A causal modelling approach to spatial and temporal confounding in environmental impact studies

Authors

  • Warren L Paul

    Corresponding author
    1. Department of Environmental Management and Ecology, La Trobe University, Albury-Wodonga, Victoria 3689, Australia
    • Department of Environmental Management and Ecology, La Trobe University, Albury-Wodonga Campus, PO Box 821, Wodonga, Victoria 3689, Australia.
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  • This article is published in Environmetrics as a special issue on Quantitative approaches to ecosystem service evaluation, edited by R. I. Smith, Centre for Ecology and Hydrology, UK; E. M. Scott, School of Mathematics and Statistics, University of Glasgow, UK; J. McP Dick, Centre for Ecology and Hydrology, UK.

Abstract

Deciding whether an anthropogenic disturbance has caused a change in an ecosystem is problematic because of spatial and temporal confounding. The generally accepted approach to this problem has been to use a before-after control-impact (BACI) type of design. However, advances in graph theory and causal modelling now provide a formal basis for selecting the covariates that need to be observed in order to control confounding bias, and the solution provided by these advances is simpler than that provided by any of the BACI-type designs including BACI itself as well as BACIP, Beyond-BACI and MBACI designs. Based on an explicit description of the nature of spatial and temporal confounding in causal models for two hypothetical environmental impact studies, it is argued that confounding can be controlled by adjusting directly for spatial or temporal location in a before-after (BA) or control-impact (CI) study. It is further argued that there is no advantage in combining these designs in a BACI-type study, either from a causal modelling perspective or from the perspective of the assumptions implicit in BACI-type designs. Copyright © 2011 John Wiley & Sons, Ltd.

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