Predict Extinction Risk Research Articles

Consistent Ecological Selectivity through Time in Pacific Island Avian Extinctions

Understanding the ecological mechanisms that lead to extinction is a central goal of conservation. Can understanding ancient avian extinctions help to predict extinction risk in modern birds? I used classification trees trained on both paleoecological and historical data from islands across the Pacific to determine the ecological traits associated with extinction risk. Intrinsic traits, including endemism, large body size, and certain feeding guilds, were tightly linked with avian extinction over the past 3500 years. Species ecology and phylogeny were better predictors of extinction risk through time than extrinsic or abiotic factors. Although human impacts on birds and their habitats have changed over time, modern endangered birds share many of the same ecological characteristics as victims of previous extinction waves. My use of detailed predictions of extinction risk to identify species potentially in need of conservation attention demonstrates the utility of paleoecological knowledge for modern conservation biology.

The diffusion approximation overestimates the extinction risk for count‐based PVA

AbstractSimple population models are increasingly being used to predict extinction risk using historical abundance estimates. A very simple model, the stochastic exponential growth (SEG) model, is surprisingly robust. Extinction risk is commonly computed for this model using a mathematical approximation (the “diffusion approximation”) that assumes continuous breeding throughout the year, an assumption that is violated by many species. Here I show that, for an organism with seasonal breeding, the diffusion approximation systematically overestimates the extinction risk. I demonstrate the conditions generating large bias (high environmental variance, intermediate extinction risk), and reanalyze 100 populations of conservation concern. Analyzing several policy applications, I find that the bias may be most important when classifying the risk status of species. The SEG model is still sound, but associated risk estimates should be calculated by performing stochastic simulations (as with all other population viability models) rather than by evaluating the diffusion approximation.

Multiple ecological pathways to extinction in mammals

As human population and resource demands continue to grow, biodiversity conservation has never been more critical. About one-quarter of all mammals are in danger of extinction, and more than half of all mammal populations are in decline. A major priority for conservation science is to understand the ecological traits that predict extinction risk and the interactions among those predictors that make certain species more vulnerable than others. Here, using a new database of nearly 4,500 mammal species, we use decision-tree models to quantify the multiple interacting factors associated with extinction risk. We show that the correlates of extinction risk vary widely across mammals and that there are unique pathways to extinction for species with different lifestyles and combinations of traits. We find that risk is relative and that all kinds of mammals, across all body sizes, can be at risk depending on their specific ecologies. Our results increase the understanding of extinction processes, generate simple rules of thumb that identify species at greatest risk, and highlight the potential of decision-tree analyses to inform conservation efforts.

Extinction risks from climate change: macroecological and historical insights

Human-induced climate change may threaten a large proportion of Earth's biota, but the uncertainties involved in projecting the future geographical distributions of species make quantitative predictions of extinction risk difficult to make. I discuss how insight from recent advances in macroecology and knowledge about species responses to past climate change can help predict extinction risks more accurately.

Use of Basic Biological Information for Rapid Prediction of the Response of Species to Habitat Loss

Much research has focused on identifying traits that can act as useful indicators of how habitat loss affects the extinction risk of species, and the results are mixed. We developed 2 simple, rapid-assessment models of the susceptibility of species to habitat loss. We based both on an index of range size, but one also incorporated an index of body mass and the other an index combining habitat and dietary specialization. We applied the models to samples of birds (Accipitridae and Bucerotidae) and to the lemurs of Madagascar and compared the models' classifications of risk with the IUCN's global threat status of each species. The model derived from ecological attributes was much more robust than the one derived from body mass. Ecological attributes identified threatened birds and lemurs with an average of 80% accuracy and endangered and critically endangered species with 100% accuracy and identified some species not currently listed as threatened that almost certainly warrant conservation consideration. Appropriate analysis of even fairly crude biological information can help raise early-warning flags to the relative susceptibilities of species to habitat loss and thus provide a useful and rapid technique for highlighting potential species-level conservation issues. Advantages of this approach to classifying risk include flexibility in the specialization parameters used as well as its applicability at a range of spatial scales.

