Assessment of reproductive behavior and hormonal cycles in geriatric western Lowland gorillas

The population of western lowland gorillas in North American zoos is aging and, as is the case with the aging human population, may have unique physical and social needs. We have documented previously that 25% of aging females (5/22) ceased to show reproductive cycles entirely, and could be defined as menopausal. Approximately 32% of females showed somewhat irregular cycling patterns. We review our hormonal and behavioral findings on reproductive aging in gorillas; describe the range of cycling patterns that we see and how we interpret these; and discuss the implications of these findings for captive management and husbandry of aging gorillas. We monitored fecal hormone metabolites (progestogens) in 30 gorillas and collected simultaneous behavioral data to evaluate the relationship between cyclicity and sexual behavior. We identified and described several discrete patterns of irregular cycling. These included extreme variability of cycle length, cyclic patterns with unusually low progestogen peak concentrations that possibly may not support luteal activity, and large variability in maximum progestogen peak height among cycles. All of these changes are consistent with age‐related hormonal changes observed in humans and may be signs of changes in fertility as well. Behaviorally, nearly all cycling females exhibited signs of estrus. Affiliative behavior between male silverbacks and estrous females was observed in the control females, but not the geriatric females. These findings suggest that pre‐menopausal females are exhibiting signs of perimenopause. As is the case in humans, such changes in hormone patterns may occur years before the onset of menopause. As enhancements in nutrition, husbandry, and veterinary medicine have led to increased longevity in our zoo populations of apes, it has become imperative that we investigate and better understand associated physiological and behavioral changes in geriatric animals to ensure appropriate management of this increasing demographic sub‐population. Zoo Biol 0:1–23, 2007. © 2007 Wiley‐Liss, Inc.     

The ‘Hutchinsonian niche’ as an assemblage of demographic niches: implications for species geographic ranges

Hutchinson defined the ecological niche as a hypervolume shaped by the environmental conditions under which a species can ‘exist indefinitely’. Although several authors further discussed the need to adopt a demographic perspective of the ecological niche theory, very few have investigated the environmental requirements of different components of species’ life cycles (i.e. vital rates) in order to examine their internal niche structures. It therefore remains unclear how species’ demography, niches and distributions are interrelated. Using comprehensive demographic data for two well‐studied, short‐lived plants (Plantago coronopus, Clarkia xantiana), we show that the arrangement of species’ demographic niches reveals key features of their environmental niches and geographic distributions. In Plantago coronopus, opposing geographic trends in some individual vital rates, through different responses to environmental gradients (demographic compensation), stabilize population growth across the range. In Clarkia xantiana, a lack of demographic compensation underlies a gradient in population growth, which could translate in a directional geographic range shift. Overall, our results highlight that occurrence and performance niches cannot be assumed to be the same, and that studying their relationship is essential for a better understanding of species’ ecological niches. Finally, we argue for the value of considering the assemblage of species’ demographic niches when studying ecological systems, and predicting the dynamics of species geographical ranges.     

A life‐history perspective on the demographic drivers of structured population dynamics in changing environments

Current understanding of life‐history evolution and how demographic parameters contribute to population dynamics across species is largely based on assumptions of either constant environments or stationary environmental variation. Meanwhile, species are faced with non‐stationary environmental conditions (changing mean, variance, or both) created by climate and landscape change. To close the gap between contemporary reality and demographic theory, we develop a set of transient life table response experiments (LTREs) for decomposing realised population growth rates into contributions from specific vital rates and components of population structure. Using transient LTREs in a theoretical framework, we reveal that established concepts in population biology will require revision because of reliance on approaches that do not address the influence of unstable population structure on population growth and mean fitness. Going forward, transient LTREs will enhance understanding of demography and improve the explanatory power of models used to understand ecological and evolutionary dynamics.     

