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Despite the importance of population structures throughout ecology, relatively little theoretical attention has been paid to understanding the implications of social groups for population dynamics. The dynamics of socially structured populations differ substantially from those of unstructured or metapopulation‐structured populations, because social groups themselves may split, fuse, and compete. These "between‐group processes" remain understudied as drivers of the dynamics of socially structured populations. Here, we explore the role of various between‐group processes in the dynamics of socially structured populations. To do so, we analyze a model that includes births, deaths, migration, fissions, fusions, and between‐group competition and flexibly allows for density dependence in each process. Both logistic growth and an Allee effect are considered for within‐group density dependence. We show that the effect of various between‐group processes is mediated by their influence on the stable distribution of group sizes, with the ultimate impact on the population determined by the interaction between within‐group density dependence and the process's effect on the group size distribution. Between‐group interactions that change the number of groups can lead to both negative and positive density dependence at the global population level (even if birth and death rates depend only on group size and not population size). We conclude with a series of case studies that illustrates different ways that age, sex, and class structure impact the dynamics of social populations. These case studies demonstrate the importance of group‐formation mechanisms, the cost of having excess males in a group, and the potential drawbacks of generating too many reproductive individuals. In sum, our results make clear the importance of within‐group density dependence, between‐group dynamics, and the interactions between them for the population dynamics of social species and provide a flexible framework for modeling social populations. [ABSTRACT FROM AUTHOR]

To understand the success of invasive alien species, it is necessary to evaluate the site-specific eco-evolutionary challenges they face in their new environments. We explored whether the rearrangement of genetic diversity is linked to the invasiveness of Prosopis juliflora by (i) comparing different stages of invasion (founding vs invasive populations) in two invaded areas (Afar Region, Ethiopia and Baringo County, Kenya) to evaluate whether different stages are dominated by different genetic attributes (e.g., characteristic genotypes or levels of genetic diversity) and by (ii) evaluating if landscape features affected dispersal between invasive populations in the two invaded areas. We hypothesised that different invasion stages would have unique genetic characteristics due to either site-specific demographic and/or dispersal dynamics. We also compared the genetic characteristics at an 'invasive–non-invasive congener' level by studying the non-invasive P. pallida, introduced to Baringo County, and assessed whether it hybridises with P. juliflora. In the Afar Region, the establishment and spread of P. juliflora were characterised by extensive gene flow that homogenised genetic diversity across all populations. In contrast, in Baringo County, invasive populations had lower genetic diversity than founders, and genetic differentiation was lower between invasive populations than between invasive and founder populations. In both invaded areas, we found no evidence that dispersal was hampered by geographic distance, bioclimatic conditions, or distance to roads, rivers and villages, at least at the spatial scales of our study; indicating frequent long-distance dispersal. Allelic richness was higher in P. juliflora than P. pallida founders and hybrids were mainly planted trees probably resulting from the sympatric cultivation of the two species following their introduction. Thus, management actions on Prosopis invasion in eastern Africa should consider site-specific dynamics occurring during the invasion. [ABSTRACT FROM AUTHOR]

Exponential model for population growth (exponential model) is a foundation to evaluate population dynamics in Population Ecology field. Here, we used a didactic experiment to teach exponential model for an undergraduate course of Population Ecology. We built nine populations of weevils with three different initial population sizes: eight, 16, and 32 individuals with three replicates each. We provided equal food resource availability, and counted their population sizes weekly for 12 weeks. We estimated the intrinsic growth rate (i.e., r parameter), by trials and errors with an exponential model build in an Excel spreadsheet. The population growth rate (i.e., dN/dt parameter) was estimated using r values. Replicates with eight and 16 individuals reached the highest values of r and dN/dt, while replicates with 32 individuals reached the lowest values. Beyond of exponential model, two density dependency issues acting in populations were observed. First, in the lowest initial population sizes we observed the effect of demographic stochasticity acting in both r and dN/dt in one of the three populations. Second, we observed the intraspecific competition reducing r values in largest initial populations. Therefore, we highlight the importance of didactic experiment into learning exponential model in Population Ecology course, both for teaching and learning practices.

Life history traits are used to predict asymptotic odds of extinction from dynamic conditions. Less is known about how life history traits interact with stochasticity and population structure of finite populations to predict near‐term odds of extinction. Through empirically parameterized matrix population models, we study the impact of life history (reproduction, pace), stochasticity (environmental, demographic), and population history (existing, novel) on the transient population dynamics of finite populations of plant species. Among fast and slow pace and either a uniform or increasing reproductive intensity or short or long reproductive lifespan, slow, semelparous species are at the greatest risk of extinction. Long reproductive lifespans buffer existing populations from extinction while the odds of extinction of novel populations decrease when the reproductive effort is uniformly spread across the reproductive lifespan. Our study highlights the importance of population structure, pace, and two distinct aspects of parity for predicting near‐term odds of extinction. [ABSTRACT FROM AUTHOR]

Species coexistence in ecological communities is a central feature of biodiversity. Different concepts, i.e., contemporary niche theory, modern coexistence theory, and the unified neutral theory, have identified many building blocks of such ecological assemblies. However, other factors, such as phenotypic plasticity and stochastic inter‐individual variation, have received little attention, in particular in animals. For example, how resource polyphenisms resulting in predator–prey interactions affect coexistence is currently unknown. Here, we present an integrative theoretical–experimental framework using the nematode plasticity model Pristionchus pacificus with its well‐studied mouth‐form dimorphism resulting in cannibalism. We develop an individual‐based model that relies upon synthetic data based on our empirical measurements of fecundity and polyphenism to preserve demographic heterogeneity. We demonstrate how the interplay between plasticity and individual stochasticity result in all‐or‐nothing outcomes at the local level. Coexistence is made possible when spatial structure is introduced. [ABSTRACT FROM AUTHOR]

