Identifying historical and future global change drivers that place species recovery at risk.

Ecosystem management in the face of global change requires understanding how co-occurring threats affect species and communities. Such an understanding allows for effective management strategies to be identified and implemented. An important component of this is differentiating between factors that are within (e.g. invasive predators) or outside (e.g. drought, large wildfires) of a local manager's control. In the global biodiversity hotspot of south-western Australia, small- and medium-sized mammal species are severely affected by anthropogenic threats and environmental disturbances, including invasive predators, fire, and declining rainfall. However, the relative importance of different drivers has not been quantified. We used data from a long-term monitoring program to fit Bayesian state-space models that estimated spatial and temporal changes in the relative abundance of four threatened mammal species: the woylie (Bettongia penicillata), chuditch (Dasyurus geoffroii), koomal (Trichosurus vulpecula) and quenda (Isoodon fusciventor). We then use Bayesian structural equation modelling to identify the direct and indirect drivers of population changes, and scenario analysis to forecast population responses to future environmental change. We found that habitat loss or conversion and reduced primary productivity (caused by rainfall declines) had greater effects on species' spatial and temporal population change than the range of fire and invasive predator (the red fox Vulpes vulpes) management actions observed in the study area. Scenario analysis revealed that a greater extent of severe fire and further rainfall declines predicted under climate change, operating in concert are likely to further reduce the abundance of these species, but may be mitigated partially by invasive predator control. Considering both historical and future drivers of population change is necessary to identify the factors that risk species recovery. Given that both anthropogenic pressures and environmental disturbances can undermine conservation efforts, managers must consider how the relative benefit of conservation actions will be shaped by ongoing global change.

Long-term livestock exclusion increases plant richness and reproductive capacity in arid woodlands.

Herbivore exclusion is implemented globally to recover ecosystems from grazing by introduced and native herbivores, but evidence for large-scale biodiversity benefits is inconsistent in arid ecosystems. We examined the effects of livestock exclusion on dryland plant richness and reproductive capacity. We collected data on plant species richness and seeding (reproductive capacity), rainfall, vegetation productivity and cover, soil strength and herbivore grazing intensity from 68 sites across 6500 km2 of arid Georgina gidgee (Acacia georginae) woodlands in central Australia between 2018 and 2020. Sites were on an actively grazed cattle station and two destocked conservation reserves. We used structural equation modeling to examine indirect (via soil or vegetation modification) versus direct (herbivory) effects of grazing intensity by two introduced herbivores (cattle, camels) and a native herbivore (red kangaroo), on seasonal plant species richness and seeding of all plants, and the richness and seeding of four plant groups (native grasses, forbs, annual chenopod shrubs, and palatable perennial shrubs). Non-native herbivores had a strong indirect effect on plant richness and seeding by reducing vegetative ground cover, resulting in decreased richness and seeding of native grasses and forbs. Herbivores also had small but negative direct impacts on plant richness and seeding. This direct effect was explained by reductions in annual chenopod and palatable perennial shrub richness under grazing activity. Responses to grazing were herbivore-dependent; introduced herbivore grazing reduced native plant richness and seeding, while native herbivore grazing had no significant effect on richness or seeding of different plant functional groups. Soil strength decreased under grazing by cattle but not camels or kangaroos. Cattle had direct effects on palatable perennial shrub richness and seeding, whereas camels had indirect effects, reducing richness and seeding by reducing the abundance of shrubs. We show that considering indirect pathways improves evaluations of the effects of disturbances on biodiversity, as focusing only on direct effects can mask critical mechanisms of change. Our results indicate substantial biodiversity benefits from excluding livestock and controlling camels in drylands. Reducing introduced herbivore impacts will improve soil and vegetation condition, ensure reproduction and seasonal persistence of species, and protect native plant diversity.

Effects of different management strategies on long-term trends of Australian threatened and near-threatened mammals.

