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Species-area Curves (species-area + curve)
Selected AbstractsBeta diversity and latitude in North American mammals: testing the hypothesis of covariationECOGRAPHY, Issue 5 2004Pilar Rodríguez Several hypotheses attempt to explain the latitudinal gradient of species diversity, but some basic aspects of the pattern remain insufficiently explored, including the effect of scales and the role of beta diversity. To explore such components of the latitudinal gradient, we tested the hypothesis of covariation, which states that the gradient of species diversity should show the same pattern regardless of the scale of analysis. The hypothesis implies that there should be no gradients of beta diversity, of regional range size within regions, and of the slope of the species-area curve. For the fauna of North American mammals, we found contrasting results for bats and non-volant species. We could reject the hypothesis of covariation for non-volant mammals, for which the number of species increases towards lower latitudes, but at different rates depending on the scale. Also, for this group, beta diversity is higher at lower latitudes, the regional range size within regions is smaller at lower latitudes, and z, the slope of the species-area relationship is higher at lower latitudes. Contrarily bats did not show significant deviations from the predictions of the hypothesis of covariation: at two different scales, species richness shows similar trends of increase at lower latitudes, and no gradient can be demonstrated for beta diversity, for regional range size, or for the slopes of the species-area curve. Our results show that the higher diversity of non-volant mammals in tropical areas of North America is a consequence of the increase in beta diversity and not of higher diversity at smaller scales. In contrast, the diversity of bats at both scales is higher at lower latitudes. These contrasting patterns suggest different causes for the latitudinal gradient of species diversity in the two groups that are ultimately determined by differences in the patterns of geographic distribution of the species. [source] The species-area relationship in the hoverfly (Diptera, Syrphidae) communities of forest fragments in southern FranceECOGRAPHY, Issue 2 2006Annie Ouin The effect of forest fragmentation was studied in hoverfly communities of 54 isolated forests (0.14,171 ha) in south west France. The positive relationship between species richness and wood patch area was investigated by testing the three hypotheses usually put forward to explain it: 1) the sampling effect hypothesis, 2) the patch heterogeneity hypothesis, 3) the hypothesis of equilibrium between distance from other patch (colonisation) and surface area of the patch (extinction). The syrphid species were divided into 3 ecological groups, based on larval biology as summarized in the "Syrph the Net" database: non forest species, facultative forest species and forest species. A total of 3317 adults belonging to 100 species, were captured in the 86 Malaise traps. Eight species were non forest (N=16), 65 facultative forest (N=2803) and 27 forest species (N=498). Comparison of the slopes of the species-area curves for species richness and species density per forest patch showed a strong sampling effect in the species-area relationship. Wood patch heterogeneity increased with wood patch area and positively influenced hoverflies richness. Less isolated wood patches presented high richness of forest species and low richness of non forest species. Only forest species richness seemed to respond to the equilibrium between surface area and isolation. Depending on which hypothesis explained best the species-area relationship, management recommendations to mitigate fragmentation effects were formulated at various spatial scales and for different stakeholders. [source] Habitat size and number in multi-habitat landscapes: a model approach based on species-area curvesECOGRAPHY, Issue 1 2002Even Tjřrve This paper discusses species diversity in simple multi-habitat environments. Its main purpose is to present simple mathematical and graphical models on how landscape patterns affect species numbers. The idea is to build models of species diversity in multi-habitat landscapes by combining species-area curves for different habitats. Predictions are made about how variables such as species richness and species overlap between habitats influence the proportion of the total landscape each habitat should constitute, and how many habitats it should be divided into in order to be able to sustain the maximal number of species. Habitat size and numbers are the only factors discussed here, not habitat spatial patterns. Among the predictions are: 1) where there are differences in species diversity between habitats, optimal landscape patterns contain larger proportions of species rich habitats. 2) Species overlap between habitats shifts the optimum further towards larger proportions of species rich habitat types. 3) Species overlap also shifts the optimum towards fewer habitat types. 4) Species diversity in landscapes with large species overlap is more resistant to changes in landscape (or reserve) size. This type of model approach can produce theories useful to nature and landscape management in general, and the design of nature reserves and national parks in particular. [source] Do plant communities exist?JOURNAL OF VEGETATION SCIENCE, Issue 5 2000Evidence from scaling-up local species-area relations to the regional level Abstract. One long tradition in ecology is that discrete communities exist, at least in the sense that there are areas of relatively uniform vegetation, with more rapid change in species composition between them. The alternative extreme view is the Self-similarity concept , that similar community variation occurs at all spatial scales. We test between these two by calculating species-area curves within areas of vegetation that are as uniform as can be found, and then extrapolating the within-community variation to much larger areas, that will contain many ,communities'. Using the Arrhenius species-area model, the extrapolations are remarkably close to the observed number of species at the regional/country level. We conclude that the type of heterogeneity that occurs within ,homogeneous' communities is sufficient to explain species richness at much larger scales. Therefore, whilst we can speak of ,communities' for convenience, the variation that certainly exists at the ,community' level can be seen as only a larger-scale manifestation of micro-habitat variation. [source] A unified mathematical framework for the measurement of richness and evenness within and among multiple communitiesOIKOS, Issue 2 2004Thomas D. Olszewski Biodiversity can be divided into two aspects: richness (the number of species or other taxa in a community or sample) and evenness (a measure of the distribution of relative abundances of different taxa in a community or sample). Sample richness is typically evaluated using rarefaction, which normalizes for sample size. Evenness is typically summarized in a single value. It is shown here that Hurlbert's probability of interspecific encounter (,1), a commonly used sample-size independent measure of evenness, equals the slope of the steepest part of the rising limb of a rarefaction curve. This means that rarefaction curves provide information on both aspects of diversity. In addition, regional diversity (gamma) can be broken down into the diversity within local communities (alpha) and differences in taxonomic composition among local communities (beta). Beta richness is expressed by the difference between the composite rarefaction curve of all samples in a region with the collector's curve for the same samples. The differences of the initial slopes of these two curves reflect the beta evenness thanks to the relationship between rarefaction and ,1. This relationship can be further extended to help interpret species-area curves (SAC's). As previous authors have described, rarefaction provides the null hypothesis of passive sampling for SAC's, which can be interpreted as regional collector's curves. This allows evaluation of richness and evenness at local and regional scales using a single family of well-established, mathematically related techniques. [source] | ||||||||||