The use of ecological traits in extinction risk assessments: A case study on geometrid moths

Identifying ecological traits that make some species more vulnerable than others is vital for predictive conservation science. By identifying these predisposing traits we can predict which species are most prone to decline and gain an understanding of the reasons behind the decline. The aim of this study was to determine the ecological traits that best predict extinction risk and distribution change in Finnish geometrid moths and to develop an understanding of the biological connections between these traits and threats. We found that larval specificity, overwintering stage and flight period length predicted distribution change and extinction risk. There was also an interaction effect between larval specificity and body size on both distribution change and extinction risk. In monophagous species the host plant distribution predicted extinction risk. Even though ecological traits are known to be important determinants of extinction risk, the IUCN red list categorization system is exclusively based on quantitative measures of populations and ignores the ecological traits. Here, we propose that taxon specific ecological data should also be used to predict extinction risk at least on a regional scale to improve the accuracy of the IUCN extinction risk classification.

Examining the extinction risk of specialized folivores: a comparative study of Colobine monkeys

Species extinctions are nonrandom with some taxa appearing to possess traits that increase their extinction risk. In this study, eight predictors of extinction risk were used as independent variables to predict the IUCN category of a subfamily of specialized folivorous primates, the Colobinae. All data were transformed into phylogenetically independent contrasts and were analyzed using bivariate regressions, multiple regression, and a maximum likelihood approach using Akaike's Information Criterion to assess model performance. Once an outlier was removed from the data set, species that devote a smaller proportion of their diet to mature leaf consumption appear to be at a greater risk of extinction. Also, as female body mass increases, so does extinction risk. In contrast, as maximum latitude and the number of habitat types increase, extinction risk appears to decrease. These findings emphasize the importance of examining detailed dietary variation for predicting extinction risk at a relatively fine taxonomic scale and, consequently, may help improve conservation management.

Doomed to die? Predicting extinction risk in the true hawks Accipitridae

AbstractOne of the most important tasks in conservation biology is identifying species at risk from extinction and establishing the most likely factors influencing this risk. Here, we consider an ecologically well‐defined, monophyletic group of organisms, the true hawks of the family Accipitridae, which are not only among the most studied, but also contain some of the rarest bird species in the world. We investigate which intrinsic and extrinsic factors, covering morphology, life history and ecology, covary with International Union for the Conservation of Nature and Natural Resources threat status, as well as global population size and geographic range size. By decomposing threat status into population size and range size, we test whether any factors are generally important: we found that species with less habitat specialization, a larger clutch size and more plumage polymorphism were associated with lower extinction risk and larger population and range sizes. Species with special habitat requirements might be less capable of dealing with habitat transformation and fragmentation, while species with small clutch sizes might not be able to reverse population declines. Plumage polymorphism might indicate the size of the species' gene pool and could be a good marker of extinction risk. The analyses also emphasized that no single factor is likely to be sufficient when predicting the threat of extinction.

Predicting extinction risk of butterflies and moths (Macrolepidoptera) from distribution patterns and species characteristics

An extensive follow-up study of day- and night-active Macrolepidoptera was performed during 2004 at the Kullaberg Nature Reserve located in the south-western part of Sweden. Butterflies were surveyed in an area of 100 km2 and night-active moths were trapped in the core area of the reserve. Macrolepidopteran species resident in the area in the 1950s were compared with species resident in the area in 2004. As much as 159 of 597 species (27%) resident in the area in 1950s were not found at all in 2004 and 22 species (4%) had colonised the area. Butterflies exhibited a disastrous decline with a loss of 45% of the fauna, and day-active species had declined more than night-active species had. Species distribution pattern and species characteristics were used to predict the probability that a species had become extinct or colonised the area. Species limited to one or a few food plants, with a short flight-period or restricted to non-forest habitats were all associated with a high extinction risk. Species occurring in fewer European countries and recorded from few provinces in Sweden were all associated with a higher extinction risk compared with ubiquitous species. For expanding species (colonisers), the best predictor was their distribution area in Sweden and colonising species were more likely to be limited to a few provinces in the southernmost part of Sweden. Species extinct from Kullaberg also have decreased in Finland and species that had colonised Kullaberg also have increased in Finland, while the species with no change in Kullaberg are also relatively constant in Finland. Indeed, the macrolepidopteran fauna was severely reduced in the last 50 years and almost 70% of the habitat specialists were lost. For red-listed species the situation was found to be alarming. Almost 70% of red-listed species, resident in the area in the 1950s, was not found in 2004. This study highlights that species composition changes rapidly even in protected nature reserves and that similar changes in the macrolepidopteran fauna seem to occur over large areas.

