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26 results for “Environmental stochasticity”
Environmental stochasticity increases extinction risk to a greater degree in pollination specialists than in generalists
<p>Pollination sustains terrestrial food webs and agricultural systems and links the dynamics of interacting plant and pollinator species. Although environmental stochasticity is ubiquitous and can propagate through communities via species interactions in a way that increases extinction risk, it is unknown whether stochasticity affects species uniformly across pollination networks. In this paper, we introduce a stochastic dynamic model that makes novel use of the birth function and apply it to pollination networks of increasing size. We start with two- and four-species networks, in order to first illustrate the effects of stochasticity per se and then how those effects combine with specialization. We then describe the relationship between partner number and stochastic extinction risk in empirical networks with >20 species. In the 2-species network, increasing the variance of the stochastic term of the model increased the size of the region in parameter space where extinctions occur. In networks with 4 or more species, specialists were more vulnerable to extinction than generalists over a broad range of variances. Extinction risk in networks with >20 species declined nonlinearly with increasing mutualist partner number. Our results demonstrate the importance of including species interactions and stochasticity when using population-dynamic models to compare species' extinction risk. While models that omit either of these factors are likely to underestimate extinction risk, they disproportionately underestimate the vulnerability of specialists.</p>
Data from: Partitioning variance in population growth for models with environmental and demographic stochasticity
<ol> <li>How demographic factors lead to variation or change in growth rates can be investigated using life table response experiments (LTRE) based on structured population models. Traditionally, LTREs focused on decomposing the asymptotic growth rate, but more recently decompositions of annual 'realized' growth rates have gained in popularity.</li> <li>Realized LTREs have been used particularly to understand how variation in vital rates translates into variation in growth for populations under long-term study. For these, complete population models may be constructed by combining data in an integrated population model (IPM). IPMs are also used to investigate how temporal variation in environmental drivers affect vital rates. Such investigations have usually come down to estimating covariate coefficients for the effects of environmental variables on vital rates, but formal ways of assessing how they lead to variation in growth rates have been lacking. </li> <li>We extend realized LTREs in two ways. First, we further partition the contributions from vital rates into contributions from temporally varying factors that affect them. The decomposition allows us to compare the resultant effect on the growth rate of different environmental factors that may each act via multiple vital rates. Second, we show how realized growth rates can be decomposed into separate components from environmental and demographic stochasticity. The latter is typically omitted in LTRE analyses.</li> <li>We illustrate how to use the approach in an IPM for data from a 26-year study on northern wheatears (Oenanthe oenanthe), a migratory passerine bird breeding in an agricultural landscape. For this population, consisting of around 50–120 breeding pairs per year, we partition variation in realized growth rates into environmental contributions from temperature, rainfall, population density, and unexplained random variation via multiple vital rates, and from demographic stochasticity.</li> <li>The case study suggests that variation in first-year survival via the random component, and adult survival via temperature are two main factors behind environmental variation in growth rates. More than half of the variation in growth rates is suggested to come from demographic stochasticity, demonstrating the importance of this factor for populations of moderate size.</li> </ol>
Data from: Partitioning variance in population growth for models with environmental and demographic stochasticity
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Data from: Dynamics of mixed-ploidy populations under demographic and environmental stochasticities
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Environmental stochasticity increases extinction risk to a greater degree in pollination specialists than in generalists
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Stochastic hydro-financial watershed modeling for environmental impact bonds
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Data from: The sensitivity of seabird populations to density-dependence, environmental stochasticity and anthropogenic mortality
1.The balance between economic growth and wildlife conservation is a priority for many governments. Enhancing realism in assessment of population‐level impacts of anthropogenic mortality can help achieve this balance. Population Viability Analysis (PVA) is commonly applied to investigate population vulnerability, but outcomes of PVA are sensitive to formulations of density‐dependence, environmental stochasticity and life‐history. Current practice in marine assessments is to use precautionary models that assume no compensation from density‐dependence or rescue‐effects via "re‐seeding" from other colonies. However, if we could empirically quantify regulatory population processes, the responses of populations to additional anthropogenic mortality may be assessed with more realism in PVA. 2. Using Bayesian state‐space models fitted to population time‐series from three sympatric seabird populations, selected for varied life histories, we inferred the extent to which their dynamics are driven by environmental stochasticity and density‐dependence. 