Showing papers by "Nadav M. Shnerb published in 2019"
TL;DR: In this article, the authors provide a comprehensive analysis of the phases of the birth-death process, taking into account both the endogenous demographic noise (random birth and death events) and the effect of environmental stochasticity that causes variations in birth anddeath rates.
Abstract: Population dynamics reflects an underlying birth-death process, where the rates associated with different events may depend on external environmental conditions and on the population density. A whole family of simple and popular deterministic models (such as logistic growth) supports a transcritical bifurcation point between an extinction phase and an active phase. Here we provide a comprehensive analysis of the phases of that system, taking into account both the endogenous demographic noise (random birth and death events) and the effect of environmental stochasticity that causes variations in birth and death rates. Three phases are identified: in the inactive phase the mean time to extinction $T$ is independent of the carrying capacity $N$ and scales logarithmically with the initial population size. In the power-law phase $T\ensuremath{\sim}{N}^{q}$, and in the exponential phase $T\ensuremath{\sim}exp(\ensuremath{\alpha}N)$. All three phases and the transitions between them are studied in detail. The breakdown of the continuum approximation is identified inside the power-law phase, and the accompanying changes in decline modes are analyzed. The applicability of the emerging picture to the analysis of ecological time series and to the management of conservation efforts is briefly discussed.
14 citations
TL;DR: In this paper, the authors considered logistic and logistic-like systems under the combined effect of demographic and bounded environmental stochasticity, and identified three phases: an inactive phase, an active phase, and a temporal Griffiths phase, with a power-law relationship between the mean time to extinction and the carrying capacity.
Abstract: Extinction is the ultimate absorbing state of any stochastic birth-death process; hence, the time to extinction is an important characteristic of any natural population. Here we consider logistic and logisticlike systems under the combined effect of demographic and bounded environmental stochasticity. Three phases are identified: an inactive phase where the mean time to extinction $T$ increases logarithmically with the initial population size, an active phase where $T$ grows exponentially with the carrying capacity $N$, and a temporal Griffiths phase, with a power-law relationship between $T$ and $N$. The system supports an exponential phase only when the noise is bounded, in which case the continuum (diffusion) approximation breaks down within the Griffiths phase. This breakdown is associated with a crossover between qualitatively different survival statistics and decline modes. To study the power-law phase we present a new WKB scheme, which is applicable both in the diffusive and in the nondiffusive regime.
11 citations
TL;DR: This work proposes a novel and easily applicable methodology for quantifying deviations from the predictions and assumptions of Dynamic Equilibrium theory by comparing observed community time-series to a randomization-based null model and shows that this methodology has good statistical properties on simulated data.
Abstract: Community assembly is governed by colonization and extinction processes, and the simplest model describing it is Dynamic Equilibrium (DE) theory, which assumes that communities are shaped solely by stochastic colonization and extinction events. Despite its potential to serve as a null model for community dynamics, there is currently no accepted methodology for measuring deviations from the theory and testing it. Here we propose a novel and easily applicable methodology for quantifying deviations from the predictions and assumptions of DE by comparing observed community time-series to a randomization-based null model. We show that this methodology has good statistical properties on simulated data, and it can detect deviations from both the assumptions and predictions of DE in the classical Florida Keys experiment. We discuss alternative methods and present guidelines for practical use of the methodology, hoping it will enhance the applicability of DE as a reference for studying changes in ecological communities.
5 citations
TL;DR: The results indicate that temporal changes in communities are predominantly driven by shared responses of co-occurring species to environmental changes, rather than by inter-specific competition, in sharp contrast to the long-term recognition of competition as a primary driver of species assembly.
Abstract: Ecological communities are assembled by colonization and extinction events, that may be regulated by ecological niches1–5. The most parsimonious explanation of local community assembly is the Dynamic Equilibrium (DE) model, which assumes that community dynamics is shaped by random colonization and extinctions events, effectively ignoring the effects of niches1, 6. Despite its empirical success in explaining diversity patterns1, 5, 7, it is unknown to what extent the assembly dynamics of communities around the globe are consistent with this model. Using a newly developed methodology, we show that in 4989 communities from 49 different datasets, representing multiple taxa, biomes and locations, changes in richness and composition are larger than expected by DE. All the fundamental assumptions of DE are violated, but the large changes in species richness and composition primarily stem from the synchrony in the dynamics of different species. These results indicate that temporal changes in communities are predominantly driven by shared responses of co-occurring species to environmental changes, rather than by inter-specific competition. This finding is in sharp contrast to the long-term recognition of competition as a primary driver of species assembly8–12. While ecological niches are often thought to stabilize species diversity and composition4, 13, 14, we found that they promote large changes in ecological communities.