Applying population and community ecology theory to advance understanding of belowground biogeochemistry

Approaches to quantifying and predicting soil biogeochemical cycles mostly consider microbial biomass and community composition as products of the abiotic environment. Current numerical approaches then primarily emphasise the importance of microbe–environment interactions and physiology as controls on biogeochemical cycles. Decidedly less attention has been paid to understanding control exerted by community dynamics and biotic interactions. Yet a rich literature of theoretical and empirical contributions highlights the importance of considering how variation in microbial population ecology, especially biotic interactions, is related to variation in key biogeochemical processes like soil carbon formation. We demonstrate how a population and community ecology perspective can be used to (1) understand the impact of microbial communities on biogeochemical cycles and (2) reframe current theory and models to include more detailed microbial ecology. Through a series of simulations we illustrate how density dependence and key biotic interactions, such as competition and predation, can determine the degree to which microbes regulate soil biogeochemical cycles. The ecological perspective and model simulations we present lay the foundation for developing empirical research and complementary models that explore the diversity of ecological mechanisms that operate in microbial communities to regulate biogeochemical processes.     

兰科植物种群动态研究进展

兰科植物种群动态研究中,种群统计学分析能够很好地揭示植物个体在时空上的变化,是研究种群动态的核心.在自然生境中,许多附生兰科植物更倾向于离散或斑块状分布,可以通过集合种群研究分析斑块之间个体的基因流动,判断物种种群保护的规模.长期的种群动态研究能够获得兰科植物生活史和种群动态方面的可靠信息,以及一定环境条件下其时空波动及与种群功能之间的关系;短期的研究能够更好地理解具有结构性的独立植株与其所处的群落间的关系.本文根据种群生态学原理以及兰科植物的生态特点,从种群的密度及分布、种群统计学、种群的调节、集合种群和种群生存力分析（PVA）模型等方面阐述了国内外兰科植物种群动态研究进展.     

Coalescence 2.0: a multiple branching of recent theoretical developments and their applications

Population genetics theory has laid the foundations for genomic analyses including the recent burst in genome scans for selection and statistical inference of past demographic events in many prokaryote, animal and plant species. Identifying SNPs under natural selection and underpinning species adaptation relies on disentangling the respective contribution of random processes (mutation, drift, migration) from that of selection on nucleotide variability. Most theory and statistical tests have been developed using the Kingman coalescent theory based on the Wright‐Fisher population model. However, these theoretical models rely on biological and life history assumptions which may be violated in many prokaryote, fungal, animal or plant species. Recent theoretical developments of the so‐called multiple merger coalescent models are reviewed here (Λ‐coalescent, beta‐coalescent, Bolthausen‐Sznitman, Ξ‐coalescent). We explain how these new models take into account various pervasive ecological and biological characteristics, life history traits or life cycles which were not accounted in previous theories such as (i) the skew in offspring production typical of marine species, (ii) fast adapting microparasites (virus, bacteria and fungi) exhibiting large variation in population sizes during epidemics, (iii) the peculiar life cycles of fungi and bacteria alternating sexual and asexual cycles and (iv) the high rates of extinction‐recolonization in spatially structured populations. We finally discuss the relevance of multiple merger models for the detection of SNPs under selection in these species, for population genomics of very large sample size and advocate to potentially examine the conclusion of previous population genetics studies.     

From simple rules to cycling in community assembly

Simulation studies of community assembly have frequently observed two related phenomena: (1) the humpty dumpty effect in which communities can not be reconstructed by "sequential" invasions (i.e. single species invasions separated by long intervals of time) and (2) cycling between sub-communities. To better understand the mechanisms underlying these phenomena, we analyze a system consisting of two predators and two prey competing for a shared resource. We show how simple dominance rules (i.e. R^* and P^* rules) lead to cycling between sub-communities consisting of predator–prey pairs; predator and prey invasions alternatively lead to prey displacement via apparent competition and predator displacement via exploitative competition. We also show that these cycles are often dynamically unstable in the population phase space. More specifically, while for too slow invasion rates (i.e. "sequential" invasions) the system cycles indefinitely, faster invasion rates lead to coexistence of all species. In the later case, the assembly dynamics exhibit transient cycling between predator-prey subcommunities and the length of these transients decreases with the invasion rate and increases with habitat productivity.     

