Does inbreeding affect the extinction risk of small populations?: predictions from Drosophila

A fundamental assumption underlying the importance of genetic risks within conservation biology is that inbreeding increases the extinction probability of populations. Although inbreeding has been shown to have a detrimental impact on individual fitness, its contribution to extinction is still poorly understood. We have studied the consequences of different levels of prior inbreeding for the persistence of small populations using Drosophila melanogaster as a model organism. To this end, we determined the extinction rate of small vial populations differing in the level of inbreeding under both optimal and stress conditions, i.e. high temperature stress and ethanol stress. We show that inbred populations have a significantly higher short‐term probability of extinction than non‐inbred populations, even for low levels of inbreeding, and that the extinction probability increases with increasing inbreeding levels. In addition, we observed that the effects of inbreeding become greatly enhanced under stressful environmental conditions. More importantly, our results show that the impact of environmental stress becomes significantly greater for higher inbreeding levels, demonstrating explicitly that inbreeding and environmental stress are not independent but can act synergistically. These effects seem long lasting as the impact of prior inbreeding was still qualitatively the same after the inbred populations had been expanded to appreciable numbers and maintained as such for approximately 50 generations. Our observations have significant consequences for conservation biology.     

Climate change and spotted owls: potentially contrasting responses in the Southwestern United States

Developing strategies that reduce the impacts of climate change on biodiversity will require projections of the future status of species under alternative climate change scenarios. Demographic models based on empirical data that link temporal variation in climate with vital rates can improve the accuracy of such predictions and help guide conservation efforts. Here, we characterized how population dynamics and extinction risk might be affected by climate change for three spotted owl (Strix occidentalis) populations in the Southwestern United States over the next century. Specifically, we used stochastic, stage‐based matrix models parameterized with vital rates linked to annual variation in temperature and precipitation to project owl populations forward in time under three IPCC emissions scenarios relative to contemporary climate. Owl populations in Arizona and New Mexico were predicted to decline rapidly over the next century and had a much greater probability of extinction under all three emissions scenarios than under current climate conditions. In contrast, owl population dynamics in Southern California were relatively insensitive to predicted changes in climate, and extinction risk was low for this population under all scenarios. The difference in predicted climate change impacts between these areas was due to negative associations between warm, dry conditions and owl vital rates in Arizona and New Mexico, whereas cold, wet springs reduced reproduction in Southern California. Predicted changes in population growth rates were mediated more by weather‐induced changes in fecundity than survival, and were generally more sensitive to increases in temperature than declines in precipitation. Our results indicate that spotted owls in arid environments may be highly vulnerable to climate change, even in core parts of the owl's range. More broadly, contrasting responses to climate change among populations highlight the need to tailor conservation strategies regionally, and modeling efforts such as ours can help prioritize the allocation of resources in this regard.     

Demographic factors and genetic variation influence population persistence under environmental change

Population persistence has been studied in a conservation context to predict the fate of small or declining populations. Persistence models have explored effects on extinction of random demographic and environmental fluctuations, but in the face of directional environmental change they should also integrate factors affecting whether a population can adapt. Here, we examine the population‐size dependence of demographic and genetic factors and their likely contributions to extinction time under scenarios of environmental change. Parameter estimates were derived from experimental populations of the rainforest species, Drosophila birchii, held in the lab for 10 generations at census sizes of 20, 100 and 1000, and later exposed to five generations of heat‐knockdown selection. Under a model of directional change in the thermal environment, rapid extinction of populations of size 20 was caused by a combination of low growth rate (r) and high stochasticity in r. Populations of 100 had significantly higher reproductive output, lower stochasticity in r and more additive genetic variance (V_A) than populations of 20, but they were predicted to persist less well than the largest size class. Even populations of 1000 persisted only a few hundred generations under realistic estimates of environmental change because of low V_A for heat‐knockdown resistance. The experimental results document population‐size dependence of demographic and adaptability factors. The simulations illustrate a threshold influence of demographic factors on population persistence, while genetic variance has a more elastic impact on persistence under environmental change.     

