Synchronization in ecological systems by weak dispersal coupling with time delay

One of the most salient spatiotemporal patterns in population ecology is the synchronization of fluctuating local populations across vast spatial extent. Synchronization of abundance has been widely observed across a range of spatial scales in relation to the rate of dispersal among discrete populations. However, the dependence of synchrony on patterns of among-patch movement across heterogeneous landscapes has been largely ignored. Here, we consider the duration of movement between two predator–prey communities connected by weak dispersal and its effect on population synchrony. More specifically, we introduce time-delayed dispersal to incorporate the finite transmission time between discrete populations across a continuous landscape. Reducing the system to a phase model using weakly connected network theory, it is found that the time delay is an important factor determining the nature and stability of phase-locked states. Our analysis predicts enhanced convergence to stable synchronous fluctuations in general and a decreased ability of systems to produce in-phase synchronization dynamics in the presence of delayed dispersal. These results introduce delayed dispersal as a tool for understanding the importance of dispersal time across a landscape matrix in affecting metacommunity dynamics. They further highlight the importance of landscape and dispersal patterns for predicting the onset of synchrony between weakly coupled populations.     

Dispersal, Environmental Correlation, and Spatial Synchrony in Population Dynamics

Many species exhibit widespread spatial synchrony in population fluctuations. This pattern is of great ecological interest and can be a source of concern when the species is rare or endangered. Both dispersal and spatial correlations in the environment have been implicated as possible causes of this pattern, but these two factors have rarely been studied in combination. We develop a spatially structured population model, simple enough to obtain analytic solutions for the population correlation, that incorporates both dispersal and environmental correlation. We ask whether these two synchronizing factors contribute additively to the total spatial population covariance. We find that there is always an interaction between these two factors and that this interaction is small only when one or both of the environmental correlation and the dispersal rate are small. The interaction is opposite in sign to the environmental correlation; so, in the normal case of positive environmental correlation across sites, the population synchrony will be lower than predicted by simply adding the effects of dispersal and environmental correlation. We also find that population synchrony declines as the strength of population regulation increases. These results indicate that dispersal and environmental correlation need to be considered in combination as explanations for observed patterns of population synchrony.     

Synchrony of butterfly populations across species' geographic ranges

Understanding the mechanisms by which global climate change and habitat loss impact upon biodiversity is essential in order to mitigate any negative impacts. One such impact may be changes to population synchrony (defined as correlated fluctuations in the density of separate populations). It is well established that synchrony depends on both dispersal ability and correlated environmental conditions, for example shared climate. However, what is not clear is whether differences in habitat or position within a species' range also mediate synchrony. Since synchronous metapopulations are thought to be more extinction‐prone, establishing the drivers of synchrony has clear conservation implications. Using three butterfly species (Maniola jurtina, Pyronia tithonus and Aphantopus hyperantus) we investigated the effects of habitat similarity and range position on population synchrony, after accounting for the effects of distance and climate. Range position was present in all minimum adequate models, though non‐significant using Mantel randomization tests in one case. We show that M. jurtina and P. tithonus synchrony is not consistent across species' ranges, with marginal populations showing more synchronous dynamics. Increased climatic constraints on marginal populations, leading to a narrower range of suitable microhabitats may be responsible for this, which is supported by the result that habitat similarity between sites was also positively correlated with population synchrony. As the landscape becomes increasingly homogeneous, overall population synchrony may be expected to rise. We conclude that habitat modification and climate change have the capacity to drive changes in population synchrony that could make species more vulnerable to extinction.     

The Moran effect revisited: spatial population synchrony under global warming

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.     

局域种群的Allee效应和集合种群的同步性

从包含Allee效应的局域种群出发,建立了耦合映像格子模型,即集合种群模型.通过分析和计算机模拟表明:(1)当局域种群受到Allee效应强度较大时,集合种群同步灭绝;(2)而当Allee效应强度相对较弱时,通过稳定局域种群动态(减少混沌)使得集合种群发生同步波动,而这种同步波动能够增加集合种群的灭绝风险;(3)斑块间的连接程度对集合种群同步波动的发生有很大的影响,适当的破碎化有利于集合种群的续存.全局迁移和Allee效应结合起来增加了集合种群同步波动的可能,从而增加集合种群的灭绝风险.这些结果对理解同步性的机理、利用同步机理来制定物种保护策略和害虫防治都有重要的意义.     

