Making Consistent IUCN Classifications under Uncertainty

Abstract: The World Conservation Union (IUCN) defined a set of categories for conservation status supported by decision rules based on thresholds of parameters such as distributional range, population size, population history, and risk of extinction. These rules have received international acceptance and have become one of the most important decision tools in conservation biology because of their wide applicability, objectivity, and simplicity of use. The input data for these rules are often estimated with considerable uncertainty due to measurement error, natural variation, and vagueness in definitions of parameters used in the rules. Currently, no specific guidelines exist for dealing with uncertainty. Interpretation of uncertain data by different assessors may lead to inconsistent classifications because attitudes toward uncertainty and risk may have an important influence on the classification of threatened species. We propose a method of dealing with uncertainty that can be applied to the current IUCN criteria without altering the rules, thresholds, or intent of these criteria. Our method propagates the uncertainty in the input parameters and assigns the evaluated species either to a single category (as the current criteria do) or to a range of plausible categories, depending on the nature and extent of uncertainties.     

Impact of alternative metrics on estimates of extent of occurrence for extinction risk assessment

In International Union for Conservation of Nature (IUCN) Red List assessments, extent of occurrence (EOO) is a key measure of extinction risk. However, the way assessors estimate EOO from maps of species’ distributions is inconsistent among assessments of different species and among major taxonomic groups. Assessors often estimate EOO from the area of mapped distribution, but these maps often exclude areas that are not habitat in idiosyncratic ways and are not created at the same spatial resolutions. We assessed the impact on extinction risk categories of applying different methods (minimum convex polygon, alpha hull) for estimating EOO for 21,763 species of mammals, birds, and amphibians. Overall, the percentage of threatened species requiring down listing to a lower category of threat (taking into account other Red List criteria under which they qualified) spanned 11–13% for all species combined (14–15% for mammals, 7–8% for birds, and 12–15% for amphibians). These down listings resulted from larger estimates of EOO and depended on the EOO calculation method. Using birds as an example, we found that 14% of threatened and near threatened species could require down listing based on the minimum convex polygon (MCP) approach, an approach that is now recommended by IUCN. Other metrics (such as alpha hull) had marginally smaller impacts. Our results suggest that uniformly applying the MCP approach may lead to a one‐time down listing of hundreds of species but ultimately ensure consistency across assessments and realign the calculation of EOO with the theoretical basis on which the metric was founded.     

Effects of uncertainty and variability on population declines and IUCN Red List classifications

The International Union for Conservation of Nature (IUCN) Red List Categories and Criteria is a quantitative framework for classifying species according to extinction risk. Population models may be used to estimate extinction risk or population declines. Uncertainty and variability arise in threat classifications through measurement and process error in empirical data and uncertainty in the models used to estimate extinction risk and population declines. Furthermore, species traits are known to affect extinction risk. We investigated the effects of measurement and process error, model type, population growth rate, and age at first reproduction on the reliability of risk classifications based on projected population declines on IUCN Red List classifications. We used an age‐structured population model to simulate true population trajectories with different growth rates, reproductive ages and levels of variation, and subjected them to measurement error. We evaluated the ability of scalar and matrix models parameterized with these simulated time series to accurately capture the IUCN Red List classification generated with true population declines. Under all levels of measurement error tested and low process error, classifications were reasonably accurate; scalar and matrix models yielded roughly the same rate of misclassifications, but the distribution of errors differed; matrix models led to greater overestimation of extinction risk than underestimations; process error tended to contribute to misclassifications to a greater extent than measurement error; and more misclassifications occurred for fast, rather than slow, life histories. These results indicate that classifications of highly threatened taxa (i.e., taxa with low growth rates) under criterion A are more likely to be reliable than for less threatened taxa when assessed with population models. Greater scrutiny needs to be placed on data used to parameterize population models for species with high growth rates, particularly when available evidence indicates a potential transition to higher risk categories.     

