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

The invasive emerald ash borer (Agrilus planipennis) causes damages to street trees estimated to reach US$ 900 million over the next 30 years.Although millions of dollars are spent annually to control this species, such approaches are often based on heuristics. Here, we reveal an optimal management strategy to protect urban trees in North America from A. planipennis. To achieve this, we embedded a pest dispersal model within a mixed integer programming framework. We discovered that optimized strategies consistently outperformed those based on heuristics, potentially resulting in the protection of an additional nearly one million street trees and savings of $ 627 million. Critically, the best management strategies always relied on quarantines and biological control (constituting 83-95% and 5-17% of the project budget, respectively), in contrast with current practices, which have shifted responsibility for quarantines to state authorities. Our findings serve to inform future pest control efforts, and can potentially protect many more trees from this invasive species.

Agricultural and livestock production involves significant trade-offs between multiple sustainable development goals, including reducing hunger and poverty, and reducing emissions of greenhouse gasses. Here we describe a multi-objective optimization tool for livestock production to evaluate trade-offs among environmental and economic objectives with high spatial granularity and the capability to be aggregated to national or global scales. We illustrate the use of this tool analysing how and where to produce beef to optimize the weighted sum of environmental and economic objectives, in this case minimizing greenhouse gas emissions and minimizing costs of production. We present how the outputs of this model can inform a sustainable transition of the industry and policy decisions, with a focus on inherent trade-offs. By comparing optimal production with current production, we highlight the potential environmental and economic efficiencies that can be made by changing the location or methods of production. As such, this tool provides a platform to identify trade-offs and synergies among multiple diverse sustainability goals, critical in the livestock and agricultural sectors.

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.

Among the conservation community, it is well known that Earth’s mass species extinction crisis is getting worse. Yet, an often neglected problem is the need for effectively communicating the species extinction crisis to diverse audiences in ways that catalyse immediate action. Here we generated a streamlined threatened species recovery report card methodology, which combined two input indicators including planning and funding, one output indicator capturing habitat protection, and one outcome indicator which highlights threatened species trajectories, to provide simple scores for all Australian threatened species. We show that just 41 (2.3%) of species achieved an A grade for the input indicator (i.e., recovery plans and federal funding), 240 (13.3%) achieved a C grade, and 1,521 (84.4%) achieved an F. Five hundred and twenty nine (29.3%) species achieved an A for the output indicator (i.e, habitat protection), 130 (7.2%) achieved a B, 158 (8.8%) achieved a C, 189 (10.5%) achieved a D, 212 (11.8%) achieved an E, and 584 (32.4%) achieved a F. While five (0.3%) species achieved an A for the output indicator (i.e., threat status improvement), every other species (99.7%) achieved an F. We provide a method to combine scores to test how individual jurisdictions are tracking and show that Australia is achieving an F for the input and outcome indicators, and a D for the output indicator. While the threatened species recovery report card highlighted a clear failure in many federal environmental legislation responsibilities, it provides a baseline from which different governments can track policy progress and outlines clear direction for immediate improvement including developing adequate recovery plans, funding the actions in the recovery plans, protecting habitat from further destruction, verifying recovery through monitoring and evaluation of species trajectories, and supporting transparency and collaboration on the execution on the plans through an improved data infrastructure. Without an immediate step change in how Australia communicates and faces its species crisis, we will leave a tragic legacy of extinction and fail our obligations to future generations of Australians, and the international community.

The invasive emerald ash borer (Agrilus planipennis) causes damages to street trees estimated at US$ 900 million in the next 30 years. Although millions of dollars are spent annually to control this species, such approaches are often based on rules-of-thumb. Here, we reveal an optimal management strategy to protect urban trees in North America from A. planipennis. To achieve this, we embedded a pest dispersal model within a mixed integer programming framework. We discovered that optimized strategies consistently outperformed those based on rules-of-thumb, potentially resulting in the protection of an additional one million street trees and savings of $585 million. Critically, the best management strategies always relied on quarantines and biological control (constituting 74-89% and 11-26% of the project budget, respectively), in contrast with current practices, which have abandoned quarantines. Our findings serve to inform future pest control efforts, and can potentially protect many more trees from this invasive species.