Abstract Life history traits are used to predict asymptotic odds of extinction from dynamic conditions. Less is known about how life history traits interact with stochasticity and population structure of finite populations to predict near‐term odds of extinction. Through empirically parameterized matrix population models, we study the impact of life history (reproduction, pace), stochasticity (environmental, demographic), and population history (existing, novel) on the transient population dynamics of finite populations of plant species. Among fast and slow pace and either a uniform or increasing reproductive intensity or short or long reproductive lifespan, slow, semelparous species are at the greatest risk of extinction. Long reproductive lifespans buffer existing populations from extinction while the odds of extinction of novel populations decrease when the reproductive effort is uniformly spread across the reproductive lifespan. Our study highlights the importance of population structure, pace, and two distinct aspects of parity for predicting near‐term odds of extinction.

Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics.

Heterogeneity among individuals in fitness components is what selection acts upon. Evolutionary theories predict that selection in constant environments acts against such heterogeneity. But observations reveal substantial non‐genetic and also non‐environmental variability in phenotypes. Here, we examine whether there is a relationship between selection pressure and phenotypic variability by analysing structured population models based on data from a large and diverse set of species. Our findings suggest that non‐genetic, non‐environmental variation is in general neither truly neutral, selected for, nor selected against. We find much variations among species and populations within species, with mean patterns suggesting nearly neutral evolution of life‐course variability. Populations that show greater diversity of life courses do not show, in general, increased or decreased population growth rates. Our analysis suggests we are only at the beginning of understanding the evolution and maintenance of non‐genetic non‐environmental variation. [ABSTRACT FROM AUTHOR]

Abstract With species increasingly imperiled due to anthropogenic activities, conservation practitioners are tasked with determining conservation priorities to make the best use of limited resources. One way of setting priorities is to categorize species based on risk of extinction. The United States' Endangered Species Act (ESA) has two listing statuses into which imperiled species are placed to receive protections: threatened or endangered. Our objective was to identify differences between threatened and endangered (T&E) species beyond what is outlined in their ESA definitions. For 6 broad‐resolution threats (habitat modification, overutilization, pollution, species‐species interactions, environmental stochasticity, and demographic stochasticity), we investigated whether there is a difference in the number and types of threats which impacted T&E species at the time of their listing. We found that threatened (x̄ = 2.9, SD = 1.4) and endangered (x̄ = 3.0, SD = 1.1) species faced a similar number of threats at time of their listing. The only broad‐resolution threat that impacted endangered species more than threatened species was demographic stochasticity, with endangered species being 2.1 times (95% CI = 1.5–2.8) more likely to be impacted than threatened species. We examined demographic stochasticity by breaking it down into finer‐resolution threats to identify additional differences between T&E species. We found 4 finer‐resolution demographic stochasticity threats (few individuals in one population, few individuals in multiple populations, lack of reproduction, and genetic loss) to be strong predictors of endangered status. The similarities in the number and types of broad‐resolution threats faced by T&E species indicated that they are equally conservation reliant.

Contemporary studies of species coexistence are underpinned by deterministic models that assume that competing species have continuous (i.e., noninteger) densities, live in infinitely large landscapes, and coexist over infinite time horizons. By contrast, in nature, species are composed of discrete individuals subject to demographic stochasticity and occur in habitats of finite size where extinctions occur in finite time. One consequence of these discrepancies is that metrics of species' coexistence derived from deterministic theory may be unreliable predictors of the duration of species coexistence in nature. These coexistence metrics include invasion growth rates and niche and fitness differences, which are now commonly applied in theoretical and empirical studies of species coexistence. In this study, we tested the efficacy of deterministic coexistence metrics on the duration of species coexistence in a finite world. We introduce new theoretical and computational methods to estimate coexistence times in stochastic counterparts of classic deterministic models of competition. Importantly, we parameterized this model using experimental field data for 90 pairwise combinations of 18 species of annual plants, allowing us to derive biologically informed estimates of coexistence times for a natural system. Strikingly, we found that for species expected to deterministically coexist, community sizes containing only 10 individuals had predicted coexistence times of more than 1000 years. We also found that invasion growth rates explained 60% of the variation in intrinsic coexistence times, reinforcing their general usefulness in studies of coexistence. However, only by integrating information on both invasion growth rates and species' equilibrium population sizes could most (>99%) of the variation in species coexistence times be explained. This integration was achieved with demographically uncoupled single‐species models solely determined by the invasion growth rates and equilibrium population sizes. Moreover, because of a complex relationship between niche overlap/fitness differences and equilibrium population sizes, increasing niche overlap and increasing fitness differences did not always result in decreasing coexistence times, as deterministic theory would predict. Nevertheless, our results tend to support the informed use of deterministic theory for understanding the duration of species' coexistence while highlighting the need to incorporate information on species' equilibrium population sizes in addition to invasion growth rates. [ABSTRACT FROM AUTHOR]

