Effects of Social Structure and Prey Dynamics on Extinction Risk in Gray Wolves

Extinction models based on diffusion theory generally fail to incorporate two important aspects of population biology—social structure and prey dynamics. We include these aspects in an individual-based extinction model for small, isolated populations of the gray wolf (Canis lupus). Our model predicts mean times to extinction significantly longer than those predicted by more general (diffusion) models. According to our model, an isolated population of 50 wolves has a 95% chance of surviving just 9 years and only a 30% chance of surviving beyond 100 years. Reflecting the influence of social structure, a wolf population initially comprising 50 individuals is expected to persist only a few years longer, on average (71 years), than is a population initially comprising just a single reproductive pair (62 years). In contrast, substantially greater average prey abundance leads to dramatically longer expected persistence times. Autocorrelated prey dynamics result in a more complex distribution of extinction times than predicted by many extinction models. We contend that demographic stochasticity may pose the greatest threat to small, isolated wolf populations, although environmental stochasticity and genetic effects may compound this threat. Our work highlights the importance of considering social structure and resource dynamics in the development of population viability analyses.     

Population Variability and Extinction Risk

Abstract: Population models generally predict increased extinction risk (ER) with increased population variability (  PV  ), yet some empirical tests have provided contradictory findings. We resolve this conflict by attributing negative measured relationships to a statistical artifact that arises because PV tends to be underestimated for populations with short persistence. Such populations do not go extinct quickly as a consequence of low intrinsic variability; instead, the measured variability is low because they go extinct so quickly. Consequently, any underlying positive relationship between PV and ER tends to be obscured. We conducted a series of analyses to evaluate this claim. Simulations showed that negative measured relationships are to be expected, despite an underlying positive relationship. Simulations also identified properties of data, minimizing this bias and thereby permitting meaningful analysis. Experimental data on laboratory populations of a bruchid beetle (Callosobruchus maculatus) supported the simulation results. Likewise, with an appropriate statistical approach (Cox regression on untransformed data), reanalysis of a controversial data set on British island bird populations revealed a significant positive association between PV and ER (p = 0.03). Finally, a similar analysis of time series for naturally regulated animal populations revealed a positive association between PV and quasiextinction risk (p < 0.01). Without exception, our simulation results, experimental findings, reanalysis of published data, and analysis of quasiextinction risk all contradict previous reports of negative or equivocal relationships. Valid analysis of meaningful data provides strong evidence that increased population variability leads to increased extinction risk.     

The Consistency of Extinction Risk Classification Protocols

Abstract:  Systematic protocols that use decision rules or scores are seen to improve consistency and transparency in classifying the conservation status of species. When applying these protocols, assessors are typically required to decide on estimates for attributes that are inherently uncertain. Input data and resulting classifications are usually treated as though they are exact and hence without operator error. We investigated the impact of data interpretation on the consistency of protocols of extinction risk classifications and diagnosed causes of discrepancies when they occurred. We tested three widely used systematic classification protocols employed by the World Conservation Union, NatureServe, and the Florida Fish and Wildlife Conservation Commission. We provided 18 assessors with identical information for 13 different species to infer estimates for each of the required parameters for the three protocols. The threat classification of several of the species varied from low risk to high risk, depending on who did the assessment. This occurred across the three protocols investigated. Assessors tended to agree on their placement of species in the highest (50–70%) and lowest risk categories (20–40%), but there was poor agreement on which species should be placed in the intermediate categories. Furthermore, the correspondence between the three classification methods was unpredictable, with large variation among assessors. These results highlight the importance of peer review and consensus among multiple assessors in species classifications and the need to be cautious with assessments carried out by a single assessor. Greater consistency among assessors requires wide use of training manuals and formal methods for estimating parameters that allow uncertainties to be represented, carried through chains of calculations, and reported transparently.     

