Framework for quantifying population responses to disturbance reveals that coastal birds are highly resilient to hurricanes

Changes in the frequency and severity of extreme weather may introduce new threats to species that are already under stress from gradual habitat loss and climate change. We provide a probabilistic framework that quantifies potential threats by applying concepts from ecological resilience to single populations. Our approach uses computation to compare disturbance–impacted projections to a population's normal range of variation, quantifying the full range of potential impacts. We illustrate this framework with projection models for coastal birds, which are commonly depicted as vulnerable to disturbances, especially hurricanes and oil spills. We found that populations of coastal specialists are resilient to extreme disturbances, with high resistance to the effects of short‐term reductions in vital rates and recovery within 20 years. Applying the general framework presented here across disturbance‐prone species and ecosystems would improve understanding of population resilience and generate specific projections of resilience that are needed for effective conservation planning.     

植物种群生存力分析研究进展

对十多年来国外植物PVA的研究进行了综合评述;具体分析了影响植物种群生存力的各种随机性因子及确定性因子;总结了植物PVA研究的方法步骤及采用的模拟模型;探讨了植物PVA的难点,PVA对管理措施的评价效果;并提出对今后植物PVA的研究展望,认为PVA是研究濒危植物种群灭绝及评价管理或保护措施的有力工具;发展描述复杂种间关系的多种种的PVA模型以及包含多个影响因素的PVA应用模型是未来植物PVA的研究方向。     

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.     

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。     

A computational approach to studying ageing at the individual level

The ageing process is actively regulated throughout an organism''s life, but studying the rate of ageing in individuals is difficult with conventional methods. Consequently, ageing studies typically make biological inference based on population mortality rates, which often do not accurately reflect the probabilities of death at the individual level. To study the relationship between individual and population mortality rates, we integrated in vivo switch experiments with in silico stochastic simulations to elucidate how carefully designed experiments allow key aspects of individual ageing to be deduced from group mortality measurements. As our case study, we used the recent report demonstrating that pheromones of the opposite sex decrease lifespan in Drosophila melanogaster by reversibly increasing population mortality rates. We showed that the population mortality reversal following pheromone removal was almost surely occurring in individuals, albeit more slowly than suggested by population measures. Furthermore, heterogeneity among individuals due to the inherent stochasticity of behavioural interactions skewed population mortality rates in middle-age away from the individual-level trajectories of which they are comprised. This article exemplifies how computational models function as important predictive tools for designing wet-laboratory experiments to use population mortality rates to understand how genetic and environmental manipulations affect ageing in the individual.     

A population‐based temporal logic gate for timing and recording chemical events

Engineered bacterial sensors have potential applications in human health monitoring, environmental chemical detection, and materials biosynthesis. While such bacterial devices have long been engineered to differentiate between combinations of inputs, their potential to process signal timing and duration has been overlooked. In this work, we present a two‐input temporal logic gate that can sense and record the order of the inputs, the timing between inputs, and the duration of input pulses. Our temporal logic gate design relies on unidirectional DNA recombination mediated by bacteriophage integrases to detect and encode sequences of input events. For an E. coli strain engineered to contain our temporal logic gate, we compare predictions of Markov model simulations with laboratory measurements of final population distributions for both step and pulse inputs. Although single cells were engineered to have digital outputs, stochastic noise created heterogeneous single‐cell responses that translated into analog population responses. Furthermore, when single‐cell genetic states were aggregated into population‐level distributions, these distributions contained unique information not encoded in individual cells. Thus, final differentiated sub‐populations could be used to deduce order, timing, and duration of transient chemical events.     

A novel statistical analysis and interpretation of flow cytometry data

A recently developed class of models incorporating the cyton model of population generation structure into a conservation-based model of intracellular label dynamics is reviewed. Statistical aspects of the data collection process are quantified and incorporated into a parameter estimation scheme. This scheme is then applied to experimental data for PHA-stimulated CD4+T and CD8+T cells collected from two healthy donors. This novel mathematical and statistical framework is shown to form the basis for accurate, meaningful analysis of cellular behaviour for a population of cells labelled with the dye carboxyfluorescein succinimidyl ester and stimulated to divide.     

