Temporal scale of environmental correlations affects ecological synchrony

Desharnais, Robert A.; Reuman, Daniel C.; Costantino, R. F.; Cohen, Joel E.

doi:10.1111/ele.13155

Cited by 18 publications

(27 citation statements)

References 73 publications

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“…Species composition in local communities varied independently throughout the year, showing a weak synchronous pattern. Synchrony results from fluctuations in population densities among sites correlated over time (Desharnais et al, 2018). The lack of synchrony among sites can be caused by the different requirements of species, resulting in distinct responses to environmental conditions (Magurran & Henderson, 2010).…”

Section: Discussionmentioning

confidence: 99%

“…Conversely, asynchrony can arise from dispersal limitation generating compensatory dynamics at the community level, that is, when groups of species increase in abundance while others decrease. However, few studies have explored how spatial synchrony influences population maintenance in terrestrial, dispersal‐limited organisms (e.g., Desharnais, Reuman, Costantino, & Cohen, 2018). Environmental heterogeneity can also buffer populations of ectotherms against climatic variation, since heterogeneous habitats have a wider range of microhabitats with diverse microclimates and resources (McCaffery et al, 2014; Oliver et al, 2010; Piha et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

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Climatic variables influence the temporal dynamics of an anuran metacommunity in a nonstationary way

Ceron

Santana

Lucas

et al. 2020

Ecology and Evolution

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Understanding the temporal dynamics of communities is crucial to predict how communities respond to climate change. Several factors can promote variation in phenology among species, including tracking of seasonal resources, adaptive responses to other species, demographic stochasticity, and physiological constraints. The activities of ectothermic vertebrates are sensitive to climatic variations due to the effect of temperature and humidity on species physiology. However, most studies on temporal dynamics have analyzed multi‐year data and do not have resolution to discriminate within‐year patterns that can determine community assembly cycles. Here, we tested the temporal stability and synchrony of calling activity and also how climatic variables influence anuran species composition throughout the year in a metacommunity in the Atlantic Forest of southern Brazil. Using a multivariate method, we described how the relationship between species composition and climatic variables changes through time. The metacommunity showed a weak synchronous spatial pattern, meaning that species responded independently to environmental variation. Interestingly, species composition exhibited a nonstationary response to climate, suggesting that climate affects species composition differently depending on the season. The species‐climate relationship was stronger during the spring, summer, and winter, mainly influenced by temperature, rainfall, and humidity. Thus, temporal community dynamics seem to be mediated by species life‐history traits, in which independent fluctuations promote community stability in temporally varying environments.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Climatic variables influence the temporal dynamics of an anuran metacommunity in a nonstationary way

Ceron

Santana

Lucas

et al. 2020

Ecology and Evolution

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“…Hugueny (2006) studied the effect of variation in log‐linear density dependence among populations, and Royama (2005) and Engen and Sæther (2005) demonstrated how parameters in nonlinear density‐dependent models influence the synchronizing effect of the environment. One key finding from these studies is that, when assuming no synchronizing effect of dispersal or trophic interactions, deviations from assumptions in Moran's theorem cause the correlation in abundance to be less than that of the environment (but see Desharnais et al 2018). Thus, the presence of nonlinear dynamics means that population synchrony observed in nature may often be the result of a much stronger underlying environmental correlation than one would predict from the original Moran theorem (Grenfell et al 1998).…”

Section: Relaxing the Assumptions: A Generalized Moran Effectmentioning

confidence: 99%

The Moran effect revisited: spatial population synchrony under global warming

et al. 2020

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The world is spatially autocorrelated. Both abiotic and biotic properties are more similar among neighboring than distant locations, and their temporal co‐fluctuations also decrease with distance. P. A. P. Moran realized the ecological importance of such ‘spatial synchrony’ when he predicted that isolated populations subject to identical log‐linear density‐dependent processes should have the same correlation in fluctuations of abundance as the correlation in environmental noise. The contribution from correlated weather to synchrony of populations has later been coined the ‘Moran effect’. Here, we investigate the potential role of the Moran effect in large‐scale ecological outcomes of global warming. Although difficult to disentangle from dispersal and species interaction effects, there is compelling evidence from across taxa and ecosystems that spatial environmental synchrony causes population synchrony. Given this, and the accelerating number of studies reporting climate change effects on local population dynamics, surprisingly little attention has been paid to the implications of global warming for spatial population synchrony. However, a handful of studies of insects, birds, plants, mammals and marine plankton indicate decadal‐scale changes in population synchrony due to trends in environmental synchrony. We combine a literature review with modeling to outline potential pathways for how global warming, through changes in the mean, variability and spatial autocorrelation of weather, can impact population synchrony over time. This is particularly likely under a ‘generalized Moran effect’, i.e. when relaxing Moran's strict assumption of identical log‐linear density‐dependence, which is highly unrealistic in the wild. Furthermore, climate change can influence spatial population synchrony indirectly, through its effects on dispersal and species interactions. Because changes in population synchrony may cascade through food‐webs, we argue that the (generalized) Moran effect is key to understanding and predicting impacts of global warming on large‐scale ecological dynamics, with implications for extinctions, conservation and management.

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“…Given the homogeneity assumption of our model, we also have: V M = V P × (1 + ϕ)/2 (Wang et al 2015). For the timescale‐specific metrics, we can similarly linearize the model and use filter theory of time series (Reinsel 1993) to derive the analytic solutions for ϕ(σ), V P (σ) and V M (σ) as functions of timescale, growth rate, dispersal and timescale‐specific variance/synchrony of environmental noise (Supporting information; Desharnais et al 2018). We note that the analytical solutions of timescale‐specific variability and synchrony correspond to Fourier transforms of infinite time series (Supporting information).…”

Section: Methodsmentioning

confidence: 99%

The effects of dispersal on spatial synchrony in metapopulations differ by timescale

Luo

Reuman

Hallett

et al. 2021

Oikos

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Understanding the processes that stabilize species populations is a fundamental question in ecology and central to conservation biology. In metapopulations, dispersal can act as a ‘double edged' sword for species stability by simultaneously decreasing local population variability (thereby decreasing local extinction risk) while increasing spatial synchrony (thereby increasing landscape‐level extinction risk). These dynamics may operate at different timescales, complicating efforts to assess their relative importance for long‐term stability. Here, we use a simple metapopulation model to understand how dispersal affects population variability and spatial synchrony across timescales. Our model shows that dispersal has contrasting effects at short versus long timescales on the variability and synchrony of populations. For populations that exhibit slow recovery when perturbed (i.e. under‐compensatory growth), dispersal decreases local population variability while increasing spatial synchrony at long timescales. In contrast, at short timescales dispersal increases local population variability while decreasing spatial synchrony. For populations that recover via damped oscillation when perturbed (i.e. over‐compensatory growth), the effects of dispersal are all opposite to those for populations with under‐compensatory growth, at both short and long timescales. The timescale‐dependent effect of dispersal has important implications for empirical studies. Specifically, studies conducted over short periods may only observe population variability increasing and spatial synchrony decreasing with dispersal, whereas the opposite patterns may predominate over longer periods. Our results provide novel insights on the dynamics underlying the role of dispersal and highlight the importance of time series length in empirical studies of metapopulations.

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Temporal scale of environmental correlations affects ecological synchrony

Cited by 18 publications

References 73 publications

Climatic variables influence the temporal dynamics of an anuran metacommunity in a nonstationary way

Climatic variables influence the temporal dynamics of an anuran metacommunity in a nonstationary way

The Moran effect revisited: spatial population synchrony under global warming

The effects of dispersal on spatial synchrony in metapopulations differ by timescale

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