How success is evaluated in collaborative invasive species management: A systematic review

Invasive species are one of the most pressing global challenges for biodiversity and agriculture. They can cause species extinctions, ecosystem alterations, crop damage, and spread harmful diseases across broad regions. Overcoming this challenge requires collaborative management efforts that span multiple land tenures and jurisdictions. Despite evidence on the importance and approaches to collaboration, there is little understanding of how success is evaluated in the invasive species management literature. This is a major gap, considering evaluating success is crucial for enhancing the efficacy of future management projects. To overcome this knowledge gap, we systematically reviewed the published literature to identify the stages at which success is evaluated - that is, the Process stage (collaborative management actions and Processes), Outputs stage (results of management actions to protect environmental, economic, and social values) and Outcomes stage (effects of Outputs on environmental, economic, and social values) of collaborative invasive species management projects. We also assessed what indicators were used to identify success and whether these evaluations vary across different characteristics of collaborative invasive species management. Our literature search detected 1406 papers, of which 58 met our selection criteria. Out of these, the majority of papers evaluated success across two stages (n = 25, 43.1%), whereas only ten (17.2%) papers evaluated success across all stages. Outputs were the most commonly evaluated stage (n = 40, 68.9%). The most widely used indicators of success for these stages included increased collaboration of stakeholders (Process stage), the number of captured/eradicated/controlled invasive species (Outputs stage) and change in biodiversity values, such as the number of threatened species (Outcomes stage). Most indicators of success were environmentally focused. We highlight the need to align the indicators of success and evaluation stages with the fundamental objectives of the projects to increase the effectiveness of evaluations and thereby maximise the benefits of collaborative invasive species management.

Optimal restoration for pollination services increases forest cover while doubling agricultural profits

Pollinators are currently facing dramatic declines in abundance and richness across the globe. This can have profound impacts on agriculture, as 75% of globally common food crops benefit from pollination services. As many native bee species require natural areas for nesting, restoration efforts within croplands may be beneficial to support pollinators and enhance agricultural yields. Yet, restoration can be challenging to implement due to large upfront costs and the removal of land from production. Designing sustainable landscapes will require planning approaches that include the complex spatiotemporal dynamics of pollination services flowing from (restored) vegetation into crops. We present a novel planning framework to determine the best spatial arrangement for restoration in agricultural landscapes while accounting for yield improvements over 40 years following restoration. We explored a range of production and conservation goals using a coffee production landscape in Costa Rica as a case study. Our results show that strategic restoration can increase forest cover by approximately 20% while doubling collective landholder profits over 40 years, even when accounting for land taken out of production. We show that restoration can provide immense economic benefits in the long run, which may be pivotal to motivating local landholders to undertake conservation endeavours in pollinator-dependent croplands.

Analysis of sloppiness in model simulations: Unveiling parameter uncertainty when mathematical models are fitted to data

This work introduces a comprehensive approach to assess the sensitivity of model outputs to changes in parameter values, constrained by the combination of prior beliefs and data. This approach identifies stiff parameter combinations strongly affecting the quality of the model-data fit while simultaneously revealing which of these key parameter combinations are informed primarily by the data or are also substantively influenced by the priors. We focus on the very common context in complex systems where the amount and quality of data are low compared to the number of model parameters to be collectively estimated, and showcase the benefits of this technique for applications in biochemistry, ecology, and cardiac electrophysiology. We also show how stiff parameter combinations, once identified, uncover controlling mechanisms underlying the system being modeled and inform which of the model parameters need to be prioritized in future experiments for improved parameter inference from collective model-data fitting.