Toward a conceptual synthesis for climate change responses

Aim To identify hypotheses for how climate change affects long‐term population persistence that can be used as a framework for future syntheses of ecological responses to climate change. Location Global. Methods We surveyed ecological and evolutionary concepts related to how a changing climate might alter population persistence. We organized established concepts into a two‐stage framework that relates abiotic change to population persistence via changes in the rates or outcomes of ecological and evolutionary processes. We surveyed reviews of climate change responses, and evaluated patterns in light of our conceptual framework. Results We classified hypotheses for population responses to climate change as one of two types: (1) hypotheses that relate rates of ecological and evolutionary processes (plasticity, dispersal, population growth and evolution) to abiotic change, and (2) hypotheses that relate changes in these processes to four fundamental population‐level responses (colonization, acclimatization, adaptation or extinction). We found that a disproportionate emphasis on response in the climate change literature is difficult to reconcile with ecological and evolutionary theories that emphasize processes. We discuss a set of 24 hypotheses that represent gaps in the literature that limit our ability determine whether observed climate change responses are sufficient to facilitate persistence through future climate change. Main conclusions Though theory relates environmental change to fundamental ecological and evolutionary processes and population‐level responses, clear hypotheses based on theory have not been systematically formulated and tested in the context of climate change. Stronger links between basic theory and observed impacts of climate change are required to assess which responses are common, likely or able to facilitate population persistence despite ongoing environmental change. We anticipate that a hypothesis‐testing framework will reveal that indirect effects of climate change responses are more pervasive than previously thought and related to a few general processes, even though the patterns they create are incredibly diverse.     

How to understand species’ niches and range dynamics: a demographic research agenda for biogeography

Range dynamics causes mismatches between a species’ geographical distribution and the set of suitable environments in which population growth is positive (the Hutchinsonian niche). This is because source–sink population dynamics cause species to occupy unsuitable environments, and because environmental change creates non‐equilibrium situations in which species may be absent from suitable environments (due to migration limitation) or present in unsuitable environments that were previously suitable (due to time‐delayed extinction). Because correlative species distribution models do not account for these processes, they are likely to produce biased niche estimates and biased forecasts of future range dynamics. Recently developed dynamic range models (DRMs) overcome this problem: they statistically estimate both range dynamics and the underlying environmental response of demographic rates from species distribution data. This process‐based statistical approach qualitatively advances biogeographical analyses. Yet, the application of DRMs to a broad range of species and study systems requires substantial research efforts in statistical modelling, empirical data collection and ecological theory. Here we review current and potential contributions of these fields to a demographic understanding of niches and range dynamics. Our review serves to formulate a demographic research agenda that entails: (1) advances in incorporating process‐based models of demographic responses and range dynamics into a statistical framework, (2) systematic collection of data on temporal changes in distribution and abundance and on the response of demographic rates to environmental variation, and (3) improved theoretical understanding of the scaling of demographic rates and the dynamics of spatially coupled populations. This demographic research agenda is challenging but necessary for improved comprehension and quantification of niches and range dynamics. It also forms the basis for understanding how niches and range dynamics are shaped by evolutionary dynamics and biotic interactions. Ultimately, the demographic research agenda should lead to deeper integration of biogeography with empirical and theoretical ecology.     

How complex should models be? Comparing correlative and mechanistic range dynamics models

Criticism has been levelled at climate‐change‐induced forecasts of species range shifts that do not account explicitly for complex population dynamics. The relative importance of such dynamics under climate change is, however, undetermined because direct tests comparing the performance of demographic models vs. simpler ecological niche models are still lacking owing to difficulties in evaluating forecasts using real‐world data. We provide the first comparison of the skill of coupled ecological‐niche‐population models and ecological niche models in predicting documented shifts in the ranges of 20 British breeding bird species across a 40‐year period. Forecasts from models calibrated with data centred on 1970 were evaluated using data centred on 2010. We found that more complex coupled ecological‐niche‐population models (that account for dispersal and metapopulation dynamics) tend to have higher predictive accuracy in forecasting species range shifts than structurally simpler models that only account for variation in climate. However, these better forecasts are achieved only if ecological responses to climate change are simulated without static snapshots of historic land use, taken at a single point in time. In contrast, including both static land use and dynamic climate variables in simpler ecological niche models improve forecasts of observed range shifts. Despite being less skilful at predicting range changes at the grid‐cell level, ecological niche models do as well, or better, than more complex models at predicting the magnitude of relative change in range size. Therefore, ecological niche models can provide a reasonable first approximation of the magnitude of species' potential range shifts, especially when more detailed data are lacking on dispersal dynamics, demographic processes underpinning population performance, and change in land cover.     

