Generalizations of the Moran effect explaining spatial synchrony in population fluctuations

Effects of local density dependence and temperature on the spatial synchrony of marine fish populations

Disentangling empirically the many processes affecting spatial population synchrony is a challenge in population ecology. Two processes that could have major effects on the spatial synchrony of wild population dynamics are density dependence and variation in environmental conditions like temperature. Understanding these effects is crucial for predicting the effects of climate change on local and regional population dynamics. We quantified the direct contribution of local temperature and density dependence to spatial synchrony in the population dynamics of nine fish species inhabiting the Barents Sea. First, we estimated the degree to which the annual spatial autocorrelations in density are influenced by temperature. Second, we estimated and mapped the local effects of temperature and strength of density dependence on annual changes in density. Finally, we measured the relative effects of temperature and density dependence on the spatial synchrony in changes in density. Temperature influenced the annual spatial autocorrelation in density more in species with greater affinities to the benthos and to warmer waters. Temperature correlated positively with changes in density in the eastern Barents Sea for most species. Temperature had a weak synchronizing effect on density dynamics, while increasing strength of density dependence consistently desynchronised the dynamics. Quantifying the relative effects of different processes affecting population synchrony is important to better predict how population dynamics might change when environmental conditions change. Here, high degrees of spatial synchrony in the population dynamics remained unexplained by local temperature and density dependence, confirming the presence of additional synchronizing drivers, such as trophic interactions or harvesting.

Generation time and seasonal migration explain variation in spatial population synchrony across European bird species

Spatial population synchrony is common among populations of the same species and is an important predictor of extinction risk. Despite the potential consequences for metapopulation persistence, we still largely lack understanding of what makes one species more likely to be synchronized than another given the same environmental conditions. Generally, environmental conditions in a shared environment or a species' sensitivity to the environment can explain the extent of synchrony. Populations that are closer together experience more similar fluctuations in their environments than those populations that are further apart and are therefore more synchronized. The relative importance of environmental and demographic stochasticity for population dynamics is strongly linked to species' life-history traits, such as pace of life, which may impact population synchrony. For populations that migrate, there may be multiple environmental conditions at different locations driving synchrony. However, the importance of life history and migration tactics in determining patterns of spatial population synchrony have rarely been explored empirically. We therefore hypothesize that increasing generation time, a proxy for pace of life, would decrease spatial population synchrony and that migrants would be less synchronized than resident species. We used population abundance data on breeding birds from four countries to investigate patterns of spatial population synchrony in growth rate and abundance. We calculated the mean spatial population synchrony between log-transformed population growth rates or log-transformed abundances for each species and country separately. We investigated differences in synchrony across generation times in resident (n = 67), short-distance migrant (n = 86) and long-distance migrant (n = 39) bird species. Species with shorter generation times were more synchronized than species with longer generation times. Short-distance migrants were more synchronized than long-distance migrants and resident birds. Our results provide novel empirical links between spatial population synchrony and species traits known to be of key importance for population dynamics, generation time and migration tactics. We show how these different mechanisms can be combined to understand species-specific causes of spatial population synchrony. Understanding these specific drivers of spatial population synchrony is important in the face of increasingly severe threats to biodiversity and could be key for successful future conservation outcomes.

Noise-induced swarming of active particles

We report on the effect of spatially correlated noise on the velocities of self-propelled particles. Correlations in the random forces acting on self-propelled particles can induce directed collective motion, i.e., swarming. Even with repulsive coupling in the velocity directions, which favors a disordered state, strong correlations in the fluctuations can align the velocities locally leading to a macroscopic, turbulent velocity field. On the other hand, while spatially correlated noise is aligning the velocities locally, the swarming transition to globally directed motion is inhibited when the correlation length of the noise is nonzero, but smaller than the system size. We analyze the swarming transition in d-dimensional space in a mean field model of globally coupled velocity vectors.