Seaweed farming is widely expected to transform the way we approach sustainable developments, particularly in the context of the ‘Blue Economy’. However, many claims of the social and ecological benefits from seaweed farming have limited or contextually weak empirical grounding. Here we systematically review relevant publications across four languages to form a comprehensive picture of observed—rather than theorised—social and environmental impacts of seaweed farming globally. We show that, while some impacts such as improved water quality and coastal livelihoods are consistently reported, other promulgated benefits vary across cultivation contexts or are empirically unsubstantiated. For some communities, increasing dependence on seaweed farming may improve or worsen the cultural fabric and their vulnerability to economic and environmental shocks. The empirical evidence for the impacts of seaweed farming is also restricted geographically, mainly to East Asia and South-East Asia, and taxonomically. Seaweed farming holds strong potential to contribute to sustainability objectives, but the social and ecological risks associated with scaling up global production remain only superficially understood. These risks require greater attention to ensure just, equitable, and sustainable seaweed industries can be realised.

Data hungry, complex ecosystem models are often used to predict the consequences of threatened species management, including perverse outcomes. Unfortunately, this approach is impractical in many systems, which have insufficient data to parameterize ecosystem interactions or reliably calibrate or validate such models. Here we demonstrate a different approach, using a minimum realistic model to guide decisions in data- and resource-scarce systems. We illustrate our approach with a case-study in an invaded ecosystem from Christmas Island, Australia, where there are concerns that cat eradication to protect native species, including the red-tailed tropicbird, could release meso-predation by invasive rats. We use biophysical constraints (metabolic demand) and observable parameters (e.g. prey preferences) to assess the combined cat and rat abundances which would threaten the tropicbird population. We find that the population of tropicbirds cannot be sustained if predated by 1607 rats (95% credible interval (CI) [103, 5910]) in the absence of cats, or 21 cats (95% CI [2, 82]) in the absence of rats. For every cat removed from the island, the bird's net population growth rate improves, provided that the rats do not increase by more than 77 individuals (95% CI [30, 174]). Thus, in this context, one cat is equivalent to 30-174 rats. Our methods are especially useful for on-the-ground predator control in the absence of knowledge of predator-predator interactions, to assess whether 1) the current abundance of predators threatens the prey population of interest, 2) managing one predator species alone is sufficient to protect the prey species given potential release of another predator, and 3) control of multiple predator species is needed to meet the conservation goal. Our approach demonstrates how to use limited information for maximum value in data-poor systems, by shifting the focus from predicting future trajectories, to identifying conditions which threaten the conservation goal. This article is protected by copyright. All rights reserved.

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.