Spatially autocorrelated disturbances and patterns in population synchrony

Spatially synchronous population dynamics have been documented in many taxa. The prevailing view is that the most plausible candidates to explain this pattern are extrinsic disturbances (the Moran effect) and dispersal. In most cases disentangling these factors is difficult. Theoretical studies have shown that dispersal between subpopulations is more likely to produce a negative relationship between population synchrony and distance between the patches than perturbations. As analyses of empirical data frequently show this negative relationship between the level of synchrony and distance between populations, this has emphasized the importance of dispersal as a synchronizing agent. However, several weather patterns show spatial autocorrelation, which could potentially produce patterns in population synchrony similar to those caused by dispersal. By using spatially extended versions of several population dynamic models, we show that this is indeed the case. Our results show that, especially when both factors (spatially autocorrelated perturbations and distance-dependent dispersal) act together, there may exist groups of local populations in synchrony together but fluctuating asynchronously with some other groups of local populations. We also show, by analysing 56 long-term population data sets, that patterns of population synchrony similar to those found in our simulations are found in natural populations as well. This finding highlights the subtlety in the interactions of dispersal and noise in organizing spatial patterns in population fluctuations.     

When can dispersal synchronize populations?

While spatial synchrony of oscillating populations has been observed in many ecological systems, the causes of this phenomenon are still not well understood. The most common explanations have been the Moran effect (synchronous external stochastic influences) and the effect of dispersal among populations. Since ecological systems are typically subject to large spatially varying perturbations which destroy synchrony, a plausible mechanism explaining synchrony must produce rapid convergence to synchrony. We analyze the dynamics through time of the synchronizing effects of dispersal and, consequently, determine whether dispersal can be the mechanism which produces synchrony. Specifically, using methods new to ecology, we analyze a two patch predator-prey model, with identical weak dispersal between the patches. We find that a difference in time scales (i.e. one population has dynamics occurring much faster than the other) between the predator and prey species is the most important requirement for fast convergence to synchrony.     

Synchrony in brown trout, Salmo trutta, population dynamics: a 'Moran effect' on early-life stages

Synchrony among populations (i.e. spatial covariation in temporal fluctuations of population size or growth rate) is a common feature to many animals. Both large-scale autocorrelated climatic factors (the 'Moran effect') and dispersal between populations are candidates to explain synchrony, although their relative influence is difficult to assess. Only a few investigations have reported patterns of synchrony among freshwater populations, and even fewer directly related these patterns to an environmental variable. In the present study, we analysed the spatio-temporal patterns of fluctuation of 57 brown trout populations widespread across France, each sampled continuously during 5 years. We compared the respective influence of connectivity and stream distance within basins (i.e. that potentially allow a basin-scale dispersal) and environmental factors (hydrological and air temperature variables, available for 37 sites) on the synchrony of brown trout cohort densities (0+, 1+ and adults). A series of Mantel tests revealed that the degree of synchrony was not related to connectivity or stream distance between sites, suggesting no effect of dispersal at the basin-scale. The degree of synchrony among sites for the 0+ fish was significantly related to the degree of hydrological synchrony (based on high flows during the emergence period). For all three age classes, the synchrony in the temperature patterns did not explain synchrony in trout dynamics. Our results allow us to discuss the respective influence of dispersal and climatic factors on the spatio-temporal patterns of trout dynamics at the basin scale.     

Nonlinear Effect of Dispersal Rate on Spatial Synchrony of Predator-Prey Cycles

Spatially-separated populations often exhibit positively correlated fluctuations in abundance and other population variables, a phenomenon known as spatial synchrony. Generation and maintenance of synchrony requires forces that rapidly restore synchrony in the face of desynchronizing forces such as demographic and environmental stochasticity. One such force is dispersal, which couples local populations together, thereby synchronizing them. Theory predicts that average spatial synchrony can be a nonlinear function of dispersal rate, but the form of the dispersal rate-synchrony relationship has never been quantified for any system. Theory also predicts that in the presence of demographic and environmental stochasticity, realized levels of synchrony can exhibit high variability around the average, so that ecologically-identical metapopulations might exhibit very different levels of synchrony. We quantified the dispersal rate-synchrony relationship using a model system of protist predator-prey cycles in pairs of laboratory microcosms linked by different rates of dispersal. Paired predator-prey cycles initially were anti-synchronous, and were subject to demographic stochasticity and spatially-uncorrelated temperature fluctuations, challenging the ability of dispersal to rapidly synchronize them. Mean synchrony of prey cycles was a nonlinear, saturating function of dispersal rate. Even extremely low rates of dispersal (<0.4% per prey generation) were capable of rapidly bringing initially anti-synchronous cycles into synchrony. Consistent with theory, ecologically-identical replicates exhibited very different levels of prey synchrony, especially at low to intermediate dispersal rates. Our results suggest that even the very low rates of dispersal observed in many natural systems are sufficient to generate and maintain synchrony of cyclic population dynamics, at least when environments are not too spatially heterogeneous.     