Age-dependent patterns of spatial autocorrelation in fish populations

The degree of spatial autocorrelation in population fluctuations increases with dispersal and geographical covariation in the environment, and decreases with strength of density dependence. Because the effects of these processes can vary throughout an individual's lifespan, we studied how spatial autocorrelation in abundance changed with age in three marine fish species in the Barents Sea. We found large interspecific differences in age-dependent patterns of spatial autocorrelation in density. Spatial autocorrelation increased with age in cod, the reverse trend was found in beaked redfish, while it remained constant among age classes in haddock. We also accounted for the average effect of local cohort dynamics, i.e. the expected local density of an age class given last year's local density of the cohort, with the goal of disentangling spatial autocorrelation patterns acting on an age class from those formed during younger age classes and being carried over. We found that the spatial autocorrelation pattern of older age classes became increasingly determined by the distribution of the cohort during the previous year. Lastly, we found high degrees of autocorrelation over long distances for the three species, suggesting the presence of far-reaching autocorrelating processes on these populations. We discuss how differences in the species' life history strategies could cause the observed differences in age-specific variation in spatial autocorrelation. As spatial autocorrelation can differ among age classes, our study indicates that fluctuations in age structure can influence the spatio-temporal variation in abundance of marine fish populations.

Spatial synchrony is related to environmental change in Finnish moth communities

Spatially distinct pairs of sites may have similarly fluctuating population dynamics across large geographical distances, a phenomenon called spatial synchrony. However, species rarely exist in isolation, but rather as members of interactive communities, linked with other communities through dispersal (i.e. a metacommunity). Using data on Finnish moth communities sampled across 65 sites for 20 years, we examine the complex synchronous/anti-synchronous relationships among sites using the geography of synchrony framework. We relate site-level synchrony to mean and temporal variation in climatic data, finding that colder and drier sites-and those with the most drastic temperature increases-are important for spatial synchrony. This suggests that faster-warming sites contribute most strongly to site-level estimates of synchrony, highlighting the role of a changing climate to spatial synchrony. Considering the spatial variability in climate change rates is therefore important to understand metacommunity dynamics and identify habitats which contribute most strongly to spatial synchrony.

Drivers of amphibian population dynamics and asynchrony at local and regional scales

Identifying the drivers of population fluctuations in spatially distinct populations remains a significant challenge for ecologists. Whereas regional climatic factors may generate population synchrony (i.e. the Moran effect), local factors including the level of density dependence may reduce the level of synchrony. Although divergences in the scaling of population synchrony and spatial environmental variation have been observed, the regulatory factors that underlie such mismatches are poorly understood. Few previous studies have investigated how density-dependent processes and population-specific responses to weather variation influence spatial synchrony at both local and regional scales. We addressed this issue in a pond-breeding amphibian, the great crested newt Triturus cristatus. We used capture-recapture data collected through long-term surveys in five T. cristatus populations in Western Europe. In all populations-and subpopulations within metapopulations-population size, annual survival and recruitment fluctuated over time. Likewise, there was considerable variation in these demographic rates between populations and within metapopulations. These fluctuations and variations appear to be context-dependent and more related to site-specific characteristics than local or regional climatic drivers. We found a low level of demographic synchrony at both local and regional levels. Weather has weak and spatially variable effects on survival, recruitment and population growth rate. In contrast, density dependence was a common phenomenon (at least for population growth) in almost all populations and subpopulations. Our findings support the idea that the Moran effect is low in species where the population dynamics more closely depends on local factors (e.g. population density and habitat characteristics) than on large-scale environmental fluctuation (e.g. regional climatic variation). Such responses may have far-reaching consequences for the long-term viability of spatially structured populations and their ability to respond to large-scale climatic anomalies.

When does weather synchronize life-history traits? Spatiotemporal patterns in juvenile body mass of two ungulates

Theory predicts that animal populations will be synchronized over large distances by weather and climatic conditions with high spatial synchrony. However, local variation in population responses to weather, and low synchrony in key weather variables or in other ecological processes may reduce the population synchrony. We investigated to what extent temperature and precipitation during different periods of the year synchronized juvenile body mass of moose and reindeer in Norway. We expected high synchronizing effect of weather variables with a high and consistent explanatory power on body mass dynamics across populations, and a weaker synchronizing effect of weather variables whose effect on body mass varied among populations. Juvenile body mass in both species was related to temperature and precipitation during several periods of the year. Temperature had the strongest explanatory power in both species, with a similar effect across all populations. There was higher spatial synchrony in temperature compared to precipitation, and accordingly temperature had the strongest synchronizing effect on juvenile body mass. Moreover, periods with strong explanatory power had stronger synchronizing effect on juvenile body mass in both species. However, weather variables with large variation in the effects on body mass among populations had weak synchronizing effect. The results confirm that weather has a large impact on the spatial structure of population properties but also that spatial heterogeneity, for instance, in environmental change or population density may affect how and to what extent populations are synchronized.