Inter‐individual variation promotes ecological success of populations and species: evidence from experimental and comparative studies

Biological diversity is threatened by exploitation, fragmentation of natural habitats, pollution, climate change, and anthropogenic spread of species. The question of how among‐individual variation influences the performance of populations and species is a poorly explored but currently growing field of research. Here, we review 31 experimental and 14 comparative studies and first investigate whether there is empirical support for the propositions that higher levels of among‐individual phenotypic and genetic variation promote the ecological and evolutionary success of populations and species in the face of environmental change. Next, we examine whether and how the effect of diversity depends on environmental conditions. Finally, we explore whether the relationship linking population fitness to diversity is typically linear, asymptotic, or whether the benefits peak at intermediate diversity. The reviewed studies provide strong, almost invariable, evidence that more variable populations are less vulnerable to environmental changes, show decreased fluctuations in population size, have superior establishment success, larger distribution ranges, and are less extinction prone, compared with less variable populations or species. Given the overwhelming evidence that variation promotes population performance, it is important to identify conditions when increased variation does not have the theoretically expected effect, a question of considerable importance in biodiversity management, where there are many other practical constraints. We find that experimental outcomes generally support the notion that genetic and phenotypic variation is of greater importance under more stressful than under benign conditions. Finally, population performance increased linearly with increasing diversity in the majority (10 of 12) of manipulation studies that included four or more diversity levels; only two experiments detected curvilinear relationships.     

Extinction,recolonization, and the genetic structure of tidepool copepod populations

Summary Extinction and recolonization in metapopulations may either increase or decrease genetic differentiation among populations, but recent genetic models predict increased differentiation under most circumstances of recolonization. I examine this prediction empirically using tidepool populations of the marine tidepool copepodTigriopus californicus. The probability of extinction of tidepool populations was sufficiently high to invoke the model's predictions, but varied among populations. Nearly 75% of colonizing groups consisted of 10 or fewer individuals. The genetic effective size of colonizing groups might be as high as 18, depending on assumptions, but colonists probably originated from a subset of local populations. In contrast to my predictions, genetic differentiation was smaller among younger tidepool populations than among older populations on each of three rock outcrops, suggesting that genetic differentiation was reduced by metapopulation dynamics. The discrepancy between the prediction and the results may be explained by the unmet assumptions of classical metapopulation structure underlying the genetic models.     

种群统计随机性和环境随机性对种群绝灭的影响

影响种群绝灭的随机干扰可分为种群统计随机性、环境随机性和随机灾害三大类。在相对稳定的环境条件下和相对较短的时间内,以前两类随机干扰对种群绝灭的影响为生态学家关注的焦点。但是,由于自然种群动态及其影响因子的复杂特征,进一步深入研究随机干扰对种群绝灭的作用在理论上和实践上都必须发展新的技术手段。本文回顾了种群统计随机性与环境随机性的概念起源与发展,系统阐述了其分析方法。归纳了两类随机性在种群绝灭研究中的应用范围、作用方式和特点的异同和区别方法。各类随机作用与种群动态之间关系的理论研究与对种群绝灭机理的实践研究紧密相关。根据理论模型模拟和自然种群实际分析两方面的研究现状,作者提出了进一步深入研究随机作用与种群非线性动态方法的策略。指出了随机干扰影响种群绝灭过程的研究的方向：更多的研究将从单纯的定性分析随机干扰对种群动力学简单性质的作用,转向结合特定的种群非线性动态特征和各类随机力作用特点具体分析绝灭极端动态的成因,以期做出精确的预测。     

Effects of ecogeographic variables on genetic variation in montane mammals: implications for conservation in a global warming scenario

Aim Evolutionary theory predicts that levels of genetic variation in island populations will be positively correlated with island area and negatively correlated with island isolation. These patterns have been empirically established for oceanic islands, but little is known about the determinants of variation on habitat islands. The goals of this study were twofold. Our first aim was to test whether published patterns of genetic variation in mammals occurring on montane habitat islands in the American Southwest conformed to expectations based on evolutionary theory. The second aim of this research was to develop simple heuristic models to predict changes in genetic variation that may occur in these populations as a result of reductions in available mountaintop habitat in response to global warming. Location Habitat islands of conifer forest on mountaintops in the American Southwest. Methods Relationships between island area and isolation with measures of allozyme variation in four species of small mammal, namely the least chipmunk (Tamias minimus), Colorado chipmunk (Tamias quadrivittatus), red squirrel (Tamiasciurus hudsonicus), and Mexican woodrat (Neotoma mexicana), were determined using correlation and regression techniques. Significant relationships between island area and genetic variation were used to develop three distinct statistical models with which to predict changes in genetic variation following reduction in insular habitat area arising from global warming. Results Patterns of genetic variation in each species conformed to evolutionary predictions. In general, island area was the most important determinant of heterozygosity, while island isolation was the most important determinant of polymorphism and allelic diversity. The heuristic models predicted widespread reductions in genetic variation, the extent of which depended on the population and model considered. Main conclusions The results support a generalized pattern of genetic variation for any species with an insular distribution, with reduced variation in smaller, more isolated populations. We predict widespread reductions in genetic variation in isolated populations of montane small mammals in the American Southwest as a result of global warming. We conclude that climate‐induced reductions in the various dimensions of genetic variation may increase the probability of population extinction in both the short and long term.     