Understanding the drivers of expert opinion when classifying species as extinct

The criteria as laid out by the International Union for the Conservation of Nature (IUCN) Red List are the gold standard by which the extinction risk of a species is assessed and where appropriate biological extinctions are declared. However, unlike all other categories, the category of extinct lacks a quantitative framework for assigning this category. Given its subjective nature, we surveyed expert assessors working on a diversity of taxa to explore the attributes they used to declare a species extinct. Using a choice experiment approach, we surveyed 674 experts from the IUCN Species Survival Commission specialist groups and taskforces. Data availability, time from the last sighting, detectability, habitat availability, and population decline were all important attributes favored by assessors when inferring extinction. Respondents with red-listing experience assigned more importance to the attributes data availability, time from the last sighting, and detectability when considering a species extinction, whereas those respondents working with well-known taxa gave more importance to the time from the last sighting. Respondents with no red-listing experience and those working with more well-known taxa (i.e., mammals and birds) were overall less likely to consider species extinct. Our findings on the importance assessors place on attributes used to declare a species extinct provide a basis for informing the development of specific criteria for more accurately assessing species extinctions.     

The Reliability of Using Population Viability Analysis for Risk Classification of Species

I examine whether or not it is appropriate to use extinction probabilities generated by population viability analyses, based on best estimates for model parameters, as criteria for listing species in Red Data Book categories as recently proposed by the World Conservation Union. Such extinction probabilities are influenced by how accurately model parameters are estimated and by how accurately the models depict actual population dynamics. I evaluate the effect of uncertainty in parameter estimation through simulations. Simulations based on Steller sea lions were used to evaluate bias and precision in estimates of probability of extinction and to consider the performance of two proposed classification schemes. Extinction time estimates were biased (because of violation of the assumption of stable age distribution) and underestimated the variability of probability of extinction for a given time (primarily because of uncertainty in parameter estimation). Bias and precision in extinction probabilities are important when these probabilities are used to compare the risk of extinction between species. Suggestions are given for population viability analysis techniques that incorporate parameter uncertainty. I conclude that testing classification schemes with simulations using quantitative performance objectives should precede adoption of quantitative listing criteria.     

Evaluation of Biogeographic Classification Schemes for Conservation Planning: Application to New Zealand's Coastal Marine Environment

Abstract:  For many regions worldwide, multiple and often contrasting biogeographic classifications exist that are derived from a variety of taxa and techniques. This presents a challenge for managers who must choose appropriate large-scale spatial frameworks for systematic conservation planning. We demonstrate how systematically collected community data can be used to evaluate existing biogeographic classifications, identify the most appropriate metric for biogeographic patterns seen in other taxonomic groups, and develop an independent biogeographic classification scheme for systematic conservation planning. We evaluated 6 existing biogeographic classifications for New Zealand's nearshore marine environment with community-similarity metrics derived from abundance and presence–absence data for macroalgae (107 species) and mobile macroinvertebrates (44 species). The concordance between community metrics and the previous classifications was high, as indicated by a high multivariate classification success (CS) (74.3–98.3%). Subsequently, we carried out an independent classification analysis on each community metric to identify biogeographic units within a hierarchical spatial framework. The classification derived from macroalgal presence–absence data achieved the highest CS and could be used as a mesoscale classification scheme in which 11 regional groupings (i.e., bioregions) (CS = 73.8–84.8%) are nested within northern and southern biogeographic provinces (CS = 90.3–98.7%). These techniques can be used in systematic conservation planning to inform the design of representative and comprehensive networks of marine protected areas through evaluation of the current coverage of marine reserves in each bioregion. Currently, 0.22% of the territorial sea around mainland New Zealand is protected in no-take marine protected areas in which 0–1.5% of each bioregion represented.     

Climate Change, Elevational Range Shifts, and Bird Extinctions

Abstract:  Limitations imposed on species ranges by the climatic, ecological, and physiological effects of elevation are important determinants of extinction risk. We modeled the effects of elevational limits on the extinction risk of landbirds, 87% of all bird species. Elevational limitation of range size explained 97% of the variation in the probability of being in a World Conservation Union category of extinction risk. Our model that combined elevational ranges, four Millennium Assessment habitat-loss scenarios, and an intermediate estimate of surface warming of 2.8° C, projected a best guess of 400–550 landbird extinctions, and that approximately 2150 additional species would be at risk of extinction by 2100. For Western Hemisphere landbirds, intermediate extinction estimates based on climate-induced changes in actual distributions ranged from 1.3% (1.1° C warming) to 30.0% (6.4° C warming) of these species. Worldwide, every degree of warming projected a nonlinear increase in bird extinctions of about 100–500 species. Only 21% of the species predicted to become extinct in our scenarios are currently considered threatened with extinction. Different habitat-loss and surface-warming scenarios predicted substantially different futures for landbird species. To improve the precision of climate-induced extinction estimates, there is an urgent need for high-resolution measurements of shifts in the elevational ranges of species. Given the accelerating influence of climate change on species distributions and conservation, using elevational limits in a tested, standardized, and robust manner can improve conservation assessments of terrestrial species and will help identify species that are most vulnerable to global climate change. Our climate-induced extinction estimates are broadly similar to those of bird species at risk from other factors, but these estimates largely involve different sets of species.     