Monitoring is critical to assess management effectiveness, but broadscale systematic assessments of monitoring to evaluate and improve recovery efforts are lacking. We compiled 1808 time series from 71 threatened and near-threatened terrestrial and volant mammal species and subspecies in Australia (48% of all threatened mammal taxa) to compare relative trends of populations subject to different management strategies. We adapted the Living Planet Index to develop the Threatened Species Index for Australian Mammals and track aggregate trends for all sampled threatened mammal populations and for small (<35 g), medium (35-5500 g), and large mammals (>5500 g) from 2000 to 2017. Unmanaged populations (42 taxa) declined by 63% on average; unmanaged small mammals exhibited the greatest declines (96%). Populations of 17 taxa in havens (islands and fenced areas that excluded or eliminated introduced red foxes [Vulpes vulpes] and domestic cats [Felis catus]) increased by 680%. Outside havens, populations undergoing sustained predator baiting initially declined by 75% but subsequently increased to 47% of their abundance in 2000. At sites where predators were not excluded or baited but other actions (e.g., fire management, introduced herbivore control) occurred, populations of small and medium mammals declined faster, but large mammals declined more slowly, than unmanaged populations. Only 13% of taxa had data for both unmanaged and managed populations; index comparisons for this subset showed that taxa with populations increasing inside havens declined outside havens but taxa with populations subject to predator baiting outside havens declined more slowly than populations with no management and then increased, whereas unmanaged populations continued to decline. More comprehensive and improved monitoring (particularly encompassing poorly represented management actions and taxonomic groups like bats and small mammals) is required to understand whether and where management has worked. Improved implementation of management for threats other than predation is critical to recover Australia's threatened mammals.

Efectos de diferentes estrategias de manejo sobre las tendencias a largo plazo de los mamíferos amenazados y casi amenazados de Australia Resumen El monitoreo es fundamental para evaluar la efectividad del manejo, aunque faltan evaluaciones sistemáticas y a gran escala de este monitoreo para evaluar y mejorar los esfuerzos de recuperación. Compilamos 1,808 series temporales de 71 especies y subespecies de mamíferos terrestres y voladores amenazadas y casi amenazadas en Australia (48% de todos los taxones de mamíferos amenazados) para comparar las tendencias relativas de las poblaciones sujetas a diferentes estrategias de manejo. Adaptamos el Índice Planeta Vivo para desarrollar el Índice de Especies Amenazadas para los Mamíferos Australianos y así rastrear las tendencias agregadas de todas las poblaciones muestreadas de mamíferos amenazados y de los mamíferos pequeños (<35 g), medianos (35-5,500 g) y grandes (>5,500 g) entre 2000 y 2017. Las poblaciones sin manejo (42 taxones) declinaron en un 63% en promedio; los mamíferos pequeños sin manejo exhibieron las declinaciones más marcadas (96%). Las poblaciones de 17 taxones incrementaron 680% en los refugios (islas o áreas encercadas que excluían o eliminaban al zorro rojo [Vulpes vulpes] y al gato doméstico [Felis catus], especies introducidas) Afuera de los refugios, las poblaciones sometidas al cebado constante de los depredadores en un inicio declinaron en un 75% pero después incrementaron al 47% de su abundancia para el 2000. En los sitios en donde los depredadores no fueron excluidos o cebados sino sometidos a otras acciones (manejo del fuego, control de herbívoros introducidos), las poblaciones de los mamíferos pequeños y medianos declinaron más rápido, pero los mamíferos grandes declinaron de manera más lenta que las poblaciones sin manejo. Sólo el 13% de los taxones contaron con datos para sus poblaciones con y sin manejo; las comparaciones entre índices para este subconjunto mostraron que los taxones con poblaciones en incremento dentro de los refugios declinaron afuera de éstos, pero los taxones con poblaciones sujetas al cebado de depredadores afuera de los refugios declinaron más lentamente que las poblaciones sin manejo y después incrementaron, mientras que las poblaciones sin manejo continuaron su declinación. Se requiere un monitoreo más completo y mejorado (particularmente el que engloba las acciones de manejo mal representadas y los grupos taxonómicos como los murciélagos y los mamíferos pequeños) para entender si ha funcionado el manejo y en dónde. La implementación mejorada del manejo para las amenazas distintas a la depredación es fundamental para recuperar a los mamíferos amenazados de Australia.

How to prioritize species recovery after a megafire.