A Reevaluation of Density-Dependent PopulationCycles in Open Systems

Studies motivated by consideration of barnacle populations have led to the prediction of two different dynamic states for space-limited open populations subject to density-dependent mortality. Population densities may cycle or fluctuate stochastically around a mean value. Despite the potential generality of the associated theory, there are few examples of population cycling in open systems that have been shown to be driven by density-dependent effects. This may be because settlement and growth processes are generally too slow or too variable to generate consistent cycles. An alternative explanation is examined in this article using spatially explicit simulations. Even under conditions of consistent settlement and growth, the cycles predicted in at least one previous study are shown to represent a special case. Clear population cycles are only observed when the density-dependent disturbances are constrained to reoccur in exactly the same location. In the more general case, where density-dependent disturbances respond to local variations in population density, the cycling predicted from simple models is difficult to detect. Hence, a failure to detect cycling in population density does not refute a role for density dependence. Density-dependent disturbances can create a characteristic spatial structure consisting of a mosaic of cohorts.     

A newly discovered role of evolution in previously published consumer–resource dynamics

Consumer–resource interactions are fundamental components of ecological communities. Classic features of consumer–resource models are that temporal dynamics are often cyclic, with a ¼‐period lag between resource and consumer population peaks. However, there are few published empirical examples of this pattern. Here, we show that many published examples of consumer–resource cycling show instead patterns indicating eco‐evolutionary dynamics. When prey evolve along a trade‐off between defence and competitive ability, two‐species consumer–resource cycles become longer and antiphase (half‐period lag, so consumer maxima coincide with minima of the resource species). Using stringent criteria, we identified 21 two‐species consumer–resource time series, published between 1934 and 1997, suitable to investigate for eco‐evolutionary dynamics. We developed a statistical method to probe for a transition from classic to eco‐evolutionary cycles, and find evidence for eco‐evolutionary type cycles in about half of the studies. We show that rapid prey evolution is the most likely explanation for the observed patterns.     

Describing and understanding behavioral responses to multiple stressors and multiple stimuli

Understanding the effects of environmental change on natural ecosystems is a major challenge, particularly when multiple stressors interact to produce unexpected “ecological surprises” in the form of complex, nonadditive effects that can amplify or reduce their individual effects. Animals often respond behaviorally to environmental change, and multiple stressors can have both population‐level and community‐level effects. However, the individual, not combined, effects of stressors on animal behavior are commonly studied. There is a need to understand how animals respond to the more complex combinations of stressors that occur in nature, which requires a systematic and rigorous approach to quantify the various potential behavioral responses to the independent and interactive effects of stressors. We illustrate a robust, systematic approach for understanding behavioral responses to multiple stressors based on integrating schemes used to quantitatively classify interactions in multiple‐stressor research and to qualitatively view interactions between multiple stimuli in behavioral experiments. We introduce and unify the two frameworks, highlighting their conceptual and methodological similarities, and use four case studies to demonstrate how this unification could improve our interpretation of interactions in behavioral experiments and guide efforts to manage the effects of multiple stressors. Our unified approach: (1) provides behavioral ecologists with a more rigorous and systematic way to quantify how animals respond to interactions between multiple stimuli, an important theoretical advance, (2) helps us better understand how animals behave when they encounter multiple, potentially interacting stressors, and (3) contributes more generally to the understanding of “ecological surprises” in multiple stressors research.     