Invasibility, the chance of a population to grow from rarity and become established, plays a fundamental role in population genetics, ecology, epidemiology and evolution. For many decades, the mean growth rate of a species when it is rare has been employed as an invasion criterion. Recent studies show that the mean growth rate fails as a quantitative metric for invasibility, with its magnitude sometimes even increasing while the invasibility decreases. Here we provide two novel formulae, based on the diffusion approximation and a large‐deviations (Wentzel–Kramers–Brillouin) approach, for the chance of invasion given the mean growth and its variance. The first formula has the virtue of simplicity, while the second one holds over a wider parameter range. The efficacy of the formulae, including their accompanying data analysis technique, is demonstrated using synthetic time series generated from canonical models and parameterised with empirical data. [ABSTRACT FROM AUTHOR]

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

In this paper, we utilize an absorbed diffusion process to model the dynamics of a single species under the influence of demographic stochasticity and component Allee effects. The trajectories of stochastic solutions exhibits multi-scale dynamics distinct from those of the corresponding mean-field model. The primary focus is on analyzing transient dynamics before extinction, which is described by the quasi-stationary distribution. The paper provides results on the existence, uniqueness, and exponential convergence to the quasi-stationary distribution for initial distributions with compact support. Due to the singularity of the noise at 0, we employ the idea of changing variables to transfer the model into one-dimensional Kolmogorov diffusions with a drift possibly exploding at 0, to prove the main results. [ABSTRACT FROM AUTHOR]

We analyse how migration from a large mainland influences genetic load and population numbers on an island, in a scenario where fitness-affecting variants are unconditionally deleterious, and where numbers decline with increasing load. Our analysis shows that migration can have qualitatively different effects, depending on the total mutation target and fitness effects of deleterious variants. In particular, we find that populations exhibit a genetic Allee effect across a wide range of parameter combinations, when variants are partially recessive, cycling between low-load (large-population) and high-load (sink) states. Increased migration reduces load in the sink state (by increasing heterozygosity) but further inflates load in the large-population state (by hindering purging). We identify various critical parameter thresholds at which one or other stable state collapses, and discuss how these thresholds are influenced by the genetic versus demographic effects of migration. Our analysis is based on a 'semi-deterministic' analysis, which accounts for genetic drift but neglects demographic stochasticity. We also compare against simulations which account for both demographic stochasticity and drift. Our results clarify the importance of gene flow as a key determinant of extinction risk in peripheral populations, even in the absence of ecological gradients. This article is part of the theme issue 'Species' ranges in the face of changing environments (part I)'. [ABSTRACT FROM AUTHOR]

Past environmental changes have shaped the evolutionary and ecological diversity of extant organisms. Specifically, climatic fluctuations have made environmental conditions alternatively common or rare over time. Accordingly, most taxa have undergone restriction of their distribution to local refugia during habitat contraction, from which they could expand when suitable habitat became more common. Assessing how past restrictions in refugia have shaped species distributions and genetic diversity has motivated much research in evolutionary biology and biogeography. But there is still lack of clear synthesis on whether and how the taxonomic, functional and phylogenetic composition of extant multispecies assemblages retains the imprint of past restriction in refugia. We devised an original eco-evolutionary model to investigate the temporal dynamics of a regional species pool inhabiting a given habitat today, and which have experienced habitat reduction in the past. The model includes three components: (i) a demographic component driving stochastic changes in population sizes and extinctions due to habitat availability, (ii) a mutation and speciation component representing how divergent genotypes emerge and define new species over time, and (iii) a trait evolution component representing how trait values have changed across descendants over time. We used this model to simulate dynamics of multispecies assemblages that occupied a restricted refugia in the past and could expand their distribution subsequently. We characterized the past restriction in refugia in terms of two parameters representing the ending time of past refugia, and the extent of habitat restriction in the refugia. We characterized extant patterns of taxonomic, functional and phylogenetic diversity depending on these parameters. We found that extant relative abundances reflect the lasting influence of more recent refugia on demographic dynamics, while phylogenetic composition reflects the influence of more ancient habitat change. Extant functional diversity depends on the interplay between diversification dynamics and trait evolution, offering new options to jointly infer current trait adaptation and past trait evolution dynamics.

This article analyzes the conditions for local adaptation in a metapopulation with infinitely many islands under a model of hard selection, where population size depends on local fitness. Each island belongs to one of two distinct ecological niches or habitats. Fitness is influenced by an additive trait which is under habitat‐dependent directional selection. Our analysis is based on the diffusion approximation and accounts for both genetic drift and demographic stochasticity. By neglecting linkage disequilibria, it yields the joint distribution of allele frequencies and population size on each island. We find that under hard selection, the conditions for local adaptation in a rare habitat are more restrictive for more polygenic traits: even moderate migration load per locus at very many loci is sufficient for population sizes to decline. This further reduces the efficacy of selection at individual loci due to increased drift and because smaller populations are more prone to swamping due to migration, causing a positive feedback between increasing maladaptation and declining population sizes. Our analysis also highlights the importance of demographic stochasticity, which exacerbates the decline in numbers of maladapted populations, leading to population collapse in the rare habitat at significantly lower migration than predicted by deterministic arguments. [ABSTRACT FROM AUTHOR]