The influence of patch demographics on metapopulations, with particular reference to successional landscapes

The classical view of metapopulations relates the regional abundance of a species to the balance between the extinction and colonization dynamics of identical local populations. Species in successional landscapes may represent the most appropriate examples of classical metapopulations. However, Levins‐type metapopulation models do not explicitly separate population loss due to successional habitat change from other causes of extinction. A further complication is that the chance of population loss due to successional habitat change may be related to the age of a patch. I developed simple patch occupancy models to include succession and included consideration of patch age structure to address two related questions: what are the implications of changes in patch demographic rates and when is a move to a structured patch occupancy model justified? Age‐related variation in patch demography could increase or decrease the equilibrium fraction of the available habitat occupied by a species when compared to the predictions of an unstructured model. Metapopulation persistence was enhanced when the age class of patches with the highest species occupancy suffered relatively low losses to habitat succession. Conversely, when the age class of patches with the highest species occupancy also had relatively high successional loss rates, extinction thresholds were higher that would be predicted by a simple unstructured model. Hence age‐related variation in patch successional rate introduces biases into the predictions of simple unstructured models. Such biases can be detected from field surveys of the fraction of occupied and unoccupied patches in each age class. Where a bias is demonstrated, unstructured models will not be adequate for making predictions about the effects of changing parameters on metapopulation size. Thinking in successional terms emphasizes how landscapes might be managed to enhance or reduce the patch occupancy by any particular metapopulation     

Phylogenetic,spatial and environmental components of extinction risk in carnivores

Aim Extinction risk is non‐randomly distributed across phylogeny and space and is influenced by environmental conditions. We quantified the relative contribution of these factors to extinction risk to unveil the underlying macroecological processes and derive predictive models. Location Global. Methods Based on the IUCN global assessments, we divided 192 carnivore species into two dichotomous classes representing different levels of extinction risk. We used spatial proximity, phylogenetic relationship and environmental variables together with phylogenetic eigenvector regression and spatial eigenvector filters to model and predict threat status. Results Our full models explained between 57% and 96% of the variance in extinction risk. Phylogeny and spatial proximity roughly explained between 21% and 70% of the total variation in all analyses, while the explanatory power of environmental conditions was relatively weaker (up to 15%). Phylogeny and spatial proximity contributed equally to the explained variance in the lower threat level, while spatial proximity was the most important factor in the models of the higher threat level. Prediction of threat status achieved 97% correct assignments. Main conclusions Our approach differs fundamentally from current studies of extinction risk because it does not necessarily rely on life‐history information. We clearly show that instead of treating phylogenetic inertia and spatial signal as statistical nuisances, space and phylogeny should be viewed as very useful in explaining a wide range of phenomena in comparative studies.     

Community extinction patterns in coloured environments

Understanding community responses to environmental variation is a fundamental aspect of ecological research, with direct ecological, conservation and economic implications. Here, we examined the role of the magnitude, correlation and autocorrelation structures of environmental variation on species' extinction risk (ER), and the probability of actual extinction events in model competitive communities. Both ER and probability increased with increasing positive autocorrelation when species responded independently to the environment, yet both decreased with a strong correlation between species-specific responses. These results are framed in terms of the synchrony between--and magnitude of variation within--species population sizes and are explained in terms of differences in noise amplification under different conditions. The simulation results are robust to changes in the strength of interspecific density dependence, and whether noise affects density-independent or density-dependent population processes. Similar patterns arose under different ranges of noise severity when these different model assumptions were examined. We compared our results with those from an analytically derived solution, which failed to capture many features of the simulation results.     