Spatial heterogeneity in climate change effects decouples the long-term dynamics of wild reindeer populations in the high Arctic

The 'Moran effect' predicts that dynamics of populations of a species are synchronized over similar distances as their environmental drivers. Strong population synchrony reduces species viability, but spatial heterogeneity in density dependence, the environment, or its ecological responses may decouple dynamics in space, preventing extinctions. How such heterogeneity buffers impacts of global change on large-scale population dynamics is not well studied. Here, we show that spatially autocorrelated fluctuations in annual winter weather synchronize wild reindeer dynamics across high-Arctic Svalbard, while, paradoxically, spatial variation in winter climate trends contribute to diverging local population trajectories. Warmer summers have improved the carrying capacity and apparently led to increased total reindeer abundance. However, fluctuations in population size seem mainly driven by negative effects of stochastic winter rain-on-snow (ROS) events causing icing, with strongest effects at high densities. Count data for 10 reindeer populations 8-324 km apart suggested that density-dependent ROS effects contributed to synchrony in population dynamics, mainly through spatially autocorrelated mortality. By comparing one coastal and one 'continental' reindeer population over four decades, we show that locally contrasting abundance trends can arise from spatial differences in climate change and responses to weather. The coastal population experienced a larger increase in ROS, and a stronger density-dependent ROS effect on population growth rates, than the continental population. In contrast, the latter experienced stronger summer warming and showed the strongest positive response to summer temperatures. Accordingly, contrasting net effects of a recent climate regime shift-with increased ROS and harsher winters, yet higher summer temperatures and improved carrying capacity-led to negative and positive abundance trends in the coastal and continental population respectively. Thus, synchronized population fluctuations by climatic drivers can be buffered by spatial heterogeneity in the same drivers, as well as in the ecological responses, averaging out climate change effects at larger spatial scales.

Spatial distribution and optimal harvesting of an age-structured population in a fluctuating environment

We analyze a spatial age-structured model with density regulation, age specific dispersal, stochasticity in vital rates and proportional harvesting. We include two age classes, juveniles and adults, where juveniles are subject to logistic density dependence. There are environmental stochastic effects with arbitrary spatial scales on all birth and death rates, and individuals of both age classes are subject to density independent dispersal with given rates and specified distributions of dispersal distances. We show how to simulate the joint density fields of the age classes and derive results for the spatial scales of all spatial autocovariance functions for densities. A general result is that the squared scale has an additive term equal to the squared scale of the environmental noise, corresponding to the Moran effect, as well as additive terms proportional to the dispersal rate and variance of dispersal distance for the age classes and approximately inversely proportional to the strength of density regulation. We show that the optimal harvesting strategy in the deterministic case is to harvest only juveniles when their relative value (e.g. financial) is large, and otherwise only adults. With increasing environmental stochasticity there is an interval of increasing length of values of juveniles relative to adults where both age classes should be harvested. Harvesting generally tends to increase all spatial scales of the autocovariances of densities.

Climate change-related regime shifts have altered spatial synchrony of plankton dynamics in the North Sea

During the 1980s, the North Sea plankton community underwent a well-documented ecosystem regime shift, including both spatial changes (northward species range shifts) and temporal changes (increases in the total abundances of warmer water species). This regime shift has been attributed to climate change. Plankton provide a link between climate and higher trophic-level organisms, which can forage on large spatial and temporal scales. It is therefore important to understand not only whether climate change affects purely spatial or temporal aspects of plankton dynamics, but also whether it affects spatiotemporal aspects such as metapopulation synchrony. If plankton synchrony is altered, higher trophic-level feeding patterns may be modified. A second motivation for investigating changes in synchrony is that the possibility of such alterations has been examined for few organisms, in spite of the fact that synchrony is ubiquitous and of major importance in ecology. This study uses correlation coefficients and spectral analysis to investigate whether synchrony changed between the periods 1959-1980 and 1989-2010. Twenty-three plankton taxa, sea surface temperature (SST), and wind speed were examined. Results revealed that synchrony in SST and plankton was altered. Changes were idiosyncratic, and were not explained by changes in abundance. Changes in the synchrony of Calanus helgolandicus and Para-pseudocalanus spp appeared to be driven by changes in SST synchrony. This study is one of few to document alterations of synchrony and climate-change impacts on synchrony. We discuss why climate-change impacts on synchrony may well be more common and consequential than previously recognized.

