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19 results for “spatial synchrony”
Effects of local density dependence and temperature on the spatial synchrony of marine fish populations
<ol> <li><span>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.</span></li> <li><span>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. </span></li> <li><span>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 synchronising effect on density dynamics, while increasing strength of density dependence consistently desynchronised the dynamics. </span></li> <li><span>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. </span></li> </ol>
Effects of local density dependence and temperature on the spatial synchrony of marine fish populations
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Continent-wide drivers of spatial synchrony in breeding demographic structure across wild great tit populations
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Data from: The geography of spatial synchrony
Spatial synchrony, defined as correlated temporal fluctuations among populations, is a fundamental feature of population dynamics, but many aspects of synchrony remain poorly understood. Few studies have examined detailed geographical patterns of synchrony; instead most focus on how synchrony declines with increasing linear distance between locations, making the simplifying assumption that distance decay is isotropic. By synthesising and extending prior work, we show how geography of synchrony, a term which we use to refer to detailed spatial variation in patterns of synchrony, can be leveraged to understand ecological processes including identification of drivers of synchrony, a long-standing challenge. We focus on three main objectives: (1) showing conceptually and theoretically four mechanisms that can generate geographies of synchrony; (2) documenting complex and pronounced geographies of synchrony in two important study systems; and (3) demonstrating a variety of methods capable of revealing the geography of synchrony and, through it, underlying organism ecology. For example, we introduce a new type of network, the synchrony network, the structure of which provides ecological insight. By documenting the importance of geographies of synchrony, advancing conceptual frameworks, and demonstrating powerful methods, we aim to help elevate the geography of synchrony into a mainstream area of study and application.
Dispersal increases spatial synchrony of populations but has weak effects on population variability: a meta-analysis
<p><span>The effects of dispersal on spatial synchrony and population variability have been well documented in theoretical research, and a growing number of empirical tests have been performed. Yet a synthesis is still lacking. Here, we conducted a meta-analysis of relevant experiments and examined how dispersal affected spatial synchrony and temporal population variability across scales. Our analyses showed that dispersal generally promoted spatial synchrony, and such effects </span><span>increased with dispersal rate and decreased with environmental correlation among patches. The synchronizing effect of dispersal, however, was only detected when spatial synchrony was measured using the correlation-based index, but not for the covariance-based index. In contrast to theoretical predictions, the effect of dispersal on local population variability was generally non-significant, except when environment correlation among patch was negative and/or experimental period was long. At the regional scale, while low dispersal stabilized metapopulation dynamics, high dispersal led to destabilization. </span><span>Overall, the sign and strength of dispersal effects on spatial synchrony and population variability were modulated by taxa, environmental heterogeneity, </span><span><span>type of perturbations, patch number, and experimental length. </span>Our synthesis demonstrates that dispersal can substantially affect the dynamics of spatially distributed populations, but its effects are context dependent on abiotic and biotic factors. </span></p>
Dispersal increases spatial synchrony of populations but has weak effects on population variability: a meta-analysis
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Data from: Meteorological versus spatial drivers of the spatial synchrony of forest insect pest outbreaks in North America
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Data from: Population spatial synchrony enhanced by periodicity and low detuning with environmental forcing
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Data from: The geography of spatial synchrony
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Data from: Temporal variation in spatial genetic structure during population outbreaks: distinguishing among different potential drivers of spatial synchrony
Spatial synchrony is a common characteristic of spatio-temporal population dynamics across many taxa. While it is known that both dispersal and spatially autocorrelated environmental variation (i.e., the Moran effect) can synchronize populations, the relative contributions of each, and how they interact, is generally unknown. Distinguishing these mechanisms and their effects on synchrony can help us to better understand spatial population dynamics, design conservation and management strategies, and predict climate change impacts. Population genetic data can be used to tease apart these two processes as the spatio-temporal genetic patterns they create are expected to be different. A challenge, however, is that genetic data are often collected at a single point in time, which may introduce context-specific bias. Spatio-temporal sampling strategies can be used to reduce bias and to improve our characterization of the drivers of spatial synchrony. Using spatio-temporal analyses of genotypic data, our objective was to identify the relative support for these two mechanisms to the spatial synchrony in population dynamics of the irruptive forest insect pest, the spruce budworm (Choristoneura fumiferana), in Quebec (Canada). AMOVA, cluster analysis, isolation by distance and sPCA were used to characterize spatio-temporal genomic variation using 1370 SBW larvae sampled over four years (2012-2015) and genotyped at 3,562 SNP loci. We found evidence of overall weak spatial genetic structure that decreased from 2012 to 2015 and a genetic diversity homogenization among the sites. We also found genetic evidence of a long-distance dispersal event over > 140 km. These results indicate that dispersal is the key mechanism involved in driving population synchrony of the outbreak. Early intervention management strategies that aim to control source populations have the potential to be effective through limiting dispersal. However, the timing of such interventions relative to outbreak progression is likely to influence their probability of success.
