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Demand is increasing among investors to create portfolios that encourage positive outcomes for biological diversity. The evolution of investment strategies for transitions to zero carbon over the last two decades provides insights that will assist in shaping strategies for biodiversity‐positive investments. Many emerging approaches to capture company impact and dependence on biodiversity focus on nature‐related threats to an organisation by assessing ecosystem integrity. Other approaches focus on minimising an organisation's contribution to risks of species extinction by using data sets such as the IUCN's Red List of Threatened Species. However, while these approaches are useful for assessing threats to and from biodiversity for individual companies, to be effective for investment portfolio construction, metrics need to be comparable across companies in an investment universe. Many of the threat assessments that could link corporate activities to impacts are incomplete and omit critical information. If the investment community focuses on biodiversity without sufficient forethought, there is a risk of entrenching metrics with significant flaws. In this paper, we suggest that interim approaches are needed to support investors in understanding the approaches being taken by potential investee companies. To that end, we present and discuss a disclosure‐based Biodiversity Management Quality and a classification‐based Biodiversity Revenues metric for biodiversity‐related investing. [ABSTRACT FROM AUTHOR]

Conservation science practitioners seek to preempt irreversible impacts on species, ecosystems, and social–ecological systems, requiring efficient and timely action even when data and understanding are unavailable, incomplete, dated, or biased. These challenges are exacerbated by the scientific community's capacity to consistently distinguish between reliable and unreliable evidence, including the recognition of questionable research practices (QRPs, or "questionable practices"), which may threaten the credibility of research, including harming trust in well‐designed and reliable scientific research. In this paper, we propose a "toolkit" for open and pluralistic conservation science, highlighting common questionable practices and sources of bias and indicating where remedies for these problems may be found. The toolkit provides an accessible resource for anyone conducting, reviewing, or using conservation research, to identify sources of false claims or misleading evidence that arise unintentionally, or through misunderstandings or carelessness in the application of scientific methods and analyses. We aim to influence editorial and review practices and hopefully to remedy problems before they are published or deployed in policy or conservation practice. [ABSTRACT FROM AUTHOR]

They can be vitally important to the decision, and it is necessary to consider them alongside more easily quantified objectives, such as species abundance and cost.Scarce resourcesResources (e.g., time, staff capacity, money, space) available for conservation are often limited, requiring consideration of how to best allocate resources to achieve objectives.Complex alternativesIn complex ecological decisions, the range of possible alternative actions is often very large and multifaceted.Irreversible consequences and tipping pointsConservation decisions sometimes involve tipping points between different system states or irreversible outcomes to be avoided. In our experience, decision analysis and the broader field of decision science provide a useful lens through which to address conservation problems, a greater awareness of the role of values and science in these decisions, and a process for identifying alternatives that are more likely to achieve multiple important values in a timely manner. APPLYING DECISION ANALYSIS Improving the chance of good outcomes for difficult conservation decisions (challenges listed in Table 1) arises from first knowing how to think through decisions with the foundational concepts of decision theory (Keeney, 2004; Raiffa, 2002; Smith, 2020a). Very few, typically the most complex decisions (~50 [0.5%]), will require a full decision analysis and would benefit from more time and resources gl Decisions for questions like these are difficult because they involve multiple value judgments, considerable uncertainty, potentially irreversible consequences, and other challenging characteristics common to conservation decisions (Table 1). [Extracted from the article]

Weighted aggregation of expert judgments based on their performance on calibration questions may improve mathematically aggregated judgments relative to equal weights. However, obtaining validated, relevant calibration questions can be difficult. If so, should analysts settle for equal weights? Or should they use calibration questions that are easier to obtain but less relevant? In this article, we examine what happens to the out‐of‐sample performance of weighted aggregations of the classical model (CM) compared to equal weighted aggregations when the set of calibration questions includes many so‐called "irrelevant" questions, those that might ordinarily be considered to be outside the domain of the questions of interest. We find that performance weighted aggregations outperform equal weights on the combined CM score, but not on statistical accuracy (i.e., calibration). Importantly, there was no appreciable difference in performance when weights were developed on relevant versus irrelevant questions. Experts were unable to adapt their knowledge across vastly different domains, and in‐sample validation did not accurately predict out‐of‐sample performance on irrelevant questions. We suggest that if relevant calibration questions cannot be found, then analysts should use equal weights, and draw on alternative techniques to improve judgments. Our study also indicates limits to the predictive accuracy of performance weighted aggregation, and the degree to which expertise can be adapted across domains. We note limitations in our study and urge further research into the effect of question type on the reliability of performance weighted aggregations. [ABSTRACT FROM AUTHOR]

Conservation science deals with crises and supports policy interventions devised to mitigate highly uncertain threats that pose irreversible harm. When conventional policy tools, such as quantitative risk assessments, are insufficient, the precautionary principle provides a practical framework and range of robust heuristics. Yet, precaution is often resisted in many policy arenas, especially those involving powerful self‐interests, and this resistance is compounded by structures of privilege and competitive individualism in science. We describe key drivers and effects of such resistance in conservation science. These include a loss of rigor under uncertainty, an erosion of crisis response capabilities, and a further reinforcement of privileged interests in conservation politics. We recommend open acknowledgement of the pressures exerted by power inside science; greater recognition for the value of the precautionary principle under uncertainty; deliberate measures to resist competitive individualism; support for blind review, open science, and data sharing; and a shift from hierarchical multidisciplinarity toward more egalitarian transdisciplinarity to accelerate advances in conservation science. Article impact statement: Precautionary principle, privilege structures among disciplines, and culture of individualism link to effective conservation policy making. [ABSTRACT FROM AUTHOR]

1. The establishment of new botanic gardens in tropical regions highlights a need for weed risk assessment tools suitable for tropical ecosystems. The relevance of plant traits for invasion into tropical rainforests has not been well studied.2. Working in and around four botanic gardens in Indonesia where 590 alien species have been planted, we estimated the effect of four plant traits, plus time since species introduction, on: (a) the naturalization probability and (b) abundance (density) of naturalized species in adjacent native tropical rainforests; and (c) the distance that naturalized alien plants have spread from the botanic gardens.3. We found that specific leaf area (SLA) strongly differentiated 23 naturalized from 78 non‐naturalized alien species (randomly selected from 577 non‐naturalized species) in our study. These trends may indicate that aliens with high SLA, which had a higher probability of naturalization, benefit from at least two factors when establishing in tropical forests: high growth rates and occupation of forest gaps. Naturalized aliens had high SLA and tended to be short. However, plant height was not significantly related to species' naturalization probability when considered alongside other traits.4. Alien species that were present in the gardens for over 30 years and those with small seeds also had higher probabilities of becoming naturalized, indicating that garden plants can invade the understorey of closed canopy tropical rainforests, especially when invading species are shade tolerant and have sufficient time to establish.5. On average, alien species that were not animal dispersed spread 78 m further into the forests and were more likely to naturalize than animal‐dispersed species. We did not detect relationships between the measured traits and estimated density of naturalized aliens in the adjacent forests.6. Synthesis: Traits were able to differentiate alien species from botanic gardens that naturalized in native forest from those that did not; this is promising for developing trait‐based risk assessment in the tropics. To limit the risk of invasion and spread into adjacent native forests, we suggest tropical botanic gardens avoid planting alien species with fast carbon capture strategies and those that are shade tolerant. [ABSTRACT FROM AUTHOR]

