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Current environmental changes may increase temporal variability of life history traits of species thus affecting their long-term population growth rate and extinction risk. If there is a general relationship between environmental variances (EVs) and mean annual survival rates of species, that relationship could be used as a guideline for analyses of population growth and extinction risk for populations, where data on EVs are missing. For this purpose, we present a comprehensive compilation of 252 EV estimates from 89 species belonging to five vertebrate taxa (birds, mammals, reptiles, amphibians and fish) covering mean annual survival rates from 0.01 to 0.98. Since variances of survival rates are constrained by their means, particularly for low and high mean survival rates, we assessed whether any observed relationship persisted after applying two types of commonly used variance stabilizing transformations: relativized EVs (observed/mathematical maximum) and logit-scaled EVs. With raw EVs at the arithmetic scale, mean-variance relationships of annual survival rates were hump-shaped with small EVs at low and high mean survival rates and higher (and widely variable) EVs at intermediate mean survival rates. When mean annual survival rates were related to relativized EVs the hump-shaped pattern was less distinct than for raw EVs. When transforming EVs to logit scale the relationship between mean annual survival rates and EVs largely disappeared. The within-species juvenile-adult slopes were mainly positive at low (<0.5) and negative at high (>0.5) mean survival rates for raw and relativized variances while these patterns disappeared when EVs were logit transformed. Uncertainties in how to interpret the results of relativized and logit-scaled EVs, and the observed high variation in EV's for similar mean annual survival rates illustrates that extrapolations of observed EVs and tests of life history drivers of survival-EV relationships need to also acknowledge the large variation in these parameters.
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Climate refugia are areas where species can persist through climate change with little to no movement. Among the factors associated with climate refugia are high spatial heterogeneity, such that there is only a short distance between current and future optimal climates, as well as biotic or abiotic environmental factors that buffer against variability in time. However, these types of climate refugia may be declining due to anthropogenic homogenization of environments and degradation of environmental buffers. To quantify the potential for restoration of refugia-like environmental conditions to increase population persistence under climate change, we simulated a population's capacity to track their temperature over space and time given different levels of spatial and temporal variability in temperature. To determine how species traits affected the efficacy of restoring heterogeneity, we explored an array of values for species' dispersal ability, thermal tolerance, and fecundity. We found that species were more likely to persist in environments with higher spatial heterogeneity and lower environmental stochasticity. When simulating a management action that increased the spatial heterogeneity of a previously homogenized environment, species were more likely to persist through climate change, and population sizes were generally higher, but there was little effect with mild temperature change. The benefits of heterogeneity restoration were greatest for species with limited dispersal ability. In contrast, species with longer dispersal but lower fecundity were more likely to benefit from a reduction in environmental stochasticity than an increase in spatial heterogeneity. Our results suggest that restoring environments to refugia-like conditions could promote species' persistence under the influence of climate change in addition to conservation strategies such as assisted migration, corridors, and increased protection.
Assuntos
Mudança Climática , Refúgio de Vida Selvagem , Densidade Demográfica , Temperatura , EcossistemaRESUMO
The interplay of stochastic and ecological processes that govern the establishment and persistence of host-associated microbial communities is not well understood. Here we illustrate the conceptual and practical advantages of fitting stochastic population dynamics models to multi-species bacterial time series data. We show how the stability properties, fluctuation regimes and persistence probabilities of human vaginal microbial communities can be better understood by explicitly accommodating three sources of variability in ecological stochastic models of multi-species abundances: 1) stochastic biotic and abiotic forces, 2) ecological feedback and 3) sampling error. Rooting our modeling tool in stochastic population dynamics modeling theory was key to apply standardized measures of a community's reaction to environmental variation that ultimately depends on the nature and intensity of the intra-specific and inter-specific interaction strengths. Using estimates of model parameters, we developed a Risk Prediction Monitoring (RPM) tool that estimates temporal changes in persistence probabilities for any bacterial group of interest. This method mirrors approaches that are often used in conservation biology in which a measure of extinction risks is periodically updated with any change in a population or community. Additionally, we show how to use estimates of interaction strengths and persistence probabilities to formulate hypotheses regarding the molecular mechanisms and genetic composition that underpin different types of interactions. Instead of seeking a definition of "dysbiosis" we propose to translate concepts of theoretical ecology and conservation biology methods into practical approaches for the management of human-associated bacterial communities.
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While polyploids are common in nature, existing models suggest that polyploid establishment should be difficult and rare. We explore this apparent paradox by focussing on the role of unreduced gametes, as their union is the main route for the formation of neopolyploids. Production of such gametes is affected by genetic and environmental factors, resulting in variation in the formation rate of unreduced gametes (u). Once formed, neopolyploids face minority cytotype exclusion (MCE) due to a lack of viable mating opportunities. More than a dozen theoretical models have explored factors that could permit neopolyploids to overcome MCE and become established. Until now, however, none have explored variability in u and its consequences for the rate of polyploid establishment. Here, we determine the distribution that best fits the available empirical data on u. We perform a global sensitivity analysis exploring the consequences of using empirical distributions of u to investigate effects on polyploid establishment. We determined that in many cases, u is best fit by a log-normal distribution. We found environmental stochasticity in u dramatically impacts model predictions when compared to a static u. Our results help reconcile previous modelling results suggesting high barriers to the polyploid establishment with the observation that polyploids are common in nature.
