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Methods in Comparative Plant Population Ecology, Second Edition$
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David J. Gibson

Print publication date: 2014

Print ISBN-13: 9780199671465

Published to Oxford Scholarship Online: January 2015

DOI: 10.1093/acprof:oso/9780199671465.001.0001

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Advanced statistical techniques: spatial patterns, life tables, modelling, and population viability analysis

Advanced statistical techniques: spatial patterns, life tables, modelling, and population viability analysis

Chapter:
(p.206) Chapter 8 Advanced statistical techniques: spatial patterns, life tables, modelling, and population viability analysis
Source:
Methods in Comparative Plant Population Ecology, Second Edition
Author(s):

David J. Gibson

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199671465.003.0008

This chapter moves forward from Chapter 7 (planning, choosing, and using statistics) and introduces some more advanced statistical methods that are of particular importance to plant population ecologists. The general goal of these methods is to quantify the spatiotemporal dynamics of plant populations. The basis for ecological modelling is described and advanced methods are described in four sections: first- and second-order spatial pattern analysis (including tessellation models); life table response experiments (LTREs), survivorship curves, and matrix models; cellular automata models, individual-based dynamic population models (e.g., SORTIE), and integral projection models (IPMs); and population viability analysis (PVA). Methods of spatial analysis are illustrated through use of a completely mapped plant dataset. Matrix models are illustrated through reanalysis of a published example. Recommended R packages for each method are provided.

Keywords:   Dirichlet polygons, integral projection models, IPMs, population viability analysis, PVA, life table response experiments, LTREs, matrix models, SORTIE, spatiotemporal dynamics, tessellation models

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