Diversity anomalies and spatial climate heterogeneity. Issue 9 (7th May 2014)

• Record Type: Journal Article
• Authors: Jiménez, Iván; Ricklefs, Robert E.
• Is Part Of: Global ecology & biogeography. Volume 23:Issue 9(2014:Sep.)
• Page Start: 988
• Page End: 999
• Publication Date: 2014-05-07
• Subjects: Ecology -- Periodicals; Biogeography -- Periodicals; Biodiversity -- Periodicals; Macroevolution -- Periodicals; 577
• DOI: 10.1111/geb.12181
• Languages: English
• ISSNs: 1466-822X

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <sec id="geb12181-sec-0001" sec-type="section"> <title>Aim</title> <p>Diversity anomalies are differences in species richness between areas that belong to different regions but have similar environments. Some hypotheses addressing the origin of well‐known anomalies in plant diversity propose that regions with higher environmental spatial heterogeneity have higher diversity because heterogeneity fosters diversification or coexistence. Arguments supporting these hypotheses emphasize inter‐regional comparisons of diversity and assume that spatial environmental heterogeneity is higher in: (1) eastern Asia (EA) than in eastern North America (ENA), (2) western North America (WNA) than in ENA, and (3) the Cape Floristic Region in southern Africa (CFR) than in the Southwest Australian Floristic Region (SWA). Here, we evaluate these assumptions by measuring two kinds of environmental heterogeneity – spatially implicit and explicit – each thought to affect diversity via different mechanisms. The former refers to environmental variation among sites within a region, regardless of site location. The latter refers to the spatial pattern of environmental variation across a region (e.g., monotonic or undulating).</p> </sec> <sec id="geb12181-sec-0002" sec-type="section"> <title>Location</title> <p>EA, ENA, WNA, CFR and SWA.</p> </sec> <sec id="geb12181-sec-0003" sec-type="section"> <title>Methods</title> <p>Multivariate and univariate analyses of spatially implicit and explicit heterogeneity in 17 climatic variables describing central tendency, variation and extremes of temperature and precipitation.</p> </sec> <sec id="geb12181-sec-0004" sec-type="section"> <title>Results</title> <p>Multivariate (spatially implicit and explicit) climate heterogeneity is higher in: (1) EA than in ENA, (2) WNA than in ENA, and (3) CFR than in SWA. However, univariate analysis revealed that the regions thought to be most homogeneous (ENA and SWA) were actually most heterogeneous in three or four climatic variables, including precipitation during the driest (ENA) or wettest (SWA) seasons.</p> </sec> <sec id="geb12181-sec-0005" sec-type="section"> <title>Main conclusions</title> <p>The overall inter‐regional pattern of spatially implicit and explicit heterogeneity in climate supports the three assumptions listed in the Aim. However, particular climate variables deviate from this overall pattern, implying that hypotheses linking diversity to regional heterogeneity can yield more precise predictions, and thus can be more stringently tested, than previously recognized.</p> </sec> </abstract>