Variability in Population Abundance and the Classification of Extinction Risk

Abstract: Classifying species according to their risk of extinction is a common practice and underpins much conservation activity. The reliability of such classifications rests on the accuracy of threat categorizations, but very little is known about the magnitude and types of errors that might be expected. The process of risk classification involves combining information from many sources, and understanding the quality of each source is critical to evaluating the overall status of the species. One common criterion used to classify extinction risk is a decline in abundance. Because abundance is a direct measure of conservation status, counts of individuals are generally the preferred method of evaluating whether populations are declining. Using the thresholds from criterion A of the International Union for Conservation of Nature (IUCN) Red List (critically endangered, decline in abundance of >80% over 10 years or 3 generations; endangered, decline in abundance of 50–80%; vulnerable, decline in abundance of 30–50%; least concern or near threatened, decline in abundance of 0–30%), we assessed 3 methods used to detect declines solely from estimates of abundance: use of just 2 estimates of abundance; use of linear regression on a time series of abundance; and use of state‐space models on a time series of abundance. We generated simulation data from empirical estimates of the typical variability in abundance and assessed the 3 methods for classification errors. The estimates of the proportion of falsely detected declines for linear regression and the state‐space models were low (maximum 3–14%), but 33–75% of small declines (30–50% over 15 years) were not detected. Ignoring uncertainty in estimates of abundance (with just 2 estimates of abundance) allowed more power to detect small declines (95%), but there was a high percentage (50%) of false detections. For all 3 methods, the proportion of declines estimated to be >80% was higher than the true proportion. Use of abundance data to detect species at risk of extinction may either fail to detect initial declines in abundance or have a high error rate.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.     

Correlations among Extinction Risks Assessed by Different Systems of Threatened Species Categorization

Abstract:  Many different systems are used to assess levels of threat faced by species. Prominent ones are those used by the World Conservation Union, NatureServe, and the Florida Game and Freshwater Fish Commission (now the Florida Fish and Wildlife Conservation Commission). These systems assign taxa a threat ranking by assessing their demographic and ecological characteristics. These threat rankings support the legislative protection of species and guide the placement of conservation programs in order of priority. It is not known, however, whether these assessment systems rank species in a similar order. To resolve this issue, we assessed 55 mainly vertebrate taxa with widely differing life histories under each of these systems and determined the rank correlations among them. Moderate, significant positive correlations were seen among the threat rankings provided by the three systems (correlations 0.58–0.69). Further, the threat rankings for taxa obtained using these systems were significantly correlated to their rankings based on predicted probability of extinction within 100 years as determined by population viability analysis (correlations 0.28–0.37). The different categorization systems, then, yield related but not identical threat rankings, and these rankings are associated with predicted extinction risk.     

Applying habitat and population-density models to land-cover time series to inform IUCN Red List assessments

The IUCN (International Union for Conservation of Nature) Red List categories and criteria are the most widely used framework for assessing the relative extinction risk of species. The criteria are based on quantitative thresholds relating to the size, trends, and structure of species’ distributions and populations. However, data on these parameters are sparse and uncertain for many species and unavailable for others, potentially leading to their misclassification or classification as data deficient. We devised an approach that combines data on land-cover change, species-specific habitat preferences, population abundance, and dispersal distance to estimate key parameters (extent of occurrence, maximum area of occupancy, population size and trend, and degree of fragmentation) and hence predict IUCN Red List categories for species. We applied our approach to nonpelagic birds and terrestrial mammals globally (∼15,000 species). The predicted categories were fairly consistent with published IUCN Red List assessments, but more optimistic overall. We predicted 4.2% of species (467 birds and 143 mammals) to be more threatened than currently assessed and 20.2% of data deficient species (10 birds and 114 mammals) to be at risk of extinction. Incorporating the habitat fragmentation subcriterion reduced these predictions 1.5–2.3% and 6.4–14.9% (depending on the quantitative definition of fragmentation) for threatened and data deficient species, respectively, highlighting the need for improved guidance for IUCN Red List assessors on the application of this aspect of the IUCN Red List criteria. Our approach complements traditional methods of estimating parameters for IUCN Red List assessments. Furthermore, it readily provides an early-warning system to identify species potentially warranting changes in their extinction-risk category based on periodic updates of land-cover information. Given our method relies on optimistic assumptions about species distribution and abundance, all species predicted to be more at risk than currently evaluated should be prioritized for reassessment.     