Successful reintroductions of the endangered long-lived Sargent’s cherry palm, Pseudophoenix sargentii, in the Florida Keys

The 1991–1994 reintroductions of Florida endangered Pseudophoenix sargentii to 13 Florida Keys sites represent a rare example of a successful multi-agency long-term effort to conserve a long-lived palm. To assess reintroduction success, we compared population demographics with and without reintroduced plants and conducted population viability analyses. Since 1991, the wild population has increased 6.4-fold. Survival from 2000–2004 was 94%, growth was positive ( λ = 1.013), and there was no predicted extinction risk. Recent wild population growth is attributed to good seedling recruitment and removing the greatest threats. After 14 years, reintroductions had 43% survival, increased total plants in the wild by 27%, and expanded the species’ distribution. Reintroduced plants had faster maturation rates, improved population age structure, and enhanced population growth ( λ = 1.032). Success varied with transplant year, location, microsite, and original transplant size. Failures in 1991 and at some historic sites emphasize the need for a multi-year, multi-site approach to reintroductions to buffer against stochastic losses. Rockland hammocks and the tops of coastal berms had greatest plant growth and survival. Large transplants had the greatest survival. Because no reintroduced plants are reproductive, transitions between stages are extremely slow, and plants may require >30 years to mature, continued institutional dedication to long-term monitoring will be required to assess whether the populations are self-sustaining. Horticultural expertise and ex situ collections complimented support of land managing agencies for the species’ preservation. These first rare plant reintroductions to Florida State Parks opened avenues for more plant conservation efforts and public interpretation.

Forecasting Extinction Risk With Nonstationary Matrix Models

Matrix population growth models are standard tools for forecasting population change and for managing rare species, but they are less useful for predicting extinction risk in the face of changing environmental conditions. Deterministic models provide point estimates of lambda, the finite rate of increase, as well as measures of matrix sensitivity and elasticity. Stationary matrix models can be used to estimate extinction risk in a variable environment, but they assume that the matrix elements are randomly sampled from a stationary (i.e., non-changing) distribution. Here we outline a method for using nonstationary matrix models to construct realistic forecasts of population fluctuation in changing environments. Our method requires three pieces of data: (1) field estimates of transition matrix elements, (2) experimental data on the demographic responses of populations to altered environmental conditions, and (3) forecasting data on environmental drivers. These three pieces of data are combined to generate a series of sequential transition matrices that emulate a pattern of long-term change in environmental drivers. Realistic estimates of population persistence and extinction risk can be derived from stochastic permutations of such a model. We illustrate the steps of this analysis with data from two populations of Sarracenia purpurea growing in northern New England. Sarracenia purpurea is a perennial carnivorous plant that is potentially at risk of local extinction because of increased nitrogen deposition. Long-term monitoring records or models of environmental change can be used to generate time series of driver variables under different scenarios of changing environments. Both manipulative and natural experiments can be used to construct a linking function that describes how matrix parameters change as a function of the environmental driver. This synthetic modeling approach provides quantitative estimates of extinction probability that have an explicit mechanistic basis.

Correlates of extinction risk and hunting pressure in gamebirds (Galliformes)

The 284 species of Galliformes are a highly threatened group of birds subject to direct exploitation for food, sport and cultural practices. The impact of hunting is often assumed to contribute to the high percentage of species (26.4%) listed as threatened with extinction in the IUCN Red List. We take a macroecological approach to examine the anthropogenic and ecological correlates of extinction risk and hunting pressure using linear and stepwise regression. Independent contrasts are analysed, as well as raw species data, to control for the potential confounding influence of phylogenetic trends. Extinction risk is found to be predicted both by the ecological factors considered (e.g., latitudinal range, body mass, elevational range, habitat use) and secondarily by human factors (e.g., human population density, total calorie intake, composition of diet). Hunting pressure itself is also predicted well for the threatened species by several of the anthropogenic and ecological variables. The study demonstrates that human variables can be used successfully to predict extinction risk, and represent an improvement upon methods which examine ecological variables alone. Furthermore, we show that individual threats can be explored using similar techniques, providing a more detailed insight into the processes leading to extinction. As applied to the Galliformes, both approaches provide evidence supporting the hypothesis that hunting pressure has contributed to the high proportion of threatened species in this group, and thus reinforce the case for urgent measures to reduce the impacts of direct exploitation upon these birds.

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.

