How to estimate variability in affinity relationships in partially observed groups of domestic herbivores?

Animal sociability measurements based on inter-individual distances or nearest-neighbour distributions can be obtained automatically with telemetry collars. So far, all the indices that have been used require the whole group to be observed. Here, we propose an index of the variability in affinity re...

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Main Authors: L. Della-Rossa, B. Dumont, J. Chadœuf
Format: Article
Language:English
Published: Elsevier 2014-01-01
Series:Animal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S175173111400024X
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spelling doaj-f4f73b85e476461a904bc8baf971c8882021-06-06T04:49:36ZengElsevierAnimal1751-73112014-01-0185817826How to estimate variability in affinity relationships in partially observed groups of domestic herbivores?L. Della-Rossa0B. Dumont1J. Chadœuf2Institut national de la recherche agronomique, UMR1213 Herbivores, Theix, 63122 Saint-Genès-Champanelle, FranceInstitut national de la recherche agronomique, UMR1213 Herbivores, Theix, 63122 Saint-Genès-Champanelle, FranceINRA, Statistics, UR 1052, Domaine St Maurice, 67 Allée des Chênes, CS 60094, 84143 Montfavet Cedex, FranceAnimal sociability measurements based on inter-individual distances or nearest-neighbour distributions can be obtained automatically with telemetry collars. So far, all the indices that have been used require the whole group to be observed. Here, we propose an index of the variability in affinity relationships in groups of domestic herbivores, whose definition does not depend on group size and that can be used even if some data are missing. This index and its estimators are based on a function that measures how frequently an animal is closer than another one from a third animal. When no data are missing, we show that our estimator and the variance of the sociability matrixsensu Sibbald (considered as the reference method) are strongly correlated. We then consider two cases of missing data. In the first case, some animals are randomly missing, that is, to account for random breakdown of telemetry collars. Our estimator is unbiased by such missing data and its variance decreases as the number of observation dates increases. In the second case, the same animals are missing at all observation dates, that is, in large herds where there are more individuals to be observed than available telemetry collars. Our estimator of affinity variance within a group is biased by such missing data. Thus, it requires changing animals equipped with telemetry collars regularly during the experiment. Conversely, the estimator remains unbiased at the population level, that is, if several independent groups are being analysed. We finally illustrate how this estimator can be used by investigating changes in the variability of affinities according to group size in grazing heifers.http://www.sciencedirect.com/science/article/pii/S175173111400024Xcattleglobal positioning systemgrazingmissing datasimulationsocial behaviour
collection DOAJ
language English
format Article
sources DOAJ
author L. Della-Rossa
B. Dumont
J. Chadœuf
spellingShingle L. Della-Rossa
B. Dumont
J. Chadœuf
How to estimate variability in affinity relationships in partially observed groups of domestic herbivores?
Animal
cattle
global positioning system
grazing
missing data
simulation
social behaviour
author_facet L. Della-Rossa
B. Dumont
J. Chadœuf
author_sort L. Della-Rossa
title How to estimate variability in affinity relationships in partially observed groups of domestic herbivores?
title_short How to estimate variability in affinity relationships in partially observed groups of domestic herbivores?
title_full How to estimate variability in affinity relationships in partially observed groups of domestic herbivores?
title_fullStr How to estimate variability in affinity relationships in partially observed groups of domestic herbivores?
title_full_unstemmed How to estimate variability in affinity relationships in partially observed groups of domestic herbivores?
title_sort how to estimate variability in affinity relationships in partially observed groups of domestic herbivores?
publisher Elsevier
series Animal
issn 1751-7311
publishDate 2014-01-01
description Animal sociability measurements based on inter-individual distances or nearest-neighbour distributions can be obtained automatically with telemetry collars. So far, all the indices that have been used require the whole group to be observed. Here, we propose an index of the variability in affinity relationships in groups of domestic herbivores, whose definition does not depend on group size and that can be used even if some data are missing. This index and its estimators are based on a function that measures how frequently an animal is closer than another one from a third animal. When no data are missing, we show that our estimator and the variance of the sociability matrixsensu Sibbald (considered as the reference method) are strongly correlated. We then consider two cases of missing data. In the first case, some animals are randomly missing, that is, to account for random breakdown of telemetry collars. Our estimator is unbiased by such missing data and its variance decreases as the number of observation dates increases. In the second case, the same animals are missing at all observation dates, that is, in large herds where there are more individuals to be observed than available telemetry collars. Our estimator of affinity variance within a group is biased by such missing data. Thus, it requires changing animals equipped with telemetry collars regularly during the experiment. Conversely, the estimator remains unbiased at the population level, that is, if several independent groups are being analysed. We finally illustrate how this estimator can be used by investigating changes in the variability of affinities according to group size in grazing heifers.
topic cattle
global positioning system
grazing
missing data
simulation
social behaviour
url http://www.sciencedirect.com/science/article/pii/S175173111400024X
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