Mapping areas of spatial-temporal overlap from wildlife tracking data

Jed A. Long, Stephen L. Webb, Trisalyn Nelson, Kenneth L. Gee

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Background: The study of inter-individual interactions (often termed spatial-temporal interactions, or dynamic interactions) from remote tracking data has focused primarily on identifying the presence of such interactions.New datasets and methods offer opportunity to answer more nuanced questions, such as where on the landscape interactions occur. In this paper, we provide a new approach for mapping areas of spatial-temporal overlap in wildlife from remote tracking data. The method, termed the joint potential path area (jPPA) builds from the time-geographic movement model, originally proposed for studying human movement patterns.Results: The jPPA approach can be used to delineate sub-areas of the home range where inter-individual interaction was possible. Maps of jPPA regions can be integrated with existing geographic data to explore landscape conditions and habitat associated with spatial temporal-interactions in wildlife. We apply the jPPA approach to simulated biased correlated random walks to demonstrate the method under known conditions. The jPPA method is then applied to three dyads, consisting of fine resolution (15 minute sampling interval) GPS tracking data of white-tailed deer (Odocoileus virginianus