种群生存力分析研究进展和趋势

种群生存力分析（PVA）是正在迅速发展的新方法,已成为保护生物学研究的热点。它主要研究随机干扰对小种群绝灭的影响,其目的是制定最小可存活种群（MVP）,把绝灭减少到可接受的水平。随机干扰可分四类;统计随机性,环境随机性,自然灾害和遗传随机性。确定MVP的方法有三种：理论模型,模拟模型,模拟模型和岛屿生物地理学方法。理论模型主要研究理想或特定条件下随机因素对种群的影响;模拟模型是利用计算机模拟种群绝灭过程;岛屿生物地理学方法主要分析岛屿物种的分布和存活,证实分析模型和模拟模型。已有大量的文献研究统计随机性,环境随机性和自然灾害的行为特征,但遗传因素与种群生存力之间的关系还不清楚。建立包括四种随机性的综合性模型,广泛地检验PVA模型,系统地研制目标种的遗传和生态特性以及MVP的实际应用是PVA的发展趋势。     

Trophic interactions affect the population dynamics and risk of extinction of basal species in food webs

This paper addresses effects of trophic complexity on basal species, in a Lotka–Volterra model with stochasticity. We use simple food web modules, with three trophic levels, and expose every species to random environmental stochasticity and analyze (1) the effect of the position of strong trophic interactions on temporal fluctuations in basal species’ abundances and (2) the relationship between fluctuation patterns and extinction risk. First, the numerical simulations showed that basal species do not simply track the environment, i.e. species dynamics do not simply mirror the characteristics of the applied environmental stochasticity. Second, the extinction risk of species was related to the fluctuation patterns of the species.More specifically, we show (i) that despite being forced by random stochasticity without temporal autocorrelation (i.e. white noise), there is significant temporal autocorrelation in the time series of all basal species’ abundances (i.e. the spectra of basal species are red-shifted), (ii) the degree of temporal autocorrelation in basal species time series is affected by food web structure and (iii) the degree of temporal autocorrelation tend to be correlated to the extinction risks of basal species.Our results emphasize the role of food web structure and species interactions in modifying the response of species to environmental variability. To shed some light on the mechanisms we compare the observed pattern in abundances of basal species with analytically predicted patterns and show that the change in the predicted pattern due to the addition of strong trophic interactions is correlated to the extinction risk of the basal species. We conclude that much remain to be understood about the mechanisms behind the interaction among environmental variability, species interactions, population dynamics and vulnerability before we quantitatively can predict, for example, effects of climate change on species and ecological communities. Here, however, we point out a new possible approach for identifying species that are vulnerable to environmental stochasticity by checking the degree of temporal autocorrelation in the time series of species. Increased autocorrelation in population fluctuations can be an indication of increased extinction risk.     

Food web structure and interaction strength pave the way for vulnerability to extinction

This paper focuses on how food web structure and interactions among species affects the vulnerability, due to environmental variability, to extinction of species at different positions in model food webs. Vulnerability is here not measured by a traditional extinction threshold but is instead inspired by the IUCN criteria for endangered species: an observed rapid decline in population abundance. Using model webs influenced by stochasticity with zero autocorrelation, we investigate the ecological determinants of species vulnerability, i.e. the trophic interactions between species and food web structure and how these interact with the risk of sudden drops in abundance of species. We find that (i) producers fulfil the criterion of vulnerable species more frequently than other species, (ii) food web structure is related to vulnerability, and (iii) the vulnerability of species is greater when involved in a strong trophic interaction than when not. We note that our result on the relationship between extinction risk and trophic position of species contradict previous suggestions and argue that the main reason for the discrepancy probably is due to the fact that we study the vulnerability to environmental stochasticity and not extinction risk due to overexploitation, habitat destruction or interactions with introduced species. Thus, we suggest that the vulnerability of species to environmental stochasticity may be differently related to trophic position than the vulnerability of species to other factors. Earlier research on species extinctions has looked for intrinsic traits of species that correlate with increased vulnerability to extinction. However, to fully understand the extinction process we must also consider that species interactions may affect vulnerability and that not all extinctions are the result of long, gradual reductions in species abundances. Under environmental stochasticity (which importance frequently is assumed to increase as a result of climate change) and direct and indirect interactions with other species some extinctions may occur rapidly and apparently unexpectedly. To identify the first declines of population abundances that may escalate and lead to extinctions as early as possible, we need to recognize which species are at greatest risk of entering such dangerous routes and under what circumstances. This new perspective may contribute to our understanding of the processes leading to extinction of populations and eventually species. This is especially urgent in the light of the current biodiversity crisis where a large fraction of the world's biodiversity is threatened.     