Due to climate change, megafires are increasingly common and have sudden, extensive impacts on many species over vast areas, leaving decision makers uncertain about how best to prioritize recovery. We devised a decision-support framework to prioritize conservation actions to improve species outcomes immediately after a megafire. Complementary locations are selected to extend recovery actions across all fire-affected species' habitats. We applied our method to areas burned in the 2019-2020 Australian megafires and assessed its conservation advantages by comparing our results with outcomes of a site-richness approach (i.e., identifying areas that cost-effectively recover the most species in any one location). We found that 290 threatened species were likely severely affected and will require immediate conservation action to prevent population declines and possible extirpation. We identified 179 subregions, mostly in southeastern Australia, that are key locations to extend actions that benefit multiple species. Cost savings were over AU$300 million to reduce 95% of threats across all species. Our complementarity-based prioritization also spread postfire management actions across a wider proportion of the study area compared with the site-richness method (43% vs. 37% of the landscape managed, respectively) and put more of each species' range under management (average 90% vs. 79% of every species' habitat managed). In addition to wildfire response, our framework can be used to prioritize conservation actions that will best mitigate threats affecting species following other extreme environmental events (e.g., floods and drought).

Debido al cambio climático, los mega incendios son cada vez más comunes y tienen un impacto repentino y extenso sobre muchas especies en inmensas superficies, lo que deja a los tomadores de decisiones con incertidumbre sobre cuál es la mejor manera de priorizar la recuperación. Diseñamos un marco de apoyo a las decisiones para priorizar las acciones de conservación para mejorar los resultados para las especies inmediatamente después de un mega incendio. Para esto, se seleccionan localidades complementarias para extender las acciones de recuperación por todos los hábitats de las especies afectadas por el incendio. Aplicamos nuestro método a las áreas afectadas por los mega incendios de 2019-2020 en Australia y analizamos las ventajas de conservación del método mediante la comparación entre nuestros resultados y aquellos de un enfoque en la riqueza de especies (es decir, la identificación de las áreas que recuperan de manera rentable la mayor cantidad de especies en cualquier localidad única). Encontramos que 290 especies amenazadas estuvieron probablemente afectadas de manera severa y requerirán acciones inmediatas de conservación para prevenir la declinación poblacional y la posible eliminación. Identificamos 179 subregiones, la mayoría en el sureste de Australia, que son localidades clave para extender las acciones que benefician a muchas especies. El ahorro en los gastos fue de más de AU$300 millones para reducir el 95% de las amenazas para todas las especies. Nuestra priorización basada en la complementariedad también extendió las acciones de manejo posterior al incendio a una mayor proporción del área de estudio en comparación con el método de riqueza de especies (43% versus 37% del paisaje gestionado, respectivamente) y colocó más de la distribución de cada especie bajo manejo (en promedio 90% versus 79% del hábitat manejado de cada especie). Además de la respuesta a los incendios, nuestro marco puede usarse para priorizar las acciones de conservación que mitiguen de mejor manera las amenazas que afectan a las especies después de otros eventos ambientales extremos (p. ej., inundaciones y sequía).

Ecological forecasts to inform near-term management of threats to biodiversity.

Ecosystems are being altered by rapid and interacting changes in natural processes and anthropogenic threats to biodiversity. Uncertainty in historical, current and future effectiveness of actions hampers decisions about how to mitigate changes to prevent biodiversity loss and species extinctions. Research in resource management, agriculture and health indicates that forecasts predicting the effects of near-term or seasonal environmental conditions on management greatly improve outcomes. Such forecasts help resolve uncertainties about when and how to operationalize management. We reviewed the scientific literature on environmental management to investigate whether near-term forecasts are developed to inform biodiversity decisions in Australia, a nation with one of the highest recent extinction rates across the globe. We found that forecasts focused on economic objectives (e.g. fisheries management) predict on significantly shorter timelines and answer a broader range of management questions than forecasts focused on biodiversity conservation. We then evaluated scientific literature on the effectiveness of 484 actions to manage seven major terrestrial threats in Australia, to identify opportunities for near-term forecasts to inform operational conservation decisions. Depending on the action, between 30% and 80% threat management operations experienced near-term weather impacts on outcomes before, during or after management. Disease control, species translocation/reintroduction and habitat restoration actions were most frequently impacted, and negative impacts such as increased species mortality and reduced recruitment were more likely than positive impacts. Drought or dry conditions, and rainfall, were the most frequently reported weather impacts, indicating that near-term forecasts predicting the effects of low or excessive rainfall on management outcomes are likely to have the greatest benefits. Across the world, many regions are, like Australia, becoming warmer and drier, or experiencing more extreme rainfall events. Informing conservation decisions with near-term and seasonal ecological forecasting will be critical to harness uncertainties and lower the risk of threat management failure under global change.