DEMOGRAPHIC MECHANISMS DETERMINING THE DYNAMICS OF THE RELATIVE ABUNDANCE OF PHASES IN BIPHASIC LIFE CYCLES1

Studies investigating the demographic traits that drive the patterns of phase dominance (the ploidy ratio) in isomorphic biphasic life cycles have not found an integrative solution. Either fertility or survival has been suggested independently as the main driver. Here, we provide a global theoretical framework on how demographic mechanisms determine the ploidy ratio, unifying previous numerical and observational attempts at this question. The analytical solutions of both the ploidy ratio and its elasticities to model parameters of a stage/size‐structured model patterned after the life cycle of a marine alga were derived and analyzed. A complex interaction among vital rates determines the patterns of phase dominance of biphasic life cycles. Three co‐occurring processes—growth, fertility, and looping—may dominate the dynamics of the population, determining both its growth rate and ploidy ratio. Our analyses show that in species where fertility is low, the ploidy ratio is highly elastic to looping transitions (survival, breakage, and clonal growth). Consequently, the subtle morphological, ecophysiological, and biochemistry phase differences that have been reported in isomorphic life cycles as not explaining the observed ploidy ratios, may, in fact, explain them if they translate into slight phase differences in looping transitions. In species where fertility is low, the looping dissimilarities between phases cannot be too high favoring simultaneously one phase, as the population structure would be completely dominated by that phase. In the case of ecological similarity between phases (equal looping and growth rates between phases), a ploidy ratio different from one can only be set by strong phase differences in fertility.     

Coevolution-driven predator-prey cycles: predicting the characteristics of eco-coevolutionary cycles using fast-slow dynamical systems theory

Eco-coevolutionary theory predicts that predator-prey coevolution occurring on the time scale of ecological dynamics (e.g., changes in population abundances) can drive novel kinds of predator-prey cycles, e.g., cryptic cycles where one species cycles while the other remains effectively constant and clockwise cycles where peaks in predator density precede peaks in prey density. However, because this body of theory has focused on particular models and studied the different cycle types in isolation, it is unclear what biological characteristics (e.g., costs for offense or defense) determine when a particular cycle type will arise. In this study, I explore the kinds of predator-prey cycles that arise in a general eco-coevolutionary model where there is disruptive selection and the coevolutionary dynamics are fast relative to the ecological dynamics of the system. With a graphical tool created using the theory of fast-slow dynamical systems, I predict what kinds of cycles can arise in the model and how cycle type depends on the costs for prey defense and predator offense. Fast-slow dynamical systems theory requires a separation of time scales between the ecological and evolutionary processes; however, numerical simulations show that this tool can help predict how coevolution drives populations cycles in systems where the speeds of ecological and evolutionary dynamics are comparable. Thus, this work is a step forward in building a general eco-coevolutionary theory.     

Population Cycles,Disease, and Networks of Ecological Knowledge

Wildlife populations in the northern reaches of the globe have long been observed to fluctuate or cycle periodically, with dramatic increases followed by catastrophic crashes. Focusing on the early work of Charles S. Elton, this article analyzes how investigations into population cycles shaped the development of Anglo-American animal ecology during the 1920s–1930s. Population cycling revealed patterns that challenged ideas about the “balance” of nature; stimulated efforts to quantify population data; and brought animal ecology into conversation with intellectual debates about natural selection. Elton used the problem of understanding wildlife population cycles to explore a central tension in ecological thought: the relative influences of local conditions (food supply, predation) and universal forces (such as climate change and natural selection) in regulating wild animal populations. He also sought patronage and built research practices and the influential Bureau of Animal Population around questions of population regulation during the 1930s. Focusing on disease as a local population regulator that could interact with global climatic influences, Elton facilitated an interdisciplinary and population-based approach in early animal ecology. Elton created a network of epidemiologists, conservationists, pathologists and mathematicians, who contributed to population cycle research. I argue that, although these people often remained peripheral to ecology, their ideas shaped the young discipline. Particularly important were the concepts of abundance, density, and disease; and the interactions between these factors and natural selection. However, Elton’s reliance on density dependence unwittingly helped set up conditions conducive to the development of controversies in animal ecology in later years. While ecologists did not come to consensus on the ultimate causes of population cycles, this phenomenon was an important early catalyst for the development of theory and practice in animal ecology.     