Unrecognized threat to global soil carbon by a widespread invasive species

Most of Earth's terrestrial carbon is stored in the soil and can be released as carbon dioxide (CO₂ ) when disturbed. Although humans are known to exacerbate soil CO₂ emissions through land-use change, we know little about the global carbon footprint of invasive species. We predict the soil area disturbed and resulting CO₂ emissions from wild pigs (Sus scrofa), a pervasive human-spread vertebrate that uproots soil. We do this using models of wild pig population density, soil damage, and their effect on soil carbon emissions. Our models suggest that wild pigs are uprooting a median area of 36,214 km² (mean of 123,517 km² ) in their non-native range, with a 95% prediction interval (PI) of 14,208 km² -634,238 km² . This soil disturbance results in median emissions of 4.9 million metric tonnes (MMT) CO₂ per year (equivalent to 1.1 million passenger vehicles or 0.4% of annual emissions from land use, land-use change, and forestry; mean of 16.7 MMT) but that it is highly uncertain (95% PI, 0.3-94 MMT CO₂ ) due to variability in wild pig density and soil dynamics. This uncertainty points to an urgent need for more research on the contribution of wild pigs to soil damage, not only for the reduction of anthropogenically related carbon emissions, but also for co-benefits to biodiversity and food security that are crucial for sustainable development.

Invasive wild pigs (Sus scrofa) as a human-mediated source of soil carbon emissions: Uncertainties and future directions

Invasive wild pigs (Sus scrofa) have been spread by humans outside of their native range and are now established on every continent except Antarctica. Through their uprooting of soil, they affect societal and environmental values. Our recent article explored another threat from their soil disturbance: greenhouse gas emissions (O'Bryan et al., Global Change Biology, 2021). In response to our paper, Don (Global Change Biology, 2021) claims there is no threat to global soil carbon stocks by wild pigs. While we did not investigate soil carbon stocks, we examine uncertainties regarding soil carbon emissions from wild pig uprooting and their implications for management and future research.

Informing management decisions for ecological networks, using dynamic models calibrated to noisy time-series data

Well-intentioned environmental management can backfire, causing unforeseen damage. To avoid this, managers and ecologists seek accurate predictions of the ecosystem-wide impacts of interventions, given small and imprecise datasets, which is an incredibly difficult task. We generated and analysed thousands of ecosystem population time series to investigate whether fitted models can aid decision-makers to select interventions. Using these time-series data (sparse and noisy datasets drawn from deterministic Lotka-Volterra systems with two to nine species, of known network structure), dynamic model forecasts of whether a species' future population will be positively or negatively affected by rapid eradication of another species were correct > 70% of the time. Although 70% correct classifications is only slightly better than an uninformative prediction (50%), this classification accuracy can be feasibly improved by increasing monitoring accuracy and frequency. Our findings suggest that models may not need to produce well-constrained predictions before they can inform decisions that improve environmental outcomes.

The value of understanding feedbacks from ecosystem functions to species for managing ecosystems

Ecological systems are made up of complex and often unknown interactions and feedbacks. Uncovering these interactions and feedbacks among species, ecosystem functions, and ecosystem services is challenging, costly, and time-consuming. Here, we ask: for which ecosystem features does resolving the uncertainty about the feedbacks from ecosystem function to species improve management outcomes? We develop a dynamic value of information analysis for risk-neutral and risk-prone managers on motif ecosystems and explore the influence of five ecological features. We find that learning the feedbacks from ecosystem function to species does not improve management outcomes for maximising biodiversity, yet learning which species benefit from an ecosystem function improves management outcomes for ecosystem services by up to 25% for risk-neutral managers and 231% for risk-prone managers. Our general approach provides useful guidance for managers and researchers on when learning feedbacks from ecosystem function to species can improve management outcomes for multiple conservation objectives.

Value of information analyses are a promising approach to decision-making in conservation. Here the authors develop a dynamic approach to show that knowing which species benefit from an ecosystem function improves ecosystem service and biodiversity management, particularly for risk-prone managers.