Introduction: Despite extensive science-based conservation policy recommendations, with fewer than 20 individuals remaining, the vaquita (Phocoena sinus) -endemic to the Gulf of California- is the world's most endangered marine mammal due to incidental catch in fishing nets and whether it can recover is unclear. Objective: Assess expectations for vaquita over the next two decades. Methods: We identified factors affecting the vaquita, constructed life tables, derived demographic parameters for different scenarios and conducted a population viability analysis using stochastic age-structured matrix Leslie models. Results: Analytical results indicate that the vaquita net growth rate is particularly sensitive to juvenile survival. We find that intensive, ongoing bycatch in gillnets used to poach totoaba (Totoaba macdonaldi) over the past decade brought the vaquita population to its current critically low size. Currently this seems to be exacerbated by demographic stochasticity and a potential Allee effect. Conclusions: If totoaba poaching is eliminated immediately, demographically, vaquita can recover; its long-term survival will depend on its uncertain genetic status, although a recent study found encouraging results in this regard. [ABSTRACT FROM AUTHOR]

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

Rapid evolution on ecological time scales can play a key role in species responses to environmental change. One dynamic that has the potential to generate the diversity necessary for evolution rapid enough to allow response to sudden environmental shifts is introgressive hybridization. However, if distinct sub-species exist before an environmental shift, mechanisms that impede hybridization, such as assortative mating and hybrid inferiority, are likely to be present. Here we explore the theoretical potential for introgressive hybridization to play a role in response to environmental change. In particular, we incorporate assortative mating, hybrid inferiority, and demographic stochasticity into a two-locus, two-allele population genetic model of two interacting species where one locus identifies the species and the other determines how fitness depends on the changing environment. Simulation results indicate that moderately high values for the strength of assortative mating will allow enough hybridization events to outweigh demographic stochasticity but not so many that continued hybridization outweighs backcrossing and introgression. Successful introgressive hybridization also requires intermediate relative fitness at the allele negatively affected by environmental change such that hybrid survivorship outweighs demographic stochasticity but selection remains strong enough to affect the genetic dynamics. The potential for successful introgression instead of extinction with greater environmental change is larger with monogamous rather than promiscuous mating due to lower stochasticity in mating events. These results suggest species characteristics (e.g., intermediate assortative mating and mating systems with low variation in mating likelihood) which indicate a potential for rapid evolution in response to environmental change via introgressive hybridization. © 2011 The Author(s).

Synergistic and antagonistic interactions in multi-species populations—such as resource sharing and competition—result in remarkably diverse behaviours in populations of interacting cells, such as in soil or human microbiomes, or clonal competition in cancer. The degree of inter- and intra-specific interaction can often be quantified through the notion of an ecological ‘niche’. Typically, weakly interacting species that occupy largely distinct niches result in stable mixed populations, while strong interactions and competition for the same niche result in rapid extinctions of some species and fixations of others. We investigate the transition of a deterministically stable mixed population to a stochasticity-induced fixation as a function of the niche overlap between the two species. We also investigate the effect of the niche overlap on the population stability with respect to external invasions. Our results have important implications for a number of experimental systems.

Many populations live and disperse in advective media. A fundamental question, known as the “drift paradox” in stream ecology, is how a closed population can survive when it is constantly being transported downstream by the flow. Recent population-level models have focused on the role of diffusive movement in balancing the effects of advection, predicting critical conditions for persistence. Here, we formulate an individual-based stochastic analog of the model described in (Lutscher et al., SIAM Rev. 47(4):749–772, 2005) to quantify the effects of demographic stochasticity on persistence. Population dynamics are modeled as a logistic growth process and dispersal as a position-jump process on a finite domain divided into patches. When there is no correlation in the interpatch movement of residents, stochasticity simply smooths the persistence-extinction boundary. However, when individuals disperse in “packets” from one patch to another and the flow field is memoryless on the timescale of packet transport, the probability of persistence is greatly enhanced. The latter transport mechanism may be characteristic of larval dispersal in the coastal ocean or wind-dispersed seed pods.

Demographic stochasticity can have large effects on the dynamics of small populations as well as on the persistence of rare genotypes and lineages. Survival is sensibly modeled as a binomial process, but annual reproductive success (ARS) is more complex and general models for demographic stochasticity do not exist. Here we introduce a stochastic model framework for ARS and illustrate some of its properties. We model a sequence of stochastic events: nest completion, the number of eggs or neonates produced, nest predation, and the survival of individual offspring to independence. We also allow multiple nesting attempts within a breeding season. Most of these components can be described by Bernoulli or binomial processes; the exception is the distribution of offspring number. Using clutch and litter size distributions from 53 vertebrate species, we demonstrate that among-individual variability in offspring number can usually be described by the generalized Poisson distribution. Our model framework allows the demographic variance to be calculated from underlying biological processes and can easily be linked to models of environmental stochasticity or selection because of its parametric structure. In addition, it reveals that the distributions of ARS are often multimodal and skewed, with implications for extinction risk and evolution in small populations.

Although metacommunity ecology has been a major field of research in the last decades, with both conceptual and empirical outputs, the analysis of the temporal dynamics of metacommunities has only emerged recently and consists mostly of repeated static analyses. Here we propose a novel analytical framework to assess metacommunity processes using path analyses of spatial and temporal diversity turnovers. We detail the principles and practical aspects of this framework and apply it to simulated datasets to illustrate its ability to decipher the respective contributions of entangled drivers of metacommunity dynamics. We then apply it to four empirical datasets. Empirical results support the view that metacommunity dynamics may be generally shaped by multiple ecological processes acting in concert, with environmental filtering being variable across both space and time. These results reinforce our call to go beyond static analyses of metacommunities that are blind to the temporal part of environmental variability. [ABSTRACT FROM AUTHOR]

