and performance. Here, we review the mathematical foundations of model averaging along with the diversity of approaches available. We explain that the error in model‐averaged predictions depends on each model's predictive bias and variance, as well as the covariance in predictions between models, and uncertainty about model weights. We show that model averaging is particularly useful if the predictive error of contributing model predictions is dominated by variance, and if the covariance between models is low. For noisy data, which predominate in ecology, these conditions will often be met. Many different methods to derive averaging weights exist, from Bayesian over information‐theoretical to cross‐validation optimized and resampling approaches. A general recommendation is difficult, because the performance of methods is often context dependent. Importantly, estimating weights creates some additional uncertainty. As a result, estimated model weights may not always outperform arbitrary fixed weights, such as equal weights for all models. When averaging a set of models with many inadequate models, however, estimating model weights will typically be superior to equal weights. We also investigate the quality of the confidence intervals calculated for model‐averaged predictions, showing that they differ greatly in behaviour and seldom manage to achieve nominal coverage. Our overall recommendations stress the importance of non‐parametric methods such as cross‐validation for a reliable uncertainty quantification of model‐averaged predictions. [ABSTRACT FROM AUTHOR]

Aim: Despite their often high‐trophic position and their contribution to many ecosystem functions, little is known about the factors affecting assemblage structure of medium‐ and large‐sized neotropical vertebrates. We examined the relative roles played by the physical and biological environment, and by purely spatial processes, in shaping the composition and diversities of these vertebrate assemblages. Then, based on the theory that the Guianan forest cover shrank to isolated pockets during the late Pleistocene–Holocene, we tested if the past forest refugia may have shaped current vertebrate assemblages. Location: French Guiana, Guiana Shield, South America. Methods: Abundances of 19 medium‐ and large‐sized vertebrates were estimated at 21 locations in undisturbed Guianan rain forests. Using taxonomic, functional and phylogenetic metrics, we partitioned the effects of a range of physical and biological environmental conditions and purely spatial predictors in shaping both assemblage composition and (alpha and beta) diversities. Results: We identified a significant, but weak relationship between taxonomic, functional and phylogenetic assemblage composition and environmental conditions. Assemblage diversity patterns were mainly explained by spatial predictors irrespective of the metrics. Current assemblage diversities are correlated with Pleistocene–Holocene forest history, with the highest alpha diversities outside of putative forest refugia, and the highest beta diversities inside these areas. Main conclusions: Current vertebrate assemblage composition is not strongly marked by common environmental factors. Our main conclusion is that assemblage composition results from individual species responses to the environment. Our findings also suggest that dispersal‐related processes or more probably historical processes shape (alpha and beta) diversity patterns. In fact, forest fragmentation during Pleistocene–Holocene climate changes could have led to isolated vertebrate assemblages evolving into unique species assemblages creating the current high beta diversity inside refugia, whereas the lower habitat stability outside of refugia could have led to mixed assemblages in areas recolonized by forest vertebrates (current high alpha diversity outside of refugia). [ABSTRACT FROM AUTHOR]

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Conservation of species under climate change relies on accurate predictions of species ranges under current and future climate conditions. To date, modelling studies have focused primarily on how changes in long‐term averaged climate conditions are likely to influence species distributions with much less attention paid to the potential effect of extreme events such as droughts and heatwaves which are expected to increase in frequency over coming decades. In this study we explore the benefits of tailoring predictor variables to the specific physiological constraints of species, or groups of species. We show how utilizing spatial predictors of extreme temperature and water availability (heat‐waves and droughts), derived from high‐temporal resolution, long‐term weather records, provides categorically different predictions about the future (2070) distribution of suitable environments for 188 mammal species across different biomes (from arid zones to tropical environments) covering the whole of continental Australia. Models based on long‐term averages‐only and extreme conditions‐only showed similarly high predictive performance tested by hold‐out cross‐validation on current data, and yet some predicted dramatically different future geographic ranges for the same species under 2070 climate scenarios. Our results highlight the importance of accounting for extreme conditions/events by identifying areas in the landscape where species may cope with average conditions, but cannot persist under extreme conditions known or predicted to occur there. Our approach provides an important step toward identifying the location of climate change refuges and danger zones that goes beyond the current standard of extrapolating long‐term climate averages. [ABSTRACT FROM AUTHOR]

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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. [ABSTRACT FROM AUTHOR]

