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。     

朱鹮(Nipponia nippon)种群生存力分析

到目前为止,只有一个野生朱鹮群体幸存下来,而且它的种群大小自1981年重新发现以来,一直在20只以下波动。本文应用种群生存力分析的方法,借助漩涡模型,根据朱鹮14年的种群数据,总结和预测了其种群动态,并着重研究了朱鹮的濒危程度。结果显示,按过去10余年的生存状况,朱鹮在50年内绝灭的可能性是98.5%,平均绝灭时间为15.72 年。现存种群数量很低,所以种群统计随机性对其命运有很大影响。灵敏度分析表明,当前的朱鹮种群对意外死亡和生存环境的波动较为敏感。保护工作的优先项目是对猎杀和天敌的控制以及从各个方面提高朱鹮的生活质量。     

朱■（Nipponianippon）种群生存力分析

到目前为止,只有一个野生朱群体幸存下来,而且它的种群大小自１９８１年重新发现以来,一直在２０只以下波动。本文应用种群生存力分析的方法,借助漩涡模型,根据朱１４年的种群数据,总结和预测了其种群动态,并着重研究了朱的濒危程度。结果显示,按过去１０余年的生存状况,朱在５０年内绝灭的可能性是９８．５％,平均绝灭时间为１５．７２年。现存种群数量很低,所以种群统计随机性对其命运有很大影响。灵敏度分析表明,当前的朱种群对意外死亡和生存环境的波动较为敏感。保护工作的优先项目是对猎杀和天敌的控制以及从各个方面提高朱的生活质量     

种群生存力分析:准确性和保护应用

目前已提出了五类估计濒危物种绝灭风险的种群生存力分析模型 ,即 :分析模型、单种群确定性模型、单种群随机模型、异质种群模型和显空间模型。模型的选择取决于物种的生活史特征和可用的数据。与用于保护实践的其他方法相比 ,种群生存力分析 (PVA)是相对准确的量化工具。然而 ,一些濒危物种种群统计学数据质量差和种群动态的有关假说模糊不清可能影响到模型预测的准确性 ,因此 ,要谨慎地使用PVA。在西方国家 ,PVA在濒危物种保护计划和管理中应用越来越广泛。它主要用于 :( 1)预测濒危物种未来的种群大小 ;( 2 )估计一定时间内物种的绝灭风险 ;( 3 )评估一套保护措施 ,确定哪个能使种群的存活时间最长 ;( 4)探索不同假说对小种群动态的影响 ;( 5 )指导濒危动物野外数据的搜集工作。我国的濒危物种很多 ,然而开展PVA研究的濒危物种却很少。应大力发展适合于模拟我国特有濒危物种及其保护问题的PVA模型     

污染环境中单种群生存分析

本文研究了污染环境中种群的动力学模型,基于已有结果,考虑了内禀增长率为非线性函数的情形.利用微分方程定性理论中的比较定理,对于种群的持续生存与绝灭给出了判别条件.     

非线性自食种群动力系统的稳定性

本文讨论了一类主要由昆虫自食引起的非线性种群动态模型的稳定性．首先给出确定性模型,并着重讨论其一个特殊情形．通过在参数空间中辨识稳定域的边界,可以相对直观地分析种群动态．对于随机模型,是利用在确定性模型中加入对数尺度下的正态随机项形成的,该模型具有较好的统计性质,便于将现实的非线性时间序列数据引进系统中来．     

动物的易绝灭特征与保护优先性

各种人为干扰和自然因素促使大量物种走向濒危和绝灭。物种濒危和绝灭不是随机的。具有某些特征的物种容易濒危和绝灭 ,即易绝灭特征。易绝灭特征包括个体大 ,繁殖力低 ,扩散能力弱 ,营养级高 ,家域大 ,种群小 ,种群波动大 ,分布范围窄 ,种群密度低 ,栖息地特化程度高和特殊栖息地类型等。研究物种的易绝灭特征可以为生物多样性提供预防性 (proac tive)的优先保护措施。尽管物种的易绝灭特征已经用于实际的物种保护中 ,然而由于物种的各种特征对物种濒危和绝灭的影响十分复杂 ,各个易绝灭特征还有待于进一步深入的、准确的研究。探讨适合不同类群和不同地区物种的易绝灭特征是十分必要的。由于特殊地史发育、中医药传统和边境频繁的非法野生动物贸易 ,我国动物的濒危模式可能与国外有所不同。     