In pursuit of socioeconomic development, many countries are expanding oil and mineral extraction into tropical forests. These activities seed access to remote, biologically rich areas, thereby endangering global biodiversity. We examined how protection of biodiversity and economic revenues can be balanced in biologically valuable regions. Using spatial data on oil profits and predicted species and ecosystem extents, we optimized the protection of 741 terrestrial species and 20 ecosystems of the Ecuadorian Amazon across a range of opportunity costs (i.e., sacrifices of extractive profit). We also applied spatial statistics to remotely sensed, historic deforestation data to focus the optimization on areas most threatened by imminent forest loss. Giving up 5% of a year's oil profits (US$221 million) allowed for a protected area network that retained an average of 65% of the extent of each species and ecosystem. This performance far exceeded that of the network produced by simple optimization for land area (which required a sacrifice of approximately 40% of annual oil profits [US$1.7 billion]) and used only marginally less land to achieve equivalent levels of ecological protection. We identified what we call emergency conservation targets: regions that are essential components of a cost‐effective conservation reserve network but at imminent risk of destruction, thus requiring urgent and effective protection. Governments can use our methods when evaluating extractive‐led development options to responsibly manage the associated ecological and economic trade‐offs and protect natural capital. Article Impact Statement: Governmental spatial planning of resource extraction and conservation in tropical forests helps maintain biodiversity and profits [ABSTRACT FROM AUTHOR]

Aichi Target 12 of the Convention on Biological Diversity (CBD) contains the aim to 'prevent extinctions of known threatened species'. To measure the degree to which this was achieved, we used expert elicitation to estimate the number of bird and mammal species whose extinctions were prevented by conservation action in 1993–2020 (the lifetime of the CBD) and 2010–2020 (the timing of Aichi Target 12). We found that conservation action prevented 21–32 bird and 7–16 mammal extinctions since 1993, and 9–18 bird and two to seven mammal extinctions since 2010. Many remain highly threatened and may still become extinct. Considering that 10 bird and five mammal species did go extinct (or are strongly suspected to) since 1993, extinction rates would have been 2.9–4.2 times greater without conservation action. While policy commitments have fostered significant conservation achievements, future biodiversity action needs to be scaled up to avert additional extinctions. [ABSTRACT FROM AUTHOR]

Biodiversity loss is a critical sustainability issue, and companies are beginning to seek ways to assess their biodiversity performance. Initiatives to date have developed biodiversity indicators for specific business contexts (e.g., spatial scales—from site, to product, to regional, or corporate scales); however, many are not widely translatable across different contexts making it challenging for businesses seeking indicators to manage their biodiversity performance. By synthesising the steps of common conservation and business decision‐making systems, we propose a framework to support more comprehensive development of quantitative biodiversity indicators, for a range of business contexts. The framework integrates experience from existing tried‐and‐tested conservation frameworks. We illustrate how our framework offers a pathway for businesses to assess their biodiversity performance and demonstrate responsible management by mitigating and reversing their biodiversity impacts and sustaining their dependencies, enabling them to demonstrate their contribution to emerging global biodiversity targets (e.g., Convention on Biological Diversity post‐2020 targets). [ABSTRACT FROM AUTHOR]

Performance weighted aggregation of expert judgments, using calibration questions, has been advocated to improve pooled quantitative judgments for ecological questions. However, there is little discussion or practical advice in the ecological literature regarding the application, advantages or challenges of performance weighting. In this paper we (1) illustrate how the IDEA protocol with four‐step question format can be extended to include performance weighted aggregation from the Classical Model, and (2) explore the extent to which this extension improves pooled judgments for a range of performance measures. Our case study demonstrates that performance weights can improve judgments derived from the IDEA protocol with four‐step question format. However, there is no a‐priori guarantee of improvement. We conclude that the merits of the method lie in demonstrating that the final aggregation of judgments provides the best representation of uncertainty (i.e., validation), whether that be via equally weighted or performance weighted aggregation. Whether the time and effort entailed in performance weights can be justified is a matter for decision‐makers. Our case study outlines the rationale, challenges, and benefits of performance weighted aggregations. It will help to inform decisions about the deployment of performance weighting and avoid common pitfalls in its application. [ABSTRACT FROM AUTHOR]

Quantitative expert judgements are used in reliability assessments to inform critically important decisions. Structured elicitation protocols have been advocated to improve expert judgements, yet their application in reliability is challenged by a lack of examples or evidence that they improve judgements. This paper aims to overcome these barriers. We present a case study where two world‐leading protocols, the IDEA protocol and the Classical Model, were combined and applied by the Australian Department of Defence for a reliability assessment. We assess the practicality of the methods and the extent to which they improve judgements. The average expert was extremely overconfident, with 90% credible intervals containing the true realisation 36% of the time. However, steps contained in the protocols substantially improved judgements. In particular, an equal weighted aggregation of individual judgements and the inclusion of a discussion phase and revised estimate helped to improve calibration, statistical accuracy, and the Classical Model score. Further improvements in precision and information were made via performance weighted aggregation. This paper provides useful insights into the application of structured elicitation protocols for reliability and the extent to which judgements are improved. The findings raise concerns about existing practices for utilising experts in reliability assessments and suggest greater adoption of structured protocols is warranted. We encourage the reliability community to further develop examples and insights. [ABSTRACT FROM AUTHOR]

Governments have committed to global targets to slow biodiversity loss and sustain ecosystem services. Biodiversity state indicators that measure progress toward these targets mostly focus on species, while indicators synthesizing ecosystem change are largely lacking. We fill this gap with three indices quantifying past and projected changes in ecosystems using data from the International Union for Conservation of Nature (IUCN) Red List of Ecosystems. Our indices quantify changes in risk of ecosystem collapse, ecosystem area and ecological processes, and capture variation in underlying patterns among ecosystems. We apply the indices to three case studies of regional and national assessments (American/Caribbean forests, terrestrial ecosystems of Colombia, and terrestrial ecosystems of South Africa) to illustrate the indices' complementarity and versatility in revealing patterns of interest for users across sectors. Our indices have the potential to fill the recognized need for ecosystem indicators to inform conservation targets, guide policy, and prioritize management actions. [ABSTRACT FROM AUTHOR]

Environmental decisions are often deferred to groups of experts, committees, or panels to develop climate policy, plan protected areas, or negotiate trade‐offs for biodiversity conservation. There is, however, surprisingly little empirical research on the performance of group decision making related to the environment. We examined examples from a range of different disciplines, demonstrating the emergence of collective intelligence (CI) in the elicitation of quantitative estimates, crowdsourcing applications, and small‐group problem solving. We explored the extent to which similar tools are used in environmental decision making. This revealed important gaps (e.g., a lack of integration of fundamental research in decision‐making practice, absence of systematic evaluation frameworks) that obstruct mainstreaming of CI. By making judicious use of interdisciplinary learning opportunities, CI can be harnessed effectively to improve decision making in conservation and environmental management. To elicit reliable quantitative estimates an understanding of cognitive psychology and to optimize crowdsourcing artificial intelligence tools may need to be incorporated. The business literature offers insights into the importance of soft skills and diversity in team effectiveness. Environmental problems set a challenging and rich testing ground for collective‐intelligence tools and frameworks. We argue this creates an opportunity for significant advancement in decision‐making research and practice. [ABSTRACT FROM AUTHOR]

