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Animal Dispersal Patterns: A Reassessment of Simple Mathematical Models
Author(s) -
Porter John H.,
Dooley James L.
Publication year - 1993
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.2307/1939594
Subject(s) - sampling (signal processing) , simple (philosophy) , biological dispersal , simple random sample , monte carlo method , mathematical model , field (mathematics) , statistics , statistical physics , computer science , mathematics , ecology , biology , physics , population , philosophy , demography , epistemology , filter (signal processing) , sociology , pure mathematics , computer vision
Attempts to fit simple mathematical models of animal movement to observed distributions of movements have been extremely successful. However, the extent to which these results were influenced by use of potentially distance—weighted sampling methods has not been evaluated. Of the 15 field studies used to test model fits, 13 used methods that sample unevenly over distance. We use a simple Monte—Carlo simulation model to evaluate the effects of unequal sampling over distance on results obtained from simple mathematical models of animal movement. For three data sets that provide detailed maps of observation sites, the effects of unequal sampling are profound. Prior to sampling, data simulated by our model follow a uniform distribution, but a geometric model adequately fits the "sampled" simulated data. Following corrections to the field data to mitigate the effects of distance—weighted sampling, in only one of five studies do simple mathematical models adequately fit the observed distribution of movements.