A novel approach to assessing the ecosystem-wide impacts of reintroductions

Reintroducing a species to an ecosystem can have significant impacts on the recipient ecological community. Although reintroductions can have striking and positive outcomes, they also carry risks; many well-intentioned conservation actions have had surprising and unsatisfactory outcomes. A range of network-based mathematical methods has been developed to make quantitative predictions of how communities will respond to management interventions. These methods are based on the limited knowledge of which species interact with each other and in what way. However, expert knowledge isn't perfect and can only take models so far. Fortunately, other types of data, such as abundance time series, is often available, but, to date, no quantitative method exists to integrate these various data types into these models, allowing more precise ecosystem-wide predictions. In this paper, we develop mathematical methods that combine time-series data of multiple species with knowledge of species interactions and we apply it to proposed reintroductions at Booderee National Park in Australia. There have been large fluctuations in species abundances at Booderee National Park in recent history, following intense feral fox (Vulpes vulpes) control, including the local extinction of the greater glider (Petauroides volans). These fluctuations can provide information about the system isn't readily obtained from a stable system, and we use them to inform models that we then use to predict potential outcomes of eastern quoll (Dasyurus viverrinus) and long-nosed potoroo (Potorous tridactylus) reintroductions. One of the key species of conservation concern in the park is the Eastern Bristlebird (Dasyornis brachypterus), and we find that long-nosed potoroo introduction would have very little impact on the Eastern Bristlebird population, while the eastern quoll introduction increased the likelihood of Eastern Bristlebird decline, although that depends on the strength and form of any possible interaction.

Author Correction: The contribution of predators and scavengers to human well-being

In the version of this Review originally published, there were a number of errors that the authors wish to correct.

The contribution of predators and scavengers to human well-being

Predators and scavengers are frequently persecuted for their negative effects on property, livestock and human life. Research has shown that these species play important regulatory roles in intact ecosystems including regulating herbivore and mesopredator populations that in turn affect floral, soil and hydrological systems. Yet predators and scavengers receive surprisingly little recognition for their benefits to humans in the landscapes they share. We review these benefits, highlighting the most recent studies that have documented their positive effects across a range of environments. Indeed, the benefits of predators and scavengers can be far reaching, affecting human health and well-being through disease mitigation, agricultural production and waste-disposal services. As many predators and scavengers are in a state of rapid decline, we argue that researchers must work in concert with the media, managers and policymakers to highlight benefits of these species and the need to ensure their long-term conservation. Furthermore, instead of assessing the costs of predators and scavengers only in economic terms, it is critical to recognize their beneficial contributions to human health and well-being. Given the ever-expanding human footprint, it is essential that we construct conservation solutions that allow a wide variety of species to persist in shared landscapes. Identifying, evaluating and communicating the benefits provided by species that are often considered problem animals is an important step for establishing tolerance in these shared spaces.

Two-step adaptive management for choosing between two management actions

Adaptive management is widely advocated to improve environmental management. Derivations of optimal strategies for adaptive management, however, tend to be case specific and time consuming. In contrast, managers might seek relatively simple guidance, such as insight into when a new potential management action should be considered, and how much effort should be expended on trialing such an action. We constructed a two-time-step scenario where a manager is choosing between two possible management actions. The manager has a total budget that can be split between a learning phase and an implementation phase. We use this scenario to investigate when and how much a manager should invest in learning about the management actions available. The optimal investment in learning can be understood intuitively by accounting for the expected value of sample information, the benefits that accrue during learning, the direct costs of learning, and the opportunity costs of learning. We find that the optimal proportion of the budget to spend on learning is characterized by several critical thresholds that mark a jump from spending a large proportion of the budget on learning to spending nothing. For example, as sampling variance increases, it is optimal to spend a larger proportion of the budget on learning, up to a point: if the sampling variance passes a critical threshold, it is no longer beneficial to invest in learning. Similar thresholds are observed as a function of the total budget and the difference in the expected performance of the two actions. We illustrate how this model can be applied using a case study of choosing between alternative rearing diets for hihi, an endangered New Zealand passerine. Although the model presented is a simplified scenario, we believe it is relevant to many management situations. Managers often have relatively short time horizons for management, and might be reluctant to consider further investment in learning and monitoring beyond collecting data from a single time period.

Managing consequences of climate-driven species redistribution requires integration of ecology, conservation and social science