Aim: The trait‐based vulnerability assessment (TVA) uses Boolean rules to assess species sensitivity, adaptive capacity and exposure to climate change to identify those that are climate‐change vulnerable. The protocol is being increasingly used to assess climate‐change impacts to a diversity of taxa, as it requires fewer data compared to niche and mechanistic models. However, uncertainty in TVA results remains unevaluated. We present the first quantitative investigation of the impacts of uncertainty on TVA, using global freshwater crayfish (574 species) as a representative data‐poor taxon. Location: Global. Methods: To assess uncertainty in trait selection, we measured the completeness of information for each trait and how these contributed to the number of vulnerable species. To explore the sensitivity of TVA outcomes to arbitrary threshold selection, we randomly scored 25% species as high for quantitative traits and compared the results to the standard TVA. To investigate uncertainty in climate model selections, we tested the TVA using 66 alternative global climate scenarios. Results: Given the structural rules used in TVA, as more traits are included in the protocol, more species are identified as vulnerable to climate change. Some traits also have more dominant contributions. Species vulnerability was relatively robust to arbitrary thresholds in quantitative trait variables. The number (79–156) and identity of vulnerable species varied depending on which climate scenario was selected. Ensemble means of climate models identified fewer vulnerable species, potentially softening the extremes of individual climate models. Main conclusions: Assessors applying TVA across taxa and geographical scales should use ecological thresholds for quantitative traits, where possible; most importantly perform sensitivity analyses, including (a) critically assessing assumptions and correlations underpinning the selection of traits in different dimensions; and (b) capturing variability among climate‐change models. Further research is required to fill data gaps that improve the robustness of TVA. [ABSTRACT FROM AUTHOR]

Aim: Climate change is a major threat to the persistence of biodiversity. Global assessments highlight the most climate vulnerable species and geographic regions based on species traits and measures of exposure to climate change. Yet the majority of climate change vulnerability assessments have focused on terrestrial and marine vertebrates and largely ignored the less well‐known freshwater species and invertebrates. We present the first global analysis of 574 species of freshwater crayfish (Families: Astacidae, Parastacidae and Cambaridae) using IUCN's trait‐based vulnerability assessment protocol. Location: Global. Methods: We collected species‐specific information on sensitivity (eight traits), adaptive capacity (four traits) and exposure (five traits) to climate change and combined those dimensions to assess overall species vulnerability. Results: Our results predicted that 87% of freshwater crayfish species are highly sensitive to climate change (primarily due to habitat specialization), 35% have low adaptive capacity and 57% are highly exposed (based on an ensemble mean of four general circulation models for a moderate Intergovernmental Panel on Climate Change (IPCC) scenario, RCP6.0). Combining sensitivity, low adaptive capacity and exposure, we assessed 87 species (15%) as vulnerable to climate change. These species are distributed globally with high concentrations in the south‐eastern USA (36 species), south‐eastern Australia (21 species) and Mexico (10 species), reflecting global patterns of crayfish species richness. Of the 91 species listed as threatened by climate change in the IUCN Red List, we predicted 18 species to be climate change vulnerable. Main conclusions: We identified hotspots of species vulnerable to climate change that require further conservation attention. The IUCN trait‐based protocol can help identify data gaps and key traits that should be investigated further and thus can help overcome knowledge shortfalls on the effects of climate change. Our study provides key insights for the application of climate change vulnerability assessment to data‐poor invertebrates, which remain underrepresented in global conservation priorities. [ABSTRACT FROM AUTHOR]

Abstract: In risky situations characterized by imminent decisions, scarce resources, and insufficient data, policymakers rely on experts to estimate model parameters and their associated uncertainties. Different elicitation and aggregation methods can vary substantially in their efficacy and robustness. While it is generally agreed that biases in expert judgments can be mitigated using structured elicitations involving groups rather than individuals, there is still some disagreement about how to best elicit and aggregate judgments. This mostly concerns the merits of using performance‐based weighting schemes to combine judgments of different individuals (rather than assigning equal weights to individual experts), and the way that interaction between experts should be handled. This article aims to contribute to, and complement, the ongoing discussion on these topics. [ABSTRACT FROM AUTHOR]

Abstract: Animal abundance data are essential for endangered species conservation, tracking invasive species spread, biosecurity, agricultural applications and wildlife monitoring; however, obtaining abundance data are a perennial challenge. Recent improvements in the resolution of remotely sensed imagery, and image‐processing tools and software have facilitated improvement of methods for the detection of individual, generally large‐bodied animals. The potential to monitor and survey populations from remotely sensed imagery is an exciting new development in animal ecology. We review the methods used to analyse remotely sensed imagery for their potential to estimate the abundance of wild and domestic animal populations by directly detecting, identifying and counting individuals. Despite many illustrative studies using a variety of methods for detecting animals from remotely sensed imagery, it remains problematic in many situations. Studies that demonstrated reasonably high accuracy using automated and semi‐automated techniques have been undertaken on small spatial scales relative to the geographical range of the species of interest and/or in homogenous environments such as sea ice. The major limitations are the relatively low accuracy of automated detection techniques across large spatial extents, false detections and the cost of high‐resolution data. Future developments in the analysis of remotely sensed data for population surveys will improve detection capabilities, including the advancement of algorithms, the crossover of software and technology from other disciplines, and improved availability, accessibility, cost and resolution of data. [ABSTRACT FROM AUTHOR]

Abstract: Expert judgement informs a variety of important applications in conservation and natural resource management, including threatened species management, environmental impact assessment and structured decision‐making. However, expert judgements can be prone to contextual biases. Structured elicitation protocols mitigate these biases, and improve the accuracy and transparency of the resulting judgements. Despite this, the elicitation of expert judgement within conservation and natural resource management remains largely informal. We suggest this may be attributed to financial and practical constraints, which are not addressed by many existing structured elicitation protocols. In this paper, we advocate that structured elicitation protocols must be adopted when expert judgements are used to inform science. In order to motivate a wider adoption of structured elicitation protocols, we outline the IDEA protocol. The protocol improves the accuracy of expert judgements and includes several key steps which may be familiar to many conservation researchers, such as the four‐step elicitation, and a modified Delphi procedure (“Investigate,” “Discuss,” “Estimate” and “Aggregate”). It can also incorporate remote elicitation, making structured expert judgement accessible on a modest budget. The IDEA protocol has recently been outlined in the scientific literature; however, a detailed description has been missing. This paper fills that important gap by clearly outlining each of the steps required to prepare for and undertake an elicitation. While this paper focuses on the need for the IDEA protocol within conservation and natural resource management, the protocol (and the advice contained in this paper) is applicable to a broad range of scientific domains, as evidenced by its application to biosecurity, engineering and political forecasting. By clearly outlining the IDEA protocol, we hope that structured protocols will be more widely understood and adopted, resulting in improved judgements and increased transparency when expert judgement is required. [ABSTRACT FROM AUTHOR]

