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Moran Effect (moran + effect)
Selected AbstractsSpatial abundance structures in an assemblage of gall-forming sawfliesJOURNAL OF ANIMAL ECOLOGY, Issue 3 2004M. A. McGeoch Summary 1Examination of the fine-scale internal structure of species geographical ranges, and interspecific variation therein across landscapes, contributes to a more comprehensive understanding of the structure of geographical ranges. Two components of this internal structure that require further examination are the occurrence, extent and position of spatial autocorrelation, and relationships between the spatial abundance structures of closely related, ecologically similar species. 2Here we compare the abundance structures of an assemblage of gall-forming sawflies (Tenthredinidae) across a landscape. We identify the relative roles of spatial and non-spatial factors in explaining their abundance structures and test the hypothesis that sawfly density is explained by host plant quality, as has been demonstrated repeatedly at finer scales. We use these results to distinguish between alternative sets of mechanisms that may be operating at the landscape scale. 3Species densities were mainly multimodal across the landscape and significantly spatially structured, with patch, periodic and trend components. The abundance structures thus mimic those found generally for species across the full extent of their geographical ranges. 4Many abundance structure characteristics were unique to species, with differences in their correlogram profiles, distances over which densities were positively autocorrelated, and the absence of significant spatial structure in one species. 5In contrast to previous, fine-scale studies, host plant quality explained little of the variation in sawfly gall density across the landscape, whereas unexplained spatial structure contributed between 30% and 50%. Based on knowledge of the biology of these species and the absence of competitive interactions, species dispersal characteristics and the Moran effect are suggested as probable alternative hypotheses at this scale. 6Therefore, a spatial approach has identified the hierarchical nature of mechanisms underlying the population dynamics of this sawfly assemblage for the first time. Furthermore, it has highlighted the importance of spatial processes in explaining the densities of species at the landscape scale, as well as the individualistic nature of their abundance structures. [source] Climate mediated exogenous forcing and synchrony in populations of the oak aphid in the UKOIKOS, Issue 2 2009Sergio A. Estay 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. [source] Environmental colour intensifies the Moran effect when population dynamics are spatially heterogeneousOIKOS, Issue 10 2007David A. Vasseur 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. [source] The impact of stochasticity on the behaviour of nonlinear population models: synchrony and the Moran effectOIKOS, Issue 2 2001J. V. Greenman Environmental variation is ubiquitous, but its effects on nonlinear population dynamics are poorly understood. Using simple (unstructured) nonlinear models we investigate the effects of correlated noise on the dynamics of two otherwise independent populations (the Moran effect), i.e. we focus on noise rather than dispersion or trophic interaction as the cause of population synchrony. We find that below the bifurcation threshold for periodic behaviour (1) synchrony between populations is strongly dependent on the shape of the noise distribution but largely insensitive to which model is studied, (2) there is, in general, a loss of synchrony as the noise is filtered by the model, (3) for specially structured noise distributions this loss can be effectively eliminated over a restricted range of distribution parameter values even though the model might be nonlinear, (4) for unstructured models there is no evidence of correlation enhancement, a mechanism suggested by Moran, but above the bifurcation threshold enhancement is possible for weak noise through phase-locking, (5) rapid desynchronisation occurs as the chaotic regime is approached. To carry out the investigation the stochastic models are (a) reformulated in terms of their joint asymptotic probability distributions and (b) simulated to analyse temporal patterns. [source] | ||||||||||