Climate change is driving a pervasive global redistribution of the planet's species. Species redistribution poses new questions for the study of ecosystems, conservation science and human societies that require a coordinated and integrated approach. Here we review recent progress, key gaps and strategic directions in this nascent research area, emphasising emerging themes in species redistribution biology, the importance of understanding underlying drivers and the need to anticipate novel outcomes of changes in species ranges. We highlight that species redistribution has manifest implications across multiple temporal and spatial scales and from genes to ecosystems. Understanding range shifts from ecological, physiological, genetic and biogeographical perspectives is essential for informing changing paradigms in conservation science and for designing conservation strategies that incorporate changing population connectivity and advance adaptation to climate change. Species redistributions present challenges for human well-being, environmental management and sustainable development. By synthesising recent approaches, theories and tools, our review establishes an interdisciplinary foundation for the development of future research on species redistribution. Specifically, we demonstrate how ecological, conservation and social research on species redistribution can best be achieved by working across disciplinary boundaries to develop and implement solutions to climate change challenges. Future studies should therefore integrate existing and complementary scientific frameworks while incorporating social science and human-centred approaches. Finally, we emphasise that the best science will not be useful unless more scientists engage with managers, policy makers and the public to develop responsible and socially acceptable options for the global challenges arising from species redistributions.

Using food-web theory to conserve ecosystems

Food-web theory can be a powerful guide to the management of complex ecosystems. However, we show that indices of species importance common in food-web and network theory can be a poor guide to ecosystem management, resulting in significantly more extinctions than necessary. We use Bayesian Networks and Constrained Combinatorial Optimization to find optimal management strategies for a wide range of real and hypothetical food webs. This Artificial Intelligence approach provides the ability to test the performance of any index for prioritizing species management in a network. While no single network theory index provides an appropriate guide to management for all food webs, a modified version of the Google PageRank algorithm reliably minimizes the chance and severity of negative outcomes. Our analysis shows that by prioritizing ecosystem management based on the network-wide impact of species protection rather than species loss, we can substantially improve conservation outcomes.

The influence of species conservation on food webs is less well understood than the effects of species loss. Here, the authors test several indices against optimal food web management and find no current metrics are reliably effective at identifying species conservation priorities.

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.

How to decide whether to move species threatened by climate change

Introducing species to areas outside their historical range to secure their future under climate change is a controversial strategy for preventing extinction. While the debate over the wisdom of this strategy continues, such introductions are already taking place. Previous frameworks for analysing the decision to introduce have lacked a quantifiable management objective and mathematically rigorous problem formulation. Here we develop the first rigorous quantitative framework for deciding whether or not a particular introduction should go ahead, which species to prioritize for introduction, and where and how to introduce them. It can also be used to compare introduction with alternative management actions, and to prioritise questions for future research. We apply the framework to a case study of tuatara (Sphenodon punctatus) in New Zealand. While simple and accessible, this framework can accommodate uncertainty in predictions and values. It provides essential support for the existing IUCN guidelines by presenting a quantitative process for better decision-making about conservation introductions.

A new way to measure the world's protected area coverage

Protected areas are effective at stopping biodiversity loss, but their placement is constrained by the needs of people. Consequently protected areas are often biased toward areas that are unattractive for other human uses. Current reporting metrics that emphasise the total area protected do not account for this bias. To address this problem we propose that the distribution of protected areas be evaluated with an economic metric used to quantify inequality in income— the Gini coefficient. Using a modified version of this measure we discover that 73% of countries have inequitably protected their biodiversity and that common measures of protected area coverage do not adequately reveal this bias. Used in combination with total percentage protection, the Gini coefficient will improve the effectiveness of reporting on the growth of protected area coverage, paving the way for better representation of the world's biodiversity.

The why, what, and how of global biodiversity indicators beyond the 2010 target

The 2010 biodiversity target agreed by signatories to the Convention on Biological Diversity directed the attention of conservation professionals toward the development of indicators with which to measure changes in biological diversity at the global scale. We considered why global biodiversity indicators are needed, what characteristics successful global indicators have, and how existing indicators perform. Because monitoring could absorb a large proportion of funds available for conservation, we believe indicators should be linked explicitly to monitoring objectives and decisions about which monitoring schemes deserve funding should be informed by predictions of the value of such schemes to decision making. We suggest that raising awareness among the public and policy makers, auditing management actions, and informing policy choices are the most important global monitoring objectives. Using four well-developed indicators of biological diversity (extent of forests, coverage of protected areas, Living Planet Index, Red List Index) as examples, we analyzed the characteristics needed for indicators to meet these objectives. We recommend that conservation professionals improve on existing indicators by eliminating spatial biases in data availability, fill gaps in information about ecosystems other than forests, and improve understanding of the way indicators respond to policy changes. Monitoring is not an end in itself, and we believe it is vital that the ultimate objectives of global monitoring of biological diversity inform development of new indicators.