A broader ecological context to habitat fragmentation: Why matrix habitat is more important than we thought

Abstract. Consequences of habitat fragmentation have garnered much attention over the past few decades. The resulting literature has been useful for understanding how land‐use changes influence population viability and community structure, but we are still hampered by a major aspect of the conceptual framework within which most fragmentation work arises. Specifically, habitat between fragments (‘matrix’) is usually treated as uniform and ecologically irrelevant. However, recent work on animals shows that matrix habitat can profoundly influence within‐fragment dynamics. We review related evidence for plants. Various matrix types (e.g. clear‐cutting, agriculture, or urbanization) can act in different ways to alter resource availability and movement of pollinators, seed dispersers, and herbivores. Inclusion of matrix qualities in fragmentation studies is further complicated since most matrices are not static; sites in which timber harvesting or agriculture occur develop through succession or change as crops are rotated, respectively, such that their influence on within‐fragment processes vary temporally. Also, many plants are not restricted to remnants of original habitat. Using studies of forest understory plants, we summarize work showing how diversity can change significantly through time in matrix. Understanding the persistence of a species across fragmented landscapes will require more attention to matrix habitat, and to the species utilizing the matrix.     

种群生存力分析（PVA）的方法与应用

随着人们对资源的加速利用,生境丧失和破碎化导致物种濒危问题日益严重.以岛屿生物地理学为理论起源的种群生存力分析（PVA）,通过分析和模拟种群动态过程并建立灭绝概率与种群数量之间的关系,为濒危物种保护提供了重要的理论依据和研究途径.在过去的几十年中,种群生存力分析已成为保护生物学中一项重要的研究内容.目前种群生存力分析发展稳定,但对其实际预测能力和准确性尚存质疑,应用方面也有待进一步发展.种群生存力分析的进一步完善还需要在理论和方法上的创新,特别是籍于景观生态学和可持续性科学的理念,将空间分析手段、经济社会因素纳入到物种和种群的预测和管理上,从而使其 具有更完整的理论基础和更高的实用价值.为此,本文对种群生存力分析的历史、基本概念、研究方法、模型应用和准确性进行了综述,并提出了有关的研究展望.     

Stochastic matrix models for conservation and management: a comparative review of methods

Stochastic matrix models are frequently used by conservation biologists to measure the viability of species and to explore various management actions. Models are typically parameterized using two or more sets of estimated transition rates between age/size/stage classes. While standard methods exist for analyzing a single set of transition rates, a variety of methods have been employed to analyze multiple sets of transition rates. We review applications of stochastic matrix models to problems in conservation and use simulation studies to compare the performance of different analytic methods currently in use. We find that model conclusions are likely to be robust to the choice of parametric distribution used to model vital rate fluctuations over time. However, conclusions can be highly sensitive to the within-year correlation structure among vital rates, and therefore we suggest using analytical methods that provide a means of conducting a sensitivity analysis with respect to correlation parameters. Our simulation results also suggest that the precision of population viability estimates can be improved by using matrix models that incorporate environmental covariates in conjunction with experiments to estimate transition rates under a range of environmental conditions.     

A stochastic SIR model with contact-tracing: large population limits and statistical inference

