Species synchrony and its drivers: neutral and nonneutral community dynamics in fluctuating environments

Independent species fluctuations are commonly used as a null hypothesis to test the role of competition and niche differences between species in community stability. This hypothesis, however, is unrealistic because it ignores the forces that contribute to synchronization of population dynamics. Here we present a mechanistic neutral model that describes the dynamics of a community of equivalent species under the joint influence of density dependence, environmental forcing, and demographic stochasticity. We also introduce a new standardized measure of species synchrony in multispecies communities. We show that the per capita population growth rates of equivalent species are strongly synchronized, especially when endogenous population dynamics are cyclic or chaotic, while their long-term fluctuations in population sizes are desynchronized by ecological drift. We then generalize our model to nonneutral dynamics by incorporating temporal and nontemporal forms of niche differentiation. Niche differentiation consistently decreases the synchrony of species per capita population growth rates, while its effects on the synchrony of population sizes are more complex. Comparing the observed synchrony of species per capita population growth rates with that predicted by the neutral model potentially provides a simple test of deterministic asynchrony in a community.     

Persistence in fluctuating environments

Understanding under what conditions interacting populations, whether they be plants, animals, or viral particles, coexist is a question of theoretical and practical importance in population biology. Both biotic interactions and environmental fluctuations are key factors that can facilitate or disrupt coexistence. To better understand this interplay between these deterministic and stochastic forces, we develop a mathematical theory extending the nonlinear theory of permanence for deterministic systems to stochastic difference and differential equations. Our condition for coexistence requires that there is a fixed set of weights associated with the interacting populations and this weighted combination of populations’ invasion rates is positive for any (ergodic) stationary distribution associated with a subcollection of populations. Here, an invasion rate corresponds to an average per-capita growth rate along a stationary distribution. When this condition holds and there is sufficient noise in the system, we show that the populations approach a unique positive stationary distribution. Moreover, we show that our coexistence criterion is robust to small perturbations of the model functions. Using this theory, we illustrate that (i) environmental noise enhances or inhibits coexistence in communities with rock-paper-scissor dynamics depending on correlations between interspecific demographic rates, (ii) stochastic variation in mortality rates has no effect on the coexistence criteria for discrete-time Lotka–Volterra communities, and (iii) random forcing can promote genetic diversity in the presence of exploitative interactions.

One day is fine, the next is black.—The Clash     

Invasion speeds in fluctuating environments

Biological invasions are increasingly frequent and have dramatic ecological and economic consequences. A key to coping with invasive species is our ability to predict their rates of spread. Traditional models of biological invasions assume that the environment is temporally constant. We examine the consequences for invasion speed of periodic and stochastic fluctuations in population growth rates and in dispersal distributions.     

Mutator dynamics in fluctuating environments

Populations with high mutation rates (mutator clones) are being found in increasing numbers of species, and a clear link is being established between the presence of mutator clones and drug resistance. Mutator clones exist despite the fact that in a constant environment most mutations are deleterious, with the spontaneous mutation rate generally held at a low value. This implies that mutator clones have an important role in the adaptation of organisms to changing environments. Our study examines how mutator dynamics vary according to the frequency of environmental fluctuations. Although recent studies have considered a single environmental switch, here we investigate mutator dynamics in a regularly varying environment, seeking to mimic conditions present, for example, under certain drug or pesticide regimes. Our model provides four significant new insights. First, the results demonstrate that mutators are most prevalent under intermediate rates of environmental change. When the environment oscillates more rapidly, mutators are unable to provide sufficient adaptability to keep pace with the frequent changes in selection pressure and, instead, a population of 'environmental generalists' dominates. Second, our findings reveal that mutator dynamics may be complex, exhibiting limit cycles and chaos. Third, we demonstrate that when each beneficial mutation provides a greater gain in fitness, mutators achieve higher densities in more rapidly fluctuating environments. Fourth, we find that mutators of intermediate strength reach higher densities than very weak or strong mutators.     