Predicting the Risk of Extinction through Hybridization

Abstract: Natural hybridization threatens a substantial number of plant and animal species with extinction, but extinction risk has been difficult to evaluate in the absence of a quantitative assessment of risk factors. We investigated a number of ecological parameters likely to affect extinction risk, through an individual-based model simulating the life cycle of two hybridizing annual plant species. All parameters tested, ranging from population size to variance in pollen-tube growth rates, affected extinction risk. The sensitivity of each parameter varied dramatically across parameter sets, but, overall, the competitive ability, initial frequency, and selfing rate of the native taxon had the strongest effect on extinction. In addition, prezygotic reproductive barriers had a stronger influence on extinction rates than did postzygotic barriers. A stable hybrid zone was possible only when habitat differentiation was included in the model. When there was no habitat differentiation, either one of the parental species or the hybrids eventually displaced the other two taxa. The simulations demonstrated that hybridization is perhaps the most rapidly acting genetic threat to endangered species, with extinction often taking place in less than five generations. The simulation model was also applied to naturally hybridizing species pairs for which considerable genetic and ecological information is available. The predictions from these "worked examples" are in close agreement with observed outcomes and further suggest that an endemic cordgrass species is threatened by hybridization. These simulations provide guidance concerning the kinds of data required to evaluate extinction risk and possible conservation strategies.     

Metapopulation Extinction Risk under Spatially Autocorrelated Disturbance

Abstract:  Recent extinction models generally show that spatial aggregation of habitat reduces overall extinction risk because sites emptied by local extinction are more rapidly recolonized. We extended such an investigation to include spatial structure in the disturbance regime. A spatially explicit metapopulation model was developed with a wide range of dispersal distances. The degree of aggregation of both habitat and disturbance pattern could be varied from a random distribution, through the intermediate case of a fractal distribution, all the way to complete aggregation (single block). Increasing spatial aggregation of disturbance generally increased extinction risk. The relative risk faced by populations in different landscapes varied greatly, depending on the disturbance regime. With random disturbance, the spatial aggregation of habitat reduced extinction risk, as in earlier studies. Where disturbance was spatially autocorrelated, however, this advantage was eliminated or reversed because populations in aggregated habitats are at risk of mass extinction from coarse-scale disturbance events. The effects of spatial patterns on extinction risk tended to be reduced by long-distance dispersal. Given the high levels of spatial correlation in natural and anthropogenic disturbance processes, population vulnerability may be greatly underestimated both by classical (nonspatial) models and by those that consider spatial structure in habitat alone.     

Predicting Extinction Risk of Brazilian Atlantic Forest Angiosperms

Understanding how plant life history affects species vulnerability to anthropogenic disturbances and environmental change is a major ecological challenge. We examined how vegetation type, growth form, and geographic range size relate to extinction risk throughout the Brazilian Atlantic Forest domain. We used a database containing species‐level information of 6,929 angiosperms within 112 families and a molecular‐based working phylogeny. We used decision trees, standard regression, and phylogenetic regression to explore the relationships between species attributes and extinction risk. We found a significant phylogenetic signal in extinction risk. Vegetation type, growth form, and geographic range size were related to species extinction risk, but the effect of growth form was not evident after phylogeny was controlled for. Species restricted to either rocky outcrops or scrub vegetation on sandy coastal plains exhibited the highest extinction risk among vegetation types, a finding that supports the hypothesis that species adapted to resource‐limited environments are more vulnerable to extinction. Among growth forms, epiphytes were associated with the highest extinction risk in non‐phylogenetic regression models, followed by trees, whereas shrubs and climbers were associated with lower extinction risk. However, the higher extinction risk of epiphytes was not significant after correcting for phylogenetic relatedness. Our findings provide new indicators of extinction risk and insights into the mechanisms governing plant vulnerability to extinction in a highly diverse flora where human disturbances are both frequent and widespread. Predicción del Riesgo de Extinción de Angiospermas del Bosque Atlántico Brasileño     

Effects of Human Population Density and Proximity to Markets on Coral Reef Fishes Vulnerable to Extinction by Fishing