This paper is devoted to the presentation and study of a specific stochastic epidemic model accounting for the effect of contact-tracing on the spread of an infectious disease. Precisely, one considers here the situation in which individuals identified as infected by the public health detection system may contribute to detecting other infectious individuals by providing information related to persons with whom they have had possibly infectious contacts. The control strategy, which consists of examining each individual who has been able to be identified on the basis of the information collected within a certain time period, is expected to efficiently reinforce the standard random-screening-based detection and considerably ease the epidemic. In the novel modelling of the spread of a communicable infectious disease considered here, the population of interest evolves through demographic, infection and detection processes, in a way that its temporal evolution is described by a stochastic Markov process, of which the component accounting for the contact-tracing feature is assumed to be valued in a space of point measures. For adequate scalings of the demographic, infection and detection rates, it is shown to converge to the weak deterministic solution of a PDE system, as a parameter n, interpreted as the population size, roughly speaking, becomes larger. From the perspective of the analysis of infectious disease data, this approximation result may serve as a key tool for exploring the asymptotic properties of standard inference methods such as maximum likelihood estimation. We state preliminary statistical results in this context. Eventually, relations of the model with the available data of the HIV epidemic in Cuba, in which country a contact-tracing detection system has been set up since 1986, is investigated and numerical applications are carried out.     

基于广义可加模型的昆虫种群动态非线性分析及R语言实现

昆虫种群受到气候、天敌和土壤等多种生态因子的综合作用,其动态具有复杂性、不确定性和非线性等特征。广义加性模型(generalized additive models,GAM)就是适用于响应变量与解释变量之间的关系是非线性或非单调的数据分析。本文以1973—1990年稻纵卷叶螟种群数量与降雨持续天数和降雨量的相关性分析为例,介绍了广义可加模型的应用及其R语言实现步骤,为研究昆虫种群动态及其驱动因子提供了有效的分析工具。     

A statistical light scattering approach to separating fast and slow dynamics

Light scattering is a powerful technique to study the structural and dynamical properties of biomolecular systems or other soft materials such as polymeric solutions and blends or gels. An important application of this technique is the study of the kinetics of formation of supramolecular structures. However, in such cases, the system under study is rapidly changing, and consequently the integration time for each measurement is limited. In order to overcome this difficulty, a statistical approach has been developed based on the analysis of the scattered light intensity distribution (Manno et al. 2006, 2004). Indeed the intensity distribution depends upon the ratio between the integration time of each measurement and the coherence time of scattered radiation. This method has been applied to protein aggregation (Manno et al. 2006) and to sol-gel transition (Manno et al. 2004), to obtain information on the heterogeneity of morphological and dynamical features during such processes. In the present work, we accurately test the validity of this approach by analyzing the statistical properties of the light scattered by a model system: a solution of polystyrene spherical macromolecules of different sizes. Each molecular size is related to a given diffusion coefficient and to a given coherence time of the scattered intensity. The effect of changing the experimental integration time is systematically investigated. A mixture of particles of two different sizes is also analyzed to test the validity and robustness of the model based on the convolution of a gaussian with an exponential distribution. Proceedings of the XVIII Congress of the Italian Society of Pure and Applied Biophysics (SIBPA), Palermo, Sicily, September 2006.     

Assessing seasonal demographic covariation to understand environmental‐change impacts on a hibernating mammal

Natural populations are exposed to seasonal variation in environmental factors that simultaneously affect several demographic rates (survival, development and reproduction). The resulting covariation in these rates determines population dynamics, but accounting for its numerous biotic and abiotic drivers is a significant challenge. Here, we use a factor‐analytic approach to capture partially unobserved drivers of seasonal population dynamics. We use 40 years of individual‐based demography from yellow‐bellied marmots (Marmota flaviventer) to fit and project population models that account for seasonal demographic covariation using a latent variable. We show that this latent variable, by producing positive covariation among winter demographic rates, depicts a measure of environmental quality. Simultaneously, negative responses of winter survival and reproductive‐status change to declining environmental quality result in a higher risk of population quasi‐extinction, regardless of summer demography where recruitment takes place. We demonstrate how complex environmental processes can be summarized to understand population persistence in seasonal environments.     