Extinction and invasion do not add up in noisy dynamic ecological networks

Species extinction and invasion concurrently affect the composition and properties of ecological communities, yet their effects have largely been studied separately, and with more focus on species and ecological functional groups than the whole-community level. We adopted a dynamic ecological network approach to compare the effects of simultaneous single-species primary extinction and invasion on a set of ecosystem metrics to the effects of extinction and invasion in isolation. We also investigated the relationship between the impact and reversibility of extinction or invasion through reintroduction or eradication, respectively. We used Monte Carlo simulations of bioenergetic ecological network models that combined trophic and mutualistic interactions, contained either prey-dependent or ratio-dependent trophic functional responses, and incorporated either white or pink environmental stochasticity. As the separate extinction or invasion impact increased, the simultaneous extinction–invasion impact increased but was decreasingly additive of the two separate impacts, across all ecosystem metrics. Greater extinction or invasion impact was associated with lower reversibility for most model types and ecosystem metrics. There were also systematic differences between models with prey- and ratio-dependent functional responses. These results highlight the importance of considering the combined effects of extinction and invasion in ecological studies, management and restoration.     

Density-dependent demographic variation determines extinction rate of experimental populations

Understanding population extinctions is a chief goal of ecological theory. While stochastic theories of population growth are commonly used to forecast extinction, models used for prediction have not been adequately tested with experimental data. In a previously published experiment, variation in available food was experimentally manipulated in 281 laboratory populations of Daphnia magna to test hypothesized effects of environmental variation on population persistence. Here, half of those data were used to select and fit a stochastic model of population growth to predict extinctions of populations in the other half. When density-dependent demographic stochasticity was detected and incorporated in simple stochastic models, rates of population extinction were accurately predicted or only slightly biased. However, when density-dependent demographic stochasticity was not accounted for, as is usual when forecasting extinction of threatened and endangered species, predicted extinction rates were severely biased. Thus, an experimental demonstration shows that reliable estimates of extinction risk may be obtained for populations in variable environments if high-quality data are available for model selection and if density-dependent demographic stochasticity is accounted for. These results suggest that further consideration of density-dependent demographic stochasticity is required if predicted extinction rates are to be relied upon for conservation planning.     

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。     

The effect of phenotypic variation on metapopulation persistence

Demographic stochasticity (due to the probabilistic nature of the birth–death process) and demographic heterogeneity (between-individual differences in demographic parameters) have long been seen as factors affecting extinction risk. While demographic stochasticity can be independent of underlying species traits, demographic heterogeneity may strongly depend on phenotypic variation. However, how phenotypic variation can affect extinction risk is largely unknown. Here, I develop a stochastic metapopulation model that takes into account the effects of demographic stochasticity and phenotypic variation in the traits controlling colonization rates to assess what the effect of phenotypic variation may be on the persistence of the metapopulation. Although phenotypic variation can lead to a decrease in metapopulation persistence under some conditions, it also may lead to an increase in persistence whenever phenotypic mismatch—or the distance between the optimal trait value and the population mean—is large. This mismatch can in turn arise from a variety of ecological and evolutionary reasons, including weak selection or a recent history of invasion. Last, the effect of phenotypic variation has a deterministic component on colonization rates, and a stochastic component on persistence through colonization rates, but both are important to understand the overall effect. These results have important implications for the conservation of threatened species and management practices that may historically have overlooked phenotypic variation as unimportant noise around mean values of interest.     

Stochastic population theory faces reality in the laboratory

Understanding the factors that affect most severely the extinction risk of populations is crucial for maintaining biodiversity. An important general pattern derived from stochastic population theory is that time to extinction should decrease with increasing environmental stochasticity. Drake and Lodge recently provided one of the first pieces of experimental support for this simple prediction by artificially manipulating the dynamics of populations of Daphnia. A future challenge will be to include both demographic stochasticity and environmental stochasticity in such studies.     