3. Based on these inferences, we conducted an exhaustive PVA across credible parameterisations for intrinsic and extrinsic population regulation, simulated as a closed and re‐seeded system. Scenarios of anthropogenic mortality, along a sliding scale of precaution, were applied both proportionally and as a fixed quota using Potential Biological Removal (PBR). 4. Baseline results from fitting revealed clear environmental regulation in two of our three species. Crucially, we found that for our empirically derived, realistic model parameterisations there are risks of decline to real populations even under very precautionary mortality scenarios. We find that PBR is dubious in application as a sustainable tool for population assessment when we account for regulation. Closed versus re‐seeded models showed a large divergence in outcomes, with sharper declines in closed simulations. Fixed‐quota mortality typically induced greater population declines comparative to proportional mortality, subject to regulation and re‐seeding. 5. Synthesis and applications: Practitioners using arbitrary formulations of population regulation risk over‐precaution (economic constraint) or under‐precaution (endangering populations). The demands of increased economic development and preservation of wildlife require that methodologies apply techniques that confer reality and rigour to assessment. The current practice of employing models lacking density‐dependence and empirical environmental information imposes limitations in the efficacy of estimating impacts. Here, we provide a method to quantify the conditions that predominantly regulate a population and exacerbate the risk of decline from anthropogenic mortality. It is in the interests of both developers and conservationists to apply methods in population impact assessments that capture realism in the processes driving population dynamics.
Data from: Stochastic and deterministic processes drive wetland community assembly across a gradient of environmental filtering
The role of deterministic and stochastic processes in community assembly is a key question in community ecology. We evaluated the effect of an abiotic filter (hydroperiod) on the partitioned diversity of three taxonomic groups (birds, vegetation, macroinvertebrates) from prairie pothole wetlands in Alberta, Canada, which naturally vary in water permanence. We observed that alpha and gamma diversity were higher in permanent than temporary wetlands (16-25% and 34-47% respectively, depending on the taxon). This suggests an influence of deterministic constraints on the number of species a wetland can support. Taxa which cannot persist in shallow, temporary wetlands are excluded by the deterministic constraints that a shortened hydroperiod imposes. In contrast, we observed that beta diversity was significantly higher (2-12%) in temporary wetlands than permanent ones, and temporary wetlands supported more unique combinations of community composition than permanent wetlands, despite having a smaller regional species pool. This observation contradicts prior mesocosm studies that found beta diversity mirrored the pattern in gamma diversity along an environmental filtering gradient. We conclude that deterministic processes are more influential in more stable permanent wetlands, whereas stochastic processes play a more important role in assembly in dynamic temporary wetlands that must disassemble and re-establish annually. Considering three distinct taxonomic groups differing in their relative mobility, our large-scale field study demonstrates that both stochastic and deterministic processes act together to influence the assembly of multiple communities and that the relative importance of the two processes varies consistently along a gradient of environmental filtering.
Data from: Asynchronous changes in abundance over large scales are explained by demographic variation rather than environmental stochasticity in an invasive flagellate
Environmental stochasticity is important in explaining the persistence and establishment of invasive species, but the simultaneous effects of environmental and demographic factors are difficult to separate. Understanding how demography and environmental factors affect invasive species abundance over large temporal and spatial scales is essential to anticipate populations at risk of becoming established and setting appropriate management measures. Using a hierarchical mixed modeling approach we analyzed the spatial and interannual dynamics of the invasive raphidophyte Gonyostomum semen, a noxious flagellate which is spreading in northern Europe, in response to demographic and environmental variation. We used data from 76 lakes distributed across two biogeographical regions in Sweden (Central Plains in the south and Fennoscandian region in the north) and sampled during 14 years. We found a strong asynchrony in the density dynamics of G. semen populations between the two regions. G. semen showed positive trends (i.e. increasing frequency of high density peaks) in most southern lakes, forming established populations with recurrent blooms in successive years in some of them. In contrast, G. semen populations were smaller and more stochastic in the north. G. semen previous year's abundance, a proxy for cyst production and recruitment, had a strong control on the dynamics, likely contributing to the stability of high density populations in southern lakes. Conversely, the effects of climate and habitat were weaker and their influence varied across regions. Temperature was the limiting factor in the north whereas local habitat was more important in the south. Synthesis: A full understanding of the mechanisms driving abundance changes across large scales can only be gained if endogenous and environmental factors are analyzed together. For phytoplankton species, and specially, noxious microalgae, this implies that proxies for cyst production and recruitment, which are the inoculum for next year population, should be included in e.g. distribution, bloom formation and climate models, as these may modify establishment and population response to environmental variation. Asynchronous changes in abundance across regions also indicate that management plans should be developed for small regions, as inference at a large scale may obscure the mechanisms driving local population changes.