Landscape scale, heterogeneity, and the viability of Serengeti grazers

Species persistence can be threatened by substantial temporal variation in food resources over time. On the other hand, spatial heterogeneity in resources at the landscape scale might allow mobile consumers to compensate for temporal variability in resource availability at the local scale. We evaluated this hypothesis, using an extensive data set on foraging, grass growth, and movement by Thomson's gazelles living on the Serengeti Plains. Here we show that modelled populations of Thomson's gazelles can only persist under Serengeti conditions in the face of observed levels of rainfall stochasticity by making adaptive movements to take advantage of ephemeral spatial distributions of food resources. More importantly, our models suggest that Thomson's gazelles in Serengeti require unrestricted access to relatively large areas of grassland (> 1600 km²) to guarantee long‐term persistence, particularly when there is positive spatial autocorrelation in resource abundance, as is the case in Serengeti. If this proves to be true for other species and/or other systems, then understanding of complex behavioural responses to spatially and temporally heterogeneous food supplies may be essential to successful conservation of grazing herbivores.     

A Bayesian approach to modeling associations between pulsatile hormones

Summary .  Many hormones are secreted in pulses. The pulsatile relationship between hormones regulates many biological processes. To understand endocrine system regulation, time series of hormone concentrations are collected. The goal is to characterize pulsatile patterns and associations between hormones. Currently each hormone on each subject is fitted univariately. This leads to estimates of the number of pulses and estimates of the amount of hormone secreted; however, when the signal-to-noise ratio is small, pulse detection and parameter estimation remains difficult with existing approaches. In this article, we present a bivariate deconvolution model of pulsatile hormone data focusing on incorporating pulsatile associations. Through simulation, we exhibit that using the underlying pulsatile association between two hormones improves the estimation of the number of pulses and the other parameters defining each hormone. We develop the one-to-one, driver–response case and show how birth–death Markov chain Monte Carlo can be used for estimation. We exhibit these features through a simulation study and apply the method to luteinizing and follicle stimulating hormones.     

Estimating the rate of increase for the finless porpoise with special attention to predictions for the Inland Sea population in Japan

The finless porpoise Neophocaena asiaeorientalis inhabits coastal waters and rivers in East Asia and is exposed to various human activities. This species is listed on the IUCN Red List of Threatened Species due to a reduction in abundance. Although human-induced mortality can be a threat to porpoise populations, future anthropogenic impacts have not been quantitatively evaluated due to lack of demographic information. Adequate future population projections are needed to form the basis for conservation measures before the population declines to critical levels. We conducted a population viability analysis for the population of finless porpoise in the Inland Sea, Japan using a Leslie matrix model composed of age-specific survival and fertility rates. We described the uncertainty in the annual rate of increase (λ) for the finless porpoise using randomly sampled estimates of survival rate for other cetaceans with similar life histories. Plausible median estimates of λ ranged from 1.041 (age at first reproduction [AFR] = 7) to 1.056 (AFR = 5). Future population changes and extinction probabilities were predicted after combining these estimates with a predicted human-induced mortality rate (M) and available abundance estimates. The extinction probability after 100 years was 0 %. However, the probability of the quasi-extinction (<100 individuals) was as high as 79.0 % after 100 years. The results also suggest that the persistence of the finless porpoise population could be achieved with a small effort to reduce anthropogenic mortality.     

Dynamics of isolated <Emphasis Type="Italic">Saponaria bellidifolia</Emphasis> Sm. populations at northern range periphery

Four populations of Saponaria bellidifolia situated at the species’ northern range periphery (Apuseni Mountains, southeastern Carpathians) were monitored over a period of 5 years. They were chosen to represent different habitat types (rocky, fixed screes, open screes and grassy), disturbance regime (fire), and population sizes (categorized as large and small). The reproductive effort was quantified, and matrix models were used to describe the population dynamics and to assess population viability. Saponaria bellidifolia had very stable population dynamics in the harsh and stable abiotic conditions of the outcrops where populations occur. Habitat conditions exerted a notable influence on the species’ population reproductive performance, growth rate, and vital rates, whereas population size and climate did not have a clear-cut effect on the dynamics of the species. Saponaria bellidifolia maintains viable populations in the southeastern Carpathians, at its northern range periphery.