Past states of continuous-time Markov models for ecological communities

Discrete-time Markov chains are often used to model communities of sessile organisms. The community is described by a set of discrete states, which may represent species or groups of species. Transitions between states are modelled using a stochastic matrix. A recent study showed how the time-reversal of such a Markov chain can be used to estimate the distribution of time since the last occurrence of some state of interest (such as empty space) at a point, given the current state of the point. However, if the underlying process operates in continuous time but is observed at regular intervals, this distribution describes the time since the last possible observation of the state of interest, rather than the time since its last occurrence. We show how to obtain the distribution of time since the last occurrence of a state of interest for a continuous-time homogeneous Markov chain. The expected time since the last occurrence of an initial state can be interpreted as a measure of the successional rank of a state. We show how to distinguish between different ways in which a state can have high successional rank. We apply our results to a marine subtidal community.     

Bayesian selection of continuous-time Markov chain evolutionary models

We develop a reversible jump Markov chain Monte Carlo approach to estimating the posterior distribution of phylogenies based on aligned DNA/RNA sequences under several hierarchical evolutionary models. Using a proper, yet nontruncated and uninformative prior, we demonstrate the advantages of the Bayesian approach to hypothesis testing and estimation in phylogenetics by comparing different models for the infinitesimal rates of change among nucleotides, for the number of rate classes, and for the relationships among branch lengths. We compare the relative probabilities of these models and the appropriateness of a molecular clock using Bayes factors. Our most general model, first proposed by Tamura and Nei, parameterizes the infinitesimal change probabilities among nucleotides (A, G, C, T/U) into six parameters, consisting of three parameters for the nucleotide stationary distribution, two rate parameters for nucleotide transitions, and another parameter for nucleotide transversions. Nested models include the Hasegawa, Kishino, and Yano model with equal transition rates and the Kimura model with a uniform stationary distribution and equal transition rates. To illustrate our methods, we examine simulated data, 16S rRNA sequences from 15 contemporary eubacteria, halobacteria, eocytes, and eukaryotes, 9 primates, and the entire HIV genome of 11 isolates. We find that the Kimura model is too restrictive, that the Hasegawa, Kishino, and Yano model can be rejected for some data sets, that there is evidence for more than one rate class and a molecular clock among similar taxa, and that a molecular clock can be rejected for more distantly related taxa.     

Aphids as models for ecological and evolutionary studies

Aphids （Hemiptera： Aphididae） are a group of phloemfeeding insects numbering more than 5 000 extant species（Favret, 2014a）. Most species have complex life cycles that include both asexual （viviparous parthenogenesis）and sexual reproduction. They display a high degree of intraspecific polyphenism with multiple phenotypes froman identical genotype, and they have specialized associations with their host plants （Blackman ＆ Eastop, 2000）.Some aphid species are gall-makers and even have evolved sociality with division of labor （Aoki, 1977; Stern ＆Foster, 1996）. Many aphid species are agricultural and forestry pests. They incur damage to plants and carryvector plant viruses （Blackman ＆ Eastop, 2000）. Due to their fascinating biological character and economic importance, aphids have long been popular animals for research in basic and applied biology, and are becominguseful research models for studying important questions in ecology and evolution, especially in the genomic era（Brisson ＆ Stem, 2006; Huang ＆ Qiao, 2006; Srinivasan ＆ Brisson, 2012）.     

Demographic analysis of continuous-time life-history models

I present a computational approach to calculate the population growth rate, its sensitivity to life-history parameters and associated statistics like the stable population distribution and the reproductive value for exponentially growing populations, in which individual life history is described as a continuous development through time. The method is generally applicable to analyse population growth and performance for a wide range of individual life-history models, including cases in which the population consists of different types of individuals or in which the environment is fluctuating periodically. It complements comparable methods developed for discrete-time dynamics modelled with matrix or integral projection models. The basic idea behind the method is to use Lotka's integral equation for the population growth rate and compute the integral occurring in that equation by integrating an ordinary differential equation, analogous to recently derived methods to compute steady-states of physiologically structured population models. I illustrate application of the method using a number of published life-history models.     

