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Considerations for Evaluating Controlled Exposure Studies of Tree Seedlings
Author(s) -
Peterson Charles E.,
Mickler Robert A.
Publication year - 1994
Publication title -
journal of environmental quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 171
eISSN - 1537-2537
pISSN - 0047-2425
DOI - 10.2134/jeq1994.00472425002300020006x
Subject(s) - seedling , environmental science , statistics , comparability , pollutant , tree (set theory) , inference , range (aeronautics) , replication (statistics) , econometrics , toxicology , computer science , mathematics , ecology , biology , agronomy , artificial intelligence , mathematical analysis , combinatorics , materials science , composite material
Tree seedling exposure studies, covering a wide range of experimental conditions in pollutant treatments, species, facilities, and exposure regimes, have been conducted during the past several years to determine acute effects and relative sensitivity of tree species in response to simulated acid precipitation and gaseous pollutants. Because of the difficulties inherent in conducting controlled exposures with mature trees (e.g., size, variability among experimental units, and costs associated with replication of treatments), seedling exposure studies have been initiated as the quickest way to address these issues. However, sufficient consideration has not been given to either the comparability of seedling studies or to their appropriate inference. The statistical power of any given analysis is rarely discussed when the outcomes are published. Appropriate and documented statistics of experimenter bias are often not reported, and variability in the exposure regime (i.e., treatment target levels) and the measurement of experimental variables is assumed to be zero, rather than quantified. Finally, the populations of seedlings for which seedling experiments have inference, the extent to which seedling responses are applicable to mature trees and forest condition, and the limitations in national or regional generalizations are crucial issues often left to an individual reader's interpretation without the benefit of adequate quantitative information presented by the authors.