Habitat Change and Plant Demography: Assessing the Extinction Risk of a Formerly Common Grassland Perennial

Abstract:  An important aim of conservation biology is to understand how habitat change affects the dynamics and extinction risk of populations. We used matrix models to analyze the effect of habitat degradation on the demography of the declining perennial plant Trifolium montanum in 9 calcareous grasslands in Germany over 4 years and experimentally tested the effect of grassland management. Finite population growth rates (λ) decreased with light competition, measured as leaf-area index above T. montanum plants. At unmanaged sites λ was <1 due to lower recruitment and lower survival and flowering probability of large plants. Nevertheless, in stochastic simulations, extinction of unmanaged populations of 100 flowering plants was delayed for several decades. Clipping as a management technique rapidly increased population growth because of higher survival and flowering probability of large plants in managed than in unmanaged plots. Transition-matrix simulations from these plots indicated grazing or mowing every second year would be sufficient to ensure a growth rate ≥1 if conditions stayed the same. At frequently grazed sites, the finite growth rate was approximately 1 in most populations of T. montanum . In stochastic simulations, the extinction risk of even relatively small grazed populations was low, but about half the extant populations of T. montanum in central Germany are smaller than would be sufficient for a probability of survival of >95% over 100 years. We conclude that habitat change after cessation of management strongly reduces recruitment and survival of established individuals of this perennial plant. Nevertheless, our results suggest extinction processes may take a long time in perennial plants, resulting in an extinction debt. Even if management is frequent, many remnant populations of T. montanum may be at risk because of their small size, but even a slight increase in size could considerably reduce their extinction risk.     

Population Viability Estimates: Theory and Practice for a Wild Gorilla Population

The logic of demographic modeling, the apparent simplicity of its quantifiably substantiated answers, and the ready availability of software correlate with increasing use of demographic modeling as the means of applying biology to the conservation of potentially endangered populations. I investigated that use by considering a small population (about 300 individuals) of a large, forest-dwelling mammal of the tropics, the Virunga gorilla ( Gorilla gorilla ) of Zaire, Uganda, and Rwanda. Because censuses of forest populations are so inaccurate and data on variance of some parameters takes so long to collect, models might not be broadly applicable. Therefore, simple demographic indices of potential extinction should replace sophisticated models. The current best index could be problematic, however, because it is based on detecting adult mortality, perhaps the most difficult demographic parameter to measure. Models of the Virunga gorilla population that incorporate aspects of demographic heterogeneity valuably indicate genetic and demographic persistence for several hundred years. Deterministic change in habitat is a greater threat than stochastic demographic variation, and yet our ecological ignorance is such that we could not begin to model the consequences of removal of even the main food plant. We must add to our ability to model outcomes of demographic perturbation a far greater understanding of the processes by which the perturbations occur. Demography allows us to model demographic response to demographic change, but we usually need ecology to tell us how the threat produced the demographic change in the first place. In a time of change, accurate prediction requires ecological understanding of process as well as demographic understanding of outcome.     

Extinction times in experimental populations

Predicting population extinctions is a key element of quantitative conservation biology and population ecology. Although stochastic population theories have long been used to obtain theoretical distributions of population extinction times, model-based predictions have rarely been tested. Here I report results from a quantitative analysis of extinction time in 281 experimental populations of water fleas (Daphnia magna) in variable environments. To my knowledge, this is the first quantitative estimate of the shape of the distribution of population extinction times based on extinction data for any species. The finding that the distribution of population extinction times was extraordinarily peaked is consistent with theoretical predictions for density-independent populations, but inconsistent with predictions for density-dependent populations. The tail of the extinction time distribution was not exponential. These results imply that our current theories of extinction are inadequate. Future work should focus on how demographic stochasticity scales with population size and effects of nonrandom variable environments on population growth and decline.     