Spatial synchrony in population dynamics: The effects of demographic stochasticity and density regulation with a spatial scale

We generalize a previous simple result by Lande et al. (1999) on how spatial autocorrelated noise, dispersal rate and distance as well as strength of density regulation determine the spatial scale of synchrony in population density. It is shown how demographic noise can be incorporated, what effect it has on variance and spatial scale of synchrony, and how it interacts with the point process for locations of individuals under random sampling. Although the effect of demographic noise is a rather complex interaction with environmental noise, migration and density regulation, its effect on population fluctuations and scale of synchrony can be presented in a transparent way. This is achieved by defining a characteristic area dependent on demographic and environmental variances as well as population density, and subsequently using this area to define a spatial demographic coefficient. The demographic noise acts through this coefficient on the spatial synchrony, which may increase or decrease with increasing demographic noise depending on other parameters. A second generalization yields the modeling of density regulation taking into account that regulation at a given location does not only depend on the density at that site but also on densities in the whole territory or home range of individuals. It is shown that such density regulation with a spatial scale reduces the scale of synchrony in population fluctuations relative to the simpler model with density regulation at each location determined only by the local point density, and may even generate negative spatial autocorrelations.

Accounting for sampling error when inferring population synchrony from time-series data: a Bayesian state-space modelling approach with applications

Background

Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation.

Methodology/Principal findings

The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength.

Conclusion/Significance

The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in population size estimates.

Synchrony of population dynamics of two vineyard arthropods occurs at multiple spatial and temporal scales

When populations are synchronized, they rise and fall together. Analysis of population synchrony and its relationship to distance has played a major role in population ecology but has been absent from most studies of managed populations, such as agricultural arthropods. The extent to which populations at different locations are synchronized reflects the relative roles of shared environmental impacts, such as weather, and localizing processes, such as dispersal. The strength and pattern of synchrony, and the processes generating synchrony, have direct management implications. For the first time, we bring together two major paths of population-ecology research: spatial synchrony of population dynamics, which has been studied across birds, mammals, and insects, and spatial ecology of agricultural arthropod populations. We compare and contrast synchrony of two arthropod species, a spider mite and a leafhopper, across a vineyard region spanning 30-km distances, at within-year (weekly) and between-year time scales. Despite the enormous scope of agriculture, such long-term, large-scale data sets suitable for investigating local and regional dynamics are rare. For both species, synchrony is more strongly localized for annual peak abundance across 11 years than it typically is for weekly dynamics within each year's growing season. This suggests that between-year processes such as overwintering merit greater investigation. Within each year, both localized and region-wide synchrony was found for both species, but leafhoppers showed stronger localization than spider mites, corresponding to their longer generation time and stronger dispersal ability. This demonstrates that the overall herbivore dynamics of the system occur at multiple spatial scales and that the importance of different processes generating synchrony varies by species. The analysis includes new spatiotemporal randomization and bootstrap tests that can be applied to many systems. Our results highlight the value of large-scale, long-term monitoring programs for many kinds of managed populations. They also point toward the potential to test synchrony mechanisms more directly and to synthesize synchrony and landscape analyses.