Dispersal and natural enemies interact to drive spatial synchrony and decrease stability in patchy populations

Spatial synchrony is widespread in natural populations but the mechanisms that underpin it are not yet fully understood. Two key biotic drivers of spatial synchrony have been identified: dispersal and trophic interactions (e.g. natural enemies). We used spatially structured, patchy bacterial populations to show that although increased dispersal always enhanced spatial synchrony of fluctuations in bacterial abundance, this effect was far stronger in the presence of a bacteriophage parasite. Bacteriophages drove strong within patch fluctuations in bacterial abundance that became phase locked through dispersal. Furthermore, the way in which stability, measured as constancy, responded to increasing dispersal was qualitatively different depending on whether parasites were present or not. Patch-level constancy decreased with dispersal in the presence of parasites, whereas dispersal increased patch-level constancy in the absence of parasites. Population-level constancy also decreased with dispersal in the presence of parasites, but was unaffected by dispersal in the absence of parasites. These contrasting patterns were likely due to the different role played by dispersal in the presence and absence of parasites, synchronizing dynamics in the former case and averaging stochastic fluctuations in the latter. Taken together, our findings suggest that dispersal and natural enemies can interact to drive spatially synchronous population fluctuations that decrease stability at both the patch and population level.     

Synchrony of woodland bird populations: the effect of landscape structure

The influence of environmental stochasticity and dispersal in producing patterns in population synchrony was examined for 53 woods censused annually from 1990 to 1999 for nine resident bird species (wren Troglodytes troglodytes , dunnock Prunella modularis , robin Erithacus rubecula , blackbird Turdus merula , song thrush Turdus philomelos , long-tailed tit Aegithalos caudatus , blue tit Parus caeruleus , great tit Parus major , and chaffinch Fringilla coelebs ) and four migrant bird species (garden warbler Sylvia borin , blackcap Sylvia atricapilla , chiffchaff Phylloscopus collybita and willow warbler Phylloscopus trochilus ). Twelve species showed global synchrony of population counts due to regional population trends and widespread annual population fluctuations. There was a clear link between population fluctuations and winter weather for wren, and three other species showed their largest population declines after the coldest winters. Eight species showed a decline in synchrony with distance between woods, and there was evidence for dispersal causing this pattern in three species. Landscape structure affected patterns of synchrony in several species, with lower synchrony in landscapes with less woodland. For three species, this difference in synchrony across a landscape gradient of decreasing woodland cover accounted for the decline in synchrony over distance. Three species showed greater synchrony between woods with similar amounts of hedgerow in the surrounding landscape, suggesting that the surroundings of a wood influence the population dynamics of some species breeding in the wood. Habitat fragmentation can alter the processes contributing to population synchrony. Loss of woodland reduces the relative abundance of woodland bird species. The remaining patches of habitat are smaller, more isolated and are set in a more hostile landscape, all of which may disrupt dispersal between patches and alter the population dynamics within woods.     

Spatial dynamics of Norwegian tetraonid populations

Different species in a given site or population of a given species in different sites may fluctuate in synchrony if they are affected similarly by factors such as spatially autocorrelated climate, predation, or by dispersal between populations of one species. We used county wise time series of hunting bag records of four Norwegian tetraonid species covering 24 years to examine patterns of interspecific and intraspecific synchrony. We estimated synchrony at three spatial scales; national, regional (consisting of counties with similar climate), and county level. Ecologically related species with overlapping distributions exhibited strong synchrony across Norway, but there was much variation between the different regions and counties. Regions with a long coastline to both the North Sea and the Norwegian Ocean exhibited an overall stronger synchrony than those consisting of more continental areas. Intraspecific synchrony was generally low across all counties, but stronger synchrony between counties within regions defined by climatic conditions. Synchrony was negatively related to distance between populations in three of four species. Only the synchrony in willow ptarmigan showed a clear negative relationship with distance, while the other species had both strong positive and negative correlations at short distances. Strong interspecific synchrony between some species pairs within regions and weak intraspecific synchrony across counties within regions suggest a stronger synchronizing effect from environmental factors such as weather or predation and less effect from dispersal. Our results suggest that the complete tetraonid community is structured by environmental factors affecting the different species similarly and causes widespread interspecific synchrony. Local factors affecting the population dynamics nevertheless frequently forces neighbouring populations out of phase.     

