Datensatz:

Data from: Challenges of mismatching timescales in longitudinal studies of collective behaviour

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Datum der Erstveröffentlichung

2022

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Angaben zur Forschungsförderung

European Union (EU): 850859
Swiss National Science Foundation: PCEFP3_187058

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Core Facility der Universität Konstanz
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Publikationsstatus
Published

Zusammenfassung

Datasets and R scripts for the analysis in Ogino M, Strauss E, Farine D. 2022. Challenges of mismatching timescales in longitudinal studies of collective behaviour (doi.org/10.1098/rstb.2022.0064).

20201001_20201031, 20201101_20201130, 10101201_20211231, 20210101_20210131, 20210201_20210228, 20210301_20210331: files containing daily averaged GPS pairwise distance between males for each month

Seasons_Monthly.csv: dataset containing the metadata for each sampling periods

Census.Rdata: dataset (list) with dataframes for individual metadata (data$Birds) and census observation data (data$ind_obs, data$grp_obs). The grp_obs dataframe contains the metadata for the ind_obs dataset.

Script1_GroupDetection.r: code to detect group memberships over time, using different approaches

Script2_GPSpairwisedistance.R: code to produce the boxplot showing averaged GPS pairwise distances within detected communities and GLM to quantify how methodological processes applied in different approaches drive differences in cohesiveness of detected groups. This code requires the outputs of Script1.

Script3_GroupSize.R: code to produce the boxplots showing the distribution of detected social unit sizes and Jaccard similarity between social units in consecutive sampling periods, and GLM to quantidy how methodological processes drive differences in group size and Jaccard similarity. This code requires the outputs of Script1 and Script2.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
570 Biowissenschaften, Biologie

Schlagwörter

Animal behaviour, Community detection, vulturine guineafowl, groups, animal social networks, Collective Behaviour

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Publikation
Zeitschriftenartikel
Challenges of mismatching timescales in longitudinal studies of collective behaviour
(2023) Ogino, Mina; Strauss, Eli D.; Farine, Damien R.
Erschienen in: Philosophical Transactions of the Royal Society of London, Series B : Biological Sciences. Royal Society of London. 2023, 378(1874), 20220064. ISSN 0962-8436. eISSN 1471-2970. Verfügbar unter: doi: 10.1098/rstb.2022.0064
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ISO 690OGINO, Mina, Damien R. FARINE, Eli D. STRAUSS, 2022. Data from: Challenges of mismatching timescales in longitudinal studies of collective behaviour
BibTex
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20201001_20201031, 20201101_20201130, 10101201_20211231, 20210101_20210131, 20210201_20210228, 20210301_20210331: files containing daily averaged GPS pairwise distance between males for each month


Seasons_Monthly.csv: dataset containing the metadata for each sampling periods


Census.Rdata: dataset (list) with dataframes for individual metadata (data$Birds) and census observation data (data$ind_obs, data$grp_obs). The grp_obs dataframe contains the metadata for the ind_obs dataset.


Script1_GroupDetection.r: code to detect group memberships over time, using different approaches


Script2_GPSpairwisedistance.R: code to produce the boxplot showing averaged GPS pairwise distances within detected communities and GLM to quantify how methodological processes applied in different approaches drive differences in cohesiveness of detected groups. This code requires the outputs of Script1.


Script3_GroupSize.R: code to produce the boxplots showing the distribution of detected social unit sizes and Jaccard similarity between social units in consecutive sampling periods, and GLM to quantidy how methodological processes drive differences in group size and Jaccard similarity.  This code requires the outputs of Script1 and Script2.</dcterms:abstract>
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