Quantifying introgression risk with realistic population genetics

Introgression is the permanent incorporation of genes from the genome of one population into another. This can have severe consequences, such as extinction of endemic species, or the spread of transgenes. Quantification of the risk of introgression is an important component of genetically modified crop regulation. Most theoretical introgression studies aimed at such quantification disregard one or more of the most important factors concerning introgression: realistic genetical mechanisms, repeated invasions and stochasticity. In addition, the use of linkage as a risk mitigation strategy has not been studied properly yet with genetic introgression models. Current genetic introgression studies fail to take repeated invasions and demographic stochasticity into account properly, and use incorrect measures of introgression risk that can be manipulated by arbitrary choices. In this study, we present proper methods for risk quantification that overcome these difficulties. We generalize a probabilistic risk measure, the so-called hazard rate of introgression, for application to introgression models with complex genetics and small natural population sizes. We illustrate the method by studying the effects of linkage and recombination on transgene introgression risk at different population sizes.     

Metapopulation extinction risk is increased by environmental stochasticity and assemblage complexity

Extinction risk is a key area of investigation for contemporary ecologists and conservation biologists. Practical conservation efforts for vulnerable species can be considerably enhanced by thoroughly understanding the ecological processes that interact to determine species persistence or extinction. Theory has highlighted the importance of both extrinsic environmental factors and intrinsic demographic processes. In laboratory microcosms, single-species single-habitat patch experimental designs have been widely used to validate the theoretical prediction that environmental heterogeneity can increase extinction risk. Here, we develop on this theme by testing the effects of fluctuating resource levels in experimental multispecies metapopulations. We compare a three-species host-parasitoid assemblage that exhibits apparent competition to the individual pairwise, host-parasitoid interactions. Existing theory is broadly supported for two-species assemblages: environmental stochasticity reduces trophic interaction persistence time, while metapopulation structure increases persistence time. However, with increasing assemblage complexity, the effects of trophic interactions mask environmental impacts and persistence time is further reduced, regardless of resource renewal regime. We relate our findings to recent theory, highlighting the importance of taking into account both intrinsic and extrinsic factors, over a range of spatial scales, in order to understand resource-consumer dynamics.     

Biodiversity and persistence of ecological communities in variable environments

Recent analyses of climate data indicate that the intensity and frequency of different weather extremes have increased. Such increased environmental variability may lead to increased species extinction rates and hence have important consequences for the long-term persistence of ecological communities. Here we use model communities in order to investigate the relationship between species richness and community persistence in a fluctuating environment. We model two scenarios: (1) correlated species responses to environmental fluctuations and (2) uncorrelated (independent) species responses. We quantify the risk and extent of species extinctions using the so-called community viability analysis. It is shown that species-rich communities are more sensitive to environmental stochasticity than species-poor communities. Specifically, per species risk of extinction is higher in species-rich communities than in species-poor ones. Moreover, for a given species richness, communities with uncorrelated species responses to environmental variation run a considerable higher risk of losing a fixed proportion of species compared with communities with correlated species responses. We discuss the compatibility of these results with the ecological insurance hypothesis.     

A genetic component of extinction risk in mammals

Genetic factors may play an important role in species extinction but their actual effect remains poorly understood, particularly because of a strong and potentially masking effect expected from ecological traits. We investigated the role of genetics in mammal extinction taking both ecological and genetic factors into account. As a proxy for the role of genetics we used the ratio of the rates of nonsynonymous (amino acid changing) to synonymous (leaving the amino acid unchanged) nucleotide substitutions, K_a / K_s. Because most nonsynonymous substitutions are likely to be slightly deleterious and thus selected against, this ratio is a measure of the inefficiency of selection: if large (but less than 1), it implies a low efficiency of selection against nonsynonymous mutations. As a result, nonsynonymous mutations may accumulate and thus contribute to extinction. As a proxy for the role of ecology we used body mass W, with which most extinction‐related ecological traits strongly correlate. As a measure of extinction risk we used species’ affiliation with the five levels of extinction threat according to the IUCN Red List of Threatened Species. We calculated K_a / K_s for mitochondrial protein‐coding genes of 211 mammalian species, each of which was characterized by body mass and the level of threat. Using logistic regression analysis, we then constructed a set of logistic regression models of extinction risk on ln(K_a / K_s) and lnW. We found that K_a / K_s and body mass are responsible for a 38% and a 62% increase in extinction risk, respectively. Given that the standard error of these values is 13%, the contribution of genetic factors to extinction risk in mammals is estimated to be one‐quarter to one‐half of the total of ecological and genetic effects. We conclude that the effect of genetics on extinction is significant, though it is almost certainly smaller than the effect of ecological traits. Synthesis Mutation provides the material for evolution. However, most mutations that play a role in evolution are slightly deleterious and thus may contribute to extinction. We assess the role of mitochondrial DNA mutations in mammalian extinction risk and find it to be one‐quarter to one‐half of the total of mutation and body mass effects, where body mass represents an integral measure of extinction‐related ecological traits. Genetic factors may be all the more important, because ecological traits associated with large body mass would both promote and protect from extinction, while mutation accumulation caused by low effective population size seems to have no counterbalance.     