Macroecology, geographic range size–body size relationship and minimum viable population analysis for new world carnivora

Abstract Macroecology deals with variation and covariation of complex variables, such as body size, population density and geographic range size (GRS), measured across species at broad spatial scales. Despite the increasing number of papers in this field, little attention has been given to the links between patterns at different scales. In this paper, we analysed the constraint envelope formed by the macroecological relationship between GRS and body size for 70 species of New World terrestrial Carnivora. The lower-right constraint line of this envelope is usually interpreted as the minimum viable GRS that keeps extinction risks relatively low across evolutionary time, and in this paper we fitted this line by multiplying average home range size (established by allometric equations) by different minimum viable population sizes, establishing a minimum viable GRS. Then we estimated the difference between actual geographical range size and minimum viable geographical range size, in log scale (Δ A ), which indicates how large is the geographic range of a species in relation to the minimum necessary to its long-term persistence. These Δ A values are significantly correlated with extinction risk defined by IUCN threat categories, even after keeping geographical range size constant and after taking into account phylogenetic structure in data. This gives support to the minimum viable population model explaining the relationship between GRS and body size and highlights a way to use constraint envelopes to evaluate the influence of complex variables to predict extinction risks.

USE OF POPULATION VIABILITY ANALYSIS TO IDENTIFY MANAGEMENT PRIORITIES AND SUCCESS IN REINTRODUCING PRZEWALSKI'S HORSES TO SOUTHWESTERN MONGOLIA

The Przewalski's horse (Equus caballus przewalskii) became extinct in the wild in the 1960s. Since 1997, captive-bred horses have been released into the Gobi-B Strictly Protected Area (SPA) in southwestern Mongolia, and successful reproduction in the wild started in 1999. In 2002, the population formed 3 harem groups and 1 bachelor group (total 38) in the wild, and 3 harem groups (24) awaited release in summer 2003 within acclimatization enclosures, totaling 62 individuals. We used the stochastic population simulation model VORTEX to (1) identify key variables and their threshold values in population dynamics, (2) predict extinction risk, and (3) optimize project management and release regime by comparing model parameters with our population data. Maximum age of reproduction, foal mortality, and fecundity rates were key factors in population dynamics, while number of released animals, release interval, and duration of supplementation played lesser roles. The severity level of natural catastrophes had the greatest influence on extinction risk and population size according to VORTEX. Assuming a maximum reproductive age of 16 years, an initial population of >140 horses is necessary to achieve a 95% probability of survival over 100 years under the low-severity level of catastrophes scenario. The corresponding extinction risk for high-severity level of catastrophes is 37%, even for initial population sizes >500. The low natural growth rate of the Przewalski's horse may have been the essential prerequisite for extinction in this remote area of Mongolia. However, uncertainty of results was high and limits the predictive value of the model. Comparisons between model parameters with observed population characteristics over the past 10 years reveal some discrepancies that may require readjustment of the model if present trends continue. While our model currently underestimates reproductive rate and foal survival, adult mortality tends to be higher than estimated in the model. We believe that adult survival can be improved in the wild and that the reintroduction program has a realistic chance of success. We stress the importance of an intensive monitoring program of the Przewalski's horse population and consecutive modeling exercises to reevaluate success of this reintroduction program.

Human population density and extinction risk in the world's carnivores.

Understanding why some species are at high risk of extinction, while others remain relatively safe, is central to the development of a predictive conservation science. Recent studies have shown that a species' extinction risk may be determined by two types of factors: intrinsic biological traits and exposure to external anthropogenic threats. However, little is known about the relative and interacting effects of intrinsic and external variables on extinction risk. Using phylogenetic comparative methods, we show that extinction risk in the mammal order Carnivora is predicted more strongly by biology than exposure to high-density human populations. However, biology interacts with human population density to determine extinction risk: biological traits explain 80% of variation in risk for carnivore species with high levels of exposure to human populations, compared to 45% for carnivores generally. The results suggest that biology will become a more critical determinant of risk as human populations expand. We demonstrate how a model predicting extinction risk from biology can be combined with projected human population density to identify species likely to move most rapidly towards extinction by the year 2030. African viverrid species are particularly likely to become threatened, even though most are currently considered relatively safe. We suggest that a preemptive approach to species conservation is needed to identify and protect species that may not be threatened at present but may become so in the near future.