Predator responses to fire: A global systematic review and meta-analysis.

Knowledge of how disturbances such as fire shape habitat structure and composition, and affect animal interactions, is fundamental to ecology and ecosystem management. Predators also exert strong effects on ecological communities, through top-down regulation of prey and competitors, which can result in trophic cascades. Despite their ubiquity, ecological importance and potential to interact with fire, our general understanding of how predators respond to fire remains poor, hampering ecosystem management. To address this important knowledge gap, we conducted a systematic review and meta-analysis of the effects of fire on terrestrial, vertebrate predators world-wide. We found 160 studies spanning 1978-2018. There were 36 studies with sufficient information for meta-analysis, from which we extracted 96 effect sizes (Hedges' g) for 67 predator species relating to changes in abundance indices, occupancy or resource selection in burned and unburned areas, or before and after fire. Studies spanned geographic locations, taxonomic families and study designs, but most were located in North America and Oceania (59% and 24%, respectively), and largely focussed on felids (24%) and canids (25%). Half (50%) of the studies reported responses to wildfire, and nearly one third concerned prescribed (management) fires. There were no clear, general responses of predators to fire, nor relationships with geographic area, biome or life-history traits (e.g. body mass, hunting strategy and diet). Responses varied considerably between species. Analysis of species for which at least three effect sizes had been reported in the literature revealed that red foxes Vulpes vulpes mostly responded positively to fire (e.g. higher abundance in burned compared to unburned areas) and eastern racers Coluber constrictor negatively, with variances overlapping zero only slightly for both species. Our systematic review and meta-analysis revealed strong variation in predator responses to fire, and major geographic and taxonomic knowledge gaps. Varied responses of predator species to fire likely depend on ecosystem context. Consistent reporting of ongoing monitoring and management experiments is required to improve understanding of the mechanisms driving predator responses to fire, and any broader effects (e.g. trophic interactions). The divergent responses of species in our study suggest that adaptive, context-specific management of predator-fire relationships is required.

Patch-scale culls of an overabundant bird defeated by immediate recolonization.

Overabundant native animals cause a variety of human-wildlife conflicts that can require management to reduce their social, environmental, or economic impacts. Culling is an intuitively attractive management response to overabundance, but poor monitoring of results and costs means that evidence for successful outcomes is often lacking. Furthermore, many culls worldwide have been ineffective or counterproductive due to ecological release mechanisms or compensatory responses by the overabundant species. We completed a controlled, replicated, costed, and rigorously monitored experimental cull of the endemic Australian honeyeater, the Noisy Miner (Manorina melanocephala). Aggressive exclusion of birds from remnant woodland patches by overabundant Noisy Miners is listed as a Key Threatening Process under Australian conservation legislation due to its impacts on threatened birds. The problem is particularly prevalent in the highly modified agricultural landscapes of eastern Australia. The species impacts avian assemblages at low densities (0.6-0.8 birds/ha) and at a subcontinental scale (>1 million km2 ). Some ecologists recommend culling as the only management response capable of timely reversal of declines of threatened small woodland birds. We monitored Noisy Miner abundance before and for 12 months after a culling program and found that immediate recolonization from the surrounding landscape negated the impact of the cull. We hypothesize that this is due to a vacuum effect; whereby, birds resident in more marginal habitat around treatment patches move into the vacant territory post-cull. Modeled mean abundance of Noisy Miners declined by 22% in treatment sites compared to an increase of 4% in control sites in the post-cull period. Abundance in all sites, however, remained three to five times higher than published ecological impact thresholds. Return on investment analysis indicated no relationship between culling effort and reduction in Noisy Miner abundance. We conclude that culling at a patch scale is not an efficient method of reducing Noisy Miner abundance to levels unlikely to impact threatened woodland birds in the highly modified study landscape, despite estimated costs 18 times lower than another potential management response of revegetation. Our study highlights the importance of building empirical evidence before intuitively attractive but not necessarily ecologically effective management responses are applied more widely.

Using ideal distributions of the time since habitat was disturbed to build metrics for evaluating landscape condition.