Ecological drift can override the effects of deterministic niche selection on small populations and drive the assembly of some ecological communities. We tested this hypothesis with a unique data set sampled identically in 200 streams in two regions (tropical Brazil and boreal Finland) that differ in macroinvertebrate community size by fivefold. Null models allowed us to estimate the magnitude to which β‐diversity deviates from the expectation under a random assembly process while taking differences in richness and relative abundance into account, i.e., β‐deviation. We found that both abundance‐ and incidence‐based β‐diversity was negatively related to community size only in Brazil. Also, β‐diversity of small tropical communities was closer to stochastic expectations compared with β‐diversity of large communities. We suggest that ecological drift may drive variation in some small communities by changing the expected outcome of niche selection, increasing the chances of species with low abundance and narrow distribution to occur in some communities. Habitat destruction, overexploitation, pollution, and reductions in connectivity have been reducing the size of biological communities. These environmental pressures might make smaller communities more vulnerable to novel conditions and render community dynamics more unpredictable. Incorporation of community size into ecological models should provide conceptual and applied insights into a better understanding of the processes driving biodiversity. [ABSTRACT FROM AUTHOR]

The Price equation has found widespread application in many areas of evolutionary biology, including the evolutionary epidemiology of infectious diseases. In this paper, we illustrate the utility of this approach to modelling disease evolution by first deriving a version of Price's equation that can be applied in continuous time and to populations with overlapping generations. We then show how this version of Price's equation provides an alternative perspective on pathogen evolution by considering the epidemiological meaning of each of its terms. Finally, we extend these results to the case where population size is small and generates demographic stochasticity. We show that the particular partitioning of evolutionary change given by Price's equation is also a natural way to partition the evolutionary consequences of demographic stochasticity, and demonstrate how such stochasticity tends to weaken selection on birth rate (e.g. the transmission rate of an infectious disease) and enhance selection on mortality rate (e.g. factors, like virulence, that cause the end of an infection). In the long term, if there is a trade-off between virulence and transmission across parasite strains, the weaker selection on transmission and stronger selection on virulence that arises from demographic stochasticity will tend to drive the evolution of lower levels of virulence. This article is part of the theme issue 'Fifty years of the Price equation'. [ABSTRACT FROM AUTHOR]

Empirical knowledge of diversity–stability relationships is mostly based on the analysis of temporal variability. Variability, however, often depends on external factors that act as disturbances, which makes comparisons across systems difficult to interpret. Here, we show how variability can reveal inherent stability properties of ecological communities. This requires that we abandon one‐dimensional representations, in which a single variability measurement is taken as a proxy for how stable a system is, and instead consider the whole set of variability values generated by all possible stochastic perturbations. Despite this complexity, in species‐rich systems, a generic pattern emerges from community assembly, relating variability to the abundance of perturbed species. Strikingly, the contrasting contributions of different species abundance classes to variability, driven by different types of perturbations, can lead to opposite diversity–stability patterns. We conclude that a multidimensional perspective on variability helps reveal the dynamical richness of ecological systems and the underlying meaning of their stability patterns. [ABSTRACT FROM AUTHOR]

Behaviour underpins interactions among conspecifics and between species, with consequences for the transmission of disease-causing parasites. Because many parasites lead to declines in population size and increased risk of extinction for threatened species, understanding the link between host behaviour and disease transmission is particularly important for conservation management. Here, we consider the intersection of behaviour, ecology and parasite transmission, broadly encompassing micro- and macroparasites. We focus on behaviours that have direct impacts on transmission, as well as the behaviours that result from infection. Given the important role of parasites in host survival and reproduction, the effects of behaviour on parasitism can scale up to population-level processes, thus affecting species conservation. Understanding how conservation and infectious disease control strategies actually affect transmission potential can therefore often only be understood through a behavioural lens. We highlight how behavioural perspectives of disease ecology apply to conservation by reviewing the different ways that behavioural ecology influences parasite transmission and conservation goals. This article is part of the theme issue 'Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation'. [ABSTRACT FROM AUTHOR]

One of the most important challenges in conservation biology is to predict the viability of populations of vulnerable and threatened species. This requires that the demographic stochasticity strongly affecting the ecological and evolutionary dynamics of especially small populations is correctly estimated and modelled. Here, we summarize theoretical evidence showing that the demographic variance in population dynamics is a key parameter determining the probability of extinction and also is directly linked to the magnitude of the genetic drift in the population. The demographic variance is dependent on the mating system, being larger in a polygynous than in monogamous populations. Understanding factors affecting intersexual differences in mating success is therefore essential in explaining variation in the demographic variance. We hypothesize that the strength of sexual selection, for example, quantified by the Bateman gradient, may be a useful predictor of the magnitude of the demographic stochasticity and hence the genetic drift in the population. We provide results from a field study of moose that support this claim. Thus, including central principles from behavioural ecology may increase the reliability of population viability analyses through an improvement of our understanding of factors affecting stochastic influences on population dynamics and evolutionary processes. This article is part of the theme issue 'Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation'. [ABSTRACT FROM AUTHOR]