Coral reef fisheries are crucial to the livelihoods of tens of millions of people; yet, widespread habitat degradation and unsustainable fishing are causing severe depletion of stocks of reef fish. Understanding how social and economic factors, such as human population density, access to external markets, and modernization interact with fishing and habitat degradation to affect fish stocks is vital to sustainable management of coral reef fisheries. We used fish survey data, national social and economic data, and path analyses to assess whether these factors explain variation in biomass of coral reef fishes among 25 sites in Solomon Islands. We categorized fishes into 3 groups on the basis of life‐history characteristics associated with vulnerability to extinction by fishing (high, medium, and low vulnerability). The biomass of fish with low vulnerability was positively related to habitat condition. The biomass of fishes with high vulnerability was negatively related to fishing conducted with efficient gear. Use of efficient gear, in turn, was strongly and positively related to both population density and market proximity. This result suggests local population pressure and external markets have additive negative effects on vulnerable reef fish. Biomass of the fish of medium vulnerability was not explained by fishing intensity or habitat condition, which suggests these species may be relatively resilient to both habitat degradation and fishing. Efectos de la Densidad de Poblaciones Humanas y la Proximidad del Mercado sobre Peces de Arrecifes de Coral Vulnerables a la Extinción     

Infectious Diseases and Extinction Risk in Wild Mammals

Abstract:  Parasite-driven declines in wildlife have become increasingly common and can pose significant risks to natural populations. We used the IUCN Red List of Threatened and Endangered Species and compiled data on hosts threatened by infectious disease and their parasites to better understand the role of infectious disease in contemporary host extinctions. The majority of mammal species considered threatened by parasites were either carnivores or artiodactyls, two clades that include the majority of domesticated animals. Parasites affecting host threat status were predominantly viruses and bacteria that infect a wide range of host species, including domesticated animals. Counter to our predictions, parasites transmitted by close contact were more likely to cause extinction risk than those transmitted by other routes. Mammal species threatened by parasites were not better studied for infectious diseases than other threatened mammals and did not have more parasites or differ in four key traits demonstrated to affect parasite species richness in other comparative studies. Our findings underscore the need for better information concerning the distribution and impacts of infectious diseases in populations of endangered mammals. In addition, our results suggest that evolutionary similarity to domesticated animals may be a key factor associated with parasite-mediated declines; thus, efforts to limit contact between domesticated hosts and wildlife could reduce extinction risk.     

Range Size and Extinction Risk in Forest Birds

Abstract:  Small geographical range size is the single best predictor of threat of extinction in terrestrial species. Knowing how small a species' range has to be before authorities consider it threatened with extinction would allow prediction of a species' risk from continued deforestation and warming climates and provide a baseline for conservation and management strategies aspiring to mitigate these threats. To determine the threshold at which forest-dependent bird species become threatened with extinction, we compared the range sizes of threatened and nonthreatened species. In doing so, we present a simple, repeatable, and practical protocol to quantify range size. We started with species' ranges published in field guides or comparable sources. We then trimmed these ranges, that is, we included only those parts of the ranges that met the species' requirements of elevation and types of forest preferred. Finally, we further trimmed the ranges to the amount of forest cover that remains. This protocol generated an estimate of the remaining suitable range for each species. We compared these range estimates with those from the World Conservation Union Red List. We used the smaller of the two estimates to determine the threshold, 11,000 km², below which birds should be considered threatened. Species considered threatened that have larger ranges than this qualified under other (nonspatial) red list criteria. We identified a suite of species (18) that have not yet qualified as threatened but that have perilously small ranges—about 11% of the nonthreatened birds we analyzed. These birds are likely at risk of extinction and reevaluation of their status is urgently needed.     