Biodiversity conservation decisions are difficult, especially when they involve differing values, complex multidimensional objectives, scarce resources, urgency, and considerable uncertainty. Decision science embodies a theory about how to make difficult decisions and an extensive array of frameworks and tools that make that theory practical. We sought to improve conceptual clarity and practical application of decision science to help decision makers apply decision science to conservation problems. We addressed barriers to the uptake of decision science, including a lack of training and awareness of decision science; confusion over common terminology and which tools and frameworks to apply; and the mistaken impression that applying decision science must be time consuming, expensive, and complex. To aid in navigating the extensive and disparate decision science literature, we clarify meaning of common terms: decision science, decision theory, decision analysis, structured decision-making, and decision-support tools. Applying decision science does not have to be complex or time consuming; rather, it begins with knowing how to think through the components of a decision utilizing decision analysis (i.e., define the problem, elicit objectives, develop alternatives, estimate consequences, and perform trade-offs). This is best achieved by applying a rapid-prototyping approach. At each step, decision-support tools can provide additional insight and clarity, whereas decision-support frameworks (e.g., priority threat management and systematic conservation planning) can aid navigation of multiple steps of a decision analysis for particular contexts. We summarize key decision-support frameworks and tools and describe to which step of a decision analysis, and to which contexts, each is most useful to apply. Our introduction to decision science will aid in contextualizing current approaches and new developments, and help decision makers begin to apply decision science to conservation problems.Las decisiones sobre la conservación de la biodiversidad son difíciles de tomar, especialmente cuando involucran diferentes valores, objetivos multidimensionales complejos, recursos limitados, urgencia y una incertidumbre considerable. Las ciencias de la decisión incorporan una teoría sobre cómo tomar decisiones difíciles y una variedad extensa de marcos de trabajo y herramientas que transforman esa teoría en práctica. Buscamos mejorar la claridad conceptual y la aplicación práctica de las ciencias de la decisión para ayudar al órgano decisorio a aplicar estas ciencias a los problemas de conservación. Nos enfocamos en las barreras para la aceptación de las ciencias de la decisión, incluyendo la falta de capacitación y de conciencia por estas ciencias; la confusión por la terminología común y cuáles herramientas y marcos de trabajo aplicar; y la impresión errónea de que la aplicación de estas ciencias consume tiempo y debe ser costosa y compleja. Para asistir en la navegación de la literatura extensa y dispar de las ciencias de la decisión, aclaramos el significado de varios términos comunes: ciencias de la decisión, teoría de la decisión, análisis de decisiones, toma estructurada de decisiones y herramientas de apoyo para las decisiones. La aplicación de las ciencias de la decisión no tiene que ser compleja ni debe llevar mucho tiempo; de hecho, todo comienza con saber cómo pensar detenidamente en los componentes de una decisión mediante el análisis de decisiones (es decir, definir el problema, producir objetivos, desarrollar alternativas, estimar consecuencias y realizar compensaciones). Lo anterior se logra de mejor manera mediante la aplicación de una estrategia prototipos rápidos. En cada paso, las herramientas de apoyo para las decisiones pueden proporcionar visión y claridad adicionales, mientras que los marcos de apoyo para las decisiones (p.ej.: gestión de amenazas prioritarias y planeación sistemática de la conservación) pueden asistir en la navegación de los diferentes pasos de un análisis de decisiones para contextos particulares. Resumimos los marcos de trabajo y las herramientas más importantes de apoyo para las decisiones y describimos el paso, y el contexto, del análisis de decisiones para el que es más útil aplicarlos. Nuestra introducción a las ciencias de la decisión apoyará en la contextualización de las estrategias actuales y los nuevos desarrollos, y ayudarán al órgano decisorio a comenzar a aplicar estas ciencias en los problemas de conservación.

Determining where environmental management is best applied, either through regulating single sectors of human activities or across sectors, is complicated by interactions between human impacts and the environment. In this article, we show how an explicit representation of human-environment interactions can help, via “impact networks” including activities (e.g. shipping), stressors (e.g. ship strikes), species (e.g. humpback whales) or ecosystem services (e.g. marine recreation). Impact networks can enable the identification of “leverage nodes”, which, if present, can direct managers to the activities and stressors crucial for reducing risk to important ecosystem components. Exploring an impact network for a coastal ecosystem in British Columbia, Canada, we seek to identify these leverage nodes using a new approach employing Bayesian Belief Networks of risks to ecosystems. In so doing, we address three key questions: (1) Do leverage nodes exist? (2) Do management plans for species correctly identify leverage nodes? (3) Does the management of leverage nodes for certain species realize benefits for other species and ecosystem services? We show that there are several leverage nodes across all species investigated, and show that preconceptions about the regulation of risk to species can misidentify leverage nodes, potentially leading to ineffective management. Notably, we show that managing fisheries does not reduce overall risk to herring whereas managing diverse cumulative impacts including nutrient runoff, oil spills, and marine debris can reduce risk to herring, additional species, and related ecosystem services. Thus, by targeting leverage nodes, managers can efficiently mitigate risks for whole communities, ecosystems, and ecosystem services.

Competition for land resources is intense, with growing demand for food and resources to support humanity. Despite this, global agricultural area has significantly declined over the past two decades due to socio–political trends, market changes and environmental degradation. Although expensive, restoring degraded lands that are no longer contested for agricultural use due to low productivity may present a major conservation opportunity with minimal social or political opposition. Here we present a new perspective for conservation that highlights the potential conservation value of uncontested lands. We highlight key factors that make lands uncontested, define an approach for evaluating costs and benefits on uncontested land parcels and propose methods for identifying these lands. Land use is one of the most contested issues facing global conservation, but degraded lands should be the focus of governments and trusts to take and conserve uncontested areas for nature.