Understanding what affects population growth in novel environments is fundamental to forecast organisms' responses to global change, including biological invasions and land use intensification. Novel environments are challenging because they can cause maladaptation, increasing the risk of extinction by negative population growth. Animals can avoid extinction by improving the phenotype–environment match through behavioural responses, notably matching habitat choice and learning. However, the demographic consequences of these responses remain insufficiently understood in part because they have not been analysed within a life-history context. By means of an individual-based model, we show here that matching habitat choice and learning interact with life history to influence persistence in novel environments. In maladaptive contexts, the likelihood of persisting is higher for life-history strategies that increase the value of adults over the value of offspring, even at the cost of decreasing reproduction. Such a strategy facilitates persistence in novel environments by reducing the costs of a reproductive failure while increasing the benefits of behavioural responses. Our results reinforce the view that a more predictive theory for extinction risk under rapid environmental changes requires considering behavioural responses and life history as part of a common adaptive strategy to cope with environmental changes. This article is part of the theme issue 'Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation'. [ABSTRACT FROM AUTHOR]

Attempts to identify predictors and mechanisms of invasion success have been weakened by poor data quality, mostly because monitoring does not begin immediately after introduction events. To overcome this issue, we used data from conservation translocations of threatened bird species. We analyzed information on >1200 translocation events of >150 bird species to investigate how life‐history traits affect population establishment measured based on rates of survival and reproduction. Species position along the slow–fast life‐history continuum was a key predictor of translocation success. Species with fast‐paced life histories were less likely to survive (over both short‐ and mid‐term) and more likely to breed successfully than species with slow life histories. The temporal partitioning of reproductive effort (number of clutches per year) also affected the probability of successful reproduction. Our results illustrate how conservation‐motivated reintroduction programs can provide proxies for the initial stages of the invasion process, enabling empirical tests of predictions from life‐history theory and informing management. Article impact statement: After translocations for conservation purposes, bird survival and breeding success depend on their life history. [ABSTRACT FROM AUTHOR]

Demographic events such as the birth and death of organisms are ubiquitous in nature. Disentangling the processes that underlie the demographic dynamics of species is fundamental to understanding how biodiversity is organized and will be re‐organized at multiple scales.To provide new insights on multispecies demographic dynamics, I designed the present study to focus on local and biogeographic influences on mortality and recruitment rates for tree populations in forest biomes throughout the Japanese archipelago.Most populations exhibited mortality that fell within the 95% confidence intervals of a neutral model (i.e. the expectation of demographic stochasticity). However, there were also important determinants that make population dynamics to deviate from the neutral expectation. Interspecific niche differentiation was important to reduce the mortality rate, regardless of the local rarity or ubiquity of a species. Although intraspecific aggregation that caused density‐dependent mortality was only significant for locally abundant species, the degree of isolation from a species' central or optimal range determined mortality only for locally rare species. These differences between rare and common species provide important empirical quantification of aspects of population dynamics that have been less accounted for in ecology and biogeography studies.Synthesis. Unifying different theories such as those rooted in local‐scale community ecology and macro‐scale biogeography is important. At this juncture, this study emphasizes that disentangling the interactive roles of demographic stochasticity and determinism that operate at different scales would be a clue to advance the field of ecology both in theory and practice. [ABSTRACT FROM AUTHOR]

Small populations are often at risk of extinction through processes that are effectively stochastic. Prediction of this extinction risk requires that the observed temporal variation in demographic rates be accurately partitioned between demographic stochasticity (variation among individuals) and environmental stochasticity (variation among years, correlated across individuals). However, studies of population viability analysis that include both forms of stochasticity parameterize the magnitude of environmental stochasticity incorrectly (they overestimate it). I describe and evaluate tests (1) to determine whether all the year-to-year variation in observed survivorship can be explained by demographic stochasticity alone, and (2) if not, to estimate the magnitude of environmental stochasticity in survival. The first issue can be resolved with a G test. I used simulated data to show that this test has an appropriate type I error rate, unless the individual survival probability is either very low or very high. Small amounts of environmental stochasticity often are not detected by the G test (type II error), but the hypothesis of demographic stochasticity alone is consistently rejected when environmental stochasticity is large. In contrast, estimating the magnitude of environmental stochasticity requires explicit hypotheses about the nature of the underlying variation, but I provide a flexible framework in which many such hypotheses can be examined. In particular, I show, using simulated data, that if the temporal variability in individual survival probabilities is distributed according to a beta distribution, then the maximum likelihood estimate of the variance of the survival probability is biased, but in a consistent and correctable way. The estimate obtained with my method is usually superior to an estimate that assumes that all of the variation in the observed survivorship is due to environmental stochasticity. I show how to include deterministic sources of variability, such as density dependence, and how to apply different assumptions about the underlying environmental stochasticity. I illustrate these tests with data from a population of Acorn Woodpeckers (Melanerpes formicivorus). With these data, I can determine that there is strong environmental stochasticity in juvenile survival, whereas variation in adult survival can be explained either by density dependence or by weak environmental stochasticity.

Abstract Density dependence, population regulation, and variability in population size are fundamental population processes, the manifestation and interrelationships of which are affected by environmental variability. However, there are surprisingly few empirical studies that distinguish the effect of environmental variability from the effects of population processes. We took advantage of a unique system, in which populations of the same duck species or close ecological counterparts live in highly variable (north American prairies) and in stable (north European lakes) environments, to distinguish the relative contributions of environmental variability (measured as between‐year fluctuations in wetland numbers) and intraspecific interactions (density dependence) in driving population dynamics. We tested whether populations living in stable environments (in northern Europe) were more strongly governed by density dependence than populations living in variable environments (in North America). We also addressed whether relative population dynamical responses to environmental variability versus density corresponded to differences in life history strategies between dabbling (relatively “fast species” and governed by environmental variability) and diving (relatively “slow species” and governed by density) ducks. As expected, the variance component of population fluctuations caused by changes in breeding environments was greater in North America than in Europe. Contrary to expectations, however, populations in more stable environments were not less variable nor clearly more strongly density dependent than populations in highly variable environments. Also, contrary to expectations, populations of diving ducks were neither more stable nor stronger density dependent than populations of dabbling ducks, and the effect of environmental variability on population dynamics was greater in diving than in dabbling ducks. In general, irrespective of continent and species life history, environmental variability contributed more to variation in species abundances than did density. Our findings underscore the need for more studies on populations of the same species in different environments to verify the generality of current explanations about population dynamics and its association with species life history.