Understanding ecological community succession: Causal models and theories,a review

Critical review of explanations for patterns of natural succession suggests a strong, common basis for theoretical understanding, but also suggests that several well known models are incomplete as explanations of succession. A universal, general cause for succession is unlikely, since numerous aspects of historical and environmental circumstances will impinge on the process in a unique manner. However, after disturbance, occupation of a site by any species causes changes in the conditions at the site. Sorting of species may result, since different species are adapted to different regions of environmental gradients. Such sorting can generate several patterns of species abundance in time, but commonly results in sequential replacements of species adapted to the varying conditions. This may be due to constraints on species' strategies, or life history traits, placed by the limited resources available to the organism. These constraints often result in inverse correlation between traits which confer success during early and late stages of succession. Facilitatory or inhibitory effects of species on each other are best understood in terms of these life history interactions, perhaps as restrictions on, or as moderation of, these processes.Strong support for the importance of correlations in life history traits stems from comparisons of simulated succession with and without these correlations. These simulations are reviewed in some detail, and followed by brief reviews of other prominent models for succession. Several aspects of the confusion and controversies in the successional literature are then discussed, with a view to a more optimistic synthesis and direction for successional ecology.     

生态模型的灵敏度分析

灵敏度分析用于定性或定量地评价模型参数误差对模型结果产生的影响,是模型参数化过程和模型校正过程中的有用工具,具有重要的生态学意义．灵敏度分析包括局部灵敏度分析和全局灵敏度分析．局部灵敏度分析只检验单个参数的变化对模型结果的影响程度;全局灵敏度分析则检验多个参数的变化对模型运行结果总的影响,并分析每一个参数及其参数之间相互作用对模型结果的影响．目前,在对生态模型的灵敏度分析中,越来越倾向于使用全局灵敏度分析的方法．但国内仍多采用局部灵敏度分析方法,很少采用全局灵敏度分析方法．文中详细论述了局部灵敏分析和全局灵敏度分析的主要方法(一次变换法、多元回归法、Morris法、Sobol’法、傅里叶幅度灵敏度检验法和傅里叶幅度灵敏度检验扩展法),希望能为国内生态模型的发展提供一个比较完善的灵敏度分析方法库．结合国内外的灵敏度分析发展现状,指出联合灵敏度研究、灵敏度共性研究及空间直观景观模型的灵敏度分析将为生态模型灵敏度分析研究中的热点和难点．     

Bacteriocins: ecological and evolutionary significance

Bacteriocins are compounds that are produced by bacteria and are antagonistic to other bacteria. Although they have been known for many years, recent interest in these compounds has increased because of their potential use as natural food preservatives. Although most of this research has been directed at the molecular level, a clearer picture of the ecological role played by bacteriocins in natural environments is beginning to emerge. In addition, the importance and practical implications of evolutionary aspects of bacteriocins and bacteriocin resistance are now being assessed.     

Sensitivity analysis of coexistence in ecological communities: theory and application

Sensitivity analysis, the study of how ecological variables of interest respond to changes in external conditions, is a theoretically well‐developed and widely applied approach in population ecology. Though the application of sensitivity analysis to predicting the response of species‐rich communities to disturbances also has a long history, derivation of a mathematical framework for understanding the factors leading to robust coexistence has only been a recent undertaking. Here we suggest that this development opens up a new perspective, providing advances ranging from the applied to the theoretical. First, it yields a framework to be applied in specific cases for assessing the extinction risk of community modules in the face of environmental change. Second, it can be used to determine trait combinations allowing for coexistence that is robust to environmental variation, and limits to diversity in the presence of environmental variation, for specific community types. Third, it offers general insights into the nature of communities that are robust to environmental variation. We apply recent community‐level extensions of mathematical sensitivity analysis to example models for illustration. We discuss the advantages and limitations of the method, and some of the empirical questions the theoretical framework could help answer.     