When and where to move: Dynamic occupancy models explain the range dynamics of a food nomadic bird under climate and land cover change

Globally, long‐term research is critical to monitor the responses of tropical species to climate and land cover change at the range scale. Citizen science surveys can reveal the long‐term persistence of poorly known nomadic tropical birds occupying fragmented forest patches. We applied dynamic occupancy models to 13 years (2002–2014) of citizen science‐driven presence/absence data on Cape parrot (Poicephalus robustus), a food nomadic bird endemic to South Africa. We modeled its underlying range dynamics as a function of resource distribution, and change in climate and land cover through the estimation of colonization and extinction patterns. The range occupancy of Cape parrot changed little over time (ψ = 0.75–0.83) because extinction was balanced by recolonization. Yet, there was considerable regional variability in occupancy and detection probability increased over the years. Colonizations increased with warmer temperature and area of orchards, thus explaining their range shifts southeastwards in recent years. Although colonizations were higher in the presence of nests and yellowwood trees (Afrocarpus and Podocarpus spp.), the extinctions in small forest patches (≤227 ha) and during low precipitation (≤41 mm) are attributed to resource constraints and unsuitable climatic conditions. Loss of indigenous forest cover and artificial lake/water bodies increased extinction probabilities of Cape parrot. The land use matrix (fruit farms, gardens, and cultivations) surrounding forest patches provides alternative food sources, thereby facilitating spatiotemporal colonization and extinction in the human‐modified matrix. Our models show that Cape parrots are vulnerable to extreme climatic conditions such as drought which is predicted to increase under climate change. Therefore, management of optimum sized high‐quality forest patches is essential for long‐term survival of Cape parrot populations. Our novel application of dynamic occupancy models to long‐term citizen science monitoring data unfolds the complex relationships between the environmental dynamics and range fluctuations of this food nomadic species.     

Climate and the range dynamics of species with imperfect detection

Reliable predictions for species range changes require a mechanistic understanding of range dynamics in relation to environmental variation. One obstacle is that most current models are static and confound occurrence with the probability of detecting a species if it occurs at a site. Here we draw attention to recently developed occupancy models, which can be used to examine colonization and local extinction or changes in occupancy over time. These models further account for detection probabilities, which are likely to vary spatially and temporally in many datasets. Occupancy models require repeated presence/absence surveys, for example checklists used in bird atlas projects. As an example, we examine the recent range expansion of hadeda ibises (Bostrychia hagedash) in South African protected areas. Colonization exceeded local extinction in most biomes, and the probability of occurrence was related to local climate. Extensions of the basic occupancy models can estimate abundance or species richness. Occupancy models are an appealing additional tool for studying species' responses to global change.     

Colonization in metapopulations: a review of theory and observations

In metapopulation dynamics turnover of populations in isolated patches may be frequent. Regional survival of a species in such a system with frequent extinctions hinges on its colonization ability. Colonization is more than just dispersal; when a propagule reaches a new patch it faces higher extinction probabilities than does an established population. Extinction models as well as empirical data suggest that a large propagule with a potential for rapid increase in a varying environment, or with a low mortality rate in an environment perceived as constant, has a higher probability of successful colonization. Large variation in population size when it is still small increases the risk of failure. Factors introducing such variation are demographic stochasticity and environmental variation. It is hard to single out demographic traits that ensure good colonizing ability, since colonization can be achieved in many different ways, but generalists and species with self-fertilization seem to be superior.     

Uncertainty in assessing the impacts of global change with coupled dynamic species distribution and population models

Concern over rapid global changes and the potential for interactions among multiple threats are prompting scientists to combine multiple modelling approaches to understand impacts on biodiversity. A relatively recent development is the combination of species distribution models, land‐use change predictions, and dynamic population models to predict the relative and combined impacts of climate change, land‐use change, and altered disturbance regimes on species' extinction risk. Each modelling component introduces its own source of uncertainty through different parameters and assumptions, which, when combined, can result in compounded uncertainty that can have major implications for management. Although some uncertainty analyses have been conducted separately on various model components – such as climate predictions, species distribution models, land‐use change predictions, and population models – a unified sensitivity analysis comparing various sources of uncertainty in combined modelling approaches is needed to identify the most influential and problematic assumptions. We estimated the sensitivities of long‐run population predictions to different ecological assumptions and parameter settings for a rare and endangered annual plant species (Acanthomintha ilicifolia, or San Diego thornmint). Uncertainty about habitat suitability predictions, due to the choice of species distribution model, contributed most to variation in predictions about long‐run populations.     