Aim The koala is a widely distributed Australian marsupial with regional populations that are in rapid decline, are stable or have increased in size. This study examined whether it is possible to use expert elicitation to estimate abundance and trends of populations of this species. Diverse opinions exist about estimates of abundance and, consequently, the status of populations. Location Eastern and south-eastern Australia Methods Using a structured, four-step question format, a panel of 15 experts estimated population sizes of koalas and changes in those sizes for bioregions within four states. They provided their lowest plausible estimate, highest plausible estimate, best estimate and their degree of confidence that the true values were contained within these upper and lower estimates. We derived estimates of the mean population size of koalas and associated uncertainties for each bioregion and state. Results On the basis of estimates of mean population sizes for each bioregion and state, we estimated that the total number of koalas for Australia is 329,000 (range 144,000-605,000) with an estimated average decline of 24% over the past three generations and the next three generations. Estimated percentage of loss in Queensland, New South Wales, Victoria and South Australia was 53%, 26%, 14% and 3%, respectively. Main conclusions It was not necessary to achieve high levels of certainty or consensus among experts before making informed estimates. A quantitative, scientific method for deriving estimates of koala populations and trends was possible, in the absence of empirical data on abundances. [ABSTRACT FROM AUTHOR]

Changes in natural patterns of animal behaviour and physiology resulting from anthropogenic disturbance may alter the conservation status of a population if they affect the ability of individuals to survive, breed or grow. However, information to forecast population-level consequences of such changes is often lacking., We developed an interim framework to assess the population consequences of disturbance when empirical information is sparse. We show how daily effects of disturbance, which are often straightforward to estimate, can be scaled to the disturbance duration and to multiple sources of disturbance., We used expert elicitation to estimate parameters that define how changes in individual behaviour or physiology affect vital rates and incorporated them into a stochastic population model. Model outputs can be used to evaluate cumulative impacts of disturbance over space and time. As an example, we forecast the potential effects of disturbance from offshore wind farm construction on the North Sea harbour porpoise ( Phocoena phocoena) population., Synthesis and applications. The interim framework can be used to forecast the effects of disturbances from human activities on animal populations, to assess the effectiveness of mitigation measures and to identify priority areas for research that reduces uncertainty in population forecasts. The last two applications are likely to be important in situations where there is a risk of unacceptable change in a species' conservation status. The framework should, however, be augmented with empirical data as soon as these are available. [ABSTRACT FROM AUTHOR]

An editorial is presented on the publishing of social science research in the journal "Conservation Biology." Topics discussed include changes brought by humans in ecology such as biodiversity loss; the role of human-nature relationship in sustainable development and globalization, that has enhanced human relationships with the natural environment; and the role played by social sciences in the conservation of nature.

Despite the aligned aspirations of many applied scientists and policy-makers that science should contribute directly to policy decisions, there are significant gaps between what scientists provide and what policy-makers can use. This article outlines the features that encourage effective adoption of scientific advice in public policy. It reviews some of the major impediments to its use. It describes governance mechanisms that aim to overcome these impediments, and discusses their strengths and weaknesses. Opportunities exist for designing governance mechanisms that will better support the development and persistence of the personal relationships that underpin the most effective delivery of science for policy. [ABSTRACT FROM AUTHOR]

Aim To identify the temporal patterns of plant naturalization in Australia, particularly the interaction between taxonomy, geographic origin and economic use. Location Australia. Methods From Australia's Virtual Herbarium, we compiled a database of information for the entire naturalized flora of Australia. We then examined the database in discrete time intervals to determine the changes in patterns of naturalized species taxonomy, geographic origin and economic use over time. Results Contrary to prevailing hypotheses, we found no evidence to indicate that the rate of alien flora naturalization is increasing in Australia. The number of naturalized species has grown linearly during the period 1880-2000, with the underlying rate of new species detected per thousand specimens declining over the same time period. Despite this, the diversity of both species taxonomy and geographic origin has increased over the last 120 years, leading to increased rates of growth in the total phylogenetic diversity of the Australian flora. Main Conclusions By classifying species according to their likely origin and economic use, we are able to infer the circumstances driving the patterns of naturalization. In particular, we identify how the contribution of individual pathways has changed since European settlement corresponding with the socio-economic development of the continent. Our study illustrates how the changing nature of 'high-risk' pathways is relevant to directing interventions such as biosecurity regulation. [ABSTRACT FROM AUTHOR]

In response to growing demand for ecosystem-level risk assessment in biodiversity conservation, and rapid proliferation of locally tailored protocols, the IUCN recently endorsed new Red List criteria as a global standard for ecosystem risk assessment. Four qualities were sought in the design of the IUCN criteria: generality; precision; realism; and simplicity. Drawing from extensive global consultation, we explore trade-offs among these qualities when dealing with key challenges, including ecosystem classification, measuring ecosystem dynamics, degradation and collapse, and setting decision thresholds to delimit ordinal categories of threat. Experience from countries with national lists of threatened ecosystems demonstrates well-balanced trade-offs in current and potential applications of Red Lists of Ecosystems in legislation, policy, environmental management and education. The IUCN Red List of Ecosystems should be judged by whether it achieves conservation ends and improves natural resource management, whether its limitations are outweighed by its benefits, and whether it performs better than alternative methods. Future development of the Red List of Ecosystems will benefit from the history of the Red List of Threatened Species which was trialed and adjusted iteratively over 50 years from rudimentary beginnings. We anticipate the Red List of Ecosystems will promote policy focus on conservation outcomes in situ across whole landscapes and seascapes. [ABSTRACT FROM AUTHOR]

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Aim To identify the relative importance of commonly available site and species factors on the probability of extirpating a plant species at the site scale. Location Australia. Methods We reviewed the plant eradication literature and listed the factors commonly cited as influencing eradication success. We then analysed a database of 408 site-scale extirpation attempts, across 17 species eradication programmes, by modelling the time until extirpation to determine the relative influence of these factors on the probability of extirpation, given time. Results The most commonly cited factors influencing eradication success can be classified into two groups as follows: those related to the 'organisation', being typically binary variables and amenable to management; and those related to the 'site/species', which typically were continuous values and usually beyond the control of the management agency. Detectability period, search distance, monitoring rate, infestation size, propagule longevity, time to reproductive maturity and previous eradication success all influenced the extirpation rate. Conversely, climate suitability, land use and general accessibility (distance to nearest manager) were relatively unimportant. By relating the influential site/species factors to a time-dependent model, managers and policymakers can explicitly estimate the probability of successful extirpation at a site, given a particular time horizon. These estimates can then be aggregated up to the species scale to allow managers to set realistic goals regarding eradication time frames and resource requirements. Main conclusions Our paper illustrates how the probability of extirpation at the site scale can be quantitatively estimated and how these estimates can be used to inform decisions regarding broader species-scale eradication programmes. We expect that the use of such quantitative approaches to select better eradication targets will improve eradication success rates over time. [ABSTRACT FROM AUTHOR]

Authors who adopt transparent practices for an article in I Conservation Biology i are now able to select from 3 open science badges: open data, open materials, and preregistration. Authors of 31% of these articles published in I Conservation Biology i said they shared their data or code, and all authors provide human-survey instruments in Supporting Information or via a citation or online link (i.e., shared materials). The Center for Open Science has introduced "badges" as a way to recognize authors who engage in transparent practices (for further information, see https://cos.io/our-services/open-science-badges/). [Extracted from the article]

