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Ecological Phenomena (ecological + phenomenon)
Selected AbstractsA general framework for neutral models of community dynamicsECOLOGY LETTERS, Issue 12 2009Omri Allouche Abstract Neutral models of community dynamics are a powerful tool for ecological research, but their applications are currently limited to unrealistically simple types of dynamics and ignore much of the complexity that characterize natural ecosystems. Here, we present a new analytical framework for neutral models that unifies existing models of neutral communities and extends the applicability of existing models to a much wider spectrum of ecological phenomena. The new framework extends the concept of neutrality to fitness equivalence and in spite of its simplicity explains a wide spectrum of empirical patterns of species diversity including positive, negative and unimodal productivity,diversity relationships; gradual and highly delayed declines in species diversity with habitat loss; and positive and negative responses of species diversity to habitat heterogeneity. Surprisingly, the abundance distribution in all of these cases is given by the dispersal limited multinomial (DLM), the abundance distribution in Hubbell's zero-sum model, showing DLM's robustness and demonstrating that it cannot be used to infer the underlying community dynamics. These results support the hypothesis that ecological communities are regulated by a limited set of fundamental mechanisms much simpler than could be expected from their immense complexity. Ecology Letters (2009) 12: 1287,1297 [source] On quantitative measures of indirect interactionsECOLOGY LETTERS, Issue 4 2007Toshinori Okuyama Abstract Indirect effects, whether density-mediated (DMII) or trait-mediated (TMII), have been recognized as potentially important drivers of community dynamics. However, empirical studies that have attempted to detect TMII or to quantify the relative strength of DMII and TMII in short-term studies have used a range of different metrics. We review these studies and assess both the consistency of a variety of different metrics and their robustness to (or ability to detect) ecological phenomena such as the dependence of forager behaviour on conspecific density. Quantifying indirect effects over longer time scales when behaviour and population density vary is more challenging, but also necessary if we really intend to incorporate indirect effects into predictions of long-term community dynamics; we discuss some problems associated with this effort and conclude with general recommendations for quantifying indirect effects. [source] Large-scale ecology and hydrology: an introductory perspective from the editors of the Journal of Applied EcologyJOURNAL OF APPLIED ECOLOGY, Issue 2000S.J. Ormerod 1. Five key features characterize large-scale factors in ecology: (a) they incorporate some of the most major of all ecological phenomena , the ranges of organisms, patterns of diversity, variations in ecosystem character and environmental processes such as climate, biogeochemical cycles, dispersal and migration; (b) they involve interactions across scales through both top-down and bottom-up processes; (c) they are multifaceted, and hence require an interdisciplinary perspective; (d) they reflect the cumulative effects of anthropogenic change across all scales, and so have direct relevance to environmental management; (e) they invariably exceed the range of classical ecological experiments, and so require alternative approaches to hypothesis testing. 2. Against this background, a recent research initiative on large-scale ecology and hydrology was funded jointly by the Natural Environment Research Council (NERC) and the Scottish Executive Rural Affairs Department (SERAD). Outputs from this programme are reported in this special issue of the Journal of Applied Ecology, and they illustrate some of the ecological research that is currently in progress in the UK at large spatio-temporal scales. 3. The spatial scales investigated in the papers range from hectares to whole continents, and much of the work reported here involves modelling. Although the model outputs are intrinsically valuable, several authors express the need for improved validation and testing. We suggest that this is an area requiring much development, and will need considerable innovation due to the difficulties at the scales involved (see 1d). Possible methods include: model applications to new circumstances; large-scale environmental manipulations; large-scale surveys that mimic experimental protocols; support from process studies at smaller scales. These alternatives are not mutually exclusive, and all can allow robust hypothesis testing. 4. Much of the work reported here is interdisciplinary linking, for example, geographical, mathematical, hydrological, hydrochemical and ecological concepts (see 1c). We suggest that even stronger links between environmental disciplines will further aid large-scale ecological research. 5. Most important in the context of the Journal of Applied Ecology, the work reported in this issue reveals that large-scale ecology already has applied value. Sectors benefiting include the conservation of biodiversity, the control of invasive species, and the management of land and water resources. 6. Large-scale issues continue to affect many applied ecologists, with roughly 30,40% of papers published in the Journal of Applied Ecology typically confronting such problems. This special issue adds to the growing body of seminal contributions that will add impetus to further large-scale work. Moreover, occurring in a period when other areas of biology are increasingly reductionist, this collection illustrates that, at least with respect to large-scale environmental problems, ecology still holds centre ground. [source] USING NETWORK ANALYSIS TO CHARACTERIZE FOREST STRUCTURENATURAL RESOURCE MODELING, Issue 2 2008MICHAEL M. FULLER Abstract Network analysis quantifies different structural properties of systems of interrelated parts using a single analytical framework. Many ecological phenomena have network-like properties, such as the trophic relationships of food webs, geographic structure of metapopulations, and species interactions in communities. Therefore, our ability to understand and manage such systems may benefit from the use of network-analysis techniques. But network analysis has not been applied extensively to ecological problems, and its suitability for ecological studies is uncertain. Here, we investigate the ability of network analysis to detect spatial patterns of species association in a tropical forest. We use three common graph-theoretic measures of network structure to quantify the effect of understory tree size on the spatial association of understory species with trees in the canopy: the node degree distribution (NDD), characteristic path length (CPL), and clustering coefficient (CC). We compute the NDD, CPL, and CC for each of seven size classes of understory trees. For significance testing, we compare the observed values to frequency distributions of each statistic computed from randomized data. We find that the ability of network analysis to distinguish observed patterns from those representing randomized data strongly depends on which aspects of structure are investigated. Analysis of NDD finds no significant difference between random and observed networks. However, analysis of CPL and CC detected nonrandom patterns in three and one of the seven size classes, respectively. Network analysis is a very flexible approach that holds promise for ecological studies, but more research is needed to better understand its advantages and limitations. [source] | ||||||||||