Allocating conservation resources between areas where persistence of a species is uncertain

Research on the allocation of resources to manage threatened species typically assumes that the state of the system is completely observable; for example whether a species is present or not. The majority of this research has converged on modeling problems as Markov decision processes (MDP), which give an optimal strategy driven by the current state of the system being managed. However, the presence of threatened species in an area can be uncertain. Typically, resource allocation among multiple conservation areas has been based on the biggest expected benefit (return on investment) but fails to incorporate the risk of imperfect detection. We provide the first decision-making framework for confronting the trade-off between information and return on investment, and we illustrate the approach for populations of the Sumatran tiger (Panthera tigris sumatrae) in Kerinci Seblat National Park. The problem is posed as a partially observable Markov decision process (POMDP), which extends MDP to incorporate incomplete detection and allows decisions based on our confidence in particular states. POMDP has previously been used for making optimal management decisions for a single population of a threatened species. We extend this work by investigating two populations, enabling us to explore the importance of variation in expected return on investment between populations on how we should act. We compare the performance of optimal strategies derived assuming complete (MDP) and incomplete (POMDP) observability. We find that uncertainty about the presence of a species affects how we should act. Further, we show that assuming full knowledge of a species presence will deliver poorer strategic outcomes than if uncertainty about a species status is explicitly considered. MDP solutions perform up to 90% worse than the POMDP for highly cryptic species, and they only converge in performance when we are certain of observing the species during management: an unlikely scenario for many threatened species. This study illustrates an approach to allocating limited resources to threatened species where the conservation status of the species in different areas is uncertain. The results highlight the importance of including partial observability in future models of optimal species management when the species of concern is cryptic in nature.

Is Australia ready for assisted colonization? Policy changes required to facilitate translocations under climate change

Assisted Colonization (AC) has been proposed as one method of aiding species to adapt to the impacts of climate change. AC is a form of translocation and translocation protocols for threatened species, mostly for reintroduction, are well established in Australia. We evaluate the information available from implementation of translocations to understand how existing policies and guidelines should be varied to plan, review and regulate AC. While the risks associated with AC are potentially greater than those of reintroductions, AC is likely to be the only available method, other than germplasm storage and establishment of captive populations, of conserving many taxa under future climate change. AC may also be necessary to maintain ecosystem services, particularly where keystone species are affected. Current policies and procedures for the preparation of Translocation Proposals will require modification and expansion to deal with Assisted Colonization, particularly in relation to risk management, genetic management, success criteria, moving associated species and community consultation. Further development of risk assessment processes, particularly for invasiveness, and guidelines for genetic management to maintain evolutionary potential are particularly important in the context of changing climate. Success criteria will need to respond to population establishment in the context of new and evolving ecosystems, and to reflect requirements for any co-establishment of interdependent species. Translocation Proposals should always be subjected to independent peer review before being considered by regulators. We conclude that consistent approaches by regulators and multilateral agreements between jurisdictions are required to minimize duplication, to ensure the risk of AC is adequately assessed and to ensure the potential benefits of AC are realized.

Active adaptive conservation of threatened species in the face of uncertainty

Adaptive management has a long history in the natural resource management literature, but despite this, few practitioners have developed adaptive strategies to conserve threatened species. Active adaptive management provides a framework for valuing learning by measuring the degree to which it improves long-run management outcomes. The challenge of an active adaptive approach is to find the correct balance between gaining knowledge to improve management in the future and achieving the best short-term outcome based on current knowledge. We develop and analyze a framework for active adaptive management of a threatened species. Our case study concerns a novel facial tumor disease affecting the Australian threatened species Sarcophilus harrisii: the Tasmanian devil. We use stochastic dynamic programming with Bayesian updating to identify the management strategy that maximizes the Tasmanian devil population growth rate, taking into account improvements to management through learning to better understand disease latency and the relative effectiveness of three competing management options. Exactly which management action we choose each year is driven by the credibility of competing hypotheses about disease latency and by the population growth rate predicted by each hypothesis under the competing management actions. We discover that the optimal combination of management actions depends on the number of sites available and the time remaining to implement management. Our approach to active adaptive management provides a framework to identify the optimal amount of effort to invest in learning to achieve long-run conservation objectives.