Population synchrony of a native fish across three Laurentian Great Lakes: evaluating the effects of dispersal and climate

Climate and dispersal are the two most commonly cited mechanisms to explain spatial synchrony among time series of animal populations, and climate is typically most important for fishes. Using data from 1978–2006, we quantified the spatial synchrony in recruitment and population catch-per-unit-effort (CPUE) for bloater (Coregonus hoyi) populations across lakes Superior, Michigan, and Huron. In this natural field experiment, climate was highly synchronous across lakes but the likelihood of dispersal between lakes differed. When data from all lakes were pooled, modified correlograms revealed spatial synchrony to occur up to 800 km for long-term (data not detrended) trends and up to 600 km for short-term (data detrended by the annual rate of change) trends. This large spatial synchrony more than doubles the scale previously observed in freshwater fish populations, and exceeds the scale found in most marine or estuarine populations. When analyzing the data separately for within- and between-lake pairs, spatial synchrony was always observed within lakes, up to 400 or 600 km. Conversely, between-lake synchrony did not occur among short-term trends, and for long-term trends, the scale of synchrony was highly variable. For recruit CPUE, synchrony occurred up to 600 km between both lakes Michigan and Huron (where dispersal was most likely) and lakes Michigan and Superior (where dispersal was least likely), but failed to occur between lakes Huron and Superior (where dispersal likelihood was intermediate). When considering the scale of putative bloater dispersal and genetic information from previous studies, we concluded that dispersal was likely underlying within-lake synchrony but climate was more likely underlying between-lake synchrony. The broad scale of synchrony in Great Lakes bloater populations increases their probability of extirpation, a timely message for fishery managers given current low levels of bloater abundance.     

The extended Moran effect and large-scale synchronous fluctuations in the size of great tit and blue tit populations

1. Synchronous fluctuations of geographically separated populations are in general explained by the Moran effect, i.e. a common influence on the local population dynamics of environmental variables that are correlated in space. Empirical support for such a Moran effect has been difficult to provide, mainly due to problems separating out effects of local population dynamics, demographic stochasticity and dispersal that also influence the spatial scaling of population processes. Here we generalize the Moran effect by decomposing the spatial autocorrelation function for fluctuations in the size of great tit Parus major and blue tit Cyanistes caeruleus populations into components due to spatial correlations in the environmental noise, local differences in the strength of density regulation and the effects of demographic stochasticity. 2. Differences between localities in the strength of density dependence and nonlinearity in the density regulation had a small effect on population synchrony, whereas demographic stochasticity reduced the effects of the spatial correlation in environmental noise on the spatial correlations in population size by 21.7% and 23.3% in the great tit and blue tit, respectively. 3. Different environmental variables, such as beech mast and climate, induce a common environmental forcing on the dynamics of central European great and blue tit populations. This generates synchronous fluctuations in the size of populations located several hundred kilometres apart. 4. Although these environmental variables were autocorrelated over large areas, their contribution to the spatial synchrony in the population fluctuations differed, dependent on the spatial scaling of their effects on the local population dynamics. We also demonstrate that this effect can lead to the paradoxical result that a common environmental variable can induce spatial desynchronization of the population fluctuations. 5. This demonstrates that a proper understanding of the ecological consequences of environmental changes, especially those that occur simultaneously over large areas, will require information about the spatial scaling of their effects on local population dynamics.     

Dispersal and spatial scale affect synchrony in spatial population dynamics

A large body of theoretical studies has shown that synchrony among populations is critical for the long-term persistence of species in fragmented habitats. Although the effects of dispersal and environmental factors on synchrony have been investigated theoretically, empirical studies of these relationships have been lacking. We explored the interplay between environmental and demographic factors (fecundity, survival, dispersal) on population synchrony for 53 species of birds. We show that the interspecific differences in mean synchrony were determined by global environmental factors whose action was probably mediated by the abundance of each species. After removing the effect of these global factors on synchrony, the residual synchrony was strongly correlated with dispersal distance. The relationship between dispersal and synchrony was stronger for the species nesting in wet habitats than for those nesting in dry habitats. Our results indicate that different factors synchronize bird populations at different spatial scales, thus highlighting the role of scale in understanding spatial population dynamics and extinction risks.     

