Checking billy barr’s snow log…
John Harte,1* Adam B. Smith1 and Classic theory predicts species richness scales as the quarter-power of area, yet species– David Storch2,3 area relationships (SAR) vary widely depending on habitat, taxa, and scale range. Because 1 Energy and Resources Group, power-law SAR are used to predict species loss under habitat loss, and to scale species University of California at richness from plots to biomes, insight into the wide variety of observed SAR and the Berkeley, 310 Barrows Hall, conditions under which power-law behavior should be observed is needed. Here we Berkeley, CA 94720, USA 2 derive from the maximum entropy principle, a new procedure for upscaling species Center for Theoretical Study, richness data from small census plots to larger areas, and test empirically, using multiple Charles University & Academy of Sciences of the CR, Jilská 1, 110 data sets, the prediction that up to an overall scale displacement, nested SAR lie along a 00 Praha 1, Czech Republic universal curve, with average abundance per species at each scale determining the local 3 Department of Ecology, Faculty slope of the curve. Power-law behaviour only arises in the limit of increasing average of Science, Charles University, abundance, and in that limit, the slope approaches zero, not ¼. An extrapolation of tree Vinicná 7, 128 44 Praha 2, Czech species richness in the Western Ghats to biome scale (60 000 km2) using only census Republic data at plot scale (¼ ha) is presented to illustrate the potential for applications of our *Correspondence: theory. E-mail:jharte@berkeley.edu
Knowledge graph centered on Biodiversity scales from plots to biomes with a un with 16 nodes and 61 connections. Top connected: Maximum information entropy: a foundation for ecol, On theory in ecology, Bacteria, species diversity, J. Harte.
Items connected by shared entities, co-authorship, citations, or semantic similarity.
1 in Knowledge Commons, 27 external