有色环境噪音对空间异质种群动态同步性的影响

随着种群动态和空间结构研究兴趣的增加,激发了大量的有关空间同步性的理论和实验的研究工作。空间种群的同步波动现象在自然界广泛存在,它的影响和原因引起了很多生态学家的兴趣。Moran定理是一个非常重要的解释。但以往的研究大多假设环境变化为空间相关的白噪音。越来越多的研究表明很多环境变化的时间序列具有正的时间自相关性,也就是说用红噪音来描述更加合理。因此,推广经典的Moran效应来处理空间相关红噪音的情形很有必要。利用线性的二阶自回归过程的种群模型,推导了两种群空间同步性与种群动态异质性和环境变化的时间相关性(即环境噪音的颜色)之间的关系。深入分析了种群异质性和噪音颜色对空间同步性的影响。结果表明种群动态异质性不利于空间同步性,但详细的关系比较复杂。而红色噪音的同步能力体现在两方面:一方面,本身的相关性对同步性有贡献;另一方面,环境变化时间相关性可以通过改变种群密度依赖来影响同步性,但对同步性的影响并无一致性的结论,依赖于种群的平均动态等因素。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。     

Environmental colour intensifies the Moran effect when population dynamics are spatially heterogeneous

Evidence for synchronous fluctuations of spatially separated populations is ubiquitous in the literature, including accounts within and across taxa. Among the few mechanisms explaining this phenomenon is the Moran effect, whereby independent populations are synchronized by spatially correlated environmental disturbances. The body of research on the Moran effect predominantly assumes that environmental disturbances within a local site are serially uncorrelated; that is, successive observations in time at a particular local site are independent. Yet, many environmental variables are known to possess strong temporal autocorrelation – a character which has often been described as 'colour'. The omission of environmental colour from research on the Moran effect may be due in part to the lack of methods capable of generating sets of time series with a desired colour and spatial correlation. Here I present a novel and simple method designated as 'phase partnering' to generate such sets of time series and I investigate the combined impact of spatial correlation and environmental colour on population synchrony in two common models of population dynamics. For linear population dynamics, and for a subset of nonlinear population dynamics, coloured environments intensify the Moran effect when population dynamics are spatially heterogeneous; in coloured environments the spatial correlation between populations more closely mimics the spatial correlation between their respective environments. Given that most environmental variables are coloured, these results imply that the Moran effect may be a far more significant driver of regional-scale population and interspecific synchrony than is currently believed.     

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.     

Generalizations of the Moran effect explaining spatial synchrony in population fluctuations

The Moran effect for populations separated in space states that the autocorrelations in the population fluctuations equal the autocorrelation in environmental noise, assuming the same linear density regulation in all populations. Here we generalize the Moran effect to include also nonlinear density regulation with spatial heterogeneity in local population dynamics as well as in the effects of environmental covariates by deriving a simple expression for the correlation between the sizes of two populations, using diffusion approximation to the theta-logistic model. In general, spatial variation in parameters describing the dynamics reduces population synchrony. We also show that the contribution of a covariate to spatial synchrony depends strongly on spatial heterogeneity in the covariate or in its effect on local dynamics. These analyses show exactly how spatial environmental covariation can synchronize fluctuations of spatially segregated populations with no interchange of individuals even if the dynamics are nonlinear.     

Synchrony of spatial populations: heterogeneous population dynamics and reddened environmental noise

Many species exhibit widespread spatial synchrony in population fluctuations. This pattern is of great ecological interest and can be a source of concern when a species is rare or endangered. Moran’s theorem suggests that if two (or more) populations sharing a common linear density-dependence in the renewal process are disturbed with correlated noise, they will become synchronized with correlation matching the noise correlation. In this report, correlation of nonidentical populations that are described by linear and stationary autoregressive processes is analyzed. We show that the expected spatial synchrony between two populations can be decomposed into two multiplicative components. One is the demographic component related to the values of the autoregressive coefficients and the noise color. The other is the spatial correlation of the environmental colored noise. The main results are consistent with the predictions of previous experiments and simulations, and the importance of this report is to provide theoretical support.     