Ecological data often show temporal, spatial, hierarchical (random effects), or phylogenetic structure. Modern statistical approaches are increasingly accounting for such dependencies. However, when performing cross-validation, these structures are regularly ignored, resulting in serious underestimation of predictive error. One cause for the poor performance of uncorrected (random) cross-validation, noted often by modellers, are dependence structures in the data that persist as dependence structures in model residuals, violating the assumption of independence. Even more concerning, because often overlooked, is that structured data also provides ample opportunity for overfitting with non-causal predictors. This problem can persist even if remedies such as autoregressive models, generalized least squares, or mixed models are used. Block cross-validation, where data are split strategically rather than randomly, can address these issues. However, the blocking strategy must be carefully considered. Blocking in space, time, random effects or phylogenetic distance, while accounting for dependencies in the data, may also unwittingly induce extrapolations by restricting the ranges or combinations of predictor variables available for model training, thus overestimating interpolation errors. On the other hand, deliberate blocking in predictor space may also improve error estimates when extrapolation is the modelling goal. Here, we review the ecological literature on non-random and blocked cross-validation approaches. We also provide a series of simulations and case studies, in which we show that, for all instances tested, block cross-validation is nearly universally more appropriate than random cross-validation if the goal is predicting to new data or predictor space, or for selecting causal predictors. We recommend that block cross-validation be used wherever dependence structures exist in a dataset, even if no correlation structure is visible in the fitted model residuals, or if the fitted models account for such correlations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Generalised dissimilarity modelling (GDM) is a statistical method for analysing and predicting patterns of turnover in species composition, usually in response to environmental gradients that vary in space and time. GDM is becoming widely applied in ecology and conservation science to interpret macro-ecological and biogeographical patterns, to support conservation assessment, predict changes in species distributions under climate change and prioritise biological surveys., Inferential and predictive uncertainty is difficult to characterise using current implementations of GDM, reducing the utility of GDM in ecological risk assessment and conservation decision-making. Current practice is to undertake permutation tests to assess the importance of variables in GDM. Permutation testing overcomes the issue of data-dependence (because dissimilarities are calculated on a smaller number of observations) but it does not give a quantification of uncertainty in predictions. Here, we address this issue by utilising the Bayesian bootstrap, so that the uncertainty in the observations is carried through the entire analysis (including into the predictions)., We tested our Bayesian bootstrap GDM (BBGDM) approach on simulated data sets and two benthic species data sets. We fitted BBGDMs and GDMs to compare the differences in inference and prediction of compositional turnover that resulted from a coherent treatment of model uncertainty. We showed that our BBGDM approach correctly identified the signal within the data, resulting in an improved characterisation of uncertainty and enhanced model-based inference., We show that our approach gives appropriate parameter estimates while better representing the underlying uncertainty that arises when conducting inference and making predictions with GDMs. Our approach to fitting GDMs will provide more realistic insights into parameter and prediction uncertainty. [ABSTRACT FROM AUTHOR]

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., 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., 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 109 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., 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. [ABSTRACT FROM AUTHOR]

Abstract: 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 are determined by the combination of many small forces including biotic and abiotic determinants of niche, whose relative strengths varied among species. [ABSTRACT FROM AUTHOR]

Biodiversity impact assessments under threatened species legislation often focus on individual development proposals at a single location, usually for a single species, leading to inadequate assessments of multiple impacts that accumulate over large spatial scales for multiple species. Regulations requiring ad-hoc assessments can lead to 'death by a thousand cuts,' where biodiversity is degraded by many small impacts that individually do not appear to threaten species' persistence. Spatial prioritization methods can improve the efficiency of decision-making by explicitly considering cumulative impacts of multiple proposed developments on multiple species over large spatial scales. We present an assessment approach and a unique case study in which spatial prioritization tools were used to support strategic assessment of a large development plan in Western Australia. The application of the approach helped identify relatively minor alterations to development plans that resulted in reductions in biodiversity impacts and informed expansion of the protected area network. Using these tools to assess trade-offs between conservation and development will help identify planning footprints that minimize biodiversity losses. [ABSTRACT FROM AUTHOR]

