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ELEVATIONAL SPECIES RICHNESS PATTERNS EMERGE FROM MULTIPLE LOCAL MECHANISMS IN HIMALAYAN WOODY PLANTS
Author(s) -
Oommen Meera Anna,
Shanker Kartik
Publication year - 2005
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1890/04-1837
Subject(s) - species richness , ecotone , ecology , macroecology , spatial ecology , abundance (ecology) , body size and species richness , temperate climate , species distribution , species diversity , geography , biology , habitat
We compared woody plant species distributions across nested spatial scales (local scale to entire Western Himalaya) and explored landscape scale patterns in detail to obtain inferences about the elevational gradient in species richness. Distribution data were compiled for 1100 species in the Western Himalaya, and primary data, comprising 123 species and 47 000 individuals, were collected for a landscape. Correlates of diversity were examined for the five spatial scales, and for different biogeographic groups at the landscape scale. The results indicate multiple mechanisms both within and across scales. At the landscape scale, though the mechanisms explaining unimodal species richness patterns were hard to separate, the underlying correlates of biogeographic groups were more distinct; temperate species richness followed mid‐domain model predictions, and showed a nonlinear relationship with temperature, whereas tropical species richness tracked temperature and area. Simulations demonstrated that models with varying assumptions, while resulting in monotonic, unimodal, or multimodal patterns at local scales, could all lead to unimodal patterns at regional scales when multiple local replicates are aggregated, with a peak in the major ecotone. The turnover or successive accumulation of marginal species in ecotones potentially explains the mid‐elevational peak in this zone. Landscape scale primary data on distribution and abundance could therefore be critical to understanding key aspects of macroecological patterns.

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