Data and scripts from: Experimental evidence of size-selective harvest and environmental stochasticity effects on population demography, fluctuations, and nonlinearity
<p class="MsoNormal">Theory and analyses of fisheries datasets indicate that harvesting can alter population structure and destabilize nonlinear processes, which increases population fluctuations. We conducted a factorial experiment on the population dynamics of <em>Daphnia magna</em> in relation to size-selective harvesting and stochasticity of food supply. Harvesting and stochasticity treatments both increased population fluctuations. Timeseries analysis indicated that fluctuations in control populations were nonlinear, and nonlinearity increased substantially in response to harvesting. Both harvesting and stochasticity induced population juvenescence, but harvesting did so via depletion of adults whereas stochasticity increased the abundance of juveniles. A fitted fisheries model indicated that harvesting shifted populations towards higher reproductive rates and larger-magnitude damped oscillations that amplify demographic noise. These findings provide experimental evidence that harvesting increases nonlinearity of population fluctuations and that both harvesting and stochasticity increase population variability and juvenescence.</p>
Data from: The evolution of male-biased dispersal under the joint selective forces of inbreeding load, and demographic and environmental stochasticity
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Data from: Stochastic and deterministic processes drive wetland community assembly across a gradient of environmental filtering
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Data from: Asynchronous changes in abundance over large scales are explained by demographic variation rather than environmental stochasticity in an invasive flagellate
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Data from: Estimating demographic contributions to effective population size in an age-structured wild population experiencing environmental and demographic stochasticity
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Data from: The sensitivity of seabird populations to density-dependence, environmental stochasticity and anthropogenic mortality
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Data and scripts from: Experimental evidence of size-selective harvest and environmental stochasticity effects on population demography, fluctuations, and nonlinearity
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Data from: Sex in an uncertain world: environmental stochasticity helps restore competitive balance between sexually and asexually reproducing populations
Like many organisms, individuals of the freshwater ostracod species Eucypris virens can have either obligate sexual or asexual reproductive modes. Both types of individual routinely co-occur, including in the same temporary freshwater pond (their natural habitat in which they undergo seasonal diapause). Given the well-known two-fold cost of sex, this begs the question of how sexually reproducing individuals are able to co-exist with their asexual counterparts in spite of such overwhelming costs. Environmental stochasticity in the form of "false dawn" inundations (where the first hydration is ephemeral and causes loss of early hatching individuals) may provide an advantage to the sexual subpopulation, which exhibits greater variation in hatching times following inundation. We explore the potential role of environmental stochasticity in this system using life-history data analysis, climate data and matrix projection models. In the absence of environmental stochasticity, the population growth rate is significantly lower in sexual subpopulations. Climate data reveal that "false dawn" inundations are common. Using matrix projection modeling with and without environmental stochasticity, we demonstrate that this phenomenon can restore appreciable balance to the system, in terms of growth rates. This provides support for the role of environmental stochasticity in helping to explain the maintenance of sex and the occurrence of geographic parthenogenesis.