广西银竹老山资源冷杉种群退化机制初探

资源冷杉是我国特有的珍稀濒危植物,局限分布在广西资源的银竹老山和湖南新宁的舜皇山。对银竹老山资源冷杉种群衰退状况的研究结果表明,导致资源冷杉种群退化的首要因素是发生频率高、影响范围广、持续时间长的人为砍伐破坏其所依存的森林环境以及其分布地的集中放牧,其次是它自身生物学特性的限制,也造成在自然状态下出现其种群数量不易扩大的局面。要实现资源冷杉种群的保护,解除其濒危状态,以免绝灭,必须立刻停止人为干扰,并进一步加强对它繁育系统的研究。     

贵州青岩油杉种群年龄结构和动态的研究

研究了青岩油杉种群年龄结构的类型,动态规律及其与群落演替和环境之间的相互关系。结果表明,青岩油杉种群年龄结构有增长型,稳定型,始衰型和中衰型4类,存活曲线呈现凹型,凸型,间断型和散点型,随着群落的发育和演替,青岩油杉种群年龄结构的变化趋势为增长型→稳定型→衰退型→残留型。青岩油杉本身的生物生态学特性,群落内阔叶树的发展,地理隔离,人为干扰等是影响青岩油杉种群年龄结构及其动态变化的重要因素。     

完达山东部地区东北虎主要猎物种群的时空动态模拟

基于能体现直接与间接人为干扰的不同意外死亡率和环境容纳量情景,使用景观尺度的动物种群模型（LAPS）模拟了1990—2009年完达山东部地区东北虎主要猎物种群的时空动态,研究了意外死亡率和环境容纳量对种群动态的影响,并直观展现了研究区内动物集群的时空分布状况,比较了不同生境斑块类型中个体密度的差异.结果表明：意外死亡率对研究区动物种群动态的影响较环境容纳量大;灌丛中动物种群的密度高于阔叶林中的密度.研究结果为有效进行东北虎主要猎物的保护与管理提供了科学依据,但相关的定量验证还需深入研究.     

Evolutionary rescue under demographic and environmental stochasticity

Populations suffer two types of stochasticity: demographic stochasticity, from sampling error in offspring number, and environmental stochasticity, from temporal variation in the growth rate. By modelling evolution through phenotypic selection following an abrupt environmental change, we investigate how genetic and demographic dynamics, as well as effects on population survival of the genetic variance and of the strength of stabilizing selection, differ under the two types of stochasticity. We show that population survival probability declines sharply with stronger stabilizing selection under demographic stochasticity, but declines more continuously when environmental stochasticity is strengthened. However, the genetic variance that confers the highest population survival probability differs little under demographic and environmental stochasticity. Since the influence of demographic stochasticity is stronger when population size is smaller, a slow initial decline of genetic variance, which allows quicker evolution, is important for population persistence. In contrast, the influence of environmental stochasticity is population-size-independent, so higher initial fitness becomes important for survival under strong environmental stochasticity. The two types of stochasticity interact in a more than multiplicative way in reducing the population survival probability. Our work suggests the importance of explicitly distinguishing and measuring the forms of stochasticity during evolutionary rescue.     

Demographic stochasticity and temporal autocorrelation in the dynamics of structured populations

Populations can show temporal autocorrelation in the dynamics arising from different mechanisms, including fluctuations in the demographic structure. This autocorrelation is often treated as a complicating factor in the analyses of stochastic population growth and extinction risk. However, it also reflects important information about the demographic structure. Here, we consider how temporal autocorrelation is related to demographic stochasticity in structured populations. Demographic stochasticity arises from inherent randomness in the demographic processes of individuals, like survival and reproduction, and the resulting impact on population growth is measured by the demographic variance. Earlier studies have shown that population structure have positive or negative effects on the demographic variance compared to a model where the structure is ignored. Here, we derive a new expression for the demographic variance of a structured population, using the temporal autocorrelation function of the population growth rate. We show that the relative difference in demographic variance when the structure is included or ignored (the effect of structure on demographic variance) is approximately twice the sum of the autocorrelations. We demonstrate the result for a simple hypothetical example, as well as a set of empirical examples using age‐structured models of 24 mammals from the demographic database COMADRE. In the empirical examples, the sum of the autocorrelation function was negative in all cases, indicating that age structure generally has a negative effect on the demographic variance (i.e. the demographic variance is lower compared to that of a model where the structure is ignored). Other kinds of structure, such as spatial heterogeneity affecting fecundity, can have positive effects on the demographic variance, and the sum of the autocorrelations will then be positive. These results yield new insights into the complex interplay between population structure, demographic variance, and temporal autocorrelation, that shapes the population dynamics and extinction risk of populations.     