Aim Species distribution models (SDMs) are currently the most widely used tools in ecology for evaluating the suitability of environments for biodiversity in the face of future environmental change. In this study we seek to provide an assessment of the predictive performance of SDMs over time. How well do SDMs predict for future time periods and what factors influence predictive performance? Innovation We used a historical spatially explicit database of 1.8 million occurrence records for 318 tetrapod species from across continental Australia over the period 1950-2013. We fitted distribution models for each species to data from four multi-decadal time slices and used these to predict the species distributions up to 60 years after the data collection period for the fitted models. We evaluated predictions against observed data from the relevant time period. Predictions were made assuming either complete knowledge of changes in climatic and environmental conditions or assuming the environment and climate remained unchanged between the fitting and evaluation time periods. We used generalized linear mixed models to model variation in the predictive performance of SDMs over time in relation to a variety of factors, including the length of time between fitting and evaluation, species traits, taxonomic group and attributes of the dataset used to fit models. Main conclusions We found that most models provided useful predictions even when the period between model fitting and evaluation was 60 years (area under the receiver operator characteristic curve > 0.7 in 80% of the species evaluated). Variation in predictive performance over time was strongly related to the species range breadth (models for species with broad geographical ranges tended to perform worse than models for locally restricted species) and to the environmental coverage of occupancy data. Conversely, taxonomic group, habitat preferences and body size were not highly influential in describing the variation in predictive performance over time. [ABSTRACT FROM AUTHOR]

Each year, two or three species that had been considered to be extinct are rediscovered. Uncertainty about whether or not a species is extinct is common, because rare and highly threatened species are difficult to detect. Biological traits such as body size and range size are expected to be associated with extinction. However, these traits, together with the intensity of search effort, might influence the probability of detection and extinction differently. This makes statistical analysis of extinction and rediscovery challenging. Here, we use a variant of survival analysis known as cure rate modelling to differentiate factors that influence rediscovery from those that influence extinction. We analyse a global data set of 99 mammals that have been categorized as extinct or possibly extinct. We estimate the probability that each of these mammals is still extant and thus estimate the proportion of missing (presumed extinct) mammals that are incorrectly assigned extinction. We find that body mass and population density are predictors of extinction, and body mass and search effort predict rediscovery. In mammals, extinction rate increases with body mass and population density, and these traits act synergistically to greatly elevate extinction rate in large species that also occurred in formerly dense populations. However, when they remain extant, larger-bodied missing species are rediscovered sooner than smaller species. Greater search effort increases the probability of rediscovery in larger species of missing mammals, but has a minimal effect on small species, which take longer to be rediscovered, if extant. By separating the effects of species characteristics on extinction and detection, and using models with the assumption that a proportion of missing species will never be rediscovered, our new approach provides estimates of extinction probability in species with few observation records and scant ecological information. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Aim We explored the extent to which occupancy of butterflies within three biogeographic regions could be explained by vegetation structure and composition, topography and other environmental attributes; whether results were consistent among regions; and whether assumptions of closure were met with assemblage-level sampling designs. Location Chesapeake Bay Lowlands (Virginia), central Great Basin (Nevada) and western Great Basin (Nevada and California) (all USA). Methods We applied single-season occupancy models that either assumed closure or relaxed the closure assumption to data from 2013 and 2014 for 13-15 species in each region. Results Maximum single-year estimates of detection probabilities ranged from 0.14 to 0.99, and single-year occupancy from 0.28 to 0.98. The assumption of closure was met for a maximum of 54% of the species in a given region and year. Detection probabilities of > 90% of the species in each region increased as the categorical abundance of nectar or mud increased. Measures of the dominance or abundance of deciduous woody species and structural heterogeneity were included in the greatest number of occupancy models for the Chesapeake Bay Lowlands, which may in part reflect the intensity of browsing by white-tailed deer ( Odocoileus virginianus). Elevation and precipitation were prominent covariates in occupancy models for Great Basin butterflies. Main conclusions Because occupancy models do not rely on captures or observations of multiple individuals in a population, they potentially can be applied to a relatively high proportion of the species in an assemblage. However, estimation of occupancy is complicated by taxonomic, temporal and spatial variation in phenology. In multiple, widely divergent ecosystems, all or some associations between covariates and detection probability or occupancy for at least one-third of the species could not be estimated, often because a given species rarely was detected at locations with relatively low or high values of a covariate. Despite their advantages, occupancy models may leave unexplained the environmental associations with the distributions of many species. [ABSTRACT FROM AUTHOR]