Coexistence of competitors in spatially and temporally varying environments: A look at the combined effects of different sorts of variability

A stochastic model is developed for competition among organisms living in a patchy and varying environment. The model is designed to be suitable for species with sedentary adults and widely dispersing larvae or propagules, and applies best to marine systems but may also be adequate for some terrestrial systems. Three kinds of environmental variation are incorporated simultaneously in the model. These are pure spatial variation, pure temporal variation, and the space × time interaction. All three kinds of variation can promote coexistence, and when variation is restricted to immigration rates, all three kinds act very similarly. Moreover, for long-lived organisms their action is nearly identical, and their effects, when present together, combine equivalently. For short-lived organisms, however, pure temporal variation is a less effective promoter of coexistence. Variation in death rates acts quite differently from variation in birth rates for it may demote coexistence in some circumstances, while promoting coexistence in other circumstances. Furthermore, pure spatial variation in death rates has quite different effects than other kinds of death-rate variation. In addition to conditions for coexistence, information is given on population fluctuations, convergence to stationary distributions, and asymptotic distributions for long-lived organisms. While the model is presented as an ecological model, a genetical interpretation is also possible. This leads to new suggested mechanisms for the maintenance of polymorphisms in populations.     

Growth with regulation in fluctuating environments

In this paper deterministic growth laws of a logistic-like type are initially introduced. The growth equations are expressed by first order differential equations containing a third order nonlinear term. Such equations are then parameterized in a way to allow for random fluctuations of the intrinsic fertility and of the environmental carrying capacity, thus leading to diffusion processes of new types. Their transition p.d.f. and asymptotic moments are then obtained and a detailed study of the extinction problem is performed within the framework of the first passage time problem through arbitrarily fixed threshold values. Some statistically significant quantities, such as the mean time necessary for the process to attain an assigned state, are obtained in closed form. The behavior of the diffusion processes here derived is finally compared with that of the well known diffusion processes obtained by parameterizing logistic and Gompertz growth equations.Work supported in part by the Group for Mathematical Information Sciences (GNIM) of the National Research Council and by Progetto Finalizzato Sofmat, Contract No. 82.00845.97     

Stochastic gene expression in fluctuating environments

Stochastic mechanisms can cause a group of isogenic bacteria, each subject to identical environmental conditions, to nevertheless exhibit diverse patterns of gene expression. The resulting phenotypic subpopulations will typically have distinct growth rates. This behavior has been observed in several contexts, including sugar metabolism and pili phase variation. Under fixed environmental conditions, the net growth rate of the population is maximized when all cells are of the fastest growing phenotype, so it is unclear what fitness advantage is conferred by population heterogeneity. However, unlike ideal laboratory conditions, natural environments tend to fluctuate, either periodically or randomly. Here we use a stochastic population model to show that, during growth in such fluctuating environments, a dynamically heterogenous bacterial population can sometimes achieve a higher net growth rate than a homogenous one. By using stochastic mechanisms to sample several distinct phenotypes, the bacteria are able to anticipate and take advantage of sudden changes in their environment. However, this heterogeneity is beneficial only if the bacterial response rate is sufficiently low. Our results could be useful in the design of artificial evolution experiments and in the optimization of fermentation processes.     

Predator-prey models in periodically fluctuating environments

A class of ordinary or integrodifferential equations describing predator-prey dynamics is considered under the assumption that the coefficients are periodic functions of time. This class is characterized by the logistic behaviour of the prey in the absence of predators and it includes the Leslie model. We show that there exists a periodic solution provided that the average of the predator's intrinsic rate of increase is greater than a critical value. We use well-known results in bifurcation theory for nonlinear eigenvalue problems, as well as an extension to the case of non-globally defined operators of some recent results on the global nature of branches of solutions.     

Population and community variability in randomly fluctuating environments

The prediction that environmental fluctuations may destabilise populations and yet stabilise aggregate community properties has remained largely untested. We examined population and community stability under constant and fluctuating temperatures in simple planktonic assemblages of differing algal richness. Temperature dependent resource competition produced a highly asymmetric community structure where algal community biomass was dominated by one species. For a given level of species richness, temperature fluctuations induced lower community covariance and thus stabilised community biomass. However, increasing algal species richness increased the variability of population abundance and growth rates, as well as population and community variability. Consumer dynamics were directly destabilised by environmental fluctuations. These results confirm recent theoretical studies suggesting a stabilising effect of environmental fluctuations at the community level. However, they also support the theoretical prediction that increasing species richness may be of limited value for community stability, most especially in asymmetric communities, when competition directly affects population variability.     