Unprecedented Low Levels of Genetic Variation and Inbreeding Depression in an Island Population of the Black-Footed Rock-Wallaby

Abstract: It has been argued that demographic and environmental factors will cause small, isolated populations to become extinct before genetic factors have a significant negative impact. Islands provide an ideal opportunity to test this hypothesis because they often support small, isolated populations that are highly vulnerable to extinction. To assess the potential negative impact of isolation and small population size, we compared levels of genetic variation and fitness in island and mainland populations of the black-footed rock-wallaby ( Petrogale lateralis [Marsupialia: Macropodidae]). Our results indicate that the Barrow Island population of P. lateralis has unprecedented low levels of genetic variation (  H _e = 0.053, from 10 microsatellite loci) and suffers from inbreeding depression (reduced female fecundity, skewed sex ratio, increased levels of fluctuating asymmetry). Despite a long period of isolation ( ∼ 1600 generations) and small effective population size (  N _e ∼ 15), demographic and environmental factors have not yet driven this population to extinction. Nevertheless, it has been affected significantly by genetic factors. It has lost most of its genetic variation and become highly inbred (  F _e = 0.91), and it exhibits reduced fitness. Because several other island populations of P. lateralis also exhibit exceptionally low levels of genetic variation, this phenomenon may be widespread. Inbreeding in these populations is at a level associated with high rates of extinction in populations of domestic and laboratory species. Genetic factors cannot then be excluded as contributing to the extinction proneness of small, isolated populations.     

Demographic stochasticity reduces the synchronizing effect of dispersal in predator-prey metapopulations

Dispersal may affect predator-prey metapopulations by rescuing local sink populations from extinction or by synchronizing population dynamics across the metapopulation, increasing the risk of regional extinction. Dispersal is likely influenced by demographic stochasticity, however, particularly because dispersal rates are often very low in metapopulations. Yet the effects of demographic stochasticity on predator-prey metapopulations are not well known. To that end, I constructed three models of a two-patch predator-prey system. The models constitute a hierarchy of complexity, allowing direct comparisons. Two models included demographic stochasticity (pure jump process [PJP] and stochastic differential equations [SDE]), and the third was deterministic (ordinary differential equations [ODE]). One stochastic model (PJP) treated population sizes as discrete, while the other (SDE) allowed population sizes to change continuously. Both stochastic models only produced synchronized predator-prey dynamics when dispersal was high for both trophic levels. Frequent dispersal by only predators or prey in the PJP and SDE spatially decoupled the trophic interaction, reducing synchrony of the non-dispersive species. Conversely, the ODE generated synchronized predator-prey dynamics across all dispersal rates, except when initial conditions produced anti-phase transients. These results indicate that demographic stochasticity strongly reduces the synchronizing effect of dispersal, which is ironic because demographic stochasticity is often invoked post hoc as a driver of extinctions in synchronized metapopulations.     

The Long-Term Effects of Tiger Poaching on Population Viability

Poaching tigers, primarily for their bones, has become the latest threat to the persistence of wild tiger populations throughout the world. Anecdotal information indicates the seriousness of this new threat. It is important, however, to provide a quantitative analysis of poaching as a basis for strong policy action. We therefore created a tiger simulation model to explore the effects of realistic levels of poaching on population viability. The model is an individually based, stochastic spatial model that is based on the extensive data set from Royal Chitwan National Park, Nepal. We found that as poaching continues over time, the probability of population extinction increases sigmoidally; a critical zone exists in which a small, incremental increase in poaching greatly increases the probability of extinction. The implication is that poaching may not at first be seen as a threat but could suddenly become one. Moreover, even if poaching is effectively stopped, tiger populations will still be vulnerable and could go extinct due to demographic and environmental stochasticity. Our model also shows that poaching reduces genetic variability, which could further reduce population viability due to inbreeding depression. The longer poaching is allowed to continue, the more vulnerable a population will be to these stochastic events. At currently reported rates of poaching our analysis indicates that many wild tiger populations will be extirpated during the latter half of the 1990s.     

Predicting [corrected] extinction risk in spite of predator-prey oscillations.

Most population viability analyses (PVA) assume that the effects of species interactions are subsumed by population-level parameters. We examine how robust five commonly used PVA models are to violations of this assumption. We develop a stochastic, stage-structured predator-prey model and simulate prey population vital rates and abundance. We then use simulated data to parameterize and estimate risk for three demographic models (static projection matrix, stochastic projection matrix, stochastic vital rate matrix) and two time series models (diffusion approximation [DA], corrupted diffusion approximation [CDA]). Model bias is measured as the absolute deviation between estimated and observed quasi-extinction risk. Our results highlight three generalities about the application of single-species models to multi-species conservation problems. First, our collective model results suggest that most single-species PVA models overestimate extinction risk when species interactions cause periodic variation in abundance. Second, the DA model produces the most (conservatively) biased risk forecasts. Finally, the CDA model is the most robust PVA to population cycles caused by species interactions. CDA models produce virtually unbiased and relatively precise risk estimates even when populations cycle strongly. High performance of simple time series models like the CDA owes to their ability to effectively partition stochastic and deterministic sources of variation in population abundance.     

