Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A functional classification for predicting the dynamics of landscapes

A functional classification for predicting the dynamics of landscapes Abstract. Functional classifications have been derived for various purposes using subjective, objective and deductive approaches. Most of the classifications were derived to describe a static state of a region or landscape rather than to predict the dynamics of the system. Here, we suggest a simple, but comprehensive functional classification based on life history parameters that can predict the dynamics of plant communities subject to recurrent disturbances. The predicted dynamics are described in terms of survival and local extinction of the functional groups. The groups derived from the classification are probably largely independent of functional groupings that may be derived for other aspects of community composition (e.g. structure, phenology) and community interactions (roughness, albedo etc.). We emphasize that functional classification is context‐dependent and we should not expect to find a useful, universal classification into functional groups. Software has been developed to help classify the species into functional groups, to derive successional sequences and to predict community composition under different disturbance regimes both in point and landscape models. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Vegetation Science Wiley

A functional classification for predicting the dynamics of landscapes

Download PDF
8 pages

Loading next page...
 
/lp/wiley/a-functional-classification-for-predicting-the-dynamics-of-landscapes-xG0jme4YLP

References (18)

Publisher
Wiley
Copyright
1996 IAVS ‐ the International Association of Vegetation Science
ISSN
1100-9233
eISSN
1654-1103
DOI
10.2307/3236276
Publisher site
See Article on Publisher Site

Abstract

Abstract. Functional classifications have been derived for various purposes using subjective, objective and deductive approaches. Most of the classifications were derived to describe a static state of a region or landscape rather than to predict the dynamics of the system. Here, we suggest a simple, but comprehensive functional classification based on life history parameters that can predict the dynamics of plant communities subject to recurrent disturbances. The predicted dynamics are described in terms of survival and local extinction of the functional groups. The groups derived from the classification are probably largely independent of functional groupings that may be derived for other aspects of community composition (e.g. structure, phenology) and community interactions (roughness, albedo etc.). We emphasize that functional classification is context‐dependent and we should not expect to find a useful, universal classification into functional groups. Software has been developed to help classify the species into functional groups, to derive successional sequences and to predict community composition under different disturbance regimes both in point and landscape models.

Journal

Journal of Vegetation Science – Wiley

Published: Jun 1, 1996

There are no references for this article.