Assuntos
Células Germinativas , Poliploidia , Humanos , ReproduçãoRESUMO
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.
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Research into the processes governing species richness has often assumed that the environment is fixed, whereas realistic environments are often characterised by random fluctuations over time. This temporal environmental stochasticity (TES) changes the demographic rates of species populations, with cascading effects on community dynamics and species richness. Theoretical and applied studies have used process-based mathematical models to determine how TES affects species richness, but under a variety of frameworks. Here, we critically review such studies to synthesise their findings and draw general conclusions. We first provide a broad mathematical framework encompassing the different ways in which TES has been modelled. We then review studies that have analysed models with TES under the assumption of negligible interspecific interactions, such that a community is conceptualised as the sum of independent species populations. These analyses have highlighted how TES can reduce species richness by increasing the frequency at which a species becomes rare and therefore prone to extinction. Next, we review studies that have relaxed the assumption of negligible interspecific interactions. To simplify the corresponding models and make them analytically tractable, such studies have used mean-field theory to derive fixed parameters representing the typical strength of interspecific interactions under TES. The resulting analyses have highlighted community-level effects that determine how TES affects species richness, for species that compete for a common limiting resource. With short temporal correlations of environmental conditions, a non-linear averaging effect of interspecific competition strength over time gives an increase in species richness. In contrast, with long temporal correlations of environmental conditions, strong selection favouring the fittest species between changes in environmental conditions results in a decrease in species richness. We compare such results with those from invasion analysis, which examines invasion growth rates (IGRs) instead of species richness directly. Qualitative differences sometimes arise because the IGR is the expected growth rate of a species when it is rare, which does not capture the variation around this mean or the probability of the species becoming rare. Our review elucidates key processes that have been found to mediate the negative and positive effects of TES on species richness, and by doing so highlights key areas for future research.
Assuntos
Biodiversidade , Ecossistema , Modelos Teóricos , ProbabilidadeRESUMO
São propostas três causas principais para sincronia de populações: fatores exógenos, dispersão e interações interespecíficas. O presente trabalho teve por objetivo testar a influência dos fatores exógenos na sincronia de populações de Sitophilus zeamais (Mots.) (Coleoptera: Curculionidae), isoladas espacialmente (sem dispersão), em microcosmos com diferentes condições ambientais (umidade e temperatura). Doze populações com 20 indivíduos cada, foram divididas, aleatoriamente, em dois tratamentos: com lâmpada e sem lâmpada. O censo dos indivíduos adultos foi realizado semanalmente, durante sete meses. A tendência de crescimento da abundância ao longo do tempo foi eliminada através do ajuste de modelos autoregressivos. A sincronia entre as populações, detectada por meio dos coeficientes de correlação de Pearson e Spearman, foi maior dentro do que entre tratamentos, embora as populações mantidas sem lâmpada tenham sido mais sincrônicas do que as populações com lâmpada. Além de evidenciarem a influência do ambiente nas flutuações populacionais, esses resultados sugerem que o metabolismo e as interações intraespecíficas são fatores importantes na dinâmica populacional. Organismos em ambientes desfavoráveis podem apresentar taxas metabólicas anormais, contribuindo pouco para o crescimento populacional. Logo, populações pequenas sofrem maior influência da estocasticidade demográfica, reduzindo a probabilidade de sincronia entre elas. Nos ambientes mais favoráveis, espera-se que os indivíduos desenvolvam funções metabólicas normais, levando as populações a apresentar taxas de crescimento mais elevadas. Nesse caso, a estocasticidade demográfica tem menor influência, levando as populações sem lâmpada a flutuar de forma mais sincrônica.
Three main causes to population synchrony are proposed: exogenous factors, dispersal and inter-specific interactions. This paper had as main goal to test the influence of the exogenous factors in the synchrony in spatially isolated (i.e., no dispersal) populations of Sitophilus zeamais (Mots.) (Coleoptera: Curculionidae), in microcosms with different environmental conditions (humidity, temperature and light intensity). Twelve populations of 20 individuals each, were randomly assigned between two treatment conditions: with or without light. Population size and environmental factors (temperature and relative humidity) were weekly assessed for seven months. Temporal trend in populations increase was eliminated adjusting autoregressive models. Population synchrony, detected by means of Pearsons and Spearmans correlation coefficients, was higher within than between treatments, although the populations kept without lamp were more synchronized than populations with lamp. Besides demonstrating the influence of environment on population fluctuations, these results suggest that metabolism and intra-specific interactions are important factors in population dynamic. Organisms exposed to unsuitable environmental conditions may have abnormal metabolic rates, which negatively influences the population grow. Thus, small populations are more likely to suffer from demographic stochasticity, decreasing the probability of the synchrony among populations. On the other hand, in more suitable environments, individuals are expected to have normal metabolic functions, and so, to achieve higher rates of population grow. In this case, the demographic stochasticity has smaller influence, leading populations without lamp to fluctuate synchronously.