Aim Some threatened species are now recovering after a period of serious decline. Understanding and predicting the spatio-temporal recolonization of these species in a heterogeneous landscape are important for their conservation planning. We aimed to predict the range expansion of the endangered Asian crested ibis Nipponia nippon as it recovers from near-extinction to guide its in situ conservation and plan possible reintroductions. Location Central China. Methods We used a presence-only ecological niche model to predict breeding habitat suitability and a newly developed, spatially explicit and individual-based dynamic modelling platform to simulate range expansion. We performed a sensitivity analysis to assess the effects of uncertainty in demographic and dispersal parameters on the simulation of range dynamics. The impact of human-induced mortality risk was also investigated. Results Predictions showed that the Asian crested ibis population and the range extent would continue to increase over the next 50 years, and the species would recolonize parts of its historical range. However, the majority of the population would still be restricted to a relatively small region, and some potential suitable regions might not be recolonized for decades by natural dispersal. Moreover, the simulated range dynamics were sensitive to life history trait parameters, among which adult survival probability and the proportion of long-distance dispersal events showed the strongest effects. High human-induced mortality risks had a significant negative effect on population growth and range expansion. Main conclusions This study demonstrates how hybrid modelling can inform conservation management of threatened species as they recolonize former habitat. The findings enable prioritization of management efforts, highlight the need for long-term monitoring of the key life history parameters and provide evidence to guide the selection of potential reintroduction sites for the long-term survival and recovery of target species. [ABSTRACT FROM AUTHOR]

Wetlands support unique biota and provide important ecosystem services. These services are highly threatened due to the rate of loss and relative rarity of wetlands in most landscapes, an issue that is exacerbated in highly modified urban environments. Despite this, critical ecological knowledge is currently lacking for many wetland-dependent taxa, such as insectivorous bats, which can persist in urban areas if their habitats are managed appropriately. Here, we use a novel paired landscape approach to investigate the role of wetlands in urban bat conservation and examine local and landscape factors driving bat species richness and activity. We acoustically monitored bat activity at 58 urban wetlands and 35 nonwetland sites (ecologically similar sites without free-standing water) in the greater Melbourne area, southeastern Australia. We analyzed bat species richness and activity patterns using generalized linear mixed-effects models. We found that the presence of water in urban Melbourne was an important driver of bat species richness and activity at a landscape scale. Increasing distance to bushland and increasing levels of heavy metal pollution within the waterbody also negatively influenced bat richness and individual species activity. Areas with high levels of artificial night light had reduced bat species richness, and reduced activity for all species except those adapted to urban areas, such as the White-striped free-tailed bat ( Austronomus australis). Increased surrounding tree cover and wetland size had a positive effect on bat species richness. Our findings indicate that wetlands form critical habitats for insectivorous bats in urban environments. Large, unlit, and unpolluted wetlands flanked by high tree cover in close proximity to bushland contribute most to the richness of the bat community. Our findings clarify the role of wetlands for insectivorous bats in urban areas and will also allow for the preservation, construction, and management of wetlands that maximize conservation outcomes for urban bats and possibly other wetland-dependent and nocturnal fauna. [ABSTRACT FROM AUTHOR]

Climate refugia are regions that animals can retreat to, persist in and potentially then expand from under changing environmental conditions. Most forecasts of climate change refugia for species are based on correlative species distribution models ( SDMs) using long-term climate averages, projected to future climate scenarios. Limitations of such methods include the need to extrapolate into novel environments and uncertainty regarding the extent to which proximate variables included in the model capture processes driving distribution limits (and thus can be assumed to provide reliable predictions under new conditions). These limitations are well documented; however, their impact on the quality of climate refugia predictions is difficult to quantify. Here, we develop a detailed bioenergetics model for the koala. It indicates that range limits are driven by heat-induced water stress, with the timing of rainfall and heat waves limiting the koala in the warmer parts of its range. We compare refugia predictions from the bioenergetics model with predictions from a suite of competing correlative SDMs under a range of future climate scenarios. SDMs were fitted using combinations of long-term climate and weather extremes variables, to test how well each set of predictions captures the knowledge embedded in the bioenergetics model. Correlative models produced broadly similar predictions to the bioenergetics model across much of the species' current range - with SDMs that included weather extremes showing highest congruence. However, predictions in some regions diverged significantly when projecting to future climates due to the breakdown in correlation between climate variables. We provide unique insight into the mechanisms driving koala distribution and illustrate the importance of subtle relationships between the timing of weather events, particularly rain relative to hot-spells, in driving species-climate relationships and distributions. By unpacking the mechanisms captured by correlative SDMs, we can increase our certainty in forecasts of climate change impacts on species. [ABSTRACT FROM AUTHOR]

