A generalized approach to modeling and estimating indirect effects in ecology.

Abstract:

:The need to model and test hypotheses about complex ecological systems has led to a steady increase in use of path analytical techniques, which allow the modeling of multiple multivariate dependencies reflecting hypothesized causation and mechanisms. The aim is to achieve the estimation of direct, indirect, and total effects of one variable on another and to assess the adequacy of whole models. Path analytical techniques based on maximum likelihood currently used in ecology are rarely adequate for ecological data, which are often sparse, multi-level, and may contain nonlinear relationships as well as nonnormal response data such as counts or proportion data. Here I introduce a more flexible approach in the form of the joint application of hierarchical Bayes, Markov chain Monte Carlo algorithms, Shipley's d-sep test, and the potential outcomes framework to fit path models as well as to decompose and estimate effects. An example based on the direct and indirect interactions between ants, two insect herbivores, and a plant species demonstrates the implementation of these techniques, using freely available software.

journal_name

Ecology

journal_title

Ecology

authors

Clough Y

doi

10.1890/11-1899.1

subject

Has Abstract

pub_date

2012-08-01 00:00:00

pages

1809-15

issue

8

eissn

0012-9658

issn

1939-9170

journal_volume

93

pub_type

杂志文章

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