Contents Summary 52 I. Introduction 52 II. Determinants of savanna vegetation structure 53 III. Are trees in savannas really more heterogeneous? 53 IV. Are trees in savannas a ‘slow’ variable? 54 V. Are trees in savannas spatially patterned? 55 VI. Conclusions 55 Acknowledgements 55 References 56 Summary: Savannas are highly variable systems, and predicting variation, especially in the tree layer, represents a major unresolved challenge for forecasting biosphere responses to global change. Prediction to date has focused on disentangling interactions between resource limitation and chronic disturbances to identify what determines local savanna vegetation heterogeneity. By focusing at too fine a scale, this approach overlooks: sample size limitation arising from sparse tree distributions; stochasticity in demographic and environmental processes that is preserved as heterogeneity among tree populations with slow dynamics; and spatial self‐organization. Renewed focus on large (1–50 ha) permanent plots and on spatial patterns of tree‐layer variability at even larger landscape spatial scales (≥1000s of ha) promises to resolve these limitations, consistent with the goal of predicting large‐scale biosphere responses to global change. [ABSTRACT FROM AUTHOR]

Abstract: Populations of range expanding species encounter patches of both favorable and unfavorable habitat as they spread across landscapes. Theory shows that increasing patchiness slows the spread of populations modeled with continuously varying population density when dispersal is not influence by the environment or individual behavior. However, as is found in uniformly favorable landscapes, spread remains driven by fecundity and dispersal from low density individuals at the invasion front. In contrast, when modeled populations are composed of discrete individuals, patchiness causes populations to build up to high density before dispersing past unsuitable habitat, introducing an important influence of density dependence on spread velocity. To test the hypothesized interaction between habitat patchiness and density dependence, we simultaneously manipulated these factors in a greenhouse system of annual plants spreading through replicated experimental landscapes. We found that increasing the size of gaps and amplifying the strength of density dependence both slowed spread velocity, but contrary to predictions, the effect of amplified density dependence was similar across all landscape types. Our results demonstrate that the discrete nature of individuals in spreading populations has a strong influence on how both landscape patchiness and density dependence influence spread through demographic and dispersal stochasticity. Both finiteness and landscape structure should be critical components to theoretical predictions of future spread for range expanding native species or invasive species colonizing new habitat. [ABSTRACT FROM AUTHOR]

In nature, individual reproductive success is seldom independent from year to year, due to factors such as reproductive costs and individual heterogeneity. However, population projection models that incorporate temporal autocorrelations in individual reproduction can be difficult to parameterise, particularly when data are sparse. We therefore examine whether such models are necessary to avoid biased estimates of stochastic population growth and extinction risk, by comparing output from a matrix population model that incorporates reproductive autocorrelations to output from a standard age-structured matrix model that does not. We use a range of parameterisations, including a case study using moose data, treating probabilities of switching reproductive class as either fixed or fluctuating. Expected time to extinction from the two models is found to differ by only small amounts (under 10%) for most parameterisations, indicating that explicitly accounting for individual reproductive autocorrelations is in most cases not necessary to avoid bias in extinction estimates. [ABSTRACT FROM AUTHOR]

Aim The study of seed banks has been mainly conducted at local scales, thereby hampering our general understanding of the assembly processes of these biodiversity reservoirs. Here, we aim to document worldwide macroecological patterns of seed bank diversity and of their similarity with aboveground vegetation. Our second aim is to investigate the likely drivers of these macroecological patterns and to lay the foundation of a metacommunity theory of seed banks. Location Worldwide. Time period 1989-2005. Major taxa studied Plants. Methods We compiled a worldwide dataset of 130 seed banks located in grasslands. We assessed the likely drivers of seed bank diversity and similarity with aboveground vegetation, using structural equation modelling. We then developed a time-averaged neutral model of coupled seed bank-vegetation (S-V) dynamics that includes the effect of environmental stochasticity, and we compared its predictions with empirical findings. Results We found evidence for two weak latitudinal gradients in seed bank diversity and S-V similarity, with larger species richness and smaller similarity closer to the tropics. We then showed that seed bank richness and S-V similarity are correlated with the following four distinct drivers: local environmental variability, plant regional diversity, seed bank density and sampling area. Finally, we showed that the predictions of the time-averaged neutral model are remarkably in accord with empirical observations. Main conclusions Our results lay the foundations of a metacommunity theory for seed banks. They challenge the standard view that seed banks are principally structured by environmental variability, by highlighting the additional key roles of dispersal and stochastic sampling on seed bank diversity patterns. [ABSTRACT FROM AUTHOR]

