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Article << Previous     |     Next >>   Contents Vol 37(4)

Measuring female aggregation in ungulate mating-system research: a red deer case study

Javier Pérez-González A D, Juan Carranza A B, Vicente Polo C

A Biology and Ethology, University of Extremadura, 10071 Cáceres, Spain.
B Present address: Ungulate Research Unit, CRCP, University of Córdoba, 14071 Córdoba, Spain.
C Departamento de Biología y Geología, Escuela Superior de Ciencias Experimentales y Tecnología, Universidad Rey Juan Carlos, 28933 Móstoles, Madrid, Spain.
D Corresponding author. Email: jpergon@unex.es
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Context. Mating systems are of central importance to the operation of sexual selection, with consequences for evolution and for the maintenance of genetic diversity. Female aggregation is one of the most important elements of mating systems because female distribution can influence the degree of polygyny. Measuring female aggregation requires finding the scale for the distribution pattern. Several spatial methods can be used to determine the scale of a point pattern; however, only one of them has been applied to mating-system research.

Aims. Here, we assess three different spatial methods to determine the best one in finding the scale of female distribution for female-aggregation measures in a mating-system context.

Methods. We describe and compare the spatial methods by applying them to 30 Iberian red deer (Cervus elaphus hispanicus) populations. We use spatial analyses for point patterns.

Key results. Ripley’s K analysis was found to be the best method for determining the scale of female distribution and for quantifying female-aggregation parameters in our populations.

Conclusions. Ripley’s K analysis, a distance method based on circles centred in individuals and that is widely used in ecological studies, allows the estimation of female aggregation and, hence, it can be used to measure sexual selection.

Implications. This work describes the use of a distance method that can be applied to mating-system research (at least for ungulate populations) to obtain models with behavioural and evolutionary implications.

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