Assessing the Threat Status of Ecological Communities

Abstract: Conservationists are increasingly interested in determining the threat status of ecological communities as a key part of their planning efforts. Such assessments are difficult because of conceptual challenges and a lack of generally accepted criteria. We reviewed 12 protocols for assessing the threat status of communities and identified conceptual and operational issues associated with developing a rigorous, transparent, and universal set of criteria for assessing communities, analogous to the International Union for Conservation of Nature (IUCN) Red List standards for species. We examined how each protocol defines a community and its extinction and how each applies 3 overarching criteria: decline in geographic distribution, restricted geographic distribution, and changes to ecological function. The protocols vary widely in threshold values used to assess declines and distribution size and the time frames used to assess declines, leading to inconsistent assessments of threat status. Few of the protocols specify a scale for measuring distribution size, although assessment outcomes are highly sensitive to scale. Protocols that apply different thresholds for species versus communities tend to require greater declines and more restricted distributions for communities than species to be listed in equivalent threat categories. Eleven of the protocols include a reduction in ecological function as a criterion, but almost all assess it qualitatively rather than quantitatively. We argue that criteria should be explicit and repeatable in their concepts, parameters, and scale, applicable to a broad range of communities, and address synergies between types of threats. Such criteria should focus on distribution size, declines in distribution, and changes to key ecological functions, with the latter based on workable proxies for assessing the severity, scope, and immediacy of degradation. Threat categories should be delimited by thresholds that are assessed at standard scales and are logically consistent with the viability of component species and important ecological functions.     

Modeling biodiversity dynamics in countryside landscapes

The future of biodiversity hinges to a great extent on the conservation value of countryside, the growing fraction of Earth's surface heavily influenced by human activities. How many species, and which species, can persist in such landscapes (and analogous seascapes) are open questions. Here we explore two complementary theoretical frameworks to address these questions: species-area relationships and demographic models. We use the terrestrial mammal fauna of Central America to illustrate the application of both frameworks. We begin by proposing a multi-habitat species-area relationship, the countryside species-area relationship, to forecast species extinction rates. To apply it, we classify the mammal fauna by affinity to native and human-dominated habitats. We show how considering the conservation value of countryside habitats changes estimates derived from the classic species-area approach We also examine how the z value of the species-area relationship affects extinction estimates. Next, we present a framework for assessing the relative vulnerability of species to extinction in the countryside, based on the Skellam model of population dynamics. This model predicts the minimum area of contiguous native habitat required for persistence of a species, which we use as an indicator of vulnerability to habitat change. To apply the model, we use our habitat affinity classification of mammals and we estimate life-history parameters by species and habitat type. The resulting ranking of vulnerabilities is significantly correlated with the World Conservation Union (IUCN) Red List assessment.     

Multinomial mixture model with heterogeneous classification probabilities

Royle and Link (Ecology 86(9):2505?C2512, 2005) proposed an analytical method that allowed estimation of multinomial distribution parameters and classification probabilities from categorical data measured with error. While useful, we demonstrate algebraically and by simulations that this method yields biased multinomial parameter estimates when the probabilities of correct category classifications vary among sampling units. We address this shortcoming by treating these probabilities as logit-normal random variables within a Bayesian framework. We use Markov chain Monte Carlo to compute Bayes estimates from a simulated sample from the posterior distribution. Based on simulations, this elaborated Royle-Link model yields nearly unbiased estimates of multinomial and correct classification probability estimates when classification probabilities are allowed to vary according to the normal distribution on the logit scale or according to the Beta distribution. The method is illustrated using categorical submersed aquatic vegetation data.     