Life history strategies affect climate based spatial synchrony in population dynamics of West African freshwater fishes

Spatial synchrony in species abundance is a general phenomenon that has been found in populations representing virtually all major taxa. Dispersal among populations and synchronous stochastic effects (the so called "Moran effect") are the mechanisms most likely to explain such synchrony patterns. Very few studies have related the degree of spatial synchrony to the biological characteristics of species. Here we present a case where specific predictions can be made to relate river fish species characteristics and synchrony determined exclusively by a Moran effect through the expected sensitivity of species to the regional component of environmental stochasticity. By analyzing 23-year time series of abundance estimates in two isolated localities we show that species associated with synchronized reproduction during the wet season, high fecundity, small egg size and high gonado-somatic index (the so called "periodic" strategy) have a higher degree of spatial synchrony in population dynamics than species associated with the opposite traits (the so called "equilibrium" strategy). This is supported by significant relationships (P values <0.01) between species traits and the levels of synchrony after removing taxonomical relatedness. Spatial synchrony computed from summed annual total catches by groups of species, separated into strategy types also showed a significantly higher degree of synchrony for the periodic (r=0.83) than the equilibrium (r=0.46) group. Regional hydrological variability is likely to be partly responsible for the observed synchrony pattern and a regional discharge index showed better relationships with the periodic group, supporting the expected differential effect of regional environmental correlation on population dynamics.     

Spatial synchrony of recruitment in mountain-dwelling woodland caribou

Spatial synchrony in population dynamics is a ubiquitous feature across a range of taxa. Understanding factors influencing this synchrony may shed light on important drivers of population dynamics. Three mechanisms influence the degree of spatial synchrony between populations: dispersal, shared predators, and spatial environmental covariance (the Moran effect). We assessed demographic spatial synchrony in recruitment (calf:cow ratio) of 10 northern mountain caribou herds in the Yukon Territory, Canada (1982–2008). Shared predators and dispersal were ruled out as causal mechanisms of spatial recruitment synchrony in these herds and therefore any spatial synchrony should be due to the Moran effect. We also assessed the degree of spatial synchrony in April snow depth to represent environmental variability. The regional average spatial synchrony in detrended residuals of April snow depth was 0.46 (95% CI 0.37 to 0.55). Spatial synchrony in caribou recruitment was weak at 0.13 (95% CI −0.06 to 0.32). The spatial scale of synchrony in April snow depth and caribou recruitment was 330.2 km (95% CI 236.3 to 370.0 km) and 170.0 km (95% CI 69.5 to 282.8 km), respectively. We also investigated how the similarity in terrain features between herds influenced the degree of spatial synchrony using exponential decay models. Only the difference in elevation variability between herds during calving was supported by the data. Herds with more similar elevation variability may track snowmelt ablation patterns in a more similar fashion, which would subsequently result in more synchronized predation rates on calves and/or nutritional effects impacting juvenile survival. Interspecific interactions with predators and alternate prey may also influence spatial synchrony of recruitment in these herds.     

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.     

Does the pattern of population synchrony through space reveal if the Moran effect is acting?

The populations of many species fluctuate in synchrony across large geographical areas. This synchrony is often attributed to the Moran effect, that is, shared environmental fluctuations across the region. In this article, I use a series of simple metapopulation models to show that the degree of synchrony among populations separated by different distances is strongly affected by the particular way that environmental stochasticity is represented in the models. Furthermore, when multiple types of stochasticity are acting simultaneously, the synchronizing effect of any one type is difficult to discern from the resulting pattern of population synchrony. These effects can be exacerbated under certain demographic conditions or if population dynamics are affected by interspecific interactions. In general, it should be extremely difficult to determine if synchrony is caused by the Moran effect using only the synchrony–distance relationship of natural populations.     