Models for predicting ecological behaviour typically require large volumes of data for parameterisation, which is a problem because data are scarce. Qualitative modelling (QM) provides an alternative by exploring the entire range of possible parameter values. When a parameter value is completely unknown, QM typically invokes the Principle of Indifference (PoI), for example by sampling the parameter from a uniform prior distribution. However, if PoI is invoked in this probabilistic way, there may be multiple possible methods for defining a parameter space and sampling values from it, and, worryingly, two different but equally defensible methods can lead to different predictions about ecosystem responses. We investigated how probabilistic PoI can give rise to problems in QM, and developed an alternative method based on Boolean PoI that does not suffer the same limitations. We used a case study that involved predicting the responses of multiple species to the suppression of a pest. The unknown model parameters were interaction strengths between species. For the standard probabilistic method, we drew the parameters randomly from uniform (PoI) and other distributions. For our new Boolean PoI method, we instead simply specified the ranges of “possible” parameter values, and developed a Boolean analysis technique to summarise model predictions. As expected, invoking probabilistic QM yielded different predictions (species-response probabilities) for different but equally defensible parameterisation and sampling schemes. Sometimes differences were large enough to impact decision-making. In contrast, our new Boolean PoI approach simply classifies outcomes (species responses) as certain, possible, or impossible. Encouragingly, some species responses that were not consistently resolved under probabilistic PoI were shown by our method to be in fact governed by simple rules. Our method can also identify key species whose responses determine whole-system outcomes. Our non-probabilistic representation of uncertainty circumvents the philosophical problems in standard implementations of PoI for QM. Our Boolean analysis method summarises results in a way that is interpretable and potentially useful to conservation decision makers. A priority for future research is to increase the efficiency of our Boolean approach to allow it to deal with problems of higher complexity (more interactions).

As the world’s economies seek to use new renewable energy developments to address climate change and reinvigorate economies post-COVID-19, avoiding a fixation on targets in decision-making will ensure positive social and environmental outcomes.

Environmental and conservation scientists are increasingly being asked to justify their work in terms of benefits to society. This article describes economic theory for conceptualizing the benefits from environmental research, and provides a framework for estimating those benefits. In particular we discuss the evaluation of environmental science that is intended to benefit society through informing policy decisions. The chain between environmental research and its benefits through policy change includes at least four links: the research itself, policy change, behavior change and environmental change. Each of these four stages presents challenges and entails time lags. If any link fails, the chain breaks. The standard economic model of supply and demand, which is used to quantify benefits from research into market goods, can be adapted for application to environmental goods. Improved conceptualization and measurement of benefits from environmental research would assist environmental scientists to: (1) select research topics that are likely to deliver large environmental benefits; (2) design their research in a way that will increase its relevance, usefulness and potential impact on policy and, ultimately, the environment; and (3) make the case for funding particular research proposals. It could assist research agencies or research funders to: prioritize proposed research; make a case for increased funding for environmental research; and identify obstacles to the translation of research into environmental impacts, allowing attention to be focused on addressing these bottlenecks.

1. Making effective management decisions is challenging in multi-species, multi-threat systems because of uncertainty about the effects of different threats on different species. To inform management decisions, we often monitor species to detect spatial or temporal trends that can help us learn about threatening processes. However, which species to monitor and how to monitor to inform the management of threats can be difficult to determine.2. Value of information (VOI) analysis is an approach for quantifying the value of monitoring to inform management decisions. We developed a novel method that applies VOI analysis to quantify the benefits of different species monitoring strategies in multi-threat, multi-species systems. We applied the approach to compare the effectiveness of surveillance monitoring (monitoring species without experimentation) to targeted monitoring (monitoring species with experimentation to learn about a specific threat), and how prior information drives the benefits of these two different strategies and the species to monitor. We also illustrate the approach by applying it to two contrasting case studies for monitoring and managing declining mammals in Western Australia.3. Our approach shows that surveillance monitoring generally provides far lower benefits than targeted monitoring for managing threats in multi-species, multi-threat systems under economic constraints.4. Our approach also informs the choice of species to monitor and which threats to manage experimentally to most improve threat management outcomes. We show that the key parameters driving these choices include: the budget available for management, prior understanding of which threats cause declines in which species, the relative cost of managing these threats, and the background probability of decline.5. Our new VOI approach allows the evaluation of monitoring decisions in multi-species, multi-threat systems in the face of uncertainty, while explicitly accounting for the improvement in management outcomes. We recommend that managers need to explicitly consider a range of decision parameters when selecting which species to monitor to inform management. Our framework provides an objective way to do this.

