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Approximating Nature's Variation: Selecting and Using Reference Information in Restoration Ecology
Author(s) -
White Peter S.,
Walker Joan L.
Publication year - 1997
Publication title -
restoration ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.214
H-Index - 100
eISSN - 1526-100X
pISSN - 1061-2971
DOI - 10.1046/j.1526-100x.1997.00547.x
Subject(s) - variation (astronomy) , restoration ecology , temporal scales , selection (genetic algorithm) , scale (ratio) , ecology , spatial analysis , spatial variability , computer science , spatial ecology , task (project management) , environmental resource management , geography , environmental science , artificial intelligence , cartography , statistics , remote sensing , mathematics , biology , physics , management , astrophysics , economics
Restoration ecologists use reference information to define restoration goals, determine the restoration potential of sites, and evaluate the success of restoration efforts. Basic to the selection and use of reference information is the need to understand temporal and spatial variation in nature. This is a challenging task: variation is likely to be scale dependent; ecosystems vary in complex ways at several spatial and temporal scales; and there is an important interaction between spatial and temporal variation. The two most common forms of reference information are historical data from the site to be restored and contemporary data from reference sites (sites chosen as good analogs of the site to be restored). Among the problems of historical data are unmeasured factors that confound the interpretation of historical changes observed. Among the problems of individual reference sites is the difficulty of finding or proving a close match in all relevant ecological dimensions. Approximating and understanding ecological variation will require multiple sources of information. Restoration, by its inherently experimental nature, can further the understanding of the distribution, causes, and functions of nature's variation.