Optimal allocation of conservation effort among subpopulations of a threatened species: how important is patch quality?

Money is often a limiting factor in conservation, and attempting to conserve endangered species can be costly. Consequently, a framework for optimizing fiscally constrained conservation decisions for a single species is needed. In this paper we find the optimal budget allocation among isolated subpopulations of a threatened species to minimize local extinction probability. We solve the problem using stochastic dynamic programming, derive a useful and simple alternative guideline for allocating funds, and test its performance using forward simulation. The model considers subpopulations that persist in habitat patches of differing quality, which in our model is reflected in different relationships between money invested and extinction risk. We discover that, in most cases, subpopulations that are less efficient to manage should receive more money than those that are more efficient to manage, due to higher investment needed to reduce extinction risk. Our simple investment guideline performs almost as well as the exact optimal strategy. We illustrate our approach with a case study of the management of the Sumatran tiger, Panthera tigris sumatrae, in Kerinci Seblat National Park (KSNP), Indonesia. We find that different budgets should be allocated to the separate tiger subpopulations in KSNP. The subpopulation that is not at risk of extinction does not require any management investment. Based on the combination of risks of extinction and habitat quality, the optimal allocation for these particular tiger subpopulations is an unusual case: subpopulations that occur in higher-quality habitat (more efficient to manage) should receive more funds than the remaining subpopulation that is in lower-quality habitat. Because the yearly budget allocated to the KSNP for tiger conservation is small, to guarantee the persistence of all the subpopulations that are currently under threat we need to prioritize those that are easier to save. When allocating resources among subpopulations of a threatened species, the combined effects of differences in habitat quality, cost of action, and current subpopulation probability of extinction need to be integrated. We provide a useful guideline for allocating resources among isolated subpopulations of any threatened species.

Should we protect the strong or the weak? Risk, resilience, and the selection of marine protected areas

It is thought that recovery of marine habitats from uncontrollable disturbance may be faster in marine reserves than in unprotected habitats. But which marine habitats should be protected, those areas at greatest risk or those at least risk? We first defined this problem mathematically for 2 alternate conservation objectives. We then analytically solved this problem for both objectives and determined under which conditions each of the different protection strategies was optimal. If the conservation objective was to maximize the chance of having at least 1 healthy site, then the best strategy was protection of the site at lowest risk. On the other hand, if the goal was to maximize the expected number of healthy sites, the optimal strategy was more complex. If protected sites were likely to spend a significant amount of time in a degraded state, then it was best to protect low-risk sites. Alternatively, if most areas were generally healthy then, counterintuitively, it was best to protect sites at higher risk. We applied these strategies to a situation of cyclone disturbance of coral reefs on Australia's Great Barrier Reef. With regard to the risk of cyclone disturbance, the optimal reef to protect differed dramatically, depending on the expected speed of reef recovery of both protected and unprotected reefs. An adequate consideration of risk is fundamental to all conservation actions and can indicate surprising routes to conservation success.

The need for speed: informed land acquisitions for conservation in a dynamic property market

Land acquisition is a common approach to biodiversity conservation but is typically subject to property availability on the public market. Consequently, conservation plans are often unable to be implemented as intended. When properties come on the market, conservation agencies must make a choice: purchase immediately, often without a detailed knowledge of its biodiversity value; survey the parcel and accept the risk that it may be removed from the market during this process; or not purchase and hope a better parcel comes on the market at a later date. We describe both an optimal method, using stochastic dynamic programming, and a simple rule of thumb for making such decisions. The solutions to this problem illustrate how optimal conservation is necessarily dynamic and requires explicit consideration of both the time period allowed for implementation and the availability of properties.