Extinction of Mammal Populations in Western North American National Parks

Patterns of local extinction of mammal populations in western North American parks were examined in relation to current biogeographic and population lifetime models. The analysis was based on species sighting records as of 1989. While western North American parks are obviously not true isolates, patterns of mammal extinction in them are nonetheless consistent with two predictions of the land-bridge island hypothesis. First, the number of extinctions has exceeded the number of colonizations since park establishment, and, second, the rate of extinction is inversely related to park area. Factors influencing the lifetime of mammal populations were evaluated using a stepwise multivariate survival analysis procedure for censored data. Survival time for mammal populations was positively related to estimated initial population size. After accounting for population size, species within the order Lagomorpha were particularly prone to extinction. Finally, after controlling for population size and taxon variation, survival time was positively related to age of maturity, indicating that species with longer generation times—age of maturity and generation time are highly correlated in mammals—persist longer in absolute time.     

Avian Survival Rates and the Extinction Process on Barro Colorado Island, Panama

Abstract: Selective extinction following isolation of habitat patches may be due to biogeographical (e.g., island size or isolation) and ecological (species natural histories, interspecifc interactions) factors, or their interactions. Among the demographic and life history attributes commonly associated with high extinction probability are small populations, large size of individuals, and population variability. Long-term capture-recapture data from forest habitat in central Panama permit an examination of the association between mainland survival rates and extinction on a nearby land-bridge island Species of birds that no longer occur on Barro Colorado Island (BCI), Panama, have, on average, lower survival rates on the adjacent mainland than species that have persisted on BCI. Moreover, of the species that no longer occur on BCI, those with lower mainland survival rates generally disappeared earlier from the island. My analysis provides little evidence of a relationship between extinction and population size. Recolonization of BCI from the adjacent mainland by the forest undergrowth species studied here is unlikely. Reduced reproductive success on BCI combined with naturally low adult survival rates seems to be responsible for these BCI extinctions. High nest predation and/or altered landscape dynamics are probable agents in the low reproductive success. The methods used here could be employed in other circumstances to identify fragmentation-sensitive species.     

Predicting the Deleterious Effects of Mutation Load in Fragmented Populations

Abstract:  Human-induced habitat fragmentation constitutes a major threat to biodiversity. Both genetic and demographic factors combine to drive small and isolated populations into extinction vortices. Nevertheless, the deleterious effects of inbreeding and drift load may depend on population structure, migration patterns, and mating systems and are difficult to predict in the absence of crossing experiments. We performed stochastic individual-based simulations aimed at predicting the effects of deleterious mutations on population fitness (offspring viability and median time to extinction) under a variety of settings (landscape configurations, migration models, and mating systems) on the basis of easy-to-collect demographic and genetic information. Pooling all simulations, a large part (70%) of variance in offspring viability was explained by a combination of genetic structure ( F_ST ) and within-deme heterozygosity ( H_S ). A similar part of variance in median time to extinction was explained by a combination of local population size ( N ) and heterozygosity ( H_S ). In both cases the predictive power increased above 80% when information on mating systems was available. These results provide robust predictive models to evaluate the viability prospects of fragmented populations.     

Small Populations and Offspring Sex-Ratio Deviations in Eagles

Abstract:  Stochastic variation of sex ratio has long been appreciated as a potential factor driving small populations to extinction, but it is not the only source of sex-ratio bias in small populations. We examined whether some consequences of sex allocation could affect extinction risk in small populations of size-dimorphic birds such as eagles. We report variations in sex ratio at fledging from a long-term study of a declining population of Spanish Imperial Eagles ( Aquila adalberti ). Nestling sex-ratio deviation apparently was mediated by age of breeders, whereas territory quality had no obvious effect. Adult–adult pairs produced the same proportion of both sexes in high- or low-density situations, but pairs with at least one member in nonadult plumage class produced more males. As the population declined over a period of years, the proportion of breeders with immature plumage increased; consequently, the proportion of fledgling males increased. However, when population density was high, the proportion of breeders with immature plumage decreased and more female offspring were produced. This relationship between population density, composition of breeder age, and fledgling sex ratios allowed us to make predictions of extinction risk due to nonstochastic deviations of sex ratio in small, declining populations. In the study population, on the basis of the Vortex simulation results, an estimated reduction of 42.5% in predicted mean time to extinction was attributed solely to biased sex ratio.     