Developing a standardized approach to measuring the state of biodiversity in landscapes undergoing disturbance is crucial for evaluating and comparing change across different systems, assessing ecosystem vulnerability and the impacts of destructive activities, and helping direct species recovery actions. Existing ecosystem metrics of condition fail to acknowledge that a particular community could be in multiple states, and the distribution of states could worsen or improve when impacted by a disturbance process, depending on how far the current landscape distribution of states diverges from pre-anthropogenic impact baseline conditions. We propose a way of rapidly assessing regional-scale condition in ecosystems where the distribution of age classes representing increasing time since last disturbance is suspected to have diverged from an ideal benchmark reference distribution. We develop two metrics that (1) compare the observed mean time since last disturbance with an expected mean and (2) quantify the summed shortfall of vegetation age-class frequencies relative to a reference age-class distribution of time since last disturbance. We demonstrate the condition metrics using two case studies: (1) fire in threatened southwestern Australian proteaceaous mallee-heath and (2) impacts of disturbance (fire and logging) in the critically endangered southeastern Australian mountain ash Eucalyptus regnans forest on the yellow-bellied glider Petaurus australis. We explore the effects of uncertainty in benchmark time since last disturbance, and evaluate metric sensitivity using simulated age-class distributions representing alternative ecosystems. By accounting for and penalizing too-frequent and too-rare disturbances, the summed shortfall metric is more sensitive to change than mean time since last disturbance. We find that mountain ash forest is in much poorer condition (summed shortfall 38.5 out of 100 for a 120-yr benchmark disturbance interval) than indicated merely by loss of extent (84% of vegetation remaining). Proteaceaous mallee-heath is in worse condition than indicated by loss of extent for an upper benchmark interval of 80 yr, but condition almost doubles for the minimum tolerable time since last disturbance interval of 20 yr. To fully describe ecosystem degradation, we recommend that our summed shortfall metric, focused on habitat quality and informed by biologically meaningful baselines, be added to existing condition measures focused on vegetation extent. This will improve evaluation of change in ecosystem states and enhance management of ecosystems in poor condition.

Understanding the effects of different social data on selecting priority conservation areas.

Conservation success is contingent on assessing social and environmental factors so that cost-effective implementation of strategies and actions can be placed in a broad social-ecological context. Until now, the focus has been on how to include spatially explicit social data in conservation planning, whereas the value of different kinds of social data has received limited attention. In a regional systematic conservation planning case study in Australia, we examined the spatial concurrence of a range of spatially explicit social values and land-use preferences collected using a public participation geographic information system and biological data. We used Zonation to integrate the social data with the biological data in a series of spatial-prioritization scenarios to determine the effect of the different types of social data on spatial prioritization compared with biological data alone. The type of social data (i.e., conservation opportunities or constraints) significantly affected spatial prioritization outcomes. The integration of social values and land-use preferences under different scenarios was highly variable and generated spatial prioritizations 1.2-51% different from those based on biological data alone. The inclusion of conservation-compatible values and preferences added relatively few new areas to conservation priorities, whereas including noncompatible economic values and development preferences as costs significantly changed conservation priority areas (48.2% and 47.4%, respectively). Based on our results, a multifaceted conservation prioritization approach that combines spatially explicit social data with biological data can help conservation planners identify the type of social data to collect for more effective and feasible conservation actions.

Quantifying the conservation gains from shared access to linear infrastructure.

The proliferation of linear infrastructure such as roads and railways is a major global driver of cumulative biodiversity loss. One strategy for reducing habitat loss associated with development is to encourage linear infrastructure providers and users to share infrastructure networks. We quantified the reductions in biodiversity impact and capital costs under linear infrastructure sharing of a range of potential mine to port transportation links for 47 mine locations operated by 28 separate companies in the Upper Spencer Gulf Region of South Australia. We mapped transport links based on least-cost pathways for different levels of linear-infrastructure sharing and used expert-elicited impacts of linear infrastructure to estimate the consequences for biodiversity. Capital costs were calculated based on estimates of construction costs, compensation payments, and transaction costs. We evaluated proposed mine-port links by comparing biodiversity impacts and capital costs across 3 scenarios: an independent scenario, where no infrastructure is shared; a restricted-access scenario, where the largest mining companies share infrastructure but exclude smaller mining companies from sharing; and a shared scenario where all mining companies share linear infrastructure. Fully shared development of linear infrastructure reduced overall biodiversity impacts by 76% and reduced capital costs by 64% compared with the independent scenario. However, there was considerable variation among companies. Our restricted-access scenario showed only modest biodiversity benefits relative to the independent scenario, indicating that reductions are likely to be limited if the dominant mining companies restrict access to infrastructure, which often occurs without policies that promote sharing of infrastructure. Our research helps illuminate the circumstances under which infrastructure sharing can minimize the biodiversity impacts of development.