1. Payments to private landholders for providing biodiversity land can improve conservation outside protected areas. Input-based payments are widely used despite evidence they are often ineffective at improving biodiversity outcomes. Meanwhile little has been done to assess how to use outcome-based payments to maximize biodiversity, despite growing academic interest. We compare different outcome-based allocation methods to assess which returns the greatest benefits for biodiversity. 2. We predicted the likely landholder actions in response to outcome-based payments. We incorporated strategic interactions between landholders under four different funding allocation methods: the commonly applied “set-price” allocation method; capacity-based payments; proportional payment; and payment for change. We compared biodiversity outcomes (percentage change in abundance of a species of conservation interest), return on investment and cost-effectiveness of each method. 3. The set-price allocation method, despite its common usage, is the least cost-effective method that we test. Regardless of cost, it only results in better biodiversity outcomes than other methods under a very narrow range of conditions (high initial target species abundance and low profitability). 4. The profitability of the property, and to a lesser degree initial population size, will influence which allocation method will perform best. Most perform well when the initial population of the species of conservation interest is very small and profitability negligible. Only one method – based on change in population – performs well across all scenarios. This method outperforms the others particularly when the property has a higher profitability and low initial numbers of animals. 5. Policy implications. Pursuing conservation on private land using outcome-based payments for biodiversity can result in varied levels of success depending on the allocation methods used to support payment decisions. Allocation method choice should be based on a transparent analysis that incorporates both the dynamics of the ecological system and interactions between individual landholders. This analysis can guide adoption of funding allocation methods that greatly increase biodiversity outcomes.

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.

Seed dispersal by birds is central to the passive restoration of many tree communities. Reintroduction of extinct seed dispersers can therefore restore degraded forests and woodlands. To test this, we constructed a spatially explicit simulation model, parameterized with field data, to consider the effect of different seed dispersal scenarios on the extent of oak populations. We applied the model to two islands in California's Channel Islands National Park (USA), one of which has lost a key seed disperser. 2. We used an ensemble modelling approach to simulate island scrub oak (Quercus pacifica) demography. The model was developed and trained to recreate known population changes over a 20-year period on 250-km(2) Santa Cruz Island, and incorporated acorn dispersal by island scrub-jays (Aphelocoma insularis), deer mice (Peromyscus maniculatus) and gravity, as well as seed predation. We applied the trained model to 215-km(2) Santa Rosa Island to examine how reintroducing island scrub-jays would affect the rate and pattern of oak population expansion. Oak habitat on Santa Rosa Island has been greatly reduced from its historical extent due to past grazing by introduced ungulates, the last of which were removed by 2011. 3. Our simulation model predicts that a seed dispersal scenario including island scrub-jays would increase the extent of the island scrub oak population on Santa Rosa Island by 281% over 100 years, and by 544% over 200 years. Scenarios without jays would result in little expansion. Simulated long-distance seed dispersal by jays also facilitates establishment of discontinuous patches of oaks, and increases their elevational distribution. 4. Synthesis and applications. Scenario planning provides powerful decision support for conservation managers. We used ensemble modelling of plant demographic and seed dispersal processes to investigate whether the reintroduction of seed dispersers could provide cost-effective means of achieving broader ecosystem restoration goals on California's second-largest island. The simulation model, extensively parameterized with field data, suggests that re-establishing the mutualism with seed-hoarding jays would accelerate the expansion of island scrub oak, which could benefit myriad species of conservation concern.

Consumer demand for plant and animal products threatens many populations with extinction. The anthropogenic Allee effect (AAE) proposes that such extinctions can be caused by prices for wildlife products increasing with species rarity. This price-rarity relationship creates financial incentives to extract the last remaining individuals of a population, despite higher search and harvest costs. The AAE has become a standard approach for conceptualizing the threat of economic markets on endangered species. Despite its potential importance for conservation, AAE theory is based on a simple graphical model with limited analysis of possible population trajectories. By specifying a general class of functions for price-rarity relationships, we show that the classic theory can understate the risk of species extinction. AAE theory proposes that only populations below a critical Allee threshold will go extinct due to increasing price-rarity relationships. Our analysis shows that this threshold can be much higher than the original theory suggests, depending on initial harvest effort. More alarmingly, even species with population sizes above this Allee threshold, for which AAE predicts persistence, can be destined to extinction. Introducing even a minimum price for harvested individuals, close to zero, can cause large populations to cross the classic anthropogenic Allee threshold on a trajectory towards extinction. These results suggest that traditional AAE theory may give a false sense of security when managing large harvested populations.