Phenotypic distribution models corroborate species distribution models: A shift in the role and prevalence of a dominant prairie grass in response to climate change

Phenotypic distribution within species can vary widely across environmental gradients but forecasts of species’ responses to environmental change often assume species respond homogenously across their ranges. We compared predictions from species and phenotype distribution models under future climate scenarios for Andropogon gerardii, a widely distributed, dominant grass found throughout the central United States. Phenotype data on aboveground biomass, height, leaf width, and chlorophyll content were obtained from 33 populations spanning a ~1000 km gradient that encompassed the majority of the species’ environmental range. Species and phenotype distribution models were trained using current climate conditions and projected to future climate scenarios. We used permutation procedures to infer the most important variable for each model. The species‐level response to climate was most sensitive to maximum temperature of the hottest month, but phenotypic variables were most sensitive to mean annual precipitation. The phenotype distribution models predict that A. gerardii could be largely functionally eliminated from where this species currently dominates, with biomass and height declining by up to ~60% and leaf width by ~20%. By the 2070s, the core area of highest suitability for A. gerardii is projected to shift up to ~700 km northeastward. Further, short‐statured phenotypes found in the present‐day short grass prairies on the western periphery of the species’ range will become favored in the current core ~800 km eastward of their current location. Combined, species and phenotype models predict this currently dominant prairie grass will decline in prevalence and stature. Thus, sourcing plant material for grassland restoration and forage should consider changes in the phenotype that will be favored under future climate conditions. Phenotype distribution models account for the role of intraspecific variation in determining responses to anticipated climate change and thereby complement predictions from species distributions models in guiding climate adaptation strategies.     

Interspecific competition constrains local abundance in highly suitable areas

Sites with high environmental suitability for species’ occurrence, in terms of abiotic conditions, may hold populations with higher local abundances by increasing reproductive and survival rates and decreasing extinction rate. Interspecific competition, however, may affect this relationship. Here we tested the hypothesis that local abundance of the gray slender opossum Marmosops incanus is affected by the local richness of potential competitors and environmental suitability derived from ecological niche models (ENMs). We also discuss the ability of distinct modelling methods to predict species’ abundance. We compiled occurrence records and information about M. incanus’ relative abundance from museums and published articles. Environmental suitability was derived from five algorithms using seven environmental predictors. To assess our hypothesis, we chose the best statistical models among generalised linear models and quantile regressions, and then tested whether the effects of richness of competitors on local abundance are stronger under highly suitable conditions. We found that environmental suitability given by presence-only methods are positively related to the maximum abundance of M. incanus. That is, species’ local abundance is low when suitability is low but can be either low or high when suitability is high. The richness of competitors, in turn, explains the abundance variation within sites with high environmental suitability. We strongly recommend that the relationship between abundance and suitability must be carefully interpreted when using ENMs to predict species’ distribution because biotic interactions can be the main driver of local abundance within highly suitable environments.     

Native drivers of fish life history traits are lost during the invasion process

Rapid adaptation to global change can counter vulnerability of species to population declines and extinction. Theoretically, under such circumstances both genetic variation and phenotypic plasticity can maintain population fitness, but empirical support for this is currently limited. Here, we aim to characterize the role of environmental and genetic diversity, and their prior evolutionary history (via haplogroup profiles) in shaping patterns of life history traits during biological invasion. Data were derived from both genetic and life history traits including a morphological analysis of 29 native and invasive populations of topmouth gudgeon Pseudorasbora parva coupled with climatic variables from each location. General additive models were constructed to explain distribution of somatic growth rate (SGR) data across native and invasive ranges, with model selection performed using Akaike's information criteria. Genetic and environmental drivers that structured the life history of populations in their native range were less influential in their invasive populations. For some vertebrates at least, fitness‐related trait shifts do not seem to be dependent on the level of genetic diversity or haplogroup makeup of the initial introduced propagule, nor of the availability of local environmental conditions being similar to those experienced in their native range. As long as local conditions are not beyond the species physiological threshold, its local establishment and invasive potential are likely to be determined by local drivers, such as density‐dependent effects linked to resource availability or to local biotic resistance.     