Voting systems aggregate preferences efficiently and are often used for deciding conservation priorities. Desirable characteristics of voting systems include transitivity, completeness, and Pareto optimality, among others. Voting systems that are common and potentially useful for environmental decision making include simple majority, approval, and preferential voting. Unfortunately, no voting system can guarantee an outcome, while also satisfying a range of very reasonable performance criteria. Furthermore, voting methods may be manipulated by decision makers and strategic voters if they have knowledge of the voting patterns and alliances of others in the voting populations. The difficult properties of voting systems arise in routine decision making when there are multiple criteria and management alternatives. Because each method has flaws, we do not endorse one method. Instead, we urge organizers to be transparent about the properties of proposed voting systems and to offer participants the opportunity to approve the voting system as part of the ground rules for operation of a group. Sistemas de Votación para Decisiones Ambientales [ABSTRACT FROM AUTHOR]

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

Aim Many mangrove communities form bands parallel to the shoreline with each community dominated by a single species. However, the key determinants of mangrove species distribution across the intertidal zone are not well understood. We aimed to quantify the relationship between species' dominance and the hydroperiod (defined as the duration of inundation in a year), soil salinity and the salinity of inundating water for three dominant species, Sonneratia alba, Rhizophora stylosa and Ceriops tagal. Location An extensive (20,000 ha), largely intact mangrove forest in northern Australia, of some note as mangrove forests are threatened globally. Methods We related species dominance to the explanatory variables by applying two statistical modelling approaches: generalized linear models ( GLMs), where a set of competing models were evaluated; and boosted regression tree models ( BRTs), an approach that automatically captures interactions and nonlinear relationships between variables. Results Both GLM and BRT models achieved strong predictive performance for all species based on cross-validation, with receiver operating characteristics above 0.85 for all species, and 88% of deviance explained for S. alba, 42% for R. stylosa and 35% for C. tagal. All models indicated that the hydroperiod was the key variable influencing distribution, followed by soil salinity. The salinity of inundating water was the least informative variable in the models. Ecological space, determined by gradients in hydroperiod and soil salinity, was partitioned between the three species with little overlap. Main conclusions As anticipated changes in sea level will alter the hydroperiod, our findings are critical for global forecasting of future distributions of mangrove communities, and for the design of mitigation and adaptation measures. [ABSTRACT FROM AUTHOR]

Aim To offer a test of expert knowledge about rarity of twenty Amazon forest bird species following an approach that equates rarity with low site occupancy and formally accounts for imperfect species detection. We define ten pairs of closely related species, each pair with one hypothetically common and one hypothetically rare species. Our null hypothesis is that members of each pair have similar occupancy, with hypothesized differences due to detection errors alone. Location A 1000-ha plot of primary rainforest in the central Brazilian Amazon. Methods We visited each of 55 sampling sites multiple times per season for three field seasons and estimated the probability of site occupancy by each species following a maximum likelihood state-space approach that also estimates the probability that a species is present yet undetected at a site. To maximize detection and account for its variation, we employed three different sampling techniques while systematically training and testing observer's ability to recognize species. Results Occupancy estimates agree with expert predictions in all but two species pairs and show no evidence of clear temporal variation in occupancy between sampling seasons. Detection probability had a positive relation with observer ability, a strong relation to time of day across species, and a strong relation with the use of playback for some species. Detection with point counts and with autonomous recorders varied between species pairs. Main conclusions We reject the null hypothesis of equal occupancy within pairs, concluding that expert knowledge on species rarity is useful and worth eliciting. Our results replace qualitative ratings of rarity with statistical estimates of occupancy, establishing a reliable baseline for future comparisons. Besides illustrating the relevance of expert knowledge, this application to Amazonian birds illustrates a flexible approach that can be used for testing knowledge about rarity for a variety of species groups and spatial scales. [ABSTRACT FROM AUTHOR]

Aim Risk assessments in applied scientific disciplines have evolved somewhat in isolation, adopting conventions, assumptions and tools from other disciplines almost haphazardly. This editorial provides background for the articles in this special issue, which sample six broad themes in risk assessment in conservation biology and presenting new innovations and applications. Location Global. Methods The articles in the special issue address themes related to species distribution modelling, population viability analysis, threatened species management, biosecurity, uncertainty analysis, cost-benefit analysis and foresight. We sought articles that address new and emerging topics in each of these areas. Results The articles identify new and potentially useful innovations in a variety of areas relevant to conservation biology. Collectively, they paint a picture of risk assessment as an important element in supporting transparent, rational decisions and effective policy. Main conclusions Policy makers and conservation managers aspire to set evidence-based priorities, and technical specialists aim to have their methods used in decision-making. Scientists will succeed if, as the articles in this issue exemplify, they develop a sound understanding of the context of the decisions in which their tools are to be used and shape them accordingly. [ABSTRACT FROM AUTHOR]

Aim Effective decisions for managing invasive species depend on feedback about the progress of eradication efforts. Panetta & Lawes () developed the eradograph, an intuitive graphical tool that summarizes the temporal trajectories of delimitation and extirpation to support decision-making. We correct and extend the tool, which was affected by incompatibilities in the units used to measure these features that made the axes impossible to interpret biologically. Location Victoria, New South Wales and Queensland, Australia. Methods Panetta and Lawes' approach represented delimitation with estimates of the changes in the area known to be infested and extirpation with changes in the mean time since the last detection. We retain the original structure but propose different metrics that improve biological interpretability. We illustrate the methods with a hypothetical example and real examples of invasion and treatment of branched broomrape ( Orobanche ramosa L.) and the guava rust complex ( Puccinia psidii ( Winter 1884)) in Australia. Results These examples illustrate the potential of the tool to guide decisions about the effectiveness of search and control activities. Main conclusions The eradograph is a graphical data summary tool that provides insight into the progress of eradication. Our correction and extension of the tool make it easier to interpret and provide managers with better decision support. [ABSTRACT FROM AUTHOR]

Aim We aim to explore the capacity of MCDA methods to successfully capture social impacts and integrate stakeholders' participation into environmental decision applications. We follow a theoretical framework that deconstructs the concept of social impact into two components: human impacts and social change processes. Location Global. Methods We systematically reviewed the literature on MCDA in the Web of Science ( ISI) database, finding 119 papers that meet our search criteria. For each paper, we identified the social change processes or human impacts objectives, along with the attributes that measured them. We also recorded the degree of stakeholder participation in each phase of the MCDA stages. Results We found that MCDA practitioners have increasingly integrated social concerns in the analysis of environmental problems, estimating the potential impacts, and developing participative procedures for stakeholders. We identified 252 objectives that represent human impacts or social change processes. Constructed attributes were the most commonly employed (56%), although natural (20%) and proxy (24%) attributes were also relevant. Estimating human impacts or social change processes can involve public participation, but is not a requirement for MCDA: 42% of papers ( n = 50) include stakeholder engagement in one or more stages of the decision-making process. We found that stakeholders engage differently across case studies, demonstrating that this process is neither simple nor homogenous. Main conclusions Our review suggests that MCDA methods are appropriate techniques to integrate a wide range of social objectives and stakeholder engagement, supporting well informed and democratic decisions. [ABSTRACT FROM AUTHOR]