Analysing the Moran effect and dispersal: their significance and interaction in synchronous population dynamics

Population synchrony over various geographical scales is known from a large number of taxa. Three main hypotheses have been put forward as explanations to this phenomenon. First, correlated environmental disturbances (so called Moran effect). Moran showed that at least for linear models, the population synchrony would exactly match that of the corresponding environment. Second, the migration, or dispersal, of individuals is liable to cause population synchrony. Third, nomadic predators have been proposed as a synchronising mechanism. In this paper, I analyse the first two explanations by linearizing a general population model with spatial structure. From this linear approximation I derive an expression for the population synchrony. The major results are: 1) Population synchrony can vary significantly depending on the timing of the population census. 2) The environmental correlation is always important. It sets the 'base level' of synchrony. 3) Dispersal is only an effective synchronising mechanism when the local dynamics are at least close to unstable. 4) These results are valid even in a model with delayed density dependence – with possibly cyclic dynamics. Time lag structure has little effect on synchrony. Some of the predictions presented here are supported by data from the literature.     

Patterns of synchrony in natterjack toad breeding activity and reproductive success at local and regional scales

Empirical studies of the spatiotemporal dynamics of populations are required to better understand natural fluctuations in abundance and reproductive success, and to better target conservation and monitoring programmes. In particular, spatial synchrony in amphibian populations remains little studied. We used data from a comprehensive three year study of natterjack toad Bufo calamita populations breeding at 36 ponds to assess whether there was spatial synchrony in the toad breeding activity (start and length of breeding season, total number of egg strings) and reproductive success (premetamorphic survival and production of metamorphs). We defined a novel approach to assess the importance of short‐term synchrony at both local and regional scales. The approach employs similarity indices and quantifies the interaction between the temporal and spatial components of populations using mixed effects models. There was no synchrony in the toad breeding activity and reproductive success at the local scale, suggesting that populations function as individual clusters independent of each other. Regional synchrony was apparent in the commencement and duration of the breeding season and in the number of egg strings laid (indicative of female population size). Regional synchrony in both rainfall and temperature are likely to explain the patterns observed (e.g. Moran effect). There was no evidence supporting regional synchrony in reproductive success, most likely due to spatial variability in the environmental conditions at the breeding ponds, and to differences in local population fitness (e.g. fecundity). The small scale asynchronous dynamics and regional synchronous dynamics in the number of breeding females indicate that it is best to monitor several populations within a subset of regions. Importantly, variations in the toad breeding activity and reproductive success are not synchronous, and it is thus important to consider them both when assessing the conservation status of pond‐breeding amphibians.     

Similarity in seasonal flow regimes,not regional environmental classifications explain synchrony in brown trout population dynamics in France

相似文献   

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.     

Using geography to infer the importance of dispersal for the synchrony of freshwater plankton

Spatial synchrony in population dynamics is a ubiquitous ecological phenomenon that can result from predator–prey interactions, synchronized environmental variation (Moran effects), or dispersal. Of these, dispersal historically has been the least well studied in natural systems, partly because of the difficulty in quantifying dispersal in situ. We hypothesized that dispersal routes of plankton were based on the major and consistent water current movements in Kentucky Lake, a large reservoir in western Kentucky, USA. Then, using 26‐year time series collected at 16 locations, we used matrix regression techniques to test whether spatial heterogeneity in strengths of hypothesized dispersal predicted spatial patterns of synchrony of phytoplankton and zooplankton, thereby testing for evidence of dispersal as a possible mechanism of synchrony in this system. Nearly all taxa showed significant spatial synchrony that did not decline with increasing linear distance between locations. All taxa also showed substantial geographic structure in synchrony that was not explained by linear distance. Matrix regression revealed that our hypothesized matrix of dispersal pathways, which differed substantially from linear distance, was a significant predictor of spatial variability in synchrony in phytoplankton biomass, and Bosmina longirostris and Daphnia lumholtzi densities. Thus dispersal was a likely mechanism of synchrony for these taxa. Our hypothesized dispersal matrix was a significant predictor of spatial patterns of synchrony for these taxa even after accounting for numerous alternative possible mechanisms, including possible Moran effects through any of ten physical/abiotic constraints. Our findings indicate that statistically comparing hypothesized or measured dispersal pathway information to synchrony data via matrix regressions can provide valuable evidence for the importance of dispersal as a mechanism of spatial synchrony.     