Rates of Movement of Threatened Bird Species between IUCN Red List Categories and toward Extinction

Abstract:  In recent centuries bird species have been deteriorating in status and becoming extinct at a rate that may be 2–3 orders of magnitude higher than in prehuman times. We examined extinction rates of bird species designated critically endangered in 1994 and the rate at which species have moved through the IUCN (World Conservation Union) Red List categories of extinction risk globally for the period 1988–2004 and regionally in Australia from 1750 to 2000. For Australia we drew on historical accounts of the extent and condition of species habitats, spread of invasive species, and changes in sighting frequencies. These data sets permitted comparison of observed rates of movement through the IUCN Red List categories with novel predictions based on the IUCN Red List criterion E, which relates to explicit extinction probabilities determined, for example, by population viability analysis. The comparison also tested whether species listed on the basis of other criteria face a similar probability of moving to a higher threat category as those listed under criterion E. For the rate at which species moved from vulnerable to endangered, there was a good match between observations and predictions, both worldwide and in Australia. Nevertheless, species have become extinct at a rate that, although historically high, is 2 (Australia) to 10 (globally) times lower than predicted. Although the extinction probability associated with the critically endangered category may be too high, the shortfall in realized extinctions can also be attributed to the beneficial impact of conservation intervention. These efforts may have reduced the number of global extinctions from 19 to 3 and substantially slowed the extinction trajectory of 33 additional critically endangered species. Our results suggest that current conservation action benefits species on the brink of extinction, but is less targeted at or has less effect on moderately threatened species.     

Establishing IUCN Red List Criteria for Threatened Ecosystems

Abstract: The potential for conservation of individual species has been greatly advanced by the International Union for Conservation of Nature's (IUCN) development of objective, repeatable, and transparent criteria for assessing extinction risk that explicitly separate risk assessment from priority setting. At the IV World Conservation Congress in 2008, the process began to develop and implement comparable global standards for ecosystems. A working group established by the IUCN has begun formulating a system of quantitative categories and criteria, analogous to those used for species, for assigning levels of threat to ecosystems at local, regional, and global levels. A final system will require definitions of ecosystems; quantification of ecosystem status; identification of the stages of degradation and loss of ecosystems; proxy measures of risk (criteria); classification thresholds for these criteria; and standardized methods for performing assessments. The system will need to reflect the degree and rate of change in an ecosystem's extent, composition, structure, and function, and have its conceptual roots in ecological theory and empirical research. On the basis of these requirements and the hypothesis that ecosystem risk is a function of the risk of its component species, we propose a set of four criteria: recent declines in distribution or ecological function, historical total loss in distribution or ecological function, small distribution combined with decline, or very small distribution. Most work has focused on terrestrial ecosystems, but comparable thresholds and criteria for freshwater and marine ecosystems are also needed. These are the first steps in an international consultation process that will lead to a unified proposal to be presented at the next World Conservation Congress in 2012.     

The Threat of Disease Increases as Species Move Toward Extinction

At local scales, infectious disease is a common driver of population declines, but globally it is an infrequent contributor to species extinction and endangerment. For species at risk of extinction from disease important questions remain unanswered, including when does disease become a threat to species and does it co‐occur, predictably, with other threats? Using newly compiled data from the International Union for Conservation of Nature (IUCN) Red List, we examined the relative role and co‐occurrence of threats associated with amphibians, birds, and mammals at 6 levels of extinction risk (i.e., Red List status categories: least concern, near threatened, vulnerable, endangered, critically endangered, and extinct in the wild/extinct). We tested the null hypothesis that the proportion of species threatened by disease is the same in all 6 Red List status categories. Our approach revealed a new method for determining when disease most frequently threatens species at risk of extinction. The proportion of species threatened by disease varied significantly between IUCN status categories and linearly increased for amphibians, birds, and all species combined as these taxa move from move from least concern to critically endangered. Disease was infrequently the single contributing threat. However, when a species was negatively affected by a major threat other than disease (e.g., invasive species, land‐use change) that species was more likely to be simultaneously threatened by disease than species that had no other threats. Potential drivers of these trends include ecological factors, clustering of phylogenetically related species in Red List status categories, discovery bias among species at greater risk of extinction, and availability of data. We echo earlier calls for baseline data on the presence of parasites and pathogens in species when they show the first signs of extinction risk and arguably before. La Amenaza de Enfermedades Incrementa a Medida que las Especies se Aproximan a la Extinción     