Aim Decision-making for conservation management often involves evaluating risks in the face of environmental uncertainty. Models support decision-making by (1) synthesizing available knowledge in a systematic, rational and transparent way and (2) providing a platform for exploring and resolving uncertainty about the consequences of management decisions. Despite their benefits, models are still not used in many conservation decision-making contexts. In this article, we provide evidence of common objections to the use of models in environmental decision-making. In response, we present a series of practical solutions for modellers to help improve the effectiveness and relevance of their work in conservation decision-making. Location Global review. Methods We reviewed scientific and grey literature for evidence of common objections to the use of models in conservation decision-making. We present a set of practical solutions based on theory, empirical evidence and best-practice examples to help modellers substantively address these objections. Results We recommend using a structured decision-making framework to guide good modelling practice in decision-making and highlight a variety of modelling techniques that can be used to support the process. We emphasize the importance of participatory decision-making to improve the knowledge-base and social acceptance of decisions and to facilitate better conservation outcomes. Improving communication and building trust are key to successfully engaging participants, and we suggest some practical solutions to help modellers develop these skills. Main conclusions If implemented, we believe these practical solutions could help broaden the use of models, forging deeper and more appropriate linkages between science and management for the improvement of conservation decision-making. [ABSTRACT FROM AUTHOR]

Aim Biosecurity responses to incursions aim to achieve pest- or disease-free status as quickly as possible. One of the critical initial response activities involves tracing known movements (trace events) to and from an infected or infested property ( IP) that could spread the pest or pathogen. During an incursion response, managers allocate surveillance resources to follow up trace events in order of priority. Prioritizing trace events is difficult and typically subjective. We present a simulation model where several dispersal mechanisms spread a pest between areas. We use model outputs to test different search strategies, using citrus canker (caused by Xanthomonas citri) as a case study. Model scenarios are based on an outbreak of citrus canker that occurred in Queensland in 2004. Location Australia. Methods Model parameters were extracted from published scientific reports and elicited from experts. We used model outputs to assess three search strategies to determine how best to monitor citrus canker spread. Parameters governing disease detectability and host susceptibility were varied in a sensitivity analysis. Results In all simulation scenarios, the 'adaptive radius' rule performed best, whereby a circular search area was placed around the IP where the disease outbreak was first detected, with a radius proportional to the estimated number of months the property was infected. Importantly, none of the search rules tested detected all IPs without searching all areas with susceptible hosts in the region. Main conclusions We identify a simple rule of thumb for searching during a citrus canker outbreak that is robust to uncertainty. We cannot generalize the results of this study for tracing other pests or pathogens. The model has created a framework that may be used to explore other contexts and disease dynamics, leading perhaps to more general rules for disease outbreak management. [ABSTRACT FROM AUTHOR]

Aim To quantify the consequences of major threats to biodiversity, such as climate and land-use change, it is important to use explicit measures of species persistence, such as extinction risk. The extinction risk of metapopulations can be approximated through simple models, providing a regional snapshot of the extinction probability of a species. We evaluated the extinction risk of three species under different climate change scenarios in three different regions of the Mexican cloud forest, a highly fragmented habitat that is particularly vulnerable to climate change. Location Cloud forests in Mexico. Methods Using Maxent, we estimated the potential distribution of cloud forest for three different time horizons (2030, 2050 and 2080) and their overlap with protected areas. Then, we calculated the extinction risk of three contrasting vertebrate species for two scenarios: (1) climate change only (all suitable areas of cloud forest through time) and (2) climate and land-use change (only suitable areas within a currently protected area), using an explicit patch-occupancy approximation model and calculating the joint probability of all populations becoming extinct when the number of remaining patches was less than five. Results Our results show that the extent of environmentally suitable areas for cloud forest in Mexico will sharply decline in the next 70 years. We discovered that if all habitat outside protected areas is transformed, then only species with small area requirements are likely to persist. With habitat loss through climate change only, high dispersal rates are sufficient for persistence, but this requires protection of all remaining cloud forest areas. Main conclusions Even if high dispersal rates mitigate the extinction risk of species due to climate change, the synergistic impacts of changing climate and land use further threaten the persistence of species with higher area requirements. Our approach for assessing the impacts of threats on biodiversity is particularly useful when there is little time or data for detailed population viability analyses. [ABSTRACT FROM AUTHOR]

Aim Decision-making in weed management involves consideration of limited budgets, long time horizons, conflicting priorities, and as a result, trade-offs. Economics provides tools that allow these issues to be addressed and is thus integral to management of the risks posed by weeds. One of the critical issues in weed risk management during the early stages of an invasion concerns feasibility of eradication. We briefly review how economics may be used in weed risk management, concentrating on this management strategy. Location Australia. Methods A range of innovative studies that investigate aspects of weed risk management are reviewed. We show how these could be applied to newly invading weeds, focussing on methods for investigating eradication feasibility. In particular, eradication feasibility is analysed in terms of cost and duration of an eradication programme, using a simulation model based on field-derived parameter values for chromolaena, Chromolaena odorata. Results The duration of an eradication programme can be reduced by investing in progressively higher amounts of search effort per hectare, but increasing search area will become relatively more expensive as search effort increases. When variation in survey and control success is taken into account, increasing search effort also reduces uncertainty around the required duration of the eradication programme. Main conclusions Economics is integral to the management of the risks posed by weeds. Decision analysis, based on economic principles, is now commonly used to tackle key issues that confront weed managers. For eradication feasibility, duration and cost of a weed eradication programme are critical components; the dimensions of both factors can usefully be estimated through simulation. [ABSTRACT FROM AUTHOR]

Aim AquaticHealth.net is an open-source aquatic biosecurity intelligence gathering and analysis application. The system collects information in much the same way as other similar systems (e.g. HealthMap, Bio Caster). However, the information collected undergoes minimal automated analysis, and analysis is largely left to Aquatic Health.net's users. The result is an automated system of intelligence gathering, combined with a manual system of intelligence analysis. This approach relies on a large number of users, and so Aquatic Health.net relies on an open-intelligence analysis method: any user can publish their own analyses for all to see and analyse further. By combining automated data collection and human analysis, Aquatic Health.net will provide fast and accurate forecasts, accompanied with nuanced explanations. These methods can be applied to other areas of biosecurity and disease surveillance. Location Canberra, Australia; College Park, Maryland, USA; Melbourne, Australia. Methods Automated: Aquatic Health.net performs hourly scans of an array of RSS feeds, blogs, social networks and news sites. It analyses this information and removes redundancies and applies taxonomy and geospatial tags. The information is then pushed to the Daily Scan, where users then analyse it further. Manual: Users assess the information for inaccuracies and its importance. They decide whether an article should be a disease alert, which is emailed to all users. Users can change tags, edit reports, add commentary, apply rankings, change search terms and summarize issues in the Emerging Issues blog (formerly a wiki). Results Aquatic Health.net publishes seven daily reports and 2 weekly disease alerts (on average). Ninety per cent of CEFAS's (www.cefas.defra.gov.uk) Emerging Disease Updates cite Aquatic Health.net. The Australian Sub- Committee for Aquatic Animal Health ( SCAAH) uses the system to compile quarterly reports. The Australian Department of Agriculture, Fisheries and Forestry ( DAFF) uses Aquatic Health.net to make forecasts-for example, used aquaculture equipment is a high-risk pathway for Os HV. Aquatic Health.net's users forecasted an increase in emerging marine finfish disease outbreaks in Southeast Asia and are actively watching this issue. Main conclusions Aquatic Health.net's open-intelligence approach has proven to be an effective and flexible biosecurity forecasting method. [ABSTRACT FROM AUTHOR]

