Literature DB >> 27759285

Incomplete Data Sets in Community Ecology and Biogeography: A Cautionary Tale.

Astrid Kodric-Brown, James H Brown.   

Abstract

Many basic and applied studies in ecology, biogeography, and conservation biology rely on data on the distribution of species and the composition of communities that are compiled from the literature or from unpublished sources. Most of these data sets are incomplete, and some contain serious biases. We examine two such data sets. New records of fishes in Australian desert springs, which corrected sampling biases in the original study, revealed different patterns of species distribution and community structure. New records of mammals on Great Basin mountaintops did not materially alter the results and interpretations of earlier studies. In order to avoid serious errors of fact, interpretation, and application, there is no substitute for first-hand field experience with the organisms and habitats. © 1993 by the Ecological Society of America.

Entities:  

Keywords:  biogeography; community ecology; community structure; incomplete data; missing data

Year:  1993        PMID: 27759285     DOI: 10.2307/1942104

Source DB:  PubMed          Journal:  Ecol Appl        ISSN: 1051-0761            Impact factor:   4.657


  4 in total

1.  When are historical data sufficient for making watershed-level stream fish management and conservation decisions?

Authors:  Katherine L Smith; Michael L Jones
Journal:  Environ Monit Assess       Date:  2007-03-21       Impact factor: 2.513

Review 2.  Modeling animal habitats based on cover types: a critical review.

Authors:  Scott Schlossberg; David I King
Journal:  Environ Manage       Date:  2008-06-17       Impact factor: 3.266

3.  Optimized grid representation of plant species richness in India-Utility of an existing national database in integrated ecological analysis.

Authors:  Poonam Tripathi; Mukund Dev Behera; Partha Sarathi Roy
Journal:  PLoS One       Date:  2017-03-15       Impact factor: 3.240

4.  Detection error influences both temporal seroprevalence predictions and risk factors associations in wildlife disease models.

Authors:  Michael A Tabak; Kerri Pedersen; Ryan S Miller
Journal:  Ecol Evol       Date:  2019-08-27       Impact factor: 2.912

  4 in total

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