3 citations
TL;DR: It is shown that for large communities the portfolio effect is dominant, leading to ITV promoting species persistence and richness, and the interplay between ITV and environmental variations tends to increase the mean fitness of diverse populations.
Abstract: Recent studies have found considerable trait variations within species. The effect of such intra-specific trait variability (ITV) on the stability, coexistence and diversity of ecological communities received considerable attention and in many models it was shown to impede coexistence and decrease species diversity. Here we present a numerical study of the effect of genetically inherited ITV on species persistence and diversity in a temporally fluctuating environment. Two mechanisms are identified. First, ITV buffers populations against varying environmental conditions (portfolio effect) and reduces abundance variations. Second, the interplay between ITV and environmental variations tends to increase the mean fitness of diverse populations. The first mechanism promotes persistence and tends to increase species richness, while the second reduces the chance of a rare species population (which is usually homogenous) to invade and decreases species richness. We show that for large communities the portfolio effect is dominant, leading to ITV promoting species persistence and richness.
2 citations
TL;DR: It is shown that in all systems (including discrete and continuous dynamics, with overlapping and non-overlapping generations) the ratio between the expected growth and its variance governs both qualitative and quantitative features of persistence and invasibility.
Abstract: The ability of random environmental variation to stabilize competitor coexistence was pointed out long ago and, in recent years, has received considerable attention. Here we suggest a novel and generic synthesis of stochasticity-induced stabilization (SIS) phenomena. The storage effect in the lottery model, together with other well-known examples drawn from population genetics, microbiology and ecology, are placed together, reviewed, and explained within a clear, coherent and transparent theoretical framework. Implementing the diffusion approximation we show that in all these systems (including discrete and continuous dynamics, with overlapping and non-overlapping generations) the ratio between the expected growth and its variance governs both qualitative and quantitative features of persistence and invasibility. We further clarify the relationships between bet-hedging strategies, generation time and SIS, study the dynamics of extinction when SIS fails and the explain effects of species richness and asymmetric competition on the stabilizing mechanism.
1 citations
TL;DR: In this article, the effect of random abundance variations on persistence properties of a population was studied and it was shown that an increase in the amplitude of stochastic temporal environmental variations leads to an increase of mean growth rate when rare, while at the same time enhancing random abundance fluctuations.
Abstract: The coexistence of many species within ecological communities poses a long-standing theoretical puzzle. Modern coexistence theory (MCT) and related techniques explore this phenomenon by examining the chance of a species population growing from rarity in the presence of all other species. The mean growth rate when rare, 𝔼[r], is used in MCT as a metric that measures persistence properties (like invasibility or time to extinction) of a population. Here we critique this reliance on 𝔼[r] and show that it fails to capture the effect of random abundance variations on persistence properties. The problem becomes particularly severe when an increase in the amplitude of stochastic temporal environmental variations leads to an increase in 𝔼[r], since at the same time it enhances random abundance fluctuations and the two effects are inherently intertwined. In this case, the chance of invasion and the mean extinction time of a population may even go down as 𝔼[r] increases.
1 citations
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TL;DR: This work considers a two-state Moran model, where selection intensity at equilibrium may differ (in amplitude and in sign) from selection during periods of sharp growth and sharp decline, and presents simple formulae for effective population size and effective selection.
Abstract: Temporal environmental variations are ubiquitous in nature, yet most of the theoretical works in population genetics and evolution assume fixed environment. Here we analyze the effect of variations in carrying capacity on the fate of a mutant type. We consider a two-state Moran model, where selection intensity at equilibrium may differ (in amplitude and in sign) from selection during periods of sharp growth and sharp decline. Using Kimura's diffusion approximation we present simple formulae for effective population size and effective selection, and use it to calculate the chance of ultimate fixation, the time to fixation and the time to absorption (either fixation or loss). Our analysis shows perfect agreement with numerical solutions for neutral, beneficial and deleterious mutant. The contributions of different processes to the mean and the variance of abundance variations are additive and commutative. As a result, when selection intensity $s$ is weak such that ${\cal O}(s^2)$ terms are negligible, periodic or stochastic environmental variations yield identical results.
1 citations
TL;DR: An empirical study of spatial synchrony in terrestrial vegetation using large scale remote sensing data and is characterized using a power-law function with stretched-exponential cutoff to find the range of correlations appears to decrease when precipitation increases and to increase over time.
Abstract: Spatial synchrony is ubiquitous in nature, and its decrease with the distance is an important feature that affects the viability of spatially structured populations. Here we present an empirical study of spatial synchrony in terrestrial vegetation using large scale remote sensing data. The decrease of synchrony with distance, as expressed by the correlation in rate of abundance change at a given time lag, is characterized using a power-law function with stretched exponential cutoff. The range of these correlations appears to decrease when precipitation increases and to increase over time. The relevance of these results to the viability of populations is discussed.