Complex dynamics occur in a single-locus,multiallelic model of general frequency-dependent selection

We examine the characteristics of non-equilibrium dynamics produced by a simple well-known model of frequency-dependent selection at a single diploid locus. An examination of the parameter space of this “pairwise-interaction model” (PIM) revealed non-equilibrium dynamics for polymorphisms of 3, 4 and 5 alleles; both allele-frequency cycling and aperiodic trajectories were detected. We measured the number, cycle length and domains of attraction of the various attractors produced by the model. The domains of attraction tended to be smaller, and the cycles longer, for systems with larger number of alleles. Fitnesses that parametrized negative frequency-dependent selection were more likely to allow cycling, and these cycles also had larger domains of attraction. Aperiodic trajectories were detected only in cases with 4 or 5 alleles. The genetic cycles produced by the model do not have periods as short as those predicted in ecological models with cycling (such as predator–prey population cycles, etc.). Consequently, in a real-world system, PIM allele-frequency cycling is likely to be indistinguishable from stable equilibria when observed over short time scales.     

The total opportunity for sexual selection and the integration of pre‐ and post‐mating episodes of sexual selection in a complex world

It is well known that sexual selection can target reproductive traits during successive pre‐ and post‐mating episodes of selection. A key focus of recent studies has been to understand and quantify how these episodes of sexual selection interact to determine overall variance in reproductive success. In this article, we review empirical developments in this field but also highlight the considerable variability in patterns of pre‐ and post‐mating sexual selection, attributable to variation in patterns of resource acquisition and allocation, ecological and social factors, genotype‐by‐environment interaction and possible methodological factors that might obscure such patterns. Our aim is to highlight how (co)variances in pre‐ and post‐mating sexually selected traits can be sensitive to changes in a range of ecological and environmental variables. We argue that failure to capture this variation when quantifying the opportunity for sexual selection may lead to erroneous conclusions about the strength, direction or form of sexual selection operating on pre‐ and post‐mating traits. Overall, we advocate for approaches that combine measures of pre‐ and post‐mating selection across contrasting environmental or ecological gradients to better understand the dynamics of sexual selection in polyandrous species. We also discuss some directions for future research in this area.     

Beyond species: why ecological interaction networks vary through space and time

Community ecology is tasked with the considerable challenge of predicting the structure, and properties, of emerging ecosystems. It requires the ability to understand how and why species interact, as this will allow the development of mechanism‐based predictive models, and as such to better characterize how ecological mechanisms act locally on the existence of inter‐specific interactions. Here we argue that the current conceptualization of species interaction networks is ill‐suited for this task. Instead, we propose that future research must start to account for the intrinsic variability of species interactions, then scale up from here onto complex networks. This can be accomplished simply by recognizing that there exists intra‐specific variability, in traits or properties related to the establishment of species interactions. By shifting the scale towards population‐based processes, we show that this new approach will improve our predictive ability and mechanistic understanding of how species interact over large spatial or temporal scales. Synthesis Although species interactions are the backbone of ecological communities, we have little insights on how (and why) they vary through space and time. In this article, we build on existing empirical literature to show that the same species may happen to interact in different ways when their local abundances vary, their trait distribution changes, or when the environment affects either of these factors. We discuss how these findings can be integrated in existing frameworks for the analysis and simulation of species interactions.     

Predicting when climate‐driven phenotypic change affects population dynamics

Species' responses to climate change are variable and diverse, yet our understanding of how different responses (e.g. physiological, behavioural, demographic) relate and how they affect the parameters most relevant for conservation (e.g. population persistence) is lacking. Despite this, studies that observe changes in one type of response typically assume that effects on population dynamics will occur, perhaps fallaciously. We use a hierarchical framework to explain and test when impacts of climate on traits (e.g. phenology) affect demographic rates (e.g. reproduction) and in turn population dynamics. Using this conceptual framework, we distinguish four mechanisms that can prevent lower‐level responses from impacting population dynamics. Testable hypotheses were identified from the literature that suggest life‐history and ecological characteristics which could predict when these mechanisms are likely to be important. A quantitative example on birds illustrates how, even with limited data and without fully‐parameterized population models, new insights can be gained; differences among species in the impacts of climate‐driven phenological changes on population growth were not explained by the number of broods or density dependence. Our approach helps to predict the types of species in which climate sensitivities of phenotypic traits have strong demographic and population consequences, which is crucial for conservation prioritization of data‐deficient species.