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Designing observational biologging studies to assess the causal effect of instrumentation


Authier, M and Peron, C and Mante, A and Vidal, P and Gremillet, D, Designing observational biologging studies to assess the causal effect of instrumentation, Methods in Ecology and Evolution, 4, (9) pp. 802-810. ISSN 2041-210X (2013) [Refereed Article]

Copyright Statement

Copyright 2013 The Authors. Methods in Ecology and Evolution Copyright 2013 British Ecological Society

DOI: doi:10.1111/2041-210X.12075


1. Biologging has improved ecological knowledge on an increasing number of species for more than 2 decades. Most studies looking at the incidence of tags on behavioural, physiological or demographic parameters rely on Ďcontrolí individuals chosen randomly within the population, assuming that they will be comparable with equipped individuals. This assumption is usually untestable and untenable since biologging studies are more observational than experimental, and often involve small sample sizes. Notably, background characteristics of wild animals are, most of the time, unknown. Consequently, investigating any causal effect of instrumentation is a difficult task, subjected to hidden biases.
2. We describe the counterfactual model to causal inference which was implicit in early biologging studies. We adopted methods developed in social and political sciences to construct a posteriori an appropriate control group. Using biologging data collected on Scopoliís shearwaters (Calonectris diomedea) from a small Mediterranean island, we used this method to achieve objective causal inference on the effect of instrumentation on breeding performance and divorce.
3. Our method revealed that the sample of instrumented birds was nonrandom. After identification of a relevant control group, we found no carry-over effects of instrumentation on breeding performance (taking into account imperfect detection probability) or divorce rate in Scopoliís shearwaters.
4. Randomly chosen control groups can be both counterproductive and ethically dubious via unnecessary additional disturbance of populations. The counterfactual approach, which can correct for selection bias, has wide applicability to biologging within long-term studies.

Item Details

Item Type:Refereed Article
Research Division:Biological Sciences
Research Group:Ecology
Research Field:Marine and estuarine ecology (incl. marine ichthyology)
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the biological sciences
UTAS Author:Peron, C (Dr Clara Peron)
ID Code:92457
Year Published:2013
Web of Science® Times Cited:15
Deposited By:Sustainable Marine Research Collaboration
Deposited On:2014-06-18
Last Modified:2014-07-10

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