Coexistence of insect species competing for a pulsed resource: toward a unified theory of biodiversity in fluctuating environments

Background

One major challenge in understanding how biodiversity is organized is finding out whether communities of competing species are shaped exclusively by species-level differences in ecological traits (niche theory), exclusively by random processes (neutral theory of biodiversity), or by both processes simultaneously. Communities of species competing for a pulsed resource are a suitable system for testing these theories: due to marked fluctuations in resource availability, the theories yield very different predictions about the timing of resource use and the synchronization of the population dynamics between the competing species. Accordingly, we explored mechanisms that might promote the local coexistence of phytophagous insects (four sister species of the genus Curculio) competing for oak acorns, a pulsed resource.

Methodology/Principal Findings

We analyzed the time partitioning of the exploitation of oak acorns by the four weevil species in two independent communities, and we assessed the level of synchronization in their population dynamics. In accordance with the niche theory, overall these species exhibited marked time partitioning of resource use, both within a given year and between different years owing to different dormancy strategies between species, as well as distinct demographic patterns. Two of the four weevil species, however, consistently exploited the resource during the same period of the year, exhibited a similar dormancy pattern, and did not show any significant difference in their population dynamics.

Conclusions/Significance

The marked time partitioning of the resource use appears as a keystone of the coexistence of these competing insect species, except for two of them which are demographically nearly equivalent. Communities of consumers of pulsed resources thus seem to offer a promising avenue for developing a unifying theory of biodiversity in fluctuating environments which might predict the co-occurrence, within the same community, of species that are ecologically either very similar, or very different.     

Eco-evolutionary maintenance of diversity in fluctuating environments

Growing evidence suggests that temporally fluctuating environments are important in maintaining variation both within and between species. To date, however, studies of genetic variation within a population have been largely conducted by evolutionary biologists (particularly population geneticists), while population and community ecologists have concentrated more on diversity at the species level. Despite considerable conceptual overlap, the commonalities and differences of these two alternative paradigms have yet to come under close scrutiny. Here, we review theoretical and empirical studies in population genetics and community ecology focusing on the ‘temporal storage effect’ and synthesise theories of diversity maintenance across different levels of biological organisation. Drawing on Chesson's coexistence theory, we explain how temporally fluctuating environments promote the maintenance of genetic variation and species diversity. We propose a further synthesis of the two disciplines by comparing models employing traditional frequency-dependent dynamics and those adopting density-dependent dynamics. We then address how temporal fluctuations promote genetic and species diversity simultaneously via rapid evolution and eco-evolutionary dynamics. Comparing and synthesising ecological and evolutionary approaches will accelerate our understanding of diversity maintenance in nature.     

Implicit frequency dependence and kin selection in fluctuating environments

Summary I consider a general model of a fluctuating environment in which the environmental state each year is drawn at random from some given distribution. Each year organisms must choose what action to perform before the environmental state for that year is known. There is no interaction with kin. In this scenario, natural selection will tend to produce organisms which maximize their geometric mean fitness. In this paper I introduce the idea of the profile of a strategy. This function quantifies how the strategy peforms for each environmental state. I show that there is a unique profile such that a strategy is optimal if and only if it has this profile. I then give a characterization of the optimal profile which generalizes previous work by others in this area. The characterization of the optimal profile has a game theoretical interpretation. Motivated by this I introduce a game in which individuals play the field in a constant environment. This game may be interpreted as a cooperative game between kin. The key result of this paper shows that a strategy maximizes geometric mean fitness in the original fluctuating environment problem if and only if it is an evolutionarily stable strategy of the deterministic environment game. It is well known that an optimal strategy in a fluctuating environment may be mixed, involving adaptive coin-flipping. Others have previously noted that this may result in some individuals sacrificing individual reproductive success for the good of the genotype. My analysis shows that one may regain the concept of individual optimization if the quantity maximized is suitably defined. Under an optimal strategy every action taken maximizes the expected number of offspring produced, where this expectation is not calculated using the true distribution of environmental states, but a distribution modified to take account of the actions of kin.     

