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Providing insights into browntail moth local outbreaks by combining life table data and semi-parametric statistics

Authors


Enric Frago, Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, U.K. E-mail: enric.frago@zoo.ox.ac.uk

Abstract

1. Life table studies have been an essential tool for the comprehension of insect population dynamics, although their use has been methodologically biased by a primary focus on mortality factors, especially natural enemies. Thus, studies in natural populations may relegate important mortality sources to the ‘unknown’ or ‘residual’ mortality categories. To overcome this limitation, life tables may be complemented by combining them with other approaches.

2. The aim of the present study was to provide insights into browntail moth Euproctis chrysorrhoea L. (Lepidoptera: Lymantriidae) local outbreaks by combining life table data and statistical modelling. First, E. chrysorrhoea population density, mortality dynamics, net reproductive rate, and reproductive potential were compared in two different Mediterranean habitats (i.e. coastal and inland). Second, we investigated the relationship of reproductive potential as well as residual mortality (i.e. not associated to any specific mortality agent) with several variables likely to play an important role in E. chrysorrhoea population dynamics. As an innovative approach, the relationship was modelled by means of generalised additive modelling (GAM models) in a multi-model inference framework.

3. The present results on E. chrysorrhoea density and life table analyses suggest that local outbreaks are more likely in coastal habitats where higher mortality was compensated by higher reproductive potential. GAMs turned out to be an effective way to gain a deep understanding of this pattern. Residual mortality was positively and non-linearly related to population density, whereas reproductive potential was not significantly related to any of the variables studied.

4. The present study was an attempt to gain a deep understanding of the information derived from descriptive life tables.

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