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.     

Estimating the functional form for the density dependence from life history data

Two contrasting approaches to the analysis of population dynamics are currently popular: demographic approaches where the associations between demographic rates and statistics summarizing the population dynamics are identified; and time series approaches where the associations between population dynamics, population density, and environmental covariates are investigated. In this paper, we develop an approach to combine these methods and apply it to detailed data from Soay sheep (Ovis aries). We examine how density dependence and climate contribute to fluctuations in population size via age- and sex-specific demographic rates, and how fluctuations in demographic structure influence population dynamics. Density dependence contributes most, followed by climatic variation, age structure fluctuations and interactions between density and climate. We then simplify the density-dependent, stochastic, age-structured demographic model and derive a new phenomenological time series which captures the dynamics better than previously selected functions. The simple method we develop has potential to provide substantial insight into the relative contributions of population and individual-level processes to the dynamics of populations in stochastic environments.     

Extinction Rate Estimates for Plant Populations in Revisitation Studies: Importance of Detectability

Abstract:  Many researchers have obtained extinction-rate estimates for plant populations by comparing historical and current records of occurrence. A population that is no longer found is assumed to have gone extinct. Extinction can then be related to characteristics of these populations, such as habitat type, size, or species, to test ideas about what factors may affect extinction. Such studies neglect the fact that a population may be overlooked, however, which may bias estimates of extinction rates upward. In addition, if populations are unequally detectable across groups to be compared, such as habitat type or population size, comparisons become distorted to an unknown degree. To illustrate the problem, I simulated two data sets, assuming a constant extinction rate, in which populations occurred in different habitats or habitats of different size and these factors affected their detectability. The conventional analysis implicitly assumed that detectability equalled 1 and used logistic regression to estimate extinction rates. It wrongly identified habitat and population size as factors affecting extinction risk. In contrast, with capture-recapture methods, unbiased estimates of extinction rates were recovered. I argue that capture-recapture methods should be considered more often in estimations of demographic parameters in plant populations and communities.     

Reliability of Absolute and Relative Predictions of Population Persistence Based on Time Series

Abstract:  Conventional population viability analysis (PVA) is often impractical because data are scarce for many threatened species. For this reason, simple count-based models are being advocated. The simplest of these models requires nothing more than a time series of abundance estimates, from which variance and autocorrelation in growth rate are estimated and predictions of population persistence are generated. What remains unclear, however, is how many years of data are needed to generate reliable estimates of these parameters and hence reliable predictions of persistence. By analyzing published and simulated time series, we show that several decades of data are needed. Predictions based on short time series were very unreliable mainly because limited data yielded biased, unreliable estimates of variance in growth rate, especially when growth rate was strongly autocorrelated. More optimistically, our results suggest that count-based PVA is sometimes useful for relative risk assessment (i.e., for ranking populations by extinction risk), even when time series are only a decade long. However, some conditions consistently lead to backward rankings. We explored the limited conditions under which simple count-based PVA may be useful for relative risk assessment.     

Geometrical Factors and Metapopulation Dynamics of the Bush Cricket, Metrioptera bicolor Philippi (Orthoptera: Tettigoniidae)

This paper presents a metapopulation study of the bush cricket, Metrioptera bicolor , living in a recently fragmented landscape. The species inhabits grass and heathland patches of varying area and isolation. Analyses are made of how these geometrical factors affect local population size and density, distribution pattern, and the probability of local extinction and colonization. The proportion of available patches occupied varied between 72 and 79% during 1985–1990. Unoccupied patches were smaller and more isolated than those that were occupied. Patches where populations became extinct during this period were smaller than those with persisting populations. Since local population size was well correlated with patch area, it was clear that stochastic extinctions only occurred in small populations. Critical patch size for population extinction was approximately half a hectare. Colonized patches were less isolated than those that had not been colonized. Critical inter-patch distance for colonization was about 100 meters. The turnover was restricted to an identifiable share of the available patches. Only 33% of the patches were so small that extinction due to stochastic causes could be considered highly probable. This metapopulation will therefore most likely persist over a considerable period in its present spatial structure. There are apparent threats of further fragmentation, however, and nothing is known about the likelihood of large-scale extinctions resulting from extremely unfavorable weather conditions. Nevertheless, our results show that it is appropriate to include geometrical factors in metapopulation models.     