Data from: Predicting bird phenology from space: satellite-derived vegetation green-up signal uncovers spatial variation in phenological synchrony between birds and their environment
Population-level studies of how tit species (Parus spp.) track the changing phenology of their caterpillar food source have provided a model system allowing inference into how populations can adjust to changing climates, but are often limited because they implicitly assume all individuals experience similar environments. Ecologists are increasingly using satellite-derived data to quantify aspects of animals' environments, but so far studies examining phenology have generally done so at large spatial scales. Considering the scale at which individuals experience their environment is likely to be key if we are to understand the ecological and evolutionary processes acting on reproductive phenology within populations. Here, we use time series of satellite images, with a resolution of 240 m, to quantify spatial variation in vegetation green-up for a 385-ha mixed-deciduous woodland. Using data spanning 13 years, we demonstrate that annual population-level measures of the timing of peak abundance of winter moth larvae (Operophtera brumata) and the timing of egg laying in great tits (Parus major) and blue tits (Cyanistes caeruleus) is related to satellite-derived spring vegetation phenology. We go on to show that timing of local vegetation green-up significantly explained individual differences in tit reproductive phenology within the population, and that the degree of synchrony between bird and vegetation phenology showed marked spatial variation across the woodland. Areas of high oak tree (Quercus robur) and hazel (Corylus avellana) density showed the strongest match between remote-sensed vegetation phenology and reproductive phenology in both species. Marked within-population variation in the extent to which phenology of different trophic levels match suggests that more attention should be given to small-scale processes when exploring the causes and consequences of phenological matching. We discuss how use of remotely sensed data to study within-population variation could broaden the scale and scope of studies exploring phenological synchrony between organisms and their environment.
Data and code for "Assessing the spatial scale of synchrony in forest tree population dynamics"
<p>The data sets and code provided here facilitate reproduction of our results from this paper on synchrony of forest tree population dynamics. </p> <h3>Description of the data and file structure</h3> <p>The analyses in the paper were conducted at three scales, and each involves its own data files:</p> <ul> <li>Local scale: The relevant data files are named, e.g., "BCI1-7,L=250m,dbh=100mm.Rdata", where "BCI1-7" indicates the ForestGEO site name ("BCI") and census intervals (1 to 7 for BCI), "L=250m" indicates the quadrat size, and "dbh=100mm" indicates the diameter-at-breast height (DBH) threshold used. There are 12 such files (two ForestGEO plots--BCI and Pasoh--times three quadrat sizes times two DBH thresholds). Each file contains a single list "N_all", whose length is equal to the number of quadrats at the given grain. Each element in the list is a data frame containing mean census times (in days), tree species' population sizes and number of survivors across the two censuses for the corresponding quadrat.</li> <li>Regional scale: The relevant data files are "Marena_data,dbh=100mm,spp_anonymised.Rdata" and "Marena_data,dbh=100mm,spp_anonymised.Rdata". Each file contains three objects: "dists" is a matrix giving the distances between all pairs of sites; "N_all1" is a list with one element for each plot, and each element being a data frame with (anonymised) species ids in the first column and abundances in the remaining columns (column names give mean census dates in days); "S_all1" has a similar structure to "N_all1" except that the data give numbers of survivors from any given census to any subsequent census (column headings indicate the two census numbers).</li> <li>Global scale: The relevant data files are "global_data,dbh=10mm,spp_anonymised.Rdata" and "global_data,dbh=100mm,spp_anonymised.Rdata". The data in the files have the same structure as in the regional-scale files.</li> </ul>
Data from: Temporal variation in spatial genetic structure during population outbreaks: distinguishing among different potential drivers of spatial synchrony
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Data from: Differences in spatial synchrony and interspecific concordance inform guild-level population trends for aerial insectivorous birds
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Data from: Predicting bird phenology from space: satellite-derived vegetation green-up signal uncovers spatial variation in phenological synchrony between birds and their environment
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Data from: Life-stage differences in spatial genetic structure in an irruptive forest insect: implications for dispersal and spatial synchrony
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Data from: Spatial synchrony in sub-arctic geometrid moth outbreaks reflects dispersal in larval and adult lifecycle stages
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Data from: Evidence of spatial synchrony in the spread of an invasive forest pest
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Data from: Occasional long-distance dispersal increases spatial synchrony of population cycles
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