Distribution, ecology, life history, genetic variation, and risk of extinction of nonhuman primates from Costa Rica

We examined the association between geographic distribution, ecological traits, life history, genetic diversity, and risk of extinction in nonhuman primate species from Costa Rica. All of the current nonhuman primate species from Costa Rica are included in the study; spider monkeys (Ateles geoffroyi), howling monkeys (Alouatta palliata), capuchins (Cebus capucinus), and squirrel monkeys (Saimiri oerstedii). Geographic distribution was characterized accessing existing databases. Data on ecology and life history traits were obtained through a literature review. Genetic diversity was characterized using isozyme electrophoresis. Risk of extinction was assessed from the literature. We found that species differed in all these traits. Using these data, we conducted a Pearson correlation between risk of extinction and ecological and life history traits, and genetic variation, for widely distributed species. We found a negative association between risk of extinction and population birth and growth rates; indicating that slower reproducing species had a greater risk of extinction. We found a positive association between genetic variation and risk of extinction; i.e., species showing higher genetic variation had a greater risk of extinction. The relevance of these traits for conservation efforts is discussed.     

Genetic similarity and hatching success in birds

The ecological correlates of fitness costs of genetic similarity in free-living, large populations of organisms are poorly understood. Using a dataset of genetic similarity as reflected by band-sharing coefficients of minisatellites, we show that bird species with higher genetic similarity experience elevated hatching failure of eggs, increasing by a factor of six across 99 species. Island distributions and cooperative breeding systems in particular were associated with elevated genetic similarity. These findings provide comparative evidence of detrimental fitness consequences of high genetic similarity across a wide range of species, and help to identify ecological factors potentially associated with increased risk of extinction.     

Genetics and conservation biology

Conservation genetics encompasses genetic management of small populations, resolution of taxonomic uncertainties and management units, and the use of molecular genetic analyses in forensics and to understanding species' biology. The role of genetic factors in extinctions of wild populations has been controversial, but evidence now shows that they make important contributions to extinction risk. Inbreeding has been shown to cause extinctions of wild populations, computer projections indicate that inbreeding depression has important effects on extinction risk, and most threatened species show signs of genetic deterioration. Inappropriate management is likely to result if genetic factors are ignored in threatened species management.     

Can life history predict the effect of demographic stochasticity on extinction risk?

Demographic stochasticity is important in determining extinction risks of small populations, but it is largely unknown how its effect depends on the life histories of species. We modeled effects of demographic stochasticity on extinction risk in a broad range of generalized life histories, using matrix models and branching processes. Extinction risks of life histories varied greatly in their sensitivity to demographic stochasticity. Comparing life histories, extinction risk generally increased with increasing fecundity and decreased with higher ages of maturation. Effects of adult survival depended on age of maturation. At lower ages of maturation, extinction risk peaked at intermediate levels of adult survival, but it increased along with adult survival at higher ages of maturation. These differences were largely explained by differences in sensitivities of population growth to perturbations of life-history traits. Juvenile survival rate contributed most to total demographic variance in the majority of life histories. Our general results confirmed earlier findings, suggesting that empirical patterns can be explained by a relatively simple model. Thus, basic life-history information can be used to assign life-history-specific sensitivity to demographic stochasticity. This is of great value when assessing the vulnerability of small populations.     

Why are Dormice rare? A case study in conservation biology

In the last 100 years, the Dormouse Muscardinus avellcmarius has disappeared from about half its geographical range in Britain. Evidence is presented which indicates that declining range and numbers are due to a complex interplay of factors which include fragmentation, deterioration and loss of specialized habitat. The Dormouse is unusual in being a relatively A-selected small mammal, with exacting ecological requirements which render it very vulnerable, particularly to habitat fragmentation. The Dormouse is also sensitive to climate, both directly and probably indirectly through the effects of weather on the timing and abundance of food (insects, flowers and fruits). Combined with low population density and low intrinsic rate of population increase, this makes the Dormouse highly vulnerable, not just to absolute climatic measures (e.g. temperature, rainfall), but especially to climatic stochasticity, particularly at the edge of its range. There are strong associations between the distribution and changing status of the Dormouse and various climatic parameters, and clear parallels with other climate-sensitive taxa, notably bats and butterflies.
The Dormouse is a very specialized species, highly sensitive to environmental change, resulting in its piecemeal, progressive extinction, particularly in northern counties. It is likely to be a very sensitive indicator species for monitoring future changing environments and an excellent model for studying the effects of habitat fragmentation, climatic shifts and climatic stochasticity.     

