Supplementary material from "Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data"

While many animal species exhibit strong conspecific interactions, movement analyses of wildlife tracking datasets still largely focus on single individuals. Multi-individual wildlife tracking studies provide new opportunities to explore how individuals move relative to one another, but such dataset...

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Main Authors: Calabrese, Justin M., Fleming, Christen H., Fagan, William F., Rimmler, Martin, Kaczensky, Petra, Bewick, Sharon, Leimgruber, Peter, Mueller, Thomas
Format: Article in Journal/Newspaper
Language:unknown
Published: Figshare 2018
Subjects:
Online Access:https://dx.doi.org/10.6084/m9.figshare.c.3999492.v2
https://figshare.com/collections/Supplementary_material_from_Disentangling_social_interactions_and_environmental_drivers_in_multi-individual_wildlife_tracking_data_/3999492/2
id ftdatacite:10.6084/m9.figshare.c.3999492.v2
record_format openpolar
spelling ftdatacite:10.6084/m9.figshare.c.3999492.v2 2023-05-15T15:53:32+02:00 Supplementary material from "Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data" Calabrese, Justin M. Fleming, Christen H. Fagan, William F. Rimmler, Martin Kaczensky, Petra Bewick, Sharon Leimgruber, Peter Mueller, Thomas 2018 https://dx.doi.org/10.6084/m9.figshare.c.3999492.v2 https://figshare.com/collections/Supplementary_material_from_Disentangling_social_interactions_and_environmental_drivers_in_multi-individual_wildlife_tracking_data_/3999492/2 unknown Figshare https://dx.doi.org/10.1098/rstb.2017.0007 https://dx.doi.org/10.6084/m9.figshare.c.3999492 CC BY 4.0 https://creativecommons.org/licenses/by/4.0 CC-BY Ecology FOS Biological sciences 60801 Animal Behaviour Collection article 2018 ftdatacite https://doi.org/10.6084/m9.figshare.c.3999492.v2 https://doi.org/10.1098/rstb.2017.0007 https://doi.org/10.6084/m9.figshare.c.3999492 2021-11-05T12:55:41Z While many animal species exhibit strong conspecific interactions, movement analyses of wildlife tracking datasets still largely focus on single individuals. Multi-individual wildlife tracking studies provide new opportunities to explore how individuals move relative to one another, but such datasets are frequently too sparse for the detailed, acceleration-based analytical methods typically employed in collective motion studies. Here, we address the methodological gap between wildlife tracking data and collective motion by developing a general method for quantifying movement correlation from sparsely sampled data. Unlike most existing techniques for studying the non-independence of individual movements with wildlife tracking data, our approach is derived from an analytically tractable stochastic model of correlated movement. Our approach partitions correlation into a deterministic tendency to move in the same direction termed ‘drift correlation’ and a stochastic component called ‘diffusive correlation’. These components suggest the mechanisms that coordinate movements, with drift correlation indicating external influences, and diffusive correlation pointing to social interactions. We use two case studies to highlight the ability of our approach both to quantify correlated movements in tracking data and to suggest the mechanisms that generate the correlation. First, we use an abrupt change in movement correlation to pinpoint the onset of spring migration in barren-ground caribou. Second, we show how spatial proximity mediates intermittently correlated movements among khulans in the Gobi desert. We conclude by discussing the linkages of our approach to the theory of collective motion. This article is part of the theme issue 'Collective movement in ecology: from emerging technologies to conservation and management'. Article in Journal/Newspaper caribou DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Ecology
FOS Biological sciences
60801 Animal Behaviour
spellingShingle Ecology
FOS Biological sciences
60801 Animal Behaviour
Calabrese, Justin M.
Fleming, Christen H.
Fagan, William F.
Rimmler, Martin
Kaczensky, Petra
Bewick, Sharon
Leimgruber, Peter
Mueller, Thomas
Supplementary material from "Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data"
topic_facet Ecology
FOS Biological sciences
60801 Animal Behaviour
description While many animal species exhibit strong conspecific interactions, movement analyses of wildlife tracking datasets still largely focus on single individuals. Multi-individual wildlife tracking studies provide new opportunities to explore how individuals move relative to one another, but such datasets are frequently too sparse for the detailed, acceleration-based analytical methods typically employed in collective motion studies. Here, we address the methodological gap between wildlife tracking data and collective motion by developing a general method for quantifying movement correlation from sparsely sampled data. Unlike most existing techniques for studying the non-independence of individual movements with wildlife tracking data, our approach is derived from an analytically tractable stochastic model of correlated movement. Our approach partitions correlation into a deterministic tendency to move in the same direction termed ‘drift correlation’ and a stochastic component called ‘diffusive correlation’. These components suggest the mechanisms that coordinate movements, with drift correlation indicating external influences, and diffusive correlation pointing to social interactions. We use two case studies to highlight the ability of our approach both to quantify correlated movements in tracking data and to suggest the mechanisms that generate the correlation. First, we use an abrupt change in movement correlation to pinpoint the onset of spring migration in barren-ground caribou. Second, we show how spatial proximity mediates intermittently correlated movements among khulans in the Gobi desert. We conclude by discussing the linkages of our approach to the theory of collective motion. This article is part of the theme issue 'Collective movement in ecology: from emerging technologies to conservation and management'.
format Article in Journal/Newspaper
author Calabrese, Justin M.
Fleming, Christen H.
Fagan, William F.
Rimmler, Martin
Kaczensky, Petra
Bewick, Sharon
Leimgruber, Peter
Mueller, Thomas
author_facet Calabrese, Justin M.
Fleming, Christen H.
Fagan, William F.
Rimmler, Martin
Kaczensky, Petra
Bewick, Sharon
Leimgruber, Peter
Mueller, Thomas
author_sort Calabrese, Justin M.
title Supplementary material from "Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data"
title_short Supplementary material from "Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data"
title_full Supplementary material from "Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data"
title_fullStr Supplementary material from "Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data"
title_full_unstemmed Supplementary material from "Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data"
title_sort supplementary material from "disentangling social interactions and environmental drivers in multi-individual wildlife tracking data"
publisher Figshare
publishDate 2018
url https://dx.doi.org/10.6084/m9.figshare.c.3999492.v2
https://figshare.com/collections/Supplementary_material_from_Disentangling_social_interactions_and_environmental_drivers_in_multi-individual_wildlife_tracking_data_/3999492/2
genre caribou
genre_facet caribou
op_relation https://dx.doi.org/10.1098/rstb.2017.0007
https://dx.doi.org/10.6084/m9.figshare.c.3999492
op_rights CC BY 4.0
https://creativecommons.org/licenses/by/4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.6084/m9.figshare.c.3999492.v2
https://doi.org/10.1098/rstb.2017.0007
https://doi.org/10.6084/m9.figshare.c.3999492
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