Quantifying the expected value of uncertain management choices for over-abundant Greylag Geese.

In many parts of the world, conservation successes or global anthropogenic changes have led to increasing native species populations that then compete with human resource use. In the Orkney Islands, Scotland, a 60-fold increase in Greylag Goose Anser anser numbers over 24 years has led to agricultural damages and culling attempts that have failed to prevent population increase. To address uncertainty about why populations have increased, we combined empirical modelling of possible drivers of Greylag Goose population change with expert-elicited benefits of alternative management actions to identify whether to learn versus act immediately to reduce damages by geese. We built linear mixed-effects models relating annual goose densities on farms to land-use and environmental covariates and estimated AICc model weights to indicate relative support for six hypotheses of change. We elicited from experts the expected likelihood that one of six actions would achieve an objective of halting goose population growth, given each hypothesis for population change. Model weights and expected effects of actions were combined in Value of Information analysis (VoI) to quantify the utility of resolving uncertainty in each hypothesis through adaptive management and monitoring. The action with the highest expected value under existing uncertainty was to increase the extent of low quality habitats, whereas assuming equal hypothesis weights changed the best action to culling. VoI analysis showed that the value of learning to resolve uncertainty in any individual hypothesis for goose population change was low, due to high support for a single hypothesis of change. Our study demonstrates a two-step framework that learns about the most likely drivers of change for an over-abundant species, and uses this knowledge to weight the utility of alternative management actions. Our approach helps inform which strategies might best be implemented to resolve uncertainty when there are competing hypotheses for change and competing management choices.

Trade-offs between data resolution, accuracy, and cost when choosing information to plan reserves for coral reef ecosystems.

Conservation planners must reconcile trade-offs associated with using biodiversity data of differing qualities to make decisions. Coarse habitat classifications are commonly used as surrogates to design marine reserve networks when fine-scale biodiversity data are incomplete or unavailable. Although finely-classified habitat maps provide more detail, they may have more misclassification errors, a common problem when remotely-sensed imagery is used. Despite these issues, planners rarely consider the effects of errors when choosing data for spatially explicit conservation prioritizations. Here we evaluate trade-offs between accuracy and resolution of hierarchical coral reef habitat data (geomorphology and benthic substrate) derived from remote sensing, in spatial planning for Kubulau District, Fiji. For both, we use accuracy information describing the probability that a mapped habitat classification is correct to design marine reserve networks that achieve habitat conservation targets, and demonstrate inadequacies of using habitat maps without accuracy data. We show that using more detailed habitat information ensures better representation of biogenic habitats (i.e. coral and seagrass), but leads to larger and more costly reserves, because these data have more misclassification errors, and are also more expensive to obtain. Reduced impacts on fishers are possible using coarsely-classified data, which are also more cost-effective for planning reserves if we account for data collection costs, but using these data may under-represent reef habitats that are important for fisheries and biodiversity, due to the maps low thematic resolution. Finally, we show that explicitly accounting for accuracy information in decisions maximizes the chance of successful conservation outcomes by reducing the risk of missing conservation representation targets, particularly when using finely classified data.

Fire management strategies to maintain species population processes in a fragmented landscape of fire-interval extremes.