Managing ecosystems to provide ecosystem services in the face of global change is a pressing challenge for policy and science. Predicting how alternative management actions and changing future conditions will alter services is complicated by interactions among components in ecological and socioeconomic systems. Failure to understand those interactions can lead to detrimental outcomes from management decisions. Network theory that integrates ecological and socioeconomic systems may provide a path to meeting this challenge. While network theory offers promising approaches to examine ecosystem services, few studies have identified how to operationalize networks for managing and assessing diverse ecosystem services. We propose a framework for how to use networks to assess how drivers and management actions will directly and indirectly alter ecosystem services.

The United Nation’s Strategic Plan for Biodiversity 2011-2020 calls for reducing species extinctions, as it is increasingly clear that human activities threaten to drive species to decline. Yet despite considerable scientific evidence pointing to the detrimental effects of interacting threats on biodiversity, many species lack information on their exposure to cumulative human pressures. Using the most comprehensive global dataset on cumulative human footprint, we assess the extent of intense human pressures across 20,529 terrestrial vertebrate species’ geographic ranges. We consider intense human pressure as areas where landscapes start to be significantly modified (a summed Human Footprint value at or above three on the index), which is where land uses such as pastureland appear. This threshold has been correlated with extinction risk for many species. We show that 85% (17,517) of the terrestrial vertebrate species assessed have >half of their range exposed to intense human pressure, with 16% (3328) of the species assessed being entirely exposed to this degree of pressure. Threatened terrestrial vertebrates and species with small ranges are disproportionately exposed to intense human pressure. Our analysis also suggests that there are at least 2478 species considered ‘least concern’ that have considerable portions of their range overlapping with these pressures, which may indicate their risk of decline. These results point to the utility of assessing cumulative human pressure data across species ranges, which may be a useful first step for measuring species vulnerability. Keywords: Human footprint, Extinction risk, Biodiversity conservation, Species threats, Overexploitation, Land use change, Urbanization, Land clearing

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.

Many migratory shorebird species are undergoing severe population declines due to habitat loss. Selecting sites for protection along migratory shorebird flyways requires accounting for connectivity between sites and representing all migratory cycle stages within a protected area network. Site protection decisions often additionally account for the economic value of habitat-related ecosystem services, as shorebird habitats often provide services such as fisheries and recreational opportunities. In this study, we develop a new approach which combines graph theory, decision science, and stochastic dynamic optimization, to investigate whether habitat protection strategies aimed at safeguarding ecosystem services can also deliver efficient protection for migratory shorebirds. We use graph theory to empirically model migration routes for two shorebird species, the Curlew Sandpiper (Calidris ferruginea) and Eastern Curlew (Numenius madagascariensis), linking their migratory networks with data on habitat-related ecosystem services within the East Asian - Australasian Flyway (EAAF). Using dynamic optimization, we calculate the optimal habitat protection strategy for both ecosystem services and shorebird conservation objectives for both species. We further investigate if, and how, these two strategies can converge to achieve both objectives, and whether there is a trade-off between strategies. Our results show that the biodiversity outcome from strategies maximizing ecosystem services provided by shorebird habitat could align closely with a species-focused conservation plan. More specifically, the optimal ecosystem services oriented strategy maintains a similar level of shorebird populations as the optimal conservation strategy, while protecting an additional 45% (Curlew Sandpiper) and 42% (Eastern Curlew) of ecosystem services throughout the network. Conservation budget also matters, as small budgets would lead to inefficient protection for biodiversity. Our research shows that conservation planning can simultaneously achieve conservation and ecosystem services objectives for migratory species. By accounting for the value of ecosystem services within shorebird habitats, we provide quantitative evidence of a win-win scenario in which both shorebird conservation and ecosystem service provision can be achieved. Our model could be applied to other migratory species to improve spatially explicit planning for both biodiversity and ecosystem service targets.