Scale Dependency of Rarity, Extinction Risk, and Conservation Priority

Abstract: In developing red data books of threatened species, the World Conservation Union uses measures of rarity, rates of decline, and population fragmentation to categorize species according to their risk of extinction. However, most quantitative measures of these three concepts are sensitive to the scale at which they are made. In particular, definitions of rarity based on an area‐of‐occupancy threshold can nearly always be met if area of occupancy is calculated from a sufficiently fine‐scale (high‐resolution) grid. Recommendations for dealing with scale dependency include (1) choosing a standard scale of measurement, (2) using multiple scales of measurement, and (3) developing indices that combine information from multiple scales. As an example of the second and third approach, the construction of a species' scale‐area curve represents a unifying method for quantifying all three indicators of extinction risk—rarity, rate of decline, and population fragmentation—as functions of area of occupancy and measurement scale. A multiscale analysis is also of practical importance because measurements made at different scales are relevant to different extinction processes. Coarse‐scale measures of rarity are most appropriate when threat is assessed on the basis of spatially autocorrelated events of a large extent, such as global climate change, whereas fine‐scale measures may best predict extinction risk due to local processes such as demographic stochasticity. We illustrate our arguments with a case study of the British distributions of two related plant species that show a 200‐fold reversal in their relative rarity when measured at different scales.

What are the best correlates of predicted extinction risk?

Direct estimates of extinction risk are frequently unavailable, so surrogate indicators are used in threatened species categorizations, but there is inadequate information on which best predict vulnerability. We compared the ability of 16 frequently-used factors to predict extinction risk for 45 vertebrate taxa. Median times to extinction were estimated using taxon-specific stochastic population models. Population size ( N) and trend were clearly the best correlates of extinction risk in our data set. Stepwise multiple regression with additive and interaction terms identified N, N × trend, plus taxonomic level, number of sub-populations × N × trend, number of offspring ( O) and N × O as predictors, and explained 70% of the variation. Trend was important in large, but not in small populations. Population size is the most important data to collect for threatened species and with trend should be the major focus in endangered species categorization and state of the environment reporting.

Extinction risk in periodically fluctuating environments

Periodically fluctuating environments occur in various ways in nature but have not, however, been studied in detail yet in the context of the color of environmental noise and extinction risk of populations. We use a stochastic model to simulate population dynamics with compensatory density regulation under four different patterns of periodically fluctuating environments. We found that extinction risk changes dramatically from what was known if the underlying environmental stochasticity driving population dynamics is periodically correlated rather than randomly correlated. Fluctuating environments with a very short period are found to decrease extinction risk over “white noise” fluctuations because a species is never in a bad environment for too long. Conversely, long periods increase extinction risk because species accumulate too much time in a bad environment. Moreover, we found the mean, variance, frequency distribution and especially the extensively studied noise color not to be sufficient for predicting extinction risk in periodically fluctuating environments. Rather, additional attributes of environmental noise have to be considered. The occurrence of monotonic trends within time series of environmental data (e.g. after ‘disturbance’ events), in combination with density regulation, may also affect extinction risk. Our study exemplifies that the investigation of periodically fluctuating environments leads to new insights into the interaction between environmental variation, population dynamics and the resulting extinction risk.

Biological correlates of extinction risk in bats.

We investigated patterns and processes of extinction and threat in bats using a multivariate phylogenetic comparative approach. Of nearly 1,000 species worldwide, 239 are considered threatened by the International Union for Conservation of Nature and Natural Resources (IUCN) and 12 are extinct. Small geographic ranges and low wing aspect ratios are independently found to predict extinction risk in bats, which explains 48% of the total variance in IUCN assessments of threat. The pattern and correlates of extinction risk in the two bat suborders are significantly different. A higher proportion (4%) of megachiropteran species have gone extinct in the last 500 years than microchiropteran bats (0.3%), and a higher proportion is currently at risk of extinction (Megachiroptera: 34%; Microchiroptera: 22%). While correlates of microchiropteran extinction risk are the same as in the order as a whole, megachiropteran extinction is correlated more with reproductive rate and less with wing morphology. Bat extinction risk is not randomly distributed phylogenetically: closely related species have more similar levels of threat than would be expected if extinction risk were random. Given the unbalanced nature of the evolutionary diversification of bats, it is probable that the amount of phylogenetic diversity lost if currently threatened taxa disappear may be greater than in other clades with numerically more threatened species.