Habitat selection and population regulation in temporally fluctuating environments

Understanding and predicting the distribution of organisms in heterogeneous environments lies at the heart of ecology, and the theory of density-dependent habitat selection (DDHS) provides ecologists with an inferential framework linking evolution and population dynamics. Current theory does not allow for temporal variation in habitat quality, a serious limitation when confronted with real ecological systems. We develop both a stochastic equivalent of the ideal free distribution to study how spatial patterns of habitat use depend on the magnitude and spatial correlation of environmental stochasticity and also a stochastic habitat selection rule. The emerging patterns are confronted with deterministic predictions based on isodar analysis, an established empirical approach to the analysis of habitat selection patterns. Our simulations highlight some consistent patterns of habitat use, indicating that it is possible to make inferences about the habitat selection process based on observed patterns of habitat use. However, isodar analysis gives results that are contingent on the magnitude and spatial correlation of environmental stochasticity. Hence, DDHS is better revealed by a measure of habitat selectivity than by empirical isodars. The detection of DDHS is but a small component of isodar theory, which remains an important conceptual framework for linking evolutionary strategies in behavior and population dynamics.     

Invasion speeds for structured populations in fluctuating environments

We live in a time where climate models predict future increases in environmental variability and biological invasions are becoming increasingly frequent. A key to developing effective responses to biological invasions in increasingly variable environments will be estimates of their rates of spatial spread and the associated uncertainty of these estimates. Using stochastic, stage-structured, integrodifference equation models, we show analytically that invasion speeds are asymptotically normally distributed with a variance that decreases in time. We apply our methods to a simple juvenile–adult model with stochastic variation in reproduction and an illustrative example with published data for the perennial herb, Calathea ovandensis. These examples buttressed by additional analysis reveal that increased variability in vital rates simultaneously slow down invasions yet generate greater uncertainty about rates of spatial spread. Moreover, while temporal autocorrelations in vital rates inflate variability in invasion speeds, the effect of these autocorrelations on the average invasion speed can be positive or negative depending on life history traits and how well vital rates “remember” the past.     

Persistence in fluctuating environments for interacting structured populations

Individuals within any species exhibit differences in size, developmental state, or spatial location. These differences coupled with environmental fluctuations in demographic rates can have subtle effects on population persistence and species coexistence. To understand these effects, we provide a general theory for coexistence of structured, interacting species living in a stochastic environment. The theory is applicable to nonlinear, multi species matrix models with stochastically varying parameters. The theory relies on long-term growth rates of species corresponding to the dominant Lyapunov exponents of random matrix products. Our coexistence criterion requires that a convex combination of these long-term growth rates is positive with probability one whenever one or more species are at low density. When this condition holds, the community is stochastically persistent: the fraction of time that a species density goes below \(\delta >0\) approaches zero as \(\delta \) approaches zero. Applications to predator-prey interactions in an autocorrelated environment, a stochastic LPA model, and spatial lottery models are provided. These applications demonstrate that positive autocorrelations in temporal fluctuations can disrupt predator-prey coexistence, fluctuations in log-fecundity can facilitate persistence in structured populations, and long-lived, relatively sedentary competing populations are likely to coexist in spatially and temporally heterogenous environments.     

Resident-invader dynamics of similar strategies in fluctuating environments

Journal of Mathematical Biology - We study resident-invader dynamics in fluctuating environments when the invader and the resident have close but distinct strategies. First we focus on a class of...     

Experimental evolution of evolutionary potential in fluctuating environments

Variation is the raw material for evolution. Evolutionary potential is determined by the amount of genetic variation, but evolution can also alter the visibility of genetic variation to natural selection. Fluctuating environments are suggested to maintain genetic variation but they can also affect environmental variance, and thus, the visibility of genetic variation to natural selection. However, experimental studies testing these ideas are relatively scarce. In order to determine differences in evolutionary potential we quantified variance attributable to population, genotype and environment for populations of the bacterium Serratia marcescens. These populations had been experimentally evolved in constant and two fluctuating environments. We found that strains that evolved in fluctuating environments exhibited larger environmental variation suggesting that adaptation to fluctuations has decreased the visibility of genetic variation to selection.