Changed fire regimes have led to declines of fire-regime-adapted species and loss of biodiversity globally. Fire affects population processes of growth, reproduction, and dispersal in different ways, but there is little guidance about the best fire regime(s) to maintain species population processes in fire-prone ecosystems. We use a process-based approach to determine the best range of fire intervals for keystone plant species in a highly modified Mediterranean ecosystem in southwestern Australia where current fire regimes vary. In highly fragmented areas, fires are few due to limited ignitions and active suppression of wildfire on private land, while in highly connected protected areas fires are frequent and extensive. Using matrix population models, we predict population growth of seven Banksia species under different environmental conditions and patch connectivity, and evaluate the sensitivity of species survival to different fire management strategies and burning intervals. We discover that contrasting, complementary patterns of species life-histories with time since fire result in no single best fire regime. All strategies result in the local patch extinction of at least one species. A small number of burning strategies secure complementary species sets depending on connectivity and post-fire growing conditions. A strategy of no fire always leads to fewer species persisting than prescribed fire or random wildfire, while too-frequent or too-rare burning regimes lead to the possible local extinction of all species. In low landscape connectivity, we find a smaller range of suitable fire intervals, and strategies of prescribed or random burning result in a lower number of species with positive growth rates after 100 years on average compared with burning high connectivity patches. Prescribed fire may reduce or increase extinction risk when applied in combination with wildfire depending on patch connectivity. Poor growing conditions result in a significantly reduced number of species exhibiting positive growth rates after 100 years of management. By exploring the consequences of managing fire, we are able to identify which species are likely to disappear under a given fire regime. Identifying the appropriate complementarity of fire intervals, and their species-specific as well as community-level consequences, is crucial to reduce local extinctions of species in fragmented fire-prone landscapes.

Using empirical models of species colonization under multiple threatening processes to identify complementary threat-mitigation strategies.

Approaches to prioritize conservation actions are gaining popularity. However, limited empirical evidence exists on which species might benefit most from threat mitigation and on what combination of threats, if mitigated simultaneously, would result in the best outcomes for biodiversity. We devised a way to prioritize threat mitigation at a regional scale with empirical evidence based on predicted changes to population dynamics-information that is lacking in most threat-management prioritization frameworks that rely on expert elicitation. We used dynamic occupancy models to investigate the effects of multiple threats (tree cover, grazing, and presence of an hyperaggressive competitor, the Noisy Miner (Manorina melanocephala) on bird-population dynamics in an endangered woodland community in southeastern Australia. The 3 threatening processes had different effects on different species. We used predicted patch-colonization probabilities to estimate the benefit to each species of removing one or more threats. We then determined the complementary set of threat-mitigation strategies that maximized colonization of all species while ensuring that redundant actions with little benefit were avoided. The single action that resulted in the highest colonization was increasing tree cover, which increased patch colonization by 5% and 11% on average across all species and for declining species, respectively. Combining Noisy Miner control with increasing tree cover increased species colonization by 10% and 19% on average for all species and for declining species respectively, and was a higher priority than changing grazing regimes. Guidance for prioritizing threat mitigation is critical in the face of cumulative threatening processes. By incorporating population dynamics in prioritization of threat management, our approach helps ensure funding is not wasted on ineffective management programs that target the wrong threats or species.

A conservation planning approach to mitigate the impacts of leakage from protected area networks.

Protected area networks are designed to restrict anthropogenic pressures in areas of high biodiversity. Resource users respond by seeking to replace some or all of the lost resources from locations elsewhere in the landscape. Protected area networks thereby perturb the pattern of human pressures by displacing extractive effort from within protected areas into the broader landscape, a process known as leakage. The negative effects of leakage on conservation outcomes have been empirically documented and modeled using homogeneous descriptions of conservation landscapes. Human resource use and biodiversity vary greatly in space, however, and a theory of leakage must describe how this heterogeneity affects the magnitude, pattern, and biodiversity impacts of leakage. We combined models of household utility, adaptive human foraging, and biodiversity conservation to provide a bioeconomic model of leakage that accounts for spatial heterogeneity. Leakage had strong and divergent impacts on the performance of protected area networks, undermining biodiversity benefits but mitigating the negative impacts on local resource users. When leakage was present, our model showed that poorly designed protected area networks resulted in a substantial net loss of biodiversity. However, the effects of leakage can be mitigated if they are incorporated ex-ante into the conservation planning process. If protected areas are coupled with nonreserve policy instruments such as market subsidies, our model shows that the trade-offs between biodiversity and human well-being can be further and more directly reduced.

Effects of threat management interactions on conservation priorities.