Erosion of Heterozygosity in Fluctuating Populations

Abstract: Demographic, environmental, and genetic stochasticity threaten the persistence of isolated populations. The relative importance of these intertwining factors remains unresolved, but a common view is that random demographic and environmental events will usually drive small populations to the brink of extinction before genetic deterioration poses a serious threat. To evaluate the potential importance of genetic factors, we analyzed a model linking demographic and environmental conditions to the loss of genetic diversity in isolated populations undergoing natural levels of fluctuation. Nongenetic processes—environmental stochasticity and population demography—were modeled according to a bounded diffusion process. Genetic processes were modeled by quantifying the rate of drift according to the effective population size, which was predicted from the same parameters used to describe the nongenetic processes. We combined these models to predict the heterozygosity remaining at the time of extinction, as predicted by the nongenetic portion of the model. Our model predicts that many populations will lose most or all of their neutral genetic diversity before nongenetic random events lead to extinction. Given the abundant evidence for inbreeding depression and recent evidence for elevated extinction rates of inbred populations, our findings suggest that inbreeding may be a greater general threat to population persistence than is generally recognized. Therefore, conservation biologists should not ignore the genetic component of extinction risk when assessing species endangerment and developing recovery plans.     

Population Viability Analysis for an Endangered Plant

Abstract: Demographic modeling is used to understand the population viability of Furbish's lousewort, Pedicularis furbishiae , a perennial plant species endemic to the St. John River Valley in northern Maine. Environment-specific summaries of demographic parameters (survivorship, growth, and fecundity) over four years, organized into stage-based projection matrices, provide predictions of future population dynamics given a deterministic extension of past conditions. Stochastic modeling, using (I) empirically observed variation in demographic parameters, and (2) estimated rates of natural catastrophes, leads to predictions of extinction probability.
P. furbishiae viability has varied widely over the study period Viable populations with finite rates of increase > 1 are found where cover is low, woody plants do not dominate, and disturbance does not occur. Rates of increase vary over time, suggesting that stochastic analyses would be realistic. Stochastic measures of population viability incorporating environmental variation suggest that early successional environments, especially wetter sites, can support viable populations in the absence of disturbance. However; observed rates of natural catastrophe dominate viability estimates of individual populations. Metapopulation dynamics feature extinction rates that are greater than recolonization rates, and may be affected by land use in the watershed Species management needs to consider a large-scale view of the riverine corridor.     

Stochastic population dynamics in populations of western terrestrial garter snakes with divergent life histories

Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (lambda(s)) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on lambda(s). The magnitude of variation in the proportion of gravid females and its effect on lambda(s) was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on lambda(s) was 4 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution.     

Exploring Population Dynamics Patterns in a Rare Fish, Zingel asper, through Capture-Mark-Recapture Methods

Abstract:  We performed a capture-mark-recapture study on one of the last populations of Zingel asper , an endemic percid species of the Rhône River basin in France. The distribution of Z. asper has decreased dramatically during the last century. We sampled three sites in suitable habitats in the Beaume River. No impact of individual tagging on survival was found. The demography of the population was analyzed using capture-recapture methods that allow the estimation of survival, recruitment, and demographic growth rates. Annual survival rates were low (0.35–0.50). The level of transience was high (5% to 25%), suggesting that a significant number of individuals were highly mobile or shifted to suboptimal habitats. Seniority rates suggested random highly variable recruitment between years. The three sites had similar variation patterns in all demographic parameters, indicating broad spatial covariation in population dynamics. We found some local differences in demographic parameters, which could be linked to local habitat quality. Individual tagging allowed for the estimation of demographic parameters that improved our understanding of Z. asper population dynamics and revealed mechanisms that may affect population persistence, such as stochastic recruitment, low survival, and frequent dispersal. The fragmentation of habitat through river damming inhibits dispersal and represents a threat to the persistence of Z. asper in the Rhône basin. Our results offer evidence of the importance of dispersal in nonmigratory fishes and confirm the usefulness of individual tagging methods in rare fish demography.