Optimization of capture–recapture monitoring of elusive species illustrated with a threatened grasshopper

Information on population sizes and trends of threatened species is essential for their conservation, but obtaining reliable estimates can be challenging. We devised a method to improve the precision of estimates of population size obtained from capture–recapture studies for species with low capture and recapture probabilities and short seasonal activity, illustrated with population data of an elusive grasshopper (Prionotropis rhodanica). We used data from 5 capture–recapture studies to identify methodological and environmental factors affecting capture and recapture probabilities and estimates of population size. In a simulation, we used the population size and capture and recapture probability estimates obtained from the field studies to identify the minimum number of sampling occasions needed to obtain unbiased and robust estimates of population size. Based on these results we optimized the capture–recapture design, implemented it in 2 additional studies, and compared their precision with those of the nonoptimized studies. Additionally, we simulated scenarios based on thresholds of population size in criteria C and D of the International Union for Conservation of Nature (IUCN) Red List to investigate whether estimates of population size for elusive species can reliably inform red-list assessments. Identifying parameters that affect capture and recapture probabilities (for the grasshopper time since emergence of first adults) and optimizing field protocols based on this information reduced study effort (−6% to −27% sampling occasions) and provided more precise estimates of population size (reduced coefficient of variation) compared with nonoptimized studies. Estimates of population size from the scenarios based on the IUCN thresholds were mostly unbiased and robust (only the combination of very small populations and little study effort produced unreliable estimates), suggesting capture–recapture can be considered reliable for informing red-list assessments. Although capture–recapture remains difficult and costly for elusive species, our optimization procedure can help determine efficient protocols to increase data quality and minimize monitoring effort.     

Regional IUCN Red Listing: the Process as Applied to Birds in the United Kingdom

Abstract:  The World Conservation Union (IUCN) has developed guidelines that enable the assessment of extinction risk at a regional scale. We used these guidelines to assess the extinction risk of birds in the United Kingdom for comparison with an existing assessment of conservation status. Sixty-four species were categorized as regionally threatened, of which 12 were critically endangered. The categorizations of the 223 species assessed agreed broadly with those from the existing U.K. system, which considers more than extinction risk, thus giving a more complete assessment of conservation status. There was, however, a tendency for the IUCN process to give higher risk status to edge-of-range species (some of which are relatively recent colonists considered of comparatively low conservation concern) and low status to those that have declined substantially but remain common (such as many farmland birds, the focus of considerable conservation effort in the United Kingdom). The final red list depended heavily on the subjective decisions made during the assessment process. An alternative interpretation of the guidelines could have resulted in as many as 19 or as few as 6 species being listed as critically endangered. We recommend the revision of the IUCN guidelines to reduce this subjectivity, in particular with respect to the effect of extralimital populations on the likelihood of regional extinction, and hence the potential for variation in the manner of application between regional red-list assessors. Preventing extinction does not have to be the principal driving force behind conservation action at a regional scale if the continuance of a species is safeguarded in other regions.     

A GIS-Based Comparison of the Mexican National and IUCN Methods for Determining Extinction Risk

Abstract:  The national systems used in the evaluation of extinction risk are often touted as more readily applied and somehow more regionally appropriate than the system of the International Union for Conservation of Nature (IUCN). We compared risk assessments of the Mexican national system (method for evaluation of risk of extinction of wild species [MER]) with the IUCN system for the 16 Polianthes taxa (Agavaceae), a genus of plants with marked variation in distribution sizes. We used a novel combination of herbarium data, geographic information systems (GIS), and species distribution models to provide rapid, repeatable estimates of extinction risk. Our GIS method showed that the MER and the IUCN system use similar data. Our comparison illustrates how the IUCN method can be applied even when all desirable data are not available, and that the MER offers no special regional advantage with respect to the IUCN regional system. Instead, our results coincided, with both systems identifying 14 taxa of conservation concern and the remaining two taxa of low risk, largely because both systems use similar information. An obstacle for the application of the MER is that there are no standards for quantifying the criteria of habitat condition and intrinsic biological vulnerability. If these impossible-to-quantify criteria are left out, what are left are geographical distribution and the impact of human activity, essentially the considerations we were able to assess for the IUCN method. Our method has the advantage of making the IUCN criteria easy to apply, and because each step can be standardized between studies, it ensures greater comparability of extinction risk estimates among taxa.