Decisions need to be made about which biodiversity management actions are undertaken to mitigate threats and about where these actions are implemented. However, management actions can interact; that is, the cost, benefit, and feasibility of one action can change when another action is undertaken. There is little guidance on how to explicitly and efficiently prioritize management for multiple threats, including deciding where to act. Integrated management could focus on one management action to abate a dominant threat or on a strategy comprising multiple actions to abate multiple threats. Furthermore management could be undertaken at sites that are in close proximity to reduce costs. We used cost-effectiveness analysis to prioritize investments in fire management, controlling invasive predators, and reducing grazing pressure in a bio-diverse region of southeastern Queensland, Australia. We compared outcomes of 5 management approaches based on different assumptions about interactions and quantified how investment needed, benefits expected, and the locations prioritized for implementation differed when interactions were taken into account. Managing for interactions altered decisions about where to invest and in which actions to invest and had the potential to deliver increased investment efficiency. Differences in high priority locations and actions were greatest between the approaches when we made different assumptions about how management actions deliver benefits through threat abatement: either all threats must be managed to conserve species or only one management action may be required. Threatened species management that does not consider interactions between actions may result in misplaced investments or misguided expectations of the effort required to mitigate threats to species.

Effect of risk aversion on prioritizing conservation projects.

Conservation outcomes are uncertain. Agencies making decisions about what threat mitigation actions to take to save which species frequently face the dilemma of whether to invest in actions with high probability of success and guaranteed benefits or to choose projects with a greater risk of failure that might provide higher benefits if they succeed. The answer to this dilemma lies in the decision maker's aversion to risk--their unwillingness to accept uncertain outcomes. Little guidance exists on how risk preferences affect conservation investment priorities. Using a prioritization approach based on cost effectiveness, we compared 2 approaches: a conservative probability threshold approach that excludes investment in projects with a risk of management failure greater than a fixed level, and a variance-discounting heuristic used in economics that explicitly accounts for risk tolerance and the probabilities of management success and failure. We applied both approaches to prioritizing projects for 700 of New Zealand's threatened species across 8303 management actions. Both decision makers' risk tolerance and our choice of approach to dealing with risk preferences drove the prioritization solution (i.e., the species selected for management). Use of a probability threshold minimized uncertainty, but more expensive projects were selected than with variance discounting, which maximized expected benefits by selecting the management of species with higher extinction risk and higher conservation value. Explicitly incorporating risk preferences within the decision making process reduced the number of species expected to be safe from extinction because lower risk tolerance resulted in more species being excluded from management, but the approach allowed decision makers to choose a level of acceptable risk that fit with their ability to accommodate failure. We argue for transparency in risk tolerance and recommend that decision makers accept risk in an adaptive management framework to maximize benefits and avoid potential extinctions due to inefficient allocation of limited resources.

Informed actions: where to cost effectively manage multiple threats to species to maximize return on investment.

Conservation practitioners, faced with managing multiple threats to biodiversity and limited funding, must prioritize investment in different management actions. From an economic perspective, it is routine practice to invest where the highest rate of return is expected. This return-on-investment (ROI) thinking can also benefit species conservation, and researchers are developing sophisticated approaches to support decision-making for cost-effective conservation. However, applied use of these approaches is limited. Managers may be wary of "black-box" algorithms or complex methods that are difficult to explain to funding agencies. As an alternative, we demonstrate the use of a basic ROI analysis for determining where to invest in cost-effective management to address threats to species. This method can be applied using basic geographic information system and spreadsheet calculations. We illustrate the approach in a management action prioritization for a biodiverse region of eastern Australia. We use ROI to prioritize management actions for two threats to a suite of threatened species: habitat degradation by cattle grazing, and predation by invasive red foxes (Vulpes vulpes). We show how decisions based on cost-effective threat management depend upon how expected benefits to species are defined and how benefits and costs co-vary. By considering a combination of species richness, restricted habitats, species vulnerability, and costs of management actions, small investments can result in greater expected benefit compared with management decisions that consider only species richness. Furthermore, a landscape management strategy that implements multiple actions is more efficient than managing only for one threat, or more traditional approaches that don't consider ROI. Our approach provides transparent and logical decision support for prioritizing different actions intended to abate threats associated with multiple species; it is of use when managers need a justifiable and repeatable approach to investment.

The value of using feasibility models in systematic conservation planning to predict landholder management uptake.

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple-use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders' willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders' decisions to engage in management. To test the utility of our best-supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost-effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost-effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost-efficient and effective manner.

Predicting species distributions for conservation decisions.

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.