Synchrony and stability of food webs in metacommunities

Synchrony has fundamental but conflicting implications for the persistence and stability of food webs at local and regional scales. In a constant environment, compensatory dynamics between species can maintain food web stability, but factors that synchronize population fluctuations within and between communities are expected to be destabilizing. We studied the dynamics of a food web in a metacommunity to determine how environmental variability and dispersal affect stability by altering compensatory dynamics and average species abundance. When dispersal rate is high, weak correlated environmental fluctuations promote food web stability by reducing the amplitude of compensatory dynamics. However, when dispersal rate is low, weak environmental fluctuations reduce food web stability by inducing intraspecific synchrony across communities. Irrespective of dispersal rate, strong environmental fluctuations disrupt compensatory dynamics and decrease stability by inducing intermittent correlated fluctuations between consumers in local food webs, which reduce both total consumer abundance and predator abundance. Strong correlated environmental fluctuations lead to (i) spatially asynchronous and highly correlated local consumer dynamics when dispersal is low and (ii) spatially synchronous but intermediate local consumer correlation when dispersal is high. By controlling intraspecific synchrony, dispersal mediates the capacity of strong environmental fluctuations to disrupt compensatory dynamics at both local and metacommunity scales.

Modeling survival at multi-population scales using mark-recapture data

The demography of vertebrate populations is governed in part by processes operating at large spatial scales that have synchronizing effects on demographic parameters over large geographic areas, and in part, by local processes that generate fluctuations that are independent across populations. We describe a statistical model for the analysis of individual monitoring data at the multi-population scale that allows us to (1) split up temporal variation in survival into two components that account for these two types of processes and (2) evaluate the role of environmental factors in generating these two components. We derive from this model an index of synchrony among populations in the pattern of temporal variation in survival, and we evaluate the extent to which environmental factors contribute to synchronize or desynchronize survival variation among populations. When applied to individual monitoring data from four colonies of the Atlantic Puffin (Fratercula arctica), 67% of between-year variance in adult survival was accounted for by a global spatial-scale component, indicating substantial synchrony among colonies. Local sea surface temperature (SST) accounted for 40% of the global spatial-scale component but also for an equally large fraction of the local-scale component. SST thus acted at the same time as both a synchronizing and a desynchronizing agent. Between-year variation in adult survival not explained by the effect of local SST was as synchronized as total between-year variation, suggesting that other unknown environmental factors acted as synchronizing agents. Our approach, which focuses on demographic mechanisms at the multi-population scale, ideally should be combined with investigations of population size time series in order to characterize thoroughly the processes that underlie patterns of multi-population dynamics and, ultimately, range dynamics.

Phase-locking and environmental fluctuations generate synchrony in a predator-prey community

Spatially synchronized fluctuations in system state are common in physical and biological systems ranging from individual atoms to species as diverse as viruses, insects and mammals. Although the causal factors are well known for many synchronized phenomena, several processes concurrently have an impact on spatial synchrony of species, making their separate effects and interactions difficult to quantify. Here we develop a general stochastic model of predator-prey spatial dynamics to predict the outcome of a laboratory microcosm experiment testing for interactions among all known synchronizing factors: (1) dispersal of individuals between populations; (2) spatially synchronous fluctuations in exogenous environmental factors (the Moran effect); and (3) interactions with other species (for example, predators) that are themselves spatially synchronized. The Moran effect synchronized populations of the ciliate protist Tetrahymena pyriformis; however, dispersal only synchronized prey populations in the presence of the predator Euplotes patella. Both model and data indicate that synchrony depends on cyclic dynamics generated by the predator. Dispersal, but not the Moran effect, 'phase-locks' cycles, which otherwise become 'decoherent' and drift out of phase. In the absence of cycles, phase-locking is not possible and the synchronizing effect of dispersal is negligible. Interspecific interactions determine population synchrony, not by providing an additional source of synchronized fluctuations, but by altering population dynamics and thereby enhancing the action of dispersal. Our results are robust to wide variation in model parameters representative of many natural predator-prey or host-pathogen systems. This explains why cyclic systems provide many of the most dramatic examples of spatial synchrony in nature.

A landscape theory for food web architecture

Ecologists have long searched for structures and processes that impart stability in nature. In particular, food web ecology has held promise in tackling this issue. Empirical patterns in food webs have consistently shown that the distributions of species and interactions in nature are more likely to be stable than randomly constructed systems with the same number of species and interactions. Food web ecology still faces two fundamental challenges, however. First, the quantity and quality of food web data required to document both the species richness and the interaction strengths among all species within food webs is largely prohibitive. Second, where food webs have been well documented, spatial and temporal variation in food web structure has been ignored. Conversely, research that has addressed spatial and temporal variation in ecosystems has generally ignored the full complexity of food web architecture. Here, we incorporate empirical patterns, largely from macroecology and behavioural ecology, into a spatially implicit food web structure to construct a simple landscape theory of food web architecture. Such an approach both captures important architectural features of food webs and allows for an exploration of food web structure across a range of spatial scales. Finally, we demonstrated that food webs are hierarchically organized along the spatial and temporal niche axes of species and their utilization of food resources in ways that stabilize ecosystems.