The Role of Density Regulation in Extinction Processes and Population Viability Analysis

We review the role of density dependence in the stochastic extinction of populations and the role density dependence has played in population viability analysis (PVA) case studies. In total, 32 approaches have been used to model density regulation in theoretical or applied extinction models, 29 of them are mathematical functions of density dependence, and one approach uses empirical relationships between density and survival, reproduction, or growth rates. In addition, quasi-extinction levels are sometimes applied as a substitute for density dependence at low population size. Density dependence further has been modelled via explicit individual spacing behaviour and/or dispersal. We briefly summarise the features of density dependence available in standard PVA software, provide summary statistics about the use of density dependence in PVA case studies, and discuss the effects of density dependence on extinction probability. The introduction of an upper limit for population size has the effect that the probability of ultimate extinction becomes 1. Mean time to extinction increases with carrying capacity if populations start at high density, but carrying capacity often does not have any effect if populations start at low numbers. In contrast, the Allee effect is usually strong when populations start at low densities but has only a limited influence on persistence when populations start at high numbers. Contrary to previous opinions, other forms of density dependence may lead to increased or decreased persistence, depending on the type and strength of density dependence, the degree of environmental variability, and the growth rate. Furthermore, effects may be reversed for different quasi-extinction levels, making the use of arbitrary quasi-extinction levels problematic. Few systematic comparisons of the effects on persistence between different models of density dependence are available. These effects can be strikingly different among models. Our understanding of the effects of density dependence on extinction of metapopulations is rudimentary, but even opposite effects of density dependence can occur when metapopulations and single populations are contrasted. We argue that spatially explicit models hold particular promise for analysing the effects of density dependence on population viability provided a good knowledge of the biology of the species under consideration exists. Since the results of PVAs may critically depend on the way density dependence is modelled, combined efforts to advance statistical methods, field sampling, and modelling are urgently needed to elucidate the relationships between density, vital rates, and extinction probability.     

Minimum viable population sizes and global extinction risk are unrelated

Theoretical and empirical work has shown that once reduced in size and geographical range, species face a considerably elevated risk of extinction. We predict minimum viable population sizes (MVP) for 1198 species based on long-term time-series data and model-averaged population dynamics simulations. The median MVP estimate was 1377 individuals (90% probability of persistence over 100 years) but the overall distribution was wide and strongly positively skewed. Factors commonly cited as correlating with extinction risk failed to predict MVP but were able to predict successfully the probability of World Conservation Union Listing. MVPs were most strongly related to local environmental variation rather than a species' intrinsic ecological and life history attributes. Further, the large variation in MVP across species is unrelated to (or at least dwarfed by) the anthropogenic threats that drive the global biodiversity crisis by causing once-abundant species to decline.     

Long-term demographic surveys reveal a consistent relationship between average occupancy and abundance within local populations of a butterfly metapopulation

Species distribution models are the tool of choice for large-scale population monitoring, environmental association studies and predictions of range shifts under future environmental conditions. Available data and familiarity of the tools rather than the underlying population dynamics often dictate the choice of specific method – especially for the case of presence–absence data. Yet, for predictive purposes, the relationship between occupancy and abundance embodied in the models should reflect the actual population dynamics of the modelled species. To understand the relationship of occupancy and abundance in a heterogeneous landscape at the scale of local populations, we built a spatio-temporal regression model of populations of the Glanville fritillary butterfly Melitaea cinxia in a Baltic Sea archipelago. Our data comprised nineteen years of habitat surveys and snapshot data of land use in the region. We used variance partitioning to quantify relative contributions of land use, habitat quality and metapopulation covariates. The model revealed a consistent and positive, but noisy relationship between average occupancy and mean abundance in local populations. Patterns of abundance were highly variable across years, with large uncorrelated random variation and strong local population stochasticity. In contrast, the spatio-temporal random effect, habitat quality, population connectivity and patch size explained variation in occupancy, vindicating metapopulation theory as the basis for modelling occupancy patterns in fragmented landscapes. Previous abundance was an important predictor in the occupancy model, which points to a spillover of abundance into occupancy dynamics. While occupancy models can successfully model large-scale population structure and average occupancy, extinction probability estimates for local populations derived from occupancy-only models are overconfident, as extinction risk is dependent on actual, not average, abundance.