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.     

Evolution of dispersal in metapopulations with local density dependence and demographic stochasticity

In this paper, we predict the outcome of dispersal evolution in metapopulations based on the following assumptions: (i) population dynamics within patches are density-regulated by realistic growth functions; (ii) demographic stochasticity resulting from finite population sizes within patches is accounted for; and (iii) the transition of individuals between patches is explicitly modelled by a disperser pool. We show, first, that evolutionarily stable dispersal rates do not necessarily increase with rates for the local extinction of populations due to external disturbances in habitable patches. Second, we describe how demographic stochasticity affects the evolution of dispersal rates: evolutionarily stable dispersal rates remain high even when disturbance-related rates of local extinction are low, and a variety of qualitatively different responses of adapted dispersal rates to varied levels of disturbance become possible. This paper shows, for the first time, that evolution of dispersal rates may give rise to monotonically increasing or decreasing responses, as well as to intermediate maxima or minima.     

Demographic stochasticity, allee effects, and extinction: the influence of mating system and sex ratio

Demographic stochasticity has a substantial influence on the growth of small populations and consequently on their extinction risk. Mating system is one of several population characteristics that may affect this. We use a stochastic pair-formation model to investigate the combined effects of mating system, sex ratio, and population size on demographic stochasticity and thus on extinction risk. Our model is designed to accommodate a continuous range of mating systems and sex ratios as well as several levels of stochasticity. We show that it is not mating system alone but combinations of mating system and sex ratio that are important in shaping the stochastic dynamics of populations. Specifically, polygyny has the potential to give a high demographic variance and to lower the stochastic population growth rate substantially, thus also shortening the time to extinction, but the outcome is highly dependent on the sex ratio. In addition, population size is shown to be important. We find a stochastic Allee effect that is amplified by polygyny. Our results demonstrate that both mating system and sex ratio must be considered in conservation planning and that appreciating the role of stochasticity is key to understanding their effects.     

Allee effects in stochastic populations

The Allee effect, or inverse density dependence at low population sizes, could seriously impact preservation and management of biological populations. The mounting evidence for widespread Allee effects has lately inspired theoretical studies of how Allee effects alter population dynamics. However, the recent mathematical models of Allee effects have been missing another important force prevalent at low population sizes: stochasticity. In this paper, the combination of Allee effects and stochasticity is studied using diffusion processes, a type of general stochastic population model that accommodates both demographic and environmental stochastic fluctuations. Including an Allee effect in a conventional deterministic population model typically produces an unstable equilibrium at a low population size, a critical population level below which extinction is certain. In a stochastic version of such a model, the probability of reaching a lower size a before reaching an upper size b , when considered as a function of initial population size, has an inflection point at the underlying deterministic unstable equilibrium. The inflection point represents a threshold in the probabilistic prospects for the population and is independent of the type of stochastic fluctuations in the model. In particular, models containing demographic noise alone (absent Allee effects) do not display this threshold behavior, even though demographic noise is considered an "extinction vortex". The results in this paper provide a new understanding of the interplay of stochastic and deterministic forces in ecological populations.     

Survival of small populations under demographic stochasticity.

We estimate the mean time to extinction of small populations in an environment with constant carrying capacity but under stochastic demography. In particular, we investigate the interaction of stochastic variation in fecundity and sex ratio under several different schemes of density dependent population growth regimes. The methods used include Markov chain theory, Monte Carlo simulations, and numerical simulations based on Markov chain theory. We find a strongly enhanced extinction risk if stochasticity in sex ratio and fluctuating population size act simultaneously as compared to the case where each mechanism acts alone. The distribution of extinction times deviates slightly from a geometric one, in particular for short extinction times. We also find that whether maximization of intrinsic growth rate decreases the risk of extinction or not depends strongly on the population regulation mechanism. If the population growth regime reduces populations above the carrying capacity to a size below the carrying capacity for large r (overshooting) then the extinction risk increases if the growth rate deviates from an optimal r-value.     

