Modelling mortality causes in longitudinal data in the presence of tag loss: application to raptor poisoning and electrocution.

Published online
15 Feb 2012
Content type
Journal article
Journal title
Journal of Applied Ecology

Tavecchia, G. & Adrover, J. & Muñoz Navarro, A. & Pradel, R.
Contact email(s)

Publication language
Balearic Islands & Spain


A first step for the effective management of vulnerable populations is to identify population threats and measure their relative impact on population fluctuations. The relative importance of proximate causes of mortality can be calculated from longitudinal data using capture-mark-recapture models. If marks are lost or cease to function, survival is underestimated. We provide an analytical framework based on conditional probabilities to obtain a robust estimate of the contribution of multiple sources of mortality while accounting for tag loss and imperfect detection. We applied this approach to radiotracking and wing tags-resighting data of red kites Milvus milvus to estimate the impact of illegal poisoning and the mortality by electrocution on power lines in the island of Mallorca (Spain). Illegal poisoning was responsible for 53% of the total mortality and electrocution on power lines for 12%. Results indicated that poisoning-related mortality was higher in immature birds, probably due to their more wide-ranging prospective behaviour. Assuming the two human-related mortalities are additive, the survival probability of kites would increase by 17% (from 0.76 to 0.91) if both threats were removed. Synthesis and applications. We present a new approach to estimate the contribution of different sources of mortality accounting for tag loss, state uncertainty and detection failures in wildlife populations. Our results will allow the demographic consequences of human-related mortality in threatened populations to be refined. The approach is suitable for the study of multiplicative latent processes in a vast range of applied conservation studies such as, for example, wildlife epidemiology.

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