Abstract
We analyze a new class of models of spatial distribution, developing mathematical properties and performing empirical tests. The models are based on a simple colonization rule operating on a rectangular grid. Two special cases within the class are traditional random placement and negative binomial models. Over three large data sets, these two cases are strongly outperformed by more flexible models within the class, in particular, models that allow more general patterns of aggregation. The models are simple and broadly applicable, with only one adjustable parameter, representing aggregation. Shortcomings of the colonization rule are studied, and extensions and applications of the models are discussed.
Original language | English (US) |
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Pages (from-to) | 269-284 |
Number of pages | 16 |
Journal | Ecological Monographs |
Volume | 77 |
Issue number | 2 |
DOIs | |
State | Published - May 2007 |
Keywords
- Aggregation
- Colonization
- Negative binomial
- Serpentine grassland
- Spatial distribution
- Tropical forest
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
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Appendix C. Derivation of Theorem 4.
Conlisk, E. (Creator), Bloxham, M. (Creator), Conlisk, J. (Creator), Enquist, B. (Creator) & Harte, J. (Creator), figshare, 2016
DOI: 10.6084/m9.figshare.3565815, https://wiley.figshare.com/articles/dataset/Appendix_C_Derivation_of_Theorem_4_/3565815
Dataset
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A NEW CLASS OF MODELS OF SPATIAL DISTRIBUTION
Conlisk, E. (Creator), Bloxham, M. (Creator), Conlisk, J. (Creator), Enquist, B. (Creator) & Harte, J. (Creator), figshare, 2016
DOI: 10.6084/m9.figshare.c.3309285.v1, https://figshare.com/collections/A_NEW_CLASS_OF_MODELS_OF_SPATIAL_DISTRIBUTION/3309285/1
Dataset
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Appendix E. Division-specific estimate of aggregation parameter.
Conlisk, E. (Creator), Bloxham, M. (Creator), Conlisk, J. (Creator), Enquist, B. (Creator) & Harte, J. (Creator), Wiley, 2016
DOI: 10.6084/m9.figshare.3565809.v1, https://wiley.figshare.com/articles/dataset/Appendix_E_Division-specific_estimate_of_aggregation_parameter_/3565809/1
Dataset