Subpopulation triage: how to allocate conservation effort among populations

Threatened species often exist in a small number of isolated subpopulations. Given limitations on conservation spending, managers must choose from strategies that range from managing just one subpopulation and risking all other subpopulations to managing all subpopulations equally and poorly, thereby risking the loss of all subpopulations. We took an economic approach to this problem in an effort to discover a simple rule of thumb for optimally allocating conservation effort among subpopulations. This rule was derived by maximizing the expected number of extant subpopulations remaining given n subpopulations are actually managed. We also derived a spatiotemporally optimized strategy through stochastic dynamic programming. The rule of thumb suggested that more subpopulations should be managed if the budget increases or if the cost of reducing local extinction probabilities decreases. The rule performed well against the exact optimal strategy that was the result of the stochastic dynamic program and much better than other simple strategies (e.g., always manage one extant subpopulation or half of the remaining subpopulation). We applied our approach to the allocation of funds in 2 contrasting case studies: reduction of poaching of Sumatran tigers (Panthera tigris sumatrae) and habitat acquisition for San Joaquin kit foxes (Vulpes macrotis mutica). For our estimated annual budget for Sumatran tiger management, the mean time to extinction was about 32 years. For our estimated annual management budget for kit foxes in the San Joaquin Valley, the mean time to extinction was approximately 24 years. Our framework allows managers to deal with the important question of how to allocate scarce conservation resources among subpopulations of any threatened species.

Control of pest mammals for biodiversity protection in Australia. I. Patterns of control and monitoring

Foxes, wild dogs, feral cats, rabbits, feral pigs and feral goats are believed to have deleterious impacts on native biodiversity in Australia. However, although considerable resources have been expended controlling these six species, little is known about national patterns and costs of control and monitoring. We therefore conducted a survey of pest-control operations undertaken by conservation-focused organisations in Australia. A total of 1306 control operations were reported, with most conducted during 1998–2003: there was little information prior to 1990. Foxes and rabbits were the most, and feral cats the least, frequently controlled pest species. The total area on which control was undertaken in 2003, the year for which most information was available, ranged from ~0.4 × 104 km2 for feral cats to ~10.7 × 104 km2 for foxes. A wide range of techniques and intensities were used to control each of the six species. The estimated cost of labour expended on control in 2003 ranged from $0.4 × 106 for feral cats to $5.3 × 106 for foxes. Monitoring of the pest or biodiversity occurred in 50–56% of control actions in which foxes, wild dogs and feral cats were targeted, but only 22–26% of control actions in which rabbits, feral pigs and feral goats were targeted. Our results are discussed in relation to previous studies of pest animal control and monitoring in Australia.

Accuracy and precision of grey-headed flying-fox (Pteropus poliocephalus) flyout counts

The principal method for estimating the abundance of bats in roosts is to count the number of bats exiting the roost at dusk (‘flyout counts’). We hypothesised that the accuracy and precision of flyout counts decrease non-linearly as the number of bats moving per unit of time increases, and that accuracy increases with observer experience. To test these hypotheses, we filmed grey-headed flying-foxes (Pteropus poliocephalus) exiting a roost in Melbourne on three consecutive evenings. The film was slowed and the number of flying-foxes flying-out in 30-s intervals was counted and assumed to be the true abundance. Thirteen other observers independently counted the number of flying-foxes flying-out in real time. We formulated our hypotheses into candidate models and compared support for these models using information-theoretic methods. Non-linear models had much greater support than linear models for all three flyouts. There was undercounting in two flyouts and overcounting in the third. There was good support for an effect of observer experience in one of the flyouts, but less support in the others. Precision declined as the true abundance increased in all three flyout counts. Our results indicate that accuracy, precision and observer effects vary with the dynamics of each flyout, and suggest that under some conditions flyout counts will often provide both inaccurate and imprecise estimates of abundance.

Possums in the park: efficient foraging under the risk of predation or of competition?

Many eutherian mammals adjust their foraging behaviour according to the presence or threat of predators. Here, we examine experimentally whether an urban population of brushtail possums, Trichosurus vulpecula, similarly adjust their foraging behaviour. Our field experiments manipulated the quantity of food items in artificial feeders placed at different distances from trees. These experiments showed that the possums remained longer at feeders placed far from the trees, but their foraging behaviour did not change with the initial amount of food. The scanning behaviour of possums did not simply increase with distance from the trees, as predicted from studies of other vertebrates. Nevertheless, the number of physical conflicts between individuals increased as the amount of available food decreased. These data suggest that the changes in the foraging behaviour of the possums in this population do not reflect a simple trade-off between foraging efficiency and the risk of predation or competition.