Using mechanistic models to understand synchrony in forest insect populations: the North American gypsy moth as a case study

In many forest insects, subpopulations fluctuate concurrently across large geographical areas, a phenomenon known as population synchrony. Because of the large spatial scales involved, empirical tests to identify the causes of synchrony are often impractical. Simple models are, therefore, a useful aid to understanding, but data often seem to contradict model predictions. For instance, chaotic population dynamics and limited dispersal are not uncommon among synchronous forest defoliators, yet both make it difficult to achieve synchrony in simple models. To test whether this discrepancy can be explained by more realistic models, we introduced dispersal and spatially correlated stochasticity into a mechanistic population model for the North American gypsy moth Lymantria dispar. The resulting model shows both chaotic dynamics and spatial synchrony, suggesting that chaos and synchrony can be reconciled by the incorporation of realistic dynamics and spatial structure. By relating alterations in model structure to changes in synchrony levels, we show that the synchrony is due to a combination of spatial covariance in environmental stochasticity and the origins of chaos in our multispecies model.

Environmental fluctuations can stabilize food web dynamics by increasing synchrony

Natural food webs are species-rich, but classical theory suggests that they should be unstable and extinction-prone. Asynchronous fluctuations in the densities of competing consumers can stabilize food web dynamics in constant environments. However, environmental fluctuations often synchronize dynamics in nature. Using the same 'diamond-shape' food web model first used to demonstrate the stabilizing effects of asynchrony in constant environments, we show that weak-to-moderate environmentally induced fluctuations in consumer mortality rates stabilize food webs while disrupting asynchrony. Synchrony actually promotes stability because: (i) synchronous declines in consumer density reduce the maximum abundance of top predators and (ii) resource competition quickly converts synchronous increases in consumer density into synchronous declines. These results are robust to details of food web topology and the implementation of environmental fluctuations. The fluctuation strengths that enhance stability are within the range experienced naturally by many species, suggesting that stabilization via environmental fluctuations is a realistic possibility.

Climate and spatio-temporal variation in the population dynamics of a long distance migrant, the white stork

1. A central question in ecology is to separate the relative contribution of density dependence and stochastic influences to annual fluctuations in population size. Here we estimate the deterministic and stochastic components of the dynamics of different European populations of white stork Ciconia ciconia. We then examined whether annual changes in population size was related to the climate during the breeding period (the 'tap hypothesis' sensu Saether, Sutherland & Engen (2004, Advances in Ecological Research, 35, 185 209) or during the nonbreeding period, especially in the winter areas in Africa (the 'tube hypothesis'). 2. A general characteristic of the population dynamics of this long-distance migrant is small environmental stochasticity and strong density regulation around the carrying capacity with short return times to equilibrium. 3. Annual changes in the size of the eastern European populations were correlated by rainfall in the wintering areas in Africa as well as local weather in the breeding areas just before arrival and in the later part of the breeding season and regional climate variation (North Atlantic Oscillation). This indicates that weather influences the population fluctuations of white storks through losses of sexually mature individuals as well as through an effect on the number of individuals that manages to establish themselves in the breeding population. Thus, both the tap and tube hypothesis explains climate influences on white stork population dynamics. 4. The spatial scale of environmental noise after accounting for the local dynamics was 67 km, suggesting that the strong density dependence reduces the synchronizing effects of climate variation on the population dynamics of white stork. 5. Several climate variables reduced the synchrony of the residual variation in population size after accounting for density dependence and demographic stochasticity, indicating that these climate variables had a synchronizing effect on the population fluctuations. In contrast, other climatic variables acted as desynchronizing agents. 6. Our results illustrate that evaluating the effects of common environmental variables on the spatio-temporal variation in population dynamics require estimates and modelling of their influence on the local dynamics.

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.