44 research outputs found

    Improvements to the Red List Index

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    The Red List Index uses information from the IUCN Red List to track trends in the projected overall extinction risk of sets of species. It has been widely recognised as an important component of the suite of indicators needed to measure progress towards the international target of significantly reducing the rate of biodiversity loss by 2010. However, further application of the RLI (to non-avian taxa in particular) has revealed some shortcomings in the original formula and approach: It performs inappropriately when a value of zero is reached; RLI values are affected by the frequency of assessments; and newly evaluated species may introduce bias. Here we propose a revision to the formula, and recommend how it should be applied in order to overcome these shortcomings. Two additional advantages of the revisions are that assessment errors are not propagated through time, and the overall level extinction risk can be determined as well as trends in this over time

    Building robust, practicable counterfactuals and scenarios to evaluate the impact of species conservation interventions using inferential approaches

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    Robust evaluation of the impact of biodiversity conservation actions is important not only for ensuring that conservation strategies are effective and maximise return on investment, but also to identify and celebrate successful conservation strategies. This evaluation can be retrospective (comparing the current situation to a counterfactual scenario) or forward-looking (comparing future scenarios with or without conservation). However, assessment of impact using experimental or quasi-experimental designs is typically difficult in conservation, so rigorous inferential approaches are required. Inferential assessment of impact is a key part of the new IUCN Green Status of Species, which greatly amplifies the need for standardised and practical species impact evaluation methods. Here, we use the Green Status of Species method as a base to review how inferential methods can be used to evaluate conservation impact at the species level. We identify three key components of the inferential impact evaluation process—estimation of scenario outcomes, selection of baseline scenario, and frame of reference—and explain, with examples, how to reduce the subjectivity of these steps. We propose a step-by-step guide, incorporating these principles, that can be used to infer scenario outcomes in order to evaluate past and future conservation impact in a wide range of situations, not just Green Status of Species assessments. We recommend that future non-experimental conservation interventions facilitate the process of evaluating impact by identifying the variable(s) that will be used to measure impact at the design stage, and by using conceptual models to help choose conservation actions most likely to have the desired impact

    Testing a global standard for quantifying species recovery and assessing conservation impact

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    Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a “Green List of Species” (now the IUCN Green Status of Species). A draft Green Status framework for assessing species’ progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species’ viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species’ recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard

    Measuring Global Trends in the Status of Biodiversity: Red List Indices for Birds

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    The rapid destruction of the planet's biodiversity has prompted the nations of the world to set a target of achieving a significant reduction in the rate of loss of biodiversity by 2010. However, we do not yet have an adequate way of monitoring progress towards achieving this target. Here we present a method for producing indices based on the IUCN Red List to chart the overall threat status (projected relative extinction risk) of all the world's bird species from 1988 to 2004. Red List Indices (RLIs) are based on the number of species in each Red List category, and on the number changing categories between assessments as a result of genuine improvement or deterioration in status. The RLI for all bird species shows that their overall threat status has continued to deteriorate since 1988. Disaggregated indices show that deteriorations have occurred worldwide and in all major ecosystems, but with particularly steep declines in the indices for Indo-Malayan birds (driven by intensifying deforestation of the Sundaic lowlands) and for albatrosses and petrels (driven by incidental mortality in commercial longline fisheries). RLIs complement indicators based on species population trends and habitat extent for quantifying global trends in the status of biodiversity. Their main weaknesses are that the resolution of status changes is fairly coarse and that delays may occur before some status changes are detected. Their greatest strength is that they are based on information from nearly all species in a taxonomic group worldwide, rather than a potentially biased subset. At present, suitable data are only available for birds, but indices for other taxonomic groups are in development, as is a sampled index based on a stratified sample from all major taxonomic groups

    Testing a global standard for quantifying species recovery and assessing conservation impact.

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    Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a "Green List of Species" (now the IUCN Green Status of Species). A draft Green Status framework for assessing species' progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species' viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species' recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard

    Optimizing Composite Sampling Protocols

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    Preventing species extinctions resulting from climate change

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    Recent studies show that current IUCN Red List assessment methods can identify species vulnerable to extinction because of climate change. But species must be assessed more completely and more regularly, and adaptation actions initiated swiftly once threatened species are identified

    Supplementary material for: Scaling range sizes to threats for robust predictions of risks to biodiversity

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    Supplementary material for: Scaling range sizes to threats for robust predictions of risks to biodiversity.<div><br></div><div><div>R code for estimating Area of Occupancy accounting for uncertainty in the location of grid origin. See the R package 'redlistr' for maintained version. https://cran.r-project.org/package=redlistr </div><div><br></div><div>Raster files of a simulated landscape with six distribution patterns (30 .tif files)</div><div><br></div><div>For further information see:</div></div><div><br></div><div>Keith, D. A., Akçakaya, H. R. and Murray, N. J. (2017), Scaling range sizes to threats for robust predictions of risks to biodiversity. Conservation Biology. doi:10.1111/cobi.12988<br></div><div><br></div
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