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Coexistence of Competitors in Patchy Environment
Author(s) -
Hanski Ilkka
Publication year - 1983
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.2307/1939969
Subject(s) - competition (biology) , ecology , competitor analysis , habitat , population , distribution (mathematics) , scale (ratio) , biology , geography , economics , demography , mathematics , mathematical analysis , management , cartography , sociology
There are two implicit assumptions in Levins' (1969) metaphorical model of regional distribution: movements by individuals are possible between any two patches in the region, and the local time scale is much faster than the regional one. These assumptions are frequently incompatible. Levins' model is modified to allow for a varying difference between the local and regional time scales, and regional competition between two species is analyzed with the new model. The main results are that two like species may or may not coexist regionally, depending on the differences between the time scales (a large difference facilitates coexistence) and on the intensity of competition; a species' precompetitive distribution is a good predictor of its competitive success, just as the carrying capacity in the Lotka—Volterra model is a good predictor of success in local competition. Regional priority effect is possible, though unlikely when the time scales are very different. The local time scale is slower than the regional one in some organism (e.g., orchids, ferns), which may survive regionally, although they may succeed in breeding only seldom. Two possible outcomes of regional competition are (1) a decrease in the fraction of habitat patches occupied by the competing species and (2) an increase in the proportion of regionally rare species, some of which may ultimately go extinct. I ask which of the two outcomes is more frequent in nature and suggest that the answer may depend on the time scales of local and regional population dynamics.