Anthropogenic conversion of natural habitats is the greatest threat to biodiversity and one of the primary reasons for establishing protected areas (PAs). Here, we show that PA establishment outpaced habitat conversion between 1993 and 2009 across all biomes and the majority (n = 567, 71.4%) of ecoregions globally. However, high historic rates of conversion meant that 447 (56.2%) ecoregions still exhibit a high ratio of conversion to protection, and of these, 127 (15.9%) experienced further increases in this ratio between 1993 and 2009. We identify 41 “crisis ecoregions” in 45 countries where recent habitat conversion is severe and PA coverage remains extremely low. While the recent growth in PAs is a notable conservation achievement, international conventions and associated finance mechanisms should prioritize areas where habitat is being lost rapidly relative to protection, such as the crisis ecoregions identified here.

Increasing the colonization rate of metapopulations can improve persistence, but can also increase exposure to threats. To make good decisions, managers must understand whether increased colonization is beneficial or detrimental to metapopulation persistence. While a number of studies have examined interactions between metapopulations, colonization, and threats, they have assumed that threat dynamics respond linearly to changes in colonization. Here, we determined when to increase colonization while explicitly accounting for non-linear dependencies between a metapopulation and its threats. We developed patch occupancy metapopulation models for species susceptible to abiotic, generalist, and specialist threats and modeled the total derivative of the equilibrium proportion of patches occupied by each metapopulation with respect to the colonization rate. By using the total derivative, we developed a rule for determining when to increase metapopulation colonization. This rule was applied to a simulated metapopulation where the dynamics of each threat responded to increased colonization following a power function. Before modifying colonization, we show that managers must understand: (1) whether a metapopulation is susceptible to a threat; (2) the type of threat acting on a metapopulation; (3) which component of threat dynamics might depend on colonization, and; (4) the likely response of a threat-dependent variable to changes in colonization. The sensitivity of management decisions to these interactions increases uncertainty in conservation planning decisions.

This study shows how failure to capture system dynamics can be detected in climate model predictions. This information should improve model projections and facilitate better decision-making.

Conservation-motivated eradications may cause unexpected perverse effects, and these undesirable consequences can be difficult to predict due to the paucity of information on species interactions. A probabilistic qualitative approach, which does not require extensive model parameterization, is becoming increasingly accepted and applied to conservation scenarios when information is limited. However, recent work has criticized this approach on philosophical grounds and proposed an alternative non-probabilistic Boolean analysis method, which circumvents the philosophical difficulties. There is a need for exploring the ability of this novel approach for informing conservation decisions. To do so, we applied the first real-world test of the non-probabilistic Boolean approach using a case study of management of Felis catus (feral cat) and Rattus rattus (black rat) on Christmas Island. We also applied the probabilistic approach as a contrast. Our modeling results showed that the probabilistic approach generated ambiguous outcomes, making it impractical to draw management recommendations. In contrast, the non-probabilistic Boolean approach revealed interpretable rules governing species responses, suggesting that while cat management alone is a risky strategy, the risk of negative effects of cat management on native species can be reduced by the addition of rat management. Thus, given limited resources, in combination with cat management it is prudent to prioritize rat management efforts in the habitats of potentially impacted native species of high concern and value. We conclude that the Boolean approach can be very useful when little information is available to model an ecological system and that it provides a way of identifying the potential risks and benefits of management strategies, enabling better informed conservation decision-making in the face of limited knowledge.

The authors regret that two co-authors were unintentionally missed in the previous paper. We have added the two co-authors to recognize their contribution to the validation data - the biophysical field observations of land conditions. The error does not change the science of this study. Zunyi Xie, Stuart R. Phinn, Edward T. Game, David J. Pannell, Richard J. Hobbs, Peter R. Briggs, Terrence S. Beutel, Christopher Holloway, Eve McDonald-MaddenKey Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng 475004, China Centre for Biodiversity and Conservation Science, School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, Australia Remote Sensing Research Centre, School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, Australia The Nature Conservancy, Brisbane, QLD 4101, Australia School of Agriculture and Environment, The University of Western Australia, Perth, WA 6009, Australia School of Biological Science, The University of Western Australia, Perth, WA 6009, Australia CSIRO Oceans and Atmosphere, Canberra, ACT 2601, Australia Department of Agriculture and Fisheries, Parkhurst, Brisbane, QLD 4701, Australia Department of Agriculture and Fisheries, Dutton Park, Brisbane, QLD 4102, Australia The authors would like to apologise for any inconvenience caused.

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.