Spatial species-richness gradients across scales: a meta-analysis

$48.00 plus tax (Refund Policy)

Download / Buy Article:

Abstract:

Abstract Aim 

We surveyed the empirical literature to determine how well six diversity hypotheses account for spatial patterns in species richness across varying scales of grain and extent. Location 

Worldwide. Methods 

We identified 393 analyses (‘cases’) in 297 publications meeting our criteria. These criteria included the requirement that more than one diversity hypothesis was tested for its relationship with species richness. We grouped variables representing the hypotheses into the following ‘correlate types’: climate/productivity, environmental heterogeneity, edaphics/nutrients, area, biotic interactions and dispersal/history (colonization limitation or other historical or evolutionary effect). For each case we determined the ‘primary’ variable: the one most strongly correlated with taxon richness. We defined ‘primacy’ as the proportion of cases in which each correlate type was represented by the primary variable, relative to the number of times it was studied. We tested for differences in both primacy and mean coefficient of determination of the primary variable between the hypotheses and between categories of five grouping variables: grain, extent, taxon (animal vs. plant), habitat medium (land vs. water) and insularity (insular vs. connected). Results 

Climate/productivity had the highest overall primacy, and environmental heterogeneity and dispersal/history had the lowest. Primacy of climate/productivity was much higher in large-grain and large-extent studies than at smaller scales. It was also higher on land than in water, and much higher in connected systems than in insular ones. For other hypotheses, differences were less pronounced. Throughout, studies on plants and animals showed similar patterns. Coefficients of determination of the primary variables differed little between hypotheses and across the grouping variables, the strongest effects being low means in the smallest grain class and for edaphics/nutrients variables, and a higher mean for water than for land in connected systems but vice versa in insular systems. We highlight areas of data deficiency. Main conclusions 

Our results support the notion that climate and productivity play an important role in determining species richness at large scales, particularly for non-insular, terrestrial habitats. At smaller extents and grain sizes, the primacy of the different types of correlates appears to differ little from null expectation. In our analysis, dispersal/history is rarely the best correlate of species richness, but this may reflect the difficulty of incorporating historical factors into regression models, and the collinearity between past and current climates. Our findings are consistent with the view that climate determines the capacity for species richness. However, its influence is less evident at smaller spatial scales, probably because (1) studies small in extent tend to sample little climatic range, and (2) at large grains some other influences on richness tend to vary mainly within the sampling unit.

Keywords: Area; climatic gradient; dispersal; diversity gradient; extent; grain; history; islands; latitudinal gradient; productivity

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1365-2699.2008.01963.x

Affiliations: 1: Department of Ecology and Evolutionary Biology, University of California, Irvine, CA, USA 2: Department of Environmental Science and Policy, University of California, Davis, CA, USA 3: Department of Biology, University of Ottawa, Ottawa, ON, Canada 4: Departamento de Biologia Geral, ICB, Universidade Federal de Goiás, Goiânia, GO, Brazil 5: Centre d’Etude sur le Polymorphisme des Micro-Organismes, CEPM/UMR CNRS-IRD 9926, Equipe: “Evolution des Systemes Symbiotiques”, IRD, Montpellier Cedex, France 6: Joint Science Department, Claremont Colleges, Claremont, CA, USA 7: Kellogg Biological Station and Department of Zoology, Michigan State University, Hickory Corners, MI, USA 8: Institut de Recherche pour le Développement (IRD), Laboratoire d’Ichtyologie, Muséum National d’Histoire Naturelle, Paris, France 9: Faculty of Biological Sciences, University of Leeds, Leeds, UK

Publication date: January 1, 2009

Tools

Favourites

Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more