Extinctions in competitive communities forced by coloured environmental variation

Understanding the relationships between environmental fluctuations, population dynamics and species interactions in natural communities is of vital theoretical and practical importance. This knowledge is essential in assessing extinction risks in communities that are, for example, pressed by changing environmental conditions and increasing exploitation. We developed a model of density dependent population renewal, in a Lotka–Volterra competitive community context, to explore the significance of interspecific interactions, demographic stochasticity, population growth rate and species abundance on extinction risk in populations under various autocorrelation (colour) regimes of environmental forcing. These factors were evaluated in two cases, where either a single species or the whole community was affected by the external forcing. Species' susceptibility to environmental noise with different autocorrelation structure depended markedly on population dynamics, species' position in the abundance hierarchy and how similarly community members responded to external forcing. We also found interactions between demographic stochasticity and environmental noise leading to a reversal in extinction probabilities from under- to overcompensatory dynamics. We compare our results with studies of single species populations and contrast possible mechanisms leading to extinctions. Our findings indicate that abundance rank, the form of population dynamics, and the colour of environmental variation interact in affecting species extinction risk. These interactions are further modified by interspecific interactions within competitive communities as the interactions filter and modulate the environmental noise.     

Determinants of extinction in fragmented plant populations: Crepis sancta (asteraceae) in urban environments

Local populations are subject to recurrent extinctions, and small populations are particularly prone to extinction. Both demographic (stochasticity and the Allee effect) and genetic factors (drift load and inbreeding depression) potentially affect extinction. In fragmented populations, regular dispersal may boost population sizes (demographic rescue effect) or/and reduce the local inbreeding level and genetic drift (genetic rescue effect), which can affect extinction risks. We studied extinction processes in highly fragmented populations of the common species Crepis sancta (Asteraceae) in urban habitats exhibiting a rapid turnover of patches. A four-year demographic monitoring survey and microsatellite genotyping of individuals allowed us to study the determinants of extinction. We documented a low genetic structure and an absence of inbreeding (estimated by multilocus heterozygosity), which suggest that genetic factors were not a major cause of patch extinction. On the contrary, local population size was the main factor in extinction, whereas connectivity was shown to decrease patch extinction, which we interpreted as a demographic rescue effect that was likely due to better pollination services for reproduction. This coupling of demographic and genetic tools highlighted the importance of dispersal in local patch extinctions of small fragmented populations connected by gene flow.     

Introgressive hybridization as a mechanism for species rescue

Rapid evolution on ecological time scales can play a key role in species responses to environmental change. One dynamic that has the potential to generate the diversity necessary for evolution rapid enough to allow response to sudden environmental shifts is introgressive hybridization. However, if distinct sub-species exist before an environmental shift, mechanisms that impede hybridization, such as assortative mating and hybrid inferiority, are likely to be present. Here we explore the theoretical potential for introgressive hybridization to play a role in response to environmental change. In particular, we incorporate assortative mating, hybrid inferiority, and demographic stochasticity into a two-locus, two-allele population genetic model of two interacting species where one locus identifies the species and the other determines how fitness depends on the changing environment. Simulation results indicate that moderately high values for the strength of assortative mating will allow enough hybridization events to outweigh demographic stochasticity but not so many that continued hybridization outweighs backcrossing and introgression. Successful introgressive hybridization also requires intermediate relative fitness at the allele negatively affected by environmental change such that hybrid survivorship outweighs demographic stochasticity but selection remains strong enough to affect the genetic dynamics. The potential for successful introgression instead of extinction with greater environmental change is larger with monogamous rather than promiscuous mating due to lower stochasticity in mating events. These results suggest species characteristics (e.g., intermediate assortative mating and mating systems with low variation in mating likelihood) which indicate a potential for rapid evolution in response to environmental change via introgressive hybridization.