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.     

Climate mediated exogenous forcing and synchrony in populations of the oak aphid in the UK

Contemporary population dynamics theory suggests that animal fluctuations in nature are the result of the combined forces of intrinsic and exogenous factors. Weather is the iconic example of an exogenous force. The common approach for analyzing the relationship between population size and climatic variables is by simple correlation or using the climate as an additive covariable in statistical models. Here, we evaluated different functional forms in which climatic variables could influence population dynamics of the oak aphid Tuberculatus annulatus both in each locality and in relation to synchrony between localities. Results indicate that in at least four of eight aphid populations, climate influences population dynamics by modifying the carrying capacity of the system (lateral effect mediated by winter precipitation). Additionally, path analysis showed that synchrony in population dynamics is highly correlated with synchrony in winter precipitation regime, and the spatial scale of both processes is similar, which suggests that this is an example of the Moran effect. Our results show the key effects of precipitation on intra and inter population processes of this aphid. The methods used, mixing population dynamics modelling and test of synchrony, allowed us to connect the direct and indirect effects of exogenous variables into each population with patterns of synchrony inter populations.     

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.     

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.     

Geographically partitioned spatial synchrony among cyclic moth populations

Many species of forest lepidopterans exhibit regular population cycles, which culminate in outbreak densities at approximately ten-year intervals. Population peaks and mass outbreaks typically occur synchronously and may lead to extensive forest damages over large geographic areas. Here, we report patterns of spatial synchrony among cyclic autumnal moth ( Epirrita autumnata ) populations across Fennoscandia, as inferred from 24 long-term (10–33 years) data sets. The study provides the first formal analysis of spatial synchrony of this pest species which damages mountain birch ( Betula pubescens ssp. czerepanovii ) forests in the sub Arctic. We detected positive cross-correlations in population growth rates between the time series, indicating overall spatial synchrony. However, we found the strongest degree of synchrony within geographically and climatically distinct regional clusters, into which time series were partitioned using cluster analyses. Within regional clusters, moth populations were exposed to the synchronizing effects of common, spatially autocorrelated environmental conditions, i.e. a Moran effect. Consequently, we conclude that a geographically and climatically restricted Moran effect, perhaps interacting with dispersal, is the most likely explanation for the regionally partitioned pattern of synchrony among autumnal moth populations in Fennoscandia. Our results emphasize that high amounts of environmental variation may result in a clear structuring of spatial synchrony at unexpectedly small scales.     

Geographical variation in the population dynamics of <Emphasis Type="Italic">Thecodiplosis japonensis</Emphasis>: causes and effects on spatial synchrony

Geographical variation in population dynamics of a species offers an opportunity to understand the factors determining observed patterns of spatial dynamics. We evaluated the spatial variation in the population dynamics of the pine needle gall midge (PNGM), Thecodiplosis japonensis, which is a severe insect pest in pine forests in Korea, and studied the influences of weather factors that could affect its population dynamics. Results revealed that PNGM population dynamics were classified into five clusters based on the analysis of autocorrelation function and self-organizing map, which is an artificial neural network. We also quantified spatial synchrony in the population dynamics of PNGM using the nonparametric covariance function. Variation in spatial synchrony was strongly related to differences in maximum temperature and precipitation in Random Forest analysis, suggesting that the synchrony in PNGM population dynamics is largely the result of the Moran effect. In addition, spatial differences in population dynamics could be influenced by transient process of synchronization following invasion. Finally, the present results indicate that differences in population dynamics can be induced by interactions among several factors such as maximum temperature, precipitation, and invasion history of species.