Body Size and Risk of Extinction in Australian Mammals

Abstract: The link between body size and risk of extinction has been the focus of much recent attention. For Australian terrestrial mammals this link is of particular interest because it is widely believed that species in the intermediate size range of 35–5500 g (the "critical weight range") have been the most prone to recent extinction. But the relationship between body size and extinction risk in Australian mammals has never been subject to a robust statistical analysis. Using a combination of randomization tests and phylogenetic comparative analyses, we found that Australian mammal extinctions and declines have been nonrandom with respect to body size, but we reject the hypothesis of a critical weight range at intermediate sizes. Small species appear to be the least prone to extinction, but extinctions have not been significantly clustered around intermediate sizes. Our results suggest that hypotheses linking intermediate body size with high risk of extinction in Australian mammals are misguided and that the focus of future research should shift to explaining why the smallest species are the most resistant to extinction.     

Linking Indices for Biodiversity Monitoring to Extinction Risk Theory

Biodiversity indices often combine data from different species when used in monitoring programs. Heuristic properties can suggest preferred indices, but we lack objective ways to discriminate between indices with similar heuristics. Biodiversity indices can be evaluated by determining how well they reflect management objectives that a monitoring program aims to support. For example, the Convention on Biological Diversity requires reporting about extinction rates, so simple indices that reflect extinction risk would be valuable. We developed 3 biodiversity indices that are based on simple models of population viability that relate extinction risk to abundance. We based the first index on the geometric mean abundance of species and the second on a more general power mean. In a third index, we integrated the geometric mean abundance and trend. These indices require the same data as previous indices, but they also relate directly to extinction risk. Field data for butterflies and woodland plants and experimental studies of protozoan communities show that the indices correlate with local extinction rates. Applying the index based on the geometric mean to global data on changes in avian abundance suggested that the average extinction probability of birds has increased approximately 1% from 1970 to 2009. Conectando Índices para el Monitoreo de la Biodiversidad con la Teoría de Riesgo de Extinción     

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.     

Risk of Local Extinction of Odonata Freshwater Habitat Generalists and Specialists

Understanding the risk of a local extinction in a single population relative to the habitat requirements of a species is important in both theoretical and applied ecology. Local extinction risk depends on several factors, such as habitat requirements, range size of species, and habitat quality. We studied the local extinctions among 31 dragonfly and damselfly species from 1930 to 1975 and from 1995 to 2003 in Central Finland. We tested whether habitat specialists had a higher local extinction rate than generalist species. Approximately 30% of the local dragonfly and damselfly populations were extirpated during the 2 study periods. The size of the geographical range of the species was negatively related to extinction rate of the local populations. In contrast to our prediction, the specialist species had lower local extinction rates than the generalist species, probably because generalist species occurred in both low‐ and high‐quality habitat. Our results are consistent with source–sink theory. Riesgo de Extinción Local de Odonatos de Agua Dulce Generalistas y Especialistas de Hábitat     

Ecological Determinants of Distribution Decline and Risk of Extinction in Moths

Abstract:  For successful conservation of species it is important to identify traits that predispose species to the risk of extinction. By identifying such traits conservation efforts can be directed toward species that are most at risk of becoming threatened. We used data derived from the literature to determine ecological traits that affect distribution, distribution change, and the risk of extinction in Finnish noctuid moths (Lepidoptera, Noctuidae). The ecological traits we examined included body size, larval specificity, length of the flight period, and overwintering stage. In addition, in monophagous species we examined the effects of resource distribution. Larval specificity, length of the flight period, and the overwintering stage each had an independent effect on the risk of extinction when the effects of other traits were controlled by entering all traits into the same regression model. Not a single trait predicted the risk of extinction when analysis was conducted without controlling for the other traits. This discrepancy among the results suggests that a single trait may not be enough to allow prediction of the risk of extinction. Instead, it seems that for successful, predictive conservation science data on several ecological characteristics are needed.     

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.     

