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Rethinking edge effects: the unaccounted role of geometric constraints
Author(s) -
Prevedello Jayme A.,
Figueiredo Marcos S. L.,
Grelle Carlos E. V.,
Vieira Marcus V.
Publication year - 2013
Publication title -
ecography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.973
H-Index - 128
eISSN - 1600-0587
pISSN - 0906-7590
DOI - 10.1111/j.1600-0587.2012.07820.x
Subject(s) - abundance (ecology) , habitat , ecology , species richness , gee , enhanced data rates for gsm evolution , geography , biology , mathematics , statistics , generalized estimating equation , computer science , telecommunications
Edge effects strongly affect the abundance and distribution of organisms across landscapes, with wide‐ranging implications in ecology and conservation biology. The extensive literature on the subject has traditionally considered that edge effects result from the active avoidance or preference of organisms for certain portions of the habitat patch, assuming that abundance is uniform across a patch when environmental conditions are uniform. We demonstrate that this assumption is incorrect due to the so‐far ignored ‘geometric edge effect’ (GEE). In the absence of environmental gradients, abundance of any organism living in a bounded habitat patch will tend to be lower in areas located near the edges compared to areas in the centre of the patch, simply because the areas in the centre receive individuals from all directions, whereas areas near the edge do not receive individuals from outside the patch. This geometric effect was already known for species richness at large geographic scales, the mid‐domain effect, but its importance in the literature of edge effects remained neglected so far. Using simulations, we show that the GEE tends to reduce population abundance and community richness near the edges of bounded habitat patches, and that apparently neutral or negative responses to the edge may occur even when habitat quality is higher near the edges. A published study that detected significant edge effects is reanalyzed, demonstrating that interpreting observed abundance patterns without taking the GEE into account – as traditionally done in the vast literature on edge effects – could provide misleading conclusions. The incorporation of the GEE into sampling and analytical protocols of future studies could advance substantially our ability to understand and predict edge effects in heterogeneous landscapes.

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