Data and climate variable selection from: Effects of density, species interactions and environmental stochasticity on the dynamics of British bird communities
<p>Our knowledge of the factors affecting species abundances is mainly based on time-series analyses of a few well-studied species at single or few localities, but we know little about whether results from such analyses can be extrapolated to the community level. We apply a Joint Species Distribution Model to long-term time-series data on British bird communities to examine the relative contribution of intra- and interspecific density dependence at different spatial scales, as well as the influence of environmental stochasticity, to spatio-temporal interspecific variation in abundance. Intraspecific density dependence has the major structuring effect on these bird communities. In addition, environmental fluctuations affect spatiotemporal differences in abundance. In contrast, species interactions had a minor impact on variation in abundance. Thus, important drivers of single-species dynamics are also strongly affecting dynamics of communities in time and space.</p>
Data from: Contrasting effects of spatial heterogeneity and environmental stochasticity on population dynamics of a perennial wildflower
Understanding how variation in growth, survival and reproduction affect population dynamics is a fundamental question in ecology. Although the effects of among-year variation (environmental stochasticity) are well understood, the effects of among-site variation (spatial heterogeneity) are less clearly defined. I evaluated the effects of spatial and temporal variation on the population dynamics of Pulsatilla patens, pasqueflower, a perennial prairie forb. I conducted a 10-year demographic monitoring study, and quantified vital rate variation among sites and years using generalized linear models. I incorporated vital rate functions using this variation into integral projection models for stochastic and spatially heterogeneous environments. I also explored the effects of temporal and spatial autocorrelation, by exploring model predictions over the range of possible values for temporal autocorrelation and local seed dispersal. Vital rates varied more among years than among sites. However, environmental stochasticity and spatial heterogeneity had similar magnitude effects on population dynamics. These effects were also qualitatively different: environmental stochasticity reduced population growth rates relative to the average, whereas spatial heterogeneity increased population growth rates. Spatial autocorrelation and negative temporal autocorrelation led to higher population growth rates, although environmental stochasticity still reduced growth rates for all autocorrelation values, and spatial heterogeneity increased growth rates for all autocorrelation values. Some form of autocorrelation would be necessary for model projections to match observed population trends. Synthesis. Spatial heterogeneity is as important as environmental stochasticity for population dynamics, but it is much less often incorporated into population projection models. This study points to a number of interesting avenues for future research into the roles of spatial heterogeneity and spatiotemporal variation for long-term population dynamics.
Data from: Temporal genetic structure in a poecilogonous polychaete: the interplay of developmental mode and environmental stochasticity
Background: Temporal variation in the genetic structure of populations can be caused by multiple factors, including natural selection, stochastic environmental variation, migration, or genetic drift. In benthic marine species, the developmental mode of larvae may indicate a possibility for temporal genetic variation: species with dispersive planktonic larvae are expected to be more likely to show temporal genetic variation than species with benthic or brooded non-dispersive larvae, due to differences in larval mortality and dispersal ability. We examined temporal genetic structure in populations of Pygospio elegans, a poecilogonous polychaete with within-species variation in developmental mode. P. elegans produces either planktonic, benthic, or intermediate larvae, varying both among and within populations, providing a within-species test of the generality of a relationship between temporal genetic variation and larval developmental mode. Results: In contrast to our expectations, our microsatellite analyses of P. elegans revealed temporal genetic stability in the UK population with planktonic larvae, whereas there was variation indicative of drift in temporal samples of the populations from the Baltic Sea, which have predominantly benthic and intermediate larvae. We also detected temporal variation in relatedness within these populations. A large temporal shift in genetic structure was detected in a population from the Netherlands, having multiple developmental modes. This shift could have been caused by local extiction due to extreme environmental conditions and (re)colonization by planktonic larvae from neighboring populations. Conclusions: In our study of P. elegans, temporal genetic variation appears to be due to not only larval developmental mode, but also the stochastic environment of adults. Large temporal genetic shifts may be more likely in marine intertidal habitats (e.g. North Sea and Wadden Sea) which are more prone to environmental stochasticity than the sub-tidal Baltic habitats. Sub-tidal and/or brackish (less saline) habitats may support smaller P. elegans populations and these may be more susceptible to the effects of random genetic drift. Moreover, higher frequencies of asexual reproduction and the benthic larval developmental mode in these populations leads to higher relatedness and contributes to drift. Our results indicate that a general relationship between larval developmental mode and temporal genetic variation may not exist.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.