Ecological information from spatial patterns of plants: insights from point process theory

Law, R., Illian, J. , Burslem, D. F.R.P., Gratzer, G., Gunatilleke, C.V.S. and Gunatilleke, I.A.U.N. (2009) Ecological information from spatial patterns of plants: insights from point process theory. Journal of Ecology, 97(4), pp. 616-628. (doi:10.1111/j.1365-2745.2009.01510.x)

Full text not currently available from Enlighten.

Abstract

Summary: 1. This article reviews the application of some summary statistics from current theory of spatial point processes for extracting information from spatial patterns of plants. Theoretical measures and issues connected with their estimation are described. Results are illustrated in the context of specific ecological questions about spatial patterns of trees in two forests. 2. The pair correlation function, related to Ripley's K function, provides a formal measure of the density of neighbouring plants and makes precise the general notion of a ‘plant's‐eye’ view of a community. The pair correlation function can also be used to describe spatial relationships of neighbouring plants with different qualitative properties, such as species identity and size class. 3. The mark correlation function can be used to describe the spatial relationships of quantitative measures (e.g. biomass). We discuss two types of correlation function for quantitative marks. Applying these functions to the distribution of biomass in a temperate forest, it is shown that the spatial pattern of biomass is uncoupled from the spatial pattern of plant locations. 4. The inhomogeneous pair correlation function enables first‐order heterogeneity in the environment to be removed from second‐order spatial statistics. We illustrate this for a tree species in a forest of high topographic heterogeneity and show that spatial aggregation remains after allowing for spatial variation in density. An alternative method, the master function, takes a weighted average of homogeneous pair correlation functions computed in subareas; when applied to the same data and compared with the former method, the spatial aggregations are smaller in size. 5. Synthesis. These spatial statistics, especially those derived from pair densities, will help ecologists to extract important ecological information from intricate spatially correlated plants in populations and communities.

Item Type:Articles
Additional Information:This work was developed in a working group ‘Spatial analysis of tropical forestbiodiversity’ funded by the Natural Environment Research Council andEnglish Nature through the NERC Centre for Population Biology and UKPopulation Biology Network. We thank the participants and Drew Purves forsharing their ideas; discussions with Antti Penttinen greatly helped our under-standing of technical matters. The Rothwald data was recorded as part ofproject P14583, funded by the Austrian Science Fund (FWF). Establishment ofthe Sinharaja plot was funded by The John D. and Catherine T. MacArthurFoundation, the Smithsonian Tropical Research Institute, the U.S. NationalScience Foundation, Arnold Arboretum of Harvard University and theNational Institute for Environmental Studies of Japan.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Illian, Professor Janine
Authors: Law, R., Illian, J., Burslem, D. F.R.P., Gratzer, G., Gunatilleke, C.V.S., and Gunatilleke, I.A.U.N.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Journal of Ecology
Publisher:Wiley for the British Ecological Society
ISSN:0022-0477
ISSN (Online):1365-2745

University Staff: Request a correction | Enlighten Editors: Update this record