Canonical functions for dispersal-induced synchrony

Two processes are universally recognized for inducing spatial synchrony in abundance: dispersal and correlated environmental stochasticity. In the present study we seek the expected relationship between synchrony and distance in populations that are synchronized by density-independent dispersal. In the absence of dispersal, synchrony among populations with simple dynamics has been shown to echo the correlation in the environment. We ask what functional form we may expect between synchrony and distance when dispersal is the synchronizing agent. We formulate a continuous-space, continuous-time model that explicitly represents the time evolution of the spatial covariance as a function of spatial distance. Solving this model gives us two simple canonical functions for dispersal-induced covariance in spatially extended populations. If dispersal is rare relative to birth and death, then covariances between nearby points will follow the dispersal distance distribution. At long distances, however, the covariance tails off according to exponential or Bessel functions (depending on whether the population moves in one or two dimensions). If dispersal is common, then the covariances will follow the mixture distribution that is approximately Gaussian around the origin and with an exponential or Bessel tail. The latter mixture results regardless of the original dispersal distance distribution. There are hence two canonical functions for dispersal-induced synchrony     

Synchrony of spatial populations induced by colored environmental noise and dispersal

Spatial synchrony of oscillating populations has been observed in many ecological systems, and its influences and causes have attracted the interest of ecologists. Spatially correlated environmental noises, dispersal, and trophic interactions have been considered as the causes of spatial synchrony. In this study, we develop a spatially structured population model, which is described by coupled-map lattices and incorporates both dispersal and colored environmental noise. A method for generating time series with desired spatial correlation and color is introduced. Then, we use these generated time series to analyze the influence of noise color on synchrony in population dynamics. The noise color refers to the temporal correlation in the time series data of the noise, and is expressed as the degree of (first-order) autocorrelation for autoregressive noise. Patterns of spatial synchrony are considered for stable, periodic and chaotic population dynamics. Numerical simulations verify that environmental noise color has a major influence on the level of synchrony, which depends strongly on how noise is introduced into the model. Furthermore, the influence of noise color also depends on patterns of dispersal between local populations. In addition, the desynchronizing effect of reddened noise is always weaker than that of white noise. From our results, we notice that the role of reddened environmental noise on spatial synchrony should be treated carefully and cautiously, especially for the spatially structured populations linked by dispersal.     

Synchrony in small mammal community dynamics across a forested landscape

Long‐term studies at local scales indicate that fluctuations in abundance among trophically similar species are often temporally synchronized. Complementary studies on synchrony across larger spatial extents are less common, as are studies that investigate the subsequent impacts on community dynamics across the landscape. We investigate the impact of species population fluctuations on concordance in community dynamics for the small mammal fauna of the White Mountain National Forest, USA. Hierarchical open population models, which account for imperfect detection, were used to model abundance of the most common species at 108 sites over a three year period. Most species displayed individualistic responses of abundance to forest type and physiographic characteristics. However, among species, we found marked synchrony in population fluctuations across years, regardless of landscape affinities or trophic level. Across the region, this population synchrony led to high within‐year concordance of community composition and aggregate properties (e.g. richness and diversity) independent of forest type and low among‐year similarity in communities, even for years with similar species richness. Results suggest that extrinsic factors primarily drive abundance fluctuations and subsequently community dynamics, although local community assembly may be modified by species dispersal abilities and biotic interactions. Concordant community dynamics across space and over time may impact the stability of regional food webs and ecosystem functions.     

Effects of patch number and dispersal patterns on population dynamics and synchrony

In this paper, we examine the effects of patch number and different dispersal patterns on dynamics of local populations and on the level of synchrony between them. Local population renewal is governed by the Ricker model and we also consider asymmetrical dispersal as well as the presence of environmental heterogeneity. Our results show that both population dynamics and the level of synchrony differ markedly between two and a larger number of local populations. For two patches different dispersal rules give very versatile dynamics. However, for a larger number of local populations the dynamics are similar irrespective of the dispersal rule. For example, for the parameter values yielding stable or periodic dynamics in a single population, the dynamics do not change when the patches are coupled with dispersal. High intensity of dispersal does not guarantee synchrony between local populations. The level of synchrony depends also on dispersal rule, the number of local populations, and the intrinsic rate of increase. In our study, the effects of density-independent and density-dependent dispersal rules do not show any consistent difference. The results call for caution when drawing general conclusions from models of only two interacting populations and question the applicability of a large number of theoretical papers dealing with two local populations.     

Evidences of Moran effect in the population synchrony: a demonstration in experimental microcosm

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 Pearson's and Spearman's 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.