Aim Species distribution models ( SDMs) coupled with metapopulation dynamics models can integrate multiple threats and population-level processes that influence species distributions. However, multiple sources of uncertainties could lead to substantial differences in model outputs and jeopardize risk assessments. We evaluate uncertainties in coupled species distribution-metapopulation dynamics models and focus on two often underappreciated sources of uncertainty: the choice of general circulation model ( GCM) and demographic parameter uncertainty of the metapopulation model. We rank the risks associated with potential climate changes and habitat loss on projected range margin dynamics of the Hooded Warbler ( Setophaga citrina). Location Breeding range of the Hooded Warbler, North America. Methods Using SDMs, we quantified variability in projected future distributions using four GCMs and a consensus model at the biogeographic scale and assessed the propagation of uncertainty through to metapopulation viability projections. We applied a global sensitivity analysis to the coupled species distribution-metapopulation models to rank the influence of choice of GCM, parameter uncertainty and simulated effects of habitat loss on metapopulation viability, thereby addressing error propagation through the whole modelling process. Results The Hooded Warbler range was consistently projected to shift north: choice of GCMs influenced the magnitude of change, and variability was spatially structured. Variability in the choice of GCMs propagated through to metapopulation viability at the northern range boundary. Although viability measures were sensitive to the GCM used, measures of direct habitat loss were more influential. Despite the high ranking of vital rates in the global sensitivity analysis, direct habitat loss had a larger negative influence on extinction risk than potential future climate changes. Main conclusions This work underscores the importance of a global sensitivity analysis framework applied to coupled models to disentangle the relative influence of uncertainties on projections. The use of multiple GCMs enabled the exploration of a range of possible outcomes relative to the consensus GCM, helping to inform risk estimates. Ranking uncertainties informs the prioritization of management actions for species affected by dynamic anthropogenic threats over multiple spatial scales. [ABSTRACT FROM AUTHOR]

Aim Population viability analysis ( PVA) is used to quantify the risks faced by species under alternative management regimes. Bayesian PVAs allow uncertainty in the parameters of the underlying population model to be easily propagated through to the predictions. We developed a Bayesian stochastic patch occupancy model ( SPOM) and used this model to assess the viability of a metapopulation of the growling grass frog ( Litoria raniformis) under different urbanization scenarios. Location Melbourne, Victoria, Australia. Methods We fitted a Bayesian model that accounted for imperfect detection to a multiseason occupancy dataset for L. raniformis collected across northern Melbourne. The probability of extinction was modelled as a function of effective wetland area, aquatic vegetation cover and connectivity, using logistic regression. The probability of colonization was modelled as a function of connectivity alone. We then simulated the dynamics of a metapopulation of L. raniformis subject to differing levels of urbanization and compensatory wetland creation. Uncertainty was propagated by conducting simulations for 5000 estimates of the parameters of the models for extinction and colonization. Results There was considerable uncertainty in both the probability of quasi-extinction and the minimum number of occupied wetlands under most urbanization scenarios. Uncertainty around the change in quasi-extinction risk and minimum metapopulation size increased with increasing habitat loss. For our focal metapopulation, the analysis revealed that significant investment in new wetlands may be required to offset the impacts of urbanization. Main conclusions Bayesian approaches to PVA allow parametric uncertainty to be propagated and considered in management decisions. They also provide means of identifying parameters that represent critical uncertainties, and, through the use of informative priors, can easily assimilate new data to reduce parametric uncertainty. These advantages, and the ready availability of software to run Bayesian analyses, will ensure that Bayesian approaches are used increasingly for PVAs. [ABSTRACT FROM AUTHOR]

Aim We developed a new method to design objective, risk-based surveillance systems for non-indigenous species of invertebrates, vertebrates and plants, which might be introduced to a natural area through an industrial project; here, we provide the invertebrate case study. The method addresses issues common to complex surveillance design problems: a statistical standard (e.g. power); information gaps; multiple targets of unclear identity; a large surveillance area of heterogeneous risk of invasion; integrating multiple sources of surveillance data; optimizing for cost. Location Barrow Island, Western Australia. Methods We mapped the surveillance area for risk to target surveillance activities. An expert group identified a set of exemplar species and identified and characterized a set of detection methods for each, such that all potential invaders would be detected. We devised multi-element surveillance systems to detect each exemplar to the design power (0.8), then integrated them to a single system that was optimized for cost. Results The surveillance system was deployed on the island to specification over 1 year, then reviewed for redesign in a second period. Main conclusions The new method provided practical, risk-based surveillance system designs that met application requirements and overcame complex issues common to many surveillance applications. A review of experiences from surveillance in the first year led to practical improvements and design efficiencies. [ABSTRACT FROM AUTHOR]

Aim Conservation managers are typically faced with limited resources, time and information. The philosophy underlying risk assessment should be robust to these limitations. While there is a broad support for the concept of risk assessments, there is a tendency to rely on expert opinion and exclude formal data analysis, possibly because available information is often scarce. When data analyses are conducted, often much simplified models are advocated, even though this means excluding processes believed by experts to be important. In this manuscript, we ask: should statistical analyses be conducted and decisions modified based on a single datum? How many data points are needed before predictions are meaningful? Given limited data, how complex should models be? Location World-wide. Methods We use simulation approaches with known 'true' values to assess which inferences are possible, given different amounts of information. We use two metrics of performance: the magnitude of uncertainty (using posterior mean squared error) and bias (using P- P plots). We assess six models of relevance to conservation ecologists. Results We show that the greatest reduction in uncertainty occurred at the smallest sample sizes for models examined, and much of parameter space could be excluded. Thus, analyses based on even a single datum potentially can be useful. Further, with only a few observations, the predicted distribution of outcomes matched the probabilities of actual occurrences, even for relatively complex state-space models with multiple sources of stochasticity. Main conclusions We highlight the utility of quantitative analyses even with severely limited data, given existing practices and arguments in the conservation literature. The purpose of our manuscript is in part a philosophical discourse, as modifications are needed to how conservation ecologists are often trained to think about problems and data, and in part a demonstration via simulation analysis. [ABSTRACT FROM AUTHOR]

Aim Rare aquatic species are a substantial component of biodiversity, and their conservation is a major objective of many management plans. However, they are difficult to assess, and their optimal habitats are often poorly known. Methods to effectively predict the likely locations of suitable rare aquatic species habitats are needed. We combine two modelling approaches to predict occurrence and general abundance of several rare fish species. Location Allegheny watershed of western New York State (USA) Methods Our method used two empirical neural network modelling approaches (species specific and assemblage based) to predict stream-by-stream occurrence and general abundance of rare darters, based on broad-scale habitat conditions. Species-specific models were developed for longhead darter ( Percina macrocephala), spotted darter ( Etheostoma maculatum) and variegate darter ( Etheostoma variatum) in the Allegheny drainage. An additional model predicted the type of rare darter-containing assemblage expected in each stream reach. Predictions from both models were then combined inclusively and exclusively and compared with additional independent data. Results Example rare darter predictions demonstrate the method's effectiveness. Models performed well ( R2 ≥ 0.79), identified where suitable darter habitat was most likely to occur, and predictions matched well to those of collection sites. Additional independent data showed that the most conservative (exclusive) model slightly underestimated the distributions of these rare darters or predictions were displaced by one stream reach, suggesting that new darter habitat types were detected in the later collections. Main conclusions Broad-scale habitat variables can be used to effectively identify rare species' habitats. Combining species-specific and assemblage-based models enhances our ability to make use of the sparse data on rare species and to identify habitat units most likely and least likely to support those species. This hybrid approach may assist managers with the prioritization of habitats to be examined or conserved for rare species. [ABSTRACT FROM AUTHOR]