A Comparative Analysis of Specialization and Extinction Risk in Temperate-Zone Bats

Abstract:  Identifying the factors that influence the extinction risk of animals is essential in conservation biology because they help identify endangered species and provide the basis for their preservation. We present a comparative study that uses data from the literature on the diet and morphological specialization of European and North American bat species to investigate the effect of specialization on extinction risk. We focused on bats because many species are endangered and their high ecological diversity makes them a good model system for our purpose. After correcting for phylogenetic inertia, we compared the influence of dietary niche breadth as a measure of food specialization and of wing morphology as a measure of foraging strategy, habitat adaptation, and migratory ability on the vulnerability of 35 insectivorous bat species. Our results do not support the hypothesis that a narrow dietary niche breadth is related to high extinction risk. Instead they suggest that habitat specialization, which is reflected in wing morphology, influences the extinction risk of bats. Our study shows that an initial risk assessment in temperate-zone bats could be based on data of wing morphology but not on dietary data obtained from fecal analyses.     

Quantification of Extinction Risk: IUCN's System for Classifying Threatened Species

Abstract: The International Union for Conservation of Nature (IUCN) Red List of Threatened Species was increasingly used during the 1980s to assess the conservation status of species for policy and planning purposes. This use stimulated the development of a new set of quantitative criteria for listing species in the categories of threat: critically endangered, endangered, and vulnerable. These criteria, which were intended to be applicable to all species except microorganisms, were part of a broader system for classifying threatened species and were fully implemented by IUCN in 2000. The system and the criteria have been widely used by conservation practitioners and scientists and now underpin one indicator being used to assess the Convention on Biological Diversity 2010 biodiversity target. We describe the process and the technical background to the IUCN Red List system. The criteria refer to fundamental biological processes underlying population decline and extinction. But given major differences between species, the threatening processes affecting them, and the paucity of knowledge relating to most species, the IUCN system had to be both broad and flexible to be applicable to the majority of described species. The system was designed to measure the symptoms of extinction risk, and uses 5 independent criteria relating to aspects of population loss and decline of range size. A species is assigned to a threat category if it meets the quantitative threshold for at least one criterion. The criteria and the accompanying rules and guidelines used by IUCN are intended to increase the consistency, transparency, and validity of its categorization system, but it necessitates some compromises that affect the applicability of the system and the species lists that result. In particular, choices were made over the assessment of uncertainty, poorly known species, depleted species, population decline, restricted ranges, and rarity; all of these affect the way red lists should be viewed and used. Processes related to priority setting and the development of national red lists need to take account of some assumptions in the formulation of the criteria.     

Effects of Recent Environmental Change on Accuracy of Inferences of Extinction Status

Correctly classifying a species as extinct or extant is of critical importance if current rates of biodiversity loss are to be accurately quantified. Observing an extinction event is rare, so in many cases extinction status is inferred using methods based on the analysis of records of historic sighting events. The accuracy of such methods is difficult to test. However, results of recent experiments with microcosm communities suggest that the rate at which a population declines to extinction, potentially driven by varying environmental conditions, may alter one's ability accurately to infer extinction status. We tested how the rate of population decline, driven by historic environmental change, alters the accuracy of 6 commonly applied sighting‐based methods used to infer extinction. We used data from small‐scale experimental communities and recorded wild population extirpations. We assessed how accuracy of the different methods was affected by rate of population decline, search effort, and number of sighting events recorded. Rate of population decline and historic population size of the species affected the accuracy of inferred extinction dates; however, faster declines produced more accurate inferred dates of extinction, but only when population sizes were higher. Optimal linear estimation (OLE) offered the most reliable and robust estimates, though no single method performed best in all situations, and it may be appropriate to use a different method if information regarding historic search efforts is available. OLE provided the most accurate estimates of extinction when the number of sighting events used was >10, and future use of this method should take this into account. Data from experimental populations provide added insight into testing techniques to discern wild extirpation events. Care should be taken designing such experiments so that they mirror closely the abundance dynamics of populations affected by real‐world extirpation events. Efectos del Cambio Ambiental Reciente sobre la Precisión de las Inferencias sobre el Estado de Extinción