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Reproducibility of vegetation cover estimates in south‐central Alaska forests
Author(s) -
Helm D.J.,
Mead B.R.
Publication year - 2004
Publication title -
journal of vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 115
eISSN - 1654-1103
pISSN - 1100-9233
DOI - 10.1111/j.1654-1103.2004.tb02234.x
Subject(s) - reproducibility , variance (accounting) , quadrat , understory , vegetation (pathology) , statistics , environmental science , explained variation , ecology , physical geography , geography , mathematics , transect , canopy , biology , accounting , medicine , pathology , business
. Reproducibility of vegetation measurements is critical for large‐scale or long‐term studies, where numerous observers collect data, but past studies have questioned repro‐ducibility of some techniques. Five methods of evaluating understory composition were appraised for reproducibility among six observers in two forest types in south‐central Alaska: ocular estimates in quadrats, overall community species rank and cover estimates, nested rooted frequency, horizontal‐vertical profiles, and pin drop (systematic points). One forest type was selected to represent structure of coastal communities, another to represent structure of interior Alaska communities. Three general methods of evaluating reproducibility were considered: standard deviations (precision among observers), components of variance (percentage of total variance attributable to observers), and analysis of variance (significance of observer variance). Observer variances were generally similar among techniques and significant in most cases. No technique stood out as being more reproducible than others. Features of techniques other than reproducibility may be more important when selecting a technique. Management decisions based on vegetation cover data should consider the observer errors involved as well as biological significance.