Aim Most risk assessments and decisions in conservation are based on surrogate approaches, where a group of species or environmental indicators are selected as proxies for other aspects of biodiversity. In the focal species approach, a suite of species is selected based on life history characteristics, such as dispersal limitation and area requirements. Testing the validity of the focal species concept has proved difficult, due to a lack of theory justifying the underlying framework, explicit objectives and measures of success. We sought to understand the conditions under which the focal species concept has merit for conservation decisions. Location Our model system comprised 10 vertebrate species in 39 patches of native forest embedded in pine plantation in New South Wales, Australia. Methods We selected three focal species based on ecological traits. We used a multiple-species reserve selection method that minimizes the expected loss of species, by estimating the risk of extinction with a metapopulation model. We found optimal reserve solutions for multiple species, including all 10 species, the three focal species, for all possible combinations of three species, and for each species individually. Results Our case study suggests that the focal species approach can work: the reserve system that minimized the expected loss of the focal species also minimized the expected species loss in the larger set of 10 species. How well the solution would perform for other species and given landscape dynamics remains unknown. Main conclusions The focal species approach may have merit as a conservation short cut if placed within a quantitative decision-making framework, where the aspects of biodiversity for which the focal species act as proxies are explicitly defined, and success is determined by whether the use of the proxy results in the same decision. Our methods provide a framework for testing other surrogate approaches used in conservation decision-making and risk assessment. [ABSTRACT FROM AUTHOR]

Aim Geographic mapping of risks is a useful analytical step in ecological risk assessments and in particular, in analyses aimed to estimate risks associated with introductions of invasive organisms. In this paper, we approach invasive species risk mapping as a portfolio allocation problem and apply techniques from decision theory to build an invasion risk map that combines risk and uncertainty in a single map product. Location Canada. Methods We divide the study area into a set of spatial domains and treat each domain as an individual 'portfolio' with a unique distribution of the expected impacts of invasion. The risk of invasion is then mapped by finding nested 'efficient' portfolio sets that identify the geographic areas exhibiting the worst combinations of the estimated risk of invasion and the uncertainty in that estimate. For Canadian municipalities, we apply the approach to quantify the risk that a given location will receive invasive forest pests with commercial freight transported via the North American road network. We compare risk allocation techniques that employ the concepts of nested mean-variance ( M-V) frontiers and second-degree stochastic dominance. Results While both methods based on M-V and the stochastic dominance principles identified similar areas of highest risk, they differed in how they demarcated moderate-risk areas. Furthermore, they address uncertainty in different ways, treating it as a risk premium (in the case of nested M-V frontiers) or producing risk-averse delineations (in the case of stochastic dominance). Main conclusions The portfolio-based approach offers a viable strategy for dealing with the typically wide variability in risk estimates caused by a lack of knowledge about a new invader. The methodology also provides a tractable way of incorporating decision-making preferences into the final risk estimates and thus better aligns risk assessments with particular decision-making scenarios about the organism of concern. [ABSTRACT FROM AUTHOR]

Climate change is an important threat to biodiversity globally, but there are major uncertainties associated with its magnitude and ecological consequences. Here, we investigate how three major classes of uncertainty, linguistic uncertainty, epistemic uncertainty (uncertainty about facts), and human decision uncertainty, have been accounted for in scientific literature about climate change. Some sources of uncertainty are poorly characterized and epistemic uncertainty is much more commonly treated than linguistic or human decision uncertainty. Furthermore, we show that linguistic and human decision uncertainties are relatively better treated in the literature on sociopolitics or economics than in natural sciences, which often overlook communication between stakeholders and socioeconomic consequences. As uncertainty can significantly influence implementation of conservation, we discuss uncertainties associated with some commonly proposed conservation adaptation actions to mitigate climate change. There may be major differences between strategies, with implications on how they should be viewed in conservation planning. We conclude that evaluating conservation strategies in terms of different types of uncertainty will facilitate communication between disciplines and stakeholders. While accounting for uncertainties in a quantitative manner is difficult and data demanding, even qualitative appreciation about the uncertainties inherent in conservation strategies can facilitate and improve decision making. [ABSTRACT FROM AUTHOR]

Aim Our goal was to use the occurrence of the influenza A virus in wild birds in Japan to create a potential risk map for the spread of avian influenza by migratory birds. Our modelling included a consideration of the multicollinearity and spatial autocorrelation of environmental variables and an examination of the reproducibility of the model results. Location Japan. Methods We used the maximum entropy approach to generate potential distribution models from presence-only data. Independent variables in the model included environmental factors such as winter temperature and precipitation, host factors such as duck population size and habitat abundance and artificial factors such as size of urban areas and poultry density. We used eigenvector-based spatial filters to alleviate spatial autocorrelation. To explore the reliability of the model, we compared the risk indices of localities positive in past winters for the influenza A virus in wild birds with those of all localities. Results The model alleviated spatial autocorrelation with a high degree of accuracy. Dabbling duck population, size of urban area, diving duck population and altitude were the variables that were most strongly correlated with the potential distribution of avian influenza. We used the frequency of occurrence of the influenza A virus in five recent years in localities where wild birds were infected to estimate the repeatability of the high-risk indices; the potential risk indices for avian influenza in wild birds were high in localities where wild birds were infected in past. Main conclusions The dabbling duck population in an area appeared to be the best indicator of high risk for the introduction of avian influenza from abroad. Priority monitoring localities for avian influenza carried by wild birds should be designated in western Japan and along the Pacific coast, which we estimated to be high-risk areas. Poultry farms in these areas should increase their biosecurity to prevent vectors from introducing avian influenza. [ABSTRACT FROM AUTHOR]

Some alien species cause substantial impacts, yet most are innocuous. Given limited resources, forecasting risks from alien species will help prioritise management. Given that risk assessment ( RA) approaches vary widely, a synthesis is timely to highlight best practices. We reviewed quantitative and scoring RAs, integrating > 300 publications into arguably the most rigorous quantitative RA framework currently existing, and mapping each study onto our framework, which combines Transport, Establishment, Abundance, Spread and Impact ( TEASI). Quantitative models generally measured single risk components (78% of studies), often focusing on Establishment alone (79%). Although dominant in academia, quantitative RAs are underused in policy, and should be made more accessible. Accommodating heterogeneous limited data, combining across risk components, and developing generalised RAs across species, space and time without requiring new models for each species may increase attractiveness for policy applications. Comparatively, scoring approaches covered more risk components (50% examined > 3 components), with Impact being the most common component (87%), and have been widely applied in policy (> 57%), but primarily employed expert opinion. Our framework provides guidance for questions asked, combining scores and other improvements. Our risk framework need not be completely parameterised to be informative, but instead identifies opportunities for improvement in alien species RA. [ABSTRACT FROM AUTHOR]