Conservation biology faces the challenge of ensuring species persistence in increasingly modified landscapes. Agriculture covers a large proportion of the Earth's surface, but the degree to which crop production is compatible with species use of the landscape is still uncertain, particularly for woodland carnivores with large territories. Here, we focus on the Iberian lynx Lynx pardinus, an emblematic endangered species that has coexisted for centuries with human-modified Mediterranean mosaics, as a case study to unravel habitat and dispersal preferences in heterogeneous landscapes., We estimated species resource selection from ≈40 000 telemetry locations for 48 GPS-collared individuals covering all the current Iberian lynx range, including more fragmented areas where the species was reintroduced from 2009. We differentiated GPS locations within home ranges (to estimate habitat suitability) and those corresponding to dispersal or exploratory movements (to estimate landscape permeability). We built mixed conditional logistic regression models with 12 land cover classes, terrain slope and roads as predictors., We found that lynx response to agriculture largely depends on the crop type and on the presence of natural vegetation remnants. Lynx largely avoided intensive cultivation areas such as irrigated arable lands when establishing home ranges, but frequently selected permanent crops (olive groves) and/or heterogeneous agricultural lands, which were used with smaller differences to the most preferred shrubland or forest covers than reported in previous studies., Such differences further narrowed down when lynx moved outside home ranges, with some agricultural covers being as permeable as shrublands for lynx dispersal. The species dispersal plasticity was also evidenced by a much weaker avoidance of roads and steep terrain when dispersing than when selecting territories., Synthesis and applications. We conclude that (i) the widespread consideration of all agricultural lands within a single (and usually regarded as unsuitable) class for the study and management of woodland or forest species is not supported and that (ii) the ability of woodland species to use fragmented and heterogeneous agricultural landscapes may have been underestimated, which may mislead conservation measures due to a priori assumptions that do not relate to the actual species responses to heterogeneous land covers. We suggest that Iberian lynx conservation and reintroduction may be successful in a wider set of more heterogeneous areas than previously thought, including mainly well-conserved Mediterranean woodlands but also some extensive agricultural lands with permanent crops and natural vegetation remnants. [ABSTRACT FROM AUTHOR]

Fire regimes are predicted to change under climate change, with associated impacts on species and ecosystems. However, the magnitude and direction of regime changes are uncertain, as will be species' responses. For many species, how they respond will determine their medium-long-term viability. We propagate fire regime and species' response uncertainties through a 50-year viability analysis of the great desert skink, Liopholis kintorei, in central Australia, characterizing fire regime change under three scenarios. Species' response uncertainty was characterized with three competing models based on fire and habitat variables, fitted to 11 years of occupancy data. We evaluate fire management options for conserving the species, based on their robustness to uncertainty about fire and species' response. Efforts to minimize the frequency and size of fires provides the most consistent improvements to species' persistence. We show that disentangling important from unimportant uncertainties enables conservation managers to make more efficient, defensible decisions. [ABSTRACT FROM AUTHOR]

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Debates about 'land-sparing' and 'land-sharing' strategies for conserving biodiversity in cities provide an overly simplistic characterization of alternate planning options. Increased urbanization manifests in a number of ways and sophisticated analyses of how species respond to urban environments are required before generalizations about the relative merits of either planning strategy should be made., We investigated how insectivorous bats respond to housing density (a measure of urbanization intensity) and a range of habitat variables by modelling the occupancy and activity of 12 species in Melbourne, Australia. In addition to species-level analyses, species were grouped into guilds ('matrix', 'patch' or 'edge' species) depending on their ecomorphology and level of patch-dependency., Housing density (dwellings per hectare: dph) was the dominant explanatory variable of occupancy and activity of most species studied. Site occupancy probabilities of patch and edge species were reduced by half at housing densities of just 1·1-4·5 dph depending on species, while their activity was halved at housing densities of 2·6-10·3 dph. The activity of two matrix species also declined, but at higher housing densities (reducing by half at 4·5-7·9 dph). Patch and edge species responded nonlinearly to tree cover at low housing densities, with peaks in occupancy and activity at 20-60%. This response broke down at medium housing densities, however, as most species were no longer present., Synthesis and applications. Occupancy probability and activity of almost all bat species studied were substantially reduced even at very low housing densities. Increasing tree cover had no positive effect on the occupancy and activity of patch and edge species once medium housing densities were reached. In order for land-sharing strategies to provide good habitat for patch and edge bat species housing densities would need to be so low as to be impractical in most urban planning contexts. By contrast, land-sparing with forested habitat remaining in 20% or more of the landscape could provide positive conservation outcomes for the species modelled here. We discuss the relevance of our findings in planning for conservation of bats and their habitats in other recently established and expanding cities. [ABSTRACT FROM AUTHOR]