Demographic stochasticity alters expected outcomes in experimental and simulated non‐neutral communities

Theory has shown that the effects of demographic stochasticity on communities may depend on the magnitude of fitness differences between species. In particular, it has been suggested that demographic stochasticity has the potential to significantly alter competitive outcomes when fitness differences are small (nearly neutral), but that it has negligible effects when fitness differences are large (highly non‐neutral). Here we test such theory experimentally and extend it to examine how demographic stochasticity affects exclusion frequency and mean densities of consumers in simple, but non‐neutral, consumer–resource communities. We used experimental microcosms of protists and rotifers feeding on a bacterial resource to test how varying absolute population sizes (a driver of demographic stochasticity) affected the probability of competitive exclusion of the weakest competitor. To explore whether demographic stochasticity could explain our experimental results, and to generalize beyond our experiment, we paired the experiment with a continuous‐time stochastic model of resource competition, which we simulated for 11 different fitness inequalities between competiting consumers. Consistent with theory, in both our experiments and our simulations we found that demographic stochasticity altered competitive outcomes in communities where fitness differences were small. However, we also found that demographic stochasticity alone could affect communities in other ways, even when fitness differences between competitors were large. Specifically, demographic stochasticity altered mean densities of both weak and strong competitors in experimental and simulated communities. These findings highlight how demographic stochasticity can change both competitive outcomes in non‐neutral communities and the processes underlying overall community dynamics.     

Demography_Lab,an educational application to evaluate population growth: Unstructured and matrix models

Training in Population Ecology asks for scalable applications capable of embarking students on a trip from basic concepts to the projection of populations under the various effects of density dependence and stochasticity. Demography_Lab is an educational tool for teaching Population Ecology aspiring to cover such a wide range of objectives. The application uses stochastic models to evaluate the future of populations. Demography_Lab may accommodate a wide range of life cycles and can construct models for populations with and without an age or stage structure. Difference equations are used for unstructured populations and matrix models for structured populations. Both types of models operate in discrete time. Models can be very simple, constructed with very limited demographic information or parameter‐rich, with a complex density‐dependence structure and detailed effects of the different sources of stochasticity. Demography_Lab allows for deterministic projections, asymptotic analysis, the extraction of confidence intervals for demographic parameters, and stochastic projections. Stochastic population growth is evaluated using up to three sources of stochasticity: environmental and demographic stochasticity and sampling error in obtaining the projection matrix. The user has full control on the effect of stochasticity on vital rates. The effect of the three sources of stochasticity may be evaluated independently for each vital rate. The user has also full control on density dependence. It may be included as a ceiling population size controlling the number of individuals in the population or it may be evaluated independently for each vital rate. Sensitivity analysis can be done for the asymptotic population growth rate or for the probability of extinction. Elasticity of the probability of extinction may be evaluated in response to changes in vital rates, and in response to changes in the intensity of density dependence and environmental stochasticity.     

Long-term demographic analysis in goshawk <Emphasis Type="Italic">Accipiter gentilis</Emphasis>: the role of density dependence and stochasticity

Density dependence and environmental stochasticity are both potentially important processes influencing population demography and long-term population growth. Quantifying the importance of these two processes for population growth requires both long-term population as well as individual-based data. I use a 30-year data set on a goshawk Accipiter gentilis population from Eastern Westphalia, Germany, to describe the key vital rate elements to which the growth rate is most sensitive and test how environmental stochasticity and density dependence affect long-term population growth. The asymptotic growth rate of the fully age-structured mean matrix model was very similar to the observed one (0.7% vs. 0.3% per annum), and population growth was most elastic to changes in survival rate at age classes 1-3. Environmental stochasticity led only to a small change in the projected population growth rate (between -0.16% and 0.67%) and did not change the elasticities qualitatively, suggesting that the goshawk life history of early reproduction coupled with high annual fertility buffers against a variable environment. Age classes most crucial to population growth were those in which density dependence seemed to act most strongly. This emphasises the importance of density dependence as a regulatory mechanism in this goshawk population. It also provides a mechanism that might enable the population to recover from population lows, because a mean matrix model incorporating observed functional responses of both vital rates to population density coupled with environmental stochasticity reduced long-term extinction risk of 30% under density-independent environmental stochasticity and 60% under demographic stochasticity to zero.