生态资产、生态补偿及生态文明科技贡献核算理论与技术

项目拟将国家生态文明制度建设科技需求与国际生态领域研究前沿结合,综合应用生态评估、社会调查、政策分析、系统模拟方法,重点研究:生态资产核算理论、技术方法与应用,生态系统生产总值与生态效益核算理论、技术方法与应用,生态保护与生态建设工程效益评估技术方法与应用,国家与地方生态补偿政策绩效评价,生态补偿模式、标准核算与政策措施,生态补偿融资机制与政策措施,科技创新对生态文明建设贡献的评估方法体系与应用示范,构建生态资产与生态效益、生态补偿、科技支撑生态文明贡献度的核算理论、方法和技术体系,为国家生态文明制度与机制建设提供科技支撑。     

The analysis of plant growth in ecological and evolutionary studies

Plant growth rate is often assumed to be an ecologically important life history trait. However, conventional plant growth analysis, while providing a useful accounting of rates of weight gain and its components, is ill-suited for testing relationships between growth and fitness, particularly in natural populations. Two new approaches that are suitable for testing such relationships have evolved over the past several years. The first - the population biology of plant parts, or 'modular demography' - permits non-destructive measures of growth rate in natural field populations. When modular demography is performed using matrix population models, controls over growth rate can be examined, as well as consequences of growth variation for reproduction. The second - demographic growth analysis - provides growth parameters analogous to those of conventional growth analysis, but can be performed in natural field populations. Demographic growth analysis allows measures of individual growth-rate variation, which, in turn, can be related to plant performance.     

Testing evolutionary theories of menopause

Why do women cease fertility rather abruptly through menopause at an age well before generalized senescence renders child rearing biologically impossible? The two main evolutionary hypotheses are that menopause serves either (i) to protect mothers from rising age-specific maternal mortality risks, thereby protecting their highly dependent younger children from death if the mother dies or (ii) to provide post-reproductive grandmothers who enhance their inclusive fitness by helping to care and provide for their daughters'' children. Recent theoretical work indicates that both factors together are necessary if menopause is to provide an evolutionary advantage. However, these ideas need to be tested using detailed data from actual human life histories lived under reasonably ‘natural’ conditions; for obvious reasons, such data are extremely scarce. We here describe a study based on a remarkably complete dataset from The Gambia. The data provided quantitative estimates for key parameters for the theoretical model, which were then used to assess the actual effects on fitness. Empirically based numerical analysis of this nature is essential if the enigma of menopause is to be explained satisfactorily in evolutionary terms. Our results point to the distinctive (and perhaps unique) role of menopause in human evolution and provide important support for the hypothesized evolutionary significance of grandmothers.     

Applying socioendocrinology to evolutionary models: Fatherhood and physiology

Owing to humans' unique life history pattern, particularly comparatively short interbirth intervals, early weaning, and prolonged support of multiple dependents, human females have greater reproductive value and higher lifetime fertility, on average, than do their Great Ape counterparts. 1 - 4 As hominin females began weaning their young early and “stacking” dependents of various ages, they must have had cooperative allomaternal care partners already in place or been successful at concurrently soliciting help to ensure a high rate of survival of their offspring. 1 - 6 Following Hrdy, I define allomaternal care (and its derivatives, such as “allomothers” and “allomothering”) as “care from anyone other than the mother,” which thus encompasses a wide range of individuals, including fathers. 7 Who the likely allomother candidates mothers were and what form that cooperation took remain intriguing, difficult‐to‐answer questions, which are limited, in some capacity, by the lines of evidence available to us. Here, I present a framework for the ways in which we can integrate neurobiological‐endocrine and social‐behavioral data (“socioendocrinology”) 8 to contribute to this dialogue in terms of evaluating fathers' roles.