Despite growing concerns regarding increasing frequency of extreme climate events and declining population sizes, the influence of environmental stochasticity on the relationship between population carrying capacity and time-to-extinction has received little empirical attention. While time-toextinction increases exponentially with carrying capacity in constant environments, theoretical models suggest increasing environmental stochasticity causes asymptotic scaling, thus making minimum viable carrying capacity vastly uncertain in variable environments. Using empirical estimates of environmental stochasticity in fish metapopulations, we showed that increasing environmental stochasticity resulting from extreme droughts was insufficient to create asymptotic scaling of time-to-extinction with carrying capacity in local populations as predicted by theory. Local timeto- extinction increased with carrying capacity due to declining sensitivity to demographic stochasticity and the slope of this relationship declined significantly as environmental stochasticity increased. However, recent 1 in 25 yr extreme droughts were insufficient to extirpate populations with large carrying capacity. Consequently, large populations may be more resilient to environmental stochasticity than previously thought. The lack of carrying capacity-related asymptotes in persistence under extreme climate variability reveals how small populations affected by habitat loss or overharvesting, may be disproportionately threatened by increases in extreme climate events with global warming. [ABSTRACT FROM AUTHOR]

Ecological drift causes species abundances to fluctuate randomly, lowering diversity within communities and increasing differences among otherwise equivalent communities. Despite broad interest in ecological drift, ecologists have little experimental evidence of its consequences in nature, where competitive forces modulate species abundances. We manipulated drift by imposing 40-fold variation in the size of experimentally assembled annual plant communities and holding their edge-to-interior ratios comparable. Drift over three generations was greater than predicted by neutral models, causing high extinction rates and fast divergence in composition among smaller communities. Competitive asymmetries drove populations of most species to small enough sizes that demographic stochasticity could markedly influence dynamics, increasing the importance of drift in communities. The strong effects of drift occurred despite stabilizing niche differences, which cause species to have greater population growth rates when at low local abundance. Overall, the importance of ecological drift appears greater in non-neutral communities than previously recognized, and varies with community size and the type and strength of density dependence. [ABSTRACT FROM AUTHOR]

Cattle populations in semiarid rangelands are currently facing severe threats due to erratic rainfall and increasing drought frequencies, leading to poor vegetation quality and a consecutive cattle population decline. However, little is known about how particular sex- and age-cohorts of cattle respond to these environmental threats and on how sales influence population trajectories. In the Borana rangelands, southern Ethiopia, much detailed information is available on the Boran cattle ( Bos indicus ) population demographics, a special breed, which is highly adapted to semiarid environmental conditions. We collected data on Boran cattle demographic and environmental factors such as carrying capacity, market values, and herderś management decisions. We generated stochastic models and assessed the future development of cattle population trajectories under four different drought scenarios. We analyzed changes in age- and sex-cohorts of cattle populations by introducing different drought frequencies and their effect on vital rates, carrying capacity, and sales. We calibrated the model on the basis of a 12-year data set of a neighboring Boran cattle group. In our population model, the cattle numbers significantly declined after 18 years under the higher drought frequency scenarios (scenarios 3 and 4) while numbers remained high over 100 years for the lower drought frequency scenarios 1 and 2. The sale of senescent and adult females most strongly (77%) affected population trajectories, and model outcomes were most sensitive to sale rates of senescent, adult, and juvenile females compared to vital rates and male sale rates of the population. Management should focus on lowering herd crashes through increasing sale of mature males, which increases feed availability to females during drought years in the Ethiopian Rangelands. Drought early-warning systems and market information must be strengthened so that pre-planned selling of cattle can be realized for a sustainable use of the animal resource. [ABSTRACT FROM AUTHOR]

This study focuses on the speed of extinction of a population living in a random environment that follows a continuous-time Markov chain. Each individual dies or reproduces at a rate that depends on the environment. The number of offspring during reproduction follows a given probability law that also depends on the environment. In the so-called subcritical case where the population goes for sure to extinction, there is an explicit formula for the speed of extinction. In some sense, environmental stochasticity slows down population extinction. [ABSTRACT FROM AUTHOR]

Temporal asynchrony among species helps diversity to stabilize ecosystem functioning, but identifying the mechanisms that determine synchrony remains a challenge. Here, we refine and test theory showing that synchrony depends on three factors: species responses to environmental variation, interspecific interactions, and demographic stochasticity. We then conduct simulation experiments with empirical population models to quantify the relative influence of these factors on the synchrony of dominant species in five semiarid grasslands. We found that the average synchrony of per capita growth rates, which can range from 0 (perfect asynchrony) to 1 (perfect synchrony), was higher when environmental variation was present (0.62) rather than absent (0.43). Removing interspecific interactions and demographic stochasticity had small effects on synchrony. For the dominant species in these plant communities, where species interactions and demographic stochasticity have little influence, synchrony reflects the covariance in species' responses to the environment. [ABSTRACT FROM AUTHOR]

Studies of microbial evolution, especially in applied contexts, have focused on the role of selection in shaping predictable, adaptive responses to the environment. However, chance events - the appearance of novel genetic variants and their establishment , i.e. outgrowth from a single cell to a sizeable population - also play critical initiating roles in adaptation. Stochasticity in establishment has received little attention in microbiology, potentially due to lack of awareness as well as practical challenges in quantification. However, methods for high-replicate culturing, mutant labelling and detection, and statistical inference now make it feasible to experimentally quantify the establishment probability of specific adaptive genotypes. I review methods that have emerged over the past decade, including experimental design and mathematical formulas to estimate establishment probability from data. Quantifying establishment in further biological settings and comparing empirical estimates to theoretical predictions represent exciting future directions. More broadly, recognition that adaptive genotypes may be stochastically lost while rare is significant both for interpreting common lab assays and for designing interventions to promote or inhibit microbial evolution.