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。     

Metapopulation moments: coupling, stochasticity and persistence

1.  Spatial heterogeneity has long been viewed as a reliable means of increasing persistence. Here, an analytical model is developed to consider the variation and, hence, the persistence of stochastic metapopulations. This model relies on a novel moment closure technique, which is equivalent to assuming log-normal distributions for the population sizes.
2.  Single-species models show the greatest persistence when the mixing between subpopulations is large, so spatial heterogeneity is of no benefit. This result is confirmed by stochastic simulation of the full metapopulation.
3.  In contrast, natural-enemy models exhibit the greatest persistence for intermediate levels of coupling. When the coupling is too low, there are insufficient rescue effects between the subpopulations to sustain the dynamics, whereas when the coupling is too high all spatial heterogeneity is lost.
4.  The difference in behaviour between the one- and two-species models can be attributed to the oscillatory nature of the natural-enemy system.     

Metapopulation extinction risk: Dispersal’s duplicity

Metapopulation extinction risk is the probability that all local populations are simultaneously extinct during a fixed time frame. Dispersal may reduce a metapopulation’s extinction risk by raising its average per-capita growth rate. By contrast, dispersal may raise a metapopulation’s extinction risk by reducing its average population density. Which effect prevails is controlled by habitat fragmentation. Dispersal in mildly fragmented habitat reduces a metapopulation’s extinction risk by raising its average per-capita growth rate without causing any appreciable drop in its average population density. By contrast, dispersal in severely fragmented habitat raises a metapopulation’s extinction risk because the rise in its average per-capita growth rate is more than offset by the decline in its average population density. The metapopulation model used here shows several other interesting phenomena. Dispersal in sufficiently fragmented habitat reduces a metapopulation’s extinction risk to that of a constant environment. Dispersal between habitat fragments reduces a metapopulation’s extinction risk insofar as local environments are asynchronous. Grouped dispersal raises the effective habitat fragmentation level. Dispersal search barriers raise metapopulation extinction risk. Nonuniform dispersal may reduce the effective fraction of suitable habitat fragments below the extinction threshold. Nonuniform dispersal may make demographic stochasticity a more potent metapopulation extinction force than environmental stochasticity.     

Pushed beyond the brink: Allee effects,environmental stochasticity,and extinction

To understand the interplay between environmental stochasticity and Allee effects, we analyse persistence, asymptotic extinction, and conditional persistence for stochastic difference equations. Our analysis reveals that persistence requires that the geometric mean of fitness at low densities is greater than one. When this geometric mean is less than one, asymptotic extinction occurs with high probability for low initial population densities. Additionally, if the population only experiences positive density-dependent feedbacks, conditional persistence occurs provided the geometric mean of fitness at high population densities is greater than one. However, if the population experiences both positive and negative density-dependent feedbacks, conditional persistence only occurs if environmental fluctuations are sufficiently small. We illustrate counter-intuitively that environmental fluctuations can increase the probability of persistence when populations are initially at low densities, and can cause asymptotic extinction of populations experiencing intermediate predation rates despite conditional persistence occurring at higher predation rates.     

Predicting extinction risks for plants: environmental stochasticity can save declining populations

An emerging generalization from theoretical and empirical studies on conservation biology is that high levels of environmental stochasticity increase the likelihood of population extinction. However, coexistence theory has illustrated that there are circumstances under which environmental stochasticity can increase the chance of population persistence. These theoretical studies have shown that the sign of the effect of environmental stochasticity on population persistence is determined by interactions between life history and environmental stochasticity. These interactions mean that the stochastic and deterministic rates of population growth might differ fundamentally. Although difficult to demonstrate in real systems, observed life histories and variance in the vital rates of populations suggest that this phenomenon is likely to be common, and is therefore of much relevance to conservation biologists.     

A study of the impact of environmental stochasticity on extinction probabilities by Monte Carlo integration

An environmental process was characterized by a stationary second order autogressive process with Gaussian noise. This process was then linked to survivorship and reproductive success by logistic transformations. The sensitivity of extinction probabilities to variations in the parameters of the environmental process was studied by computer experiments in Monte Carlo integration. Against the background of the rather limited number of fertility and mortality levels studied in these experiments, the extinction probabilities were demonstrated to be quite sensitive to variations in the parameters of the environmental process. Although more extensive experiments will need to be carried out, those conducted so far suggest that concerted efforts should be made to model those environmental factors that are critical to the survivability of an endangered species in assessing its chances for continued existence.     

Environmental stochasticity and extinction risk in a population of a small songbird, the great tit

Using a long-term demographic data set, we estimated the separate effects of demographic and environmental stochasticity in the growth rate of the great tit population in Wytham Wood, United Kingdom. Assuming logistic density regulation, both the demographic (sigma2d = 0.569) and environmental (sigma2e = 0.0793) variance, with interactions included, were significantly greater than zero. The estimates of the demographic variance seemed to be relatively insensitive to the length of the study period, whereas reliable estimates of the environmental variance required long time series (at least 15 yr of data). The demographic variance decreased significantly with increasing population density. These estimates are used in a quantitative analysis of the demographic factors affecting the risk of extinction of this population. The very long expected time to extinction of this population (approximately 10(19) yr) was related to a relatively large population size (>/=120 pairs during the study period). However, for a given population size, the expected time to extinction was sensitive to both variation in population growth rate and environmental stochasticity. Furthermore, the form of the density regulation strongly affected the expected time to extinction. Time to extinction decreased when the maximum density regulation approached K. This suggests that estimates of viability of small populations should be given both with and without inclusion of density dependence.     

Extinction conditions for isolated populations affected by environmental stochasticity

We determine the critical patch size below which extinction occurs for populations living in one-dimensional habitats surrounded by completely hostile environments in the presence of environmental fluctuations. The population dynamics is reformulated in terms of a stochastic reaction–diffusion equation and is reduced to a deterministic equation that incorporates the systematic contributions of the noise. We obtain bifurcation diagrams and relations for the mean population density at the stationary state, the critical patch size, and the mean number of individuals in the habitat. The effect of the noise differs, depending on whether it affects the net growth rate or the intraspecific competition term. Fluctuations in the net growth rate decrease the critical patch size, whereas fluctuations in the competition term do not change the critical patch size. We compare our analytical results with numerical solutions of the stochastic partial differential equations and show that our procedure proves useful in dealing with reaction–diffusion equations with multiplicative noise.     

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.     

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.     

Mating system affects population performance and extinction risk under environmental challenge

Failure of organisms to adapt to sudden environmental changes may lead to extinction. The type of mating system, by affecting fertility and the strength of sexual selection, may have a major impact on a population''s chances to adapt and survive. Here, we use experimental evolution in bulb mites (Rhizoglyphus robini) to examine the effects of the mating system on population performance under environmental change. We demonstrate that populations in which monogamy was enforced suffered a dramatic fitness decline when evolving at an increased temperature, whereas the negative effects of change in a thermal environment were alleviated in polygamous populations. Strikingly, within 17 generations, all monogamous populations experiencing higher temperature went extinct, whereas all polygamous populations survived. Our results show that the mating system may have dramatic effects on the risk of extinction under environmental change.     

Increased signal complexity is associated with increased mating success

The evolution of complex signals has often been explored by testing multiple functional hypotheses regarding how independent signal components provide selective benefits to offset the costs of their production. In the present study, we take a different approach by exploring the function of complexity per se. We test the hypothesis that increased vibratory signal complexity—based on both proportional and temporal patterning—provides selective benefits to courting male Schizocosa stridulans wolf spiders. In support of this hypothesis, all of our quantified metrics of vibratory signal complexity predicted the mating success of male S. stridulans. The rate of visual signalling, which is mechanistically tied to vibratory signal production, was also associated with mating success. We additionally found evidence that males can dynamically adjust the complexity of their vibratory signalling. Together, our results suggest that complexity per se may be a target of female choice.     

Non-linear biological responses to environmental noise affect population extinction risk

Non-linearities are commonly observed in the responses of organisms to environment. They potentially modify the qualitative and quantitative properties of population dynamics. We studied how non-linear responses to environment, or "noise filters", influence population variability and extinction risk by introducing coloured noise to the growth rate in the Hassell single-species model. The consequences of noise filtering were analysed by comparing the model dynamics with linearly filtered and non-linearly filtered noise that have the same mean. Three biologically plausible filters we used: saturating, unimodal optimum type, and sigmoid responses.
Filtering can either decrease or increase population variability when compared to linear noise response. The effect of noise filtering on variability is most pronounced with stable population dynamics and the outcome depends on the filter type, population growth rate, and noise colour.
Non-linear noise filtering predominantly increases extinction risks when population growth rate is low (R<5). As an exception, saturating filter has a window of decreased risk at very low growth rate and reddened environment. In the unstable range of the dynamics (15These results suggest that accounting for the non-linear responses to environment should be considered when estimating extinction risks and population variability. Moreover, the non-linear responses make noise colour a more important factor in these analyses.     

Poor environmental tracking can make extinction risk insensitive to the colour of environmental noise

The relative importance of environmental colour for extinction risk compared with other aspects of environmental noise (mean and interannual variability) is poorly understood. Such knowledge is currently relevant, as climate change can cause the mean, variability and temporal autocorrelation of environmental variables to change. Here, we predict that the extinction risk of a shorebird population increases with the colour of a key environmental variable: winter temperature. However, the effect is weak compared with the impact of changes in the mean and interannual variability of temperature. Extinction risk was largely insensitive to noise colour, because demographic rates are poor in tracking the colour of the environment. We show that three mechanisms-which probably act in many species-can cause poor environmental tracking: (i) demographic rates that depend nonlinearly on environmental variables filter the noise colour, (ii) demographic rates typically depend on several environmental signals that do not change colour synchronously, and (iii) demographic stochasticity whitens the colour of demographic rates at low population size. We argue that the common practice of assuming perfect environmental tracking may result in overemphasizing the importance of noise colour for extinction risk. Consequently, ignoring environmental autocorrelation in population viability analysis could be less problematic than generally thought.     

Resistance and resilience: quantifying relative extinction risk in a diverse assemblage of Australian tropical rainforest vertebrates

Aim Assessing the relative vulnerability of species within an assemblage to extinction is crucial for conservation planning at the regional scale. Here, we quantify relative vulnerability to extinction, in terms of both resistance and resilience to environmental change, in an assemblage of tropical rainforest vertebrates. Location Wet Tropics Bioregion, north Queensland, Australia. Methods We collated data on 163 vertebrates that occur in the Australian Wet Tropics, including 24 frogs, 33 reptiles, 19 mammals and 87 birds. We used the ‘seven forms of rarity’ model to assess relative vulnerability or resistance to environmental change. We then develop a new analogous eight‐celled model to assess relative resilience, or potential to recover from environmental perturbation, based on reproductive output, potential for dispersal and climatic niche marginality. Results In the rarity model, our assemblage had more species very vulnerable and very resistant than expected by chance. There was a more even distribution of species over the categories in the resilience model. The three traits included in each model were not independent of each other; species that were widespread were also habitat generalists, while species with narrow geographical ranges tended to be locally abundant. In the resilience model, species with low reproductive output had a narrow climatic niche and also a low capacity to disperse. Frogs were the most vulnerable taxonomic group overall. The model categories were compared to current IUCN category of listed species, and the product of the two models was best correlated with IUCN listings. Main conclusions The models presented here offer an objective way to predict the resistance of a species to environmental change, and its capacity to recover from disturbance. The new resilience model has similar advantages to the rarity model, in that it uses simple information and is therefore useful for examining patterns in assemblages with many poorly known species.     

Population dynamics of annuals in perennial grassland controlled by ants and environmental stochasticity

Questions: In a system of five annual plant species restricted to nest‐mounds of the ant Lasiusflavus in a perennial grassland: 1. Are the population dynamics influenced by ant disturbance? 2. Is the survival of the annuals at the scale of the whole grassland possible under the observed conditions of disturbance dynamics? 3. Which phases in the annuals’ life cycle and patch types contribute most to population growth? Location: Borec hill, northern Czechia, 50°31’ N, 13°59’ E, 446 m a.s.l. Methods: Local population dynamics of the annuals were analysed separately for five patch types that differed in the proportion of bare soil. Vitality rates were assessed directly in the field, but also in a garden experiment, during 2000–2001 and 2001–2002. Population dynamics at the scale of the whole grassland was analysed with a megamatrix approach, combining patch dynamics of the nest‐mounds with patch‐specific population dynamics. Contributions of different phases and patch types to growth rate were estimated by elasticity analysis. Results: Nest‐mounds differed in the percentage of bare soil. Increasing moss cover significantly reduced germination and seed production of all studied annuals and decreased their population growth rates (λ). Although successional processes dominated over ant disturbance, populations of all species could survive well (λ? 1) in the grassland according to the 2000–2001 megamatrix dynamics. Based on the dynamics from the following period, two species would not survive in a long‐term perspective due to random environmental variation. Whereas the A‐A transition (adult plants originating from adults of the previous year) had the highest elasticity under open conditions and ‘good period’ demography, the importance of persistent seeds increased under reverse conditions. This, however, differed among species. Conclusions: Ant‐disturbance was shown to be critical for the population survival of five annual species in the studied grassland. The fate of the annual populations in the grassland system also depends on random environmental variation, which may override the effect of ant activity.     

Correctly estimating how environmental stochasticity influences fitness and population growth

Increased temporal variance in life-history traits is generally predicted to decrease individual fitness and population growth. We show that a widely used result of stochastic sensitivity analysis that bolsters this generality is flawed because it ignores the effects of correlations between vital rates. Considering the effects of these correlations (although ignoring autocorrelations), we show that the apparently simple relationship between vital rate variance and fitness can be considerably more complex than previously thought. In particular, the previously estimated negative sensitivities of fitness or population growth to variance in a vital rate can be either enhanced by positive correlations between rates or reversed by negative correlations, even to the point that variability in a rate can increase fitness or population growth. We apply this new sensitivity calculation to data from the desert tortoise and discuss its interpretation in light of the factors generating vital rate correlations.     

The effect of selection history on extinction risk during severe environmental change

Environments rarely remain the same over time, and populations are therefore frequently at risk of going extinct when changes are significant enough to reduce fitness. Although many studies have investigated what attributes of the new environments and of the populations experiencing these changes will affect their probability of going extinct, limited work has been directed towards determining the role of population history on the probability of going extinct during severe environmental change. Here, we compare the extinction risk of populations with a history of selection in a benign environment, to populations with a history of selection in one or two stressful environments. We exposed spores and lines of the green alga Chlamydomonas reinhardtii from these three different histories to a range of severe environmental changes. We found that the extinction risk was higher for populations with a history of selection in stressful environments compared to populations with a history of selection in a benign environment. This effect was not due to differences in initial population sizes. Finally, the rates of extinction were highly repeatable within histories, indicating strong historical contingency of extinction risk. Hence, information on the selection history of a population can be used to predict their probability of going extinct during environmental change.     

Metapopulation extinction in fragmented landscapes: using bacteria and protozoa communities as model ecosystems

Extinction is notoriously difficult to study because of the long timescales involved and the difficulty in ascertaining that extinction has actually occurred. The effect of habitat subdivision, or fragmentation, on extinction risk is even harder to study, as it requires copious replication of habitat patches on large spatial scales and control of area effects between treatments. I used simple small-scale communities of bacteria and protozoa to study extinction in response to habitat loss and habitat fragmentation. I studied several different community configurations, each with three trophic levels. Unlike most metapopulation studies (experimental as well as theoretical), which have tended to deal with inherently unstable species interactions, I deliberately used community configurations that were persistent in large stock cultures. I recorded the time to extinction of the top predator in single habitat patches of different sizes and in fragmented systems with different degrees of subdivision but the same amount of available habitat. Habitat loss reduced the time to extinction of isolated populations. Fragmented systems went extinct sooner than corresponding unfragmented (continuous) systems of the same overall size. Unfragmented populations persisted longer than fragmented systems (metapopulations) with or without dispersal corridors between subpopulations. In fact, fragmented systems where the fragments were linked by dispersal corridors went extinctly significantly sooner than those where subpopulations were completely isolated from each other. If these results extend to more "natural" systems, it suggests a need for caution in management programs that emphasize widespread establishment of wildlife corridors in fragmented landscapes.