Dale, M. R. T. (1999): Spatial Pattern Analysis in Plant Ecology. In: Birks, H. J. B. & Wiens, J. A. (eds.): Cambridge Studies in Ecology, Cambridge University Press, Cambridge


Spatial Pattern Analysis in Plant Ecology
Mark R. T. Dale Professor of Biological Sciences at the University of Alberta, Edmonton Canada

The predictability of the physical arrangement of plants, at whatever scale it is viewed, is referred to as their spatial pattern. Spatial pattern is a crucial aspect of vegetation which has important implications not only for the plants themselves, but also for other organisms which interact with plants, such as herbivores and pollinators, or those animals for which plants provide a habitat. This book describes and evaluates methods for detecting and quantifying a variety of characteristics of spatial pattern. As well as discussing the concepts on which these techniques are based, examples from real field studies and worked examples are included, which, together with numerous line figures, help guide the reader through the text. The result is a book that will be of value to graduate students and research workers in the fields of vegetation science, conservation biology and applied ecology.


Spatial Pattern Analysis in Plant Ecology
Mark R. T. Dale Professor of Biological Sciences at the University of Alberta, Edmonton Canada

1. Concepts of spatial pattern
Pattern and process
Causes of spatial pattern and its development
Concepts of spatial pattern
Concluding remarks
2. Sampling
Sampling for pattern in a fixed frame of reference
Sampling for pattern relative to other plants
Location of sampling
Concluding remarks
3. Basic methods for one dimension and one species
Blocked quadrat variance
Local quadrat variances
Paired quadrat variances
New local variance
Combined analysis
Semivariogram and fractal dimension
Spectral analysis
Other methods
Concluding remarks
4. Spatial pattern of two species
At most one species per point
Several species per point
Blocked quadrat covariance (BQC)
Paired quadrat covariance (PQC) and conditional probability
Two- and three-term local quadrat covariance (TTLQC and 3TLQC)
Comparison of methods
Extensions of covariance analysis
Other approaches
Relative pattern: species association
Concluding remarks
5. Multispecies pattern
Multiscale ordination
Semivariogram and fractal dimension
Methods based on correspondence analysis
Euclidean distance
Spectral analysis
Other field results
Species associations
Concluding remarks
6. Two-dimensional analysis of spatial pattern
Blocked quadrat variance
Spatial autocorrelation and paired quadrat variance
Two-dimensional spectral analysis
Two-dimensional local quadrat variances
Four-term local quadrat variance
Random paired quadrat frequency
Paired quadrat covariance (PQC)
Four-term local quadrat covariance
Plant environment correlation
Landscape metrics
Other methods
Concluding remarks
7. Point patterns
Univariate point patterns
Bivariate point patterns
Multispecies point pattern and quantitative attributes
Concluding remarks
8. Pattern on an environmental gradient
Continuous presence/absence data
Quadrats: presence/absence data
Density data
Concluding remarks
9. Conclusions and future directions
Summary of recommendations
What next?
Three dimensions
Relation to spatial structure of physical factors
Obvious extensions
Temporal aspects of spatial pattern analysis
Questions and hypotheses
Concluding remarks
Glossary of abbreviations
List of plant species

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ER Archívum (1999/P-003)