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Designing Environmental Field Studies
Author(s) -
Eberhardt L. L.,
Thomas J. M.
Publication year - 1991
Publication title -
ecological monographs
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.254
H-Index - 156
eISSN - 1557-7015
pISSN - 0012-9615
DOI - 10.2307/1942999
Subject(s) - sampling (signal processing) , sampling design , ecology , population , sample size determination , computer science , field (mathematics) , statistics , sample (material) , econometrics , data mining , mathematics , biology , chemistry , demography , filter (signal processing) , chromatography , sociology , pure mathematics , computer vision
Field experiments in ecological and environmental research usually do not meet the criteria for modern experimental design. Subsampling is often mistakenly substituted for true replication, and sample sizes are too small for adequate power in tests of significance. In many cases, field—study objectives may be better served by various kinds of sampling procedures, even though the resulting inferences will be weaker than those obtainable through controlled experimentation. The present paper provides a classification and description of methods for designing environmental studies, with emphasis on techniques as yet little used in ecology. Eight categories of techniques for field studies are defined in terms of the nature of control exerted by the observer, by the presence or absence of a perturbation, and by the domain of study. The first two categories include classical experimental approaches, replicated and unreplicated. Sampling for modelling provides efficient designs for estimating parameters in a specified model. Intervention analysis measures the effect of a known perturbation in a time series. Observational studies contrast selected groups from a population, while analytical sampling provides comparisons over the entire population. Descriptive survey sampling estimates means or totals over an entire population, while sampling for pattern deals with spatial patterns over a selected region. We propose that the statistical concept of a "superpopulation" may be useful in ecology, and that it may be desirable to approach community and ecosystem studies in a sampling framework, with experimentation used for a fairly narrow range of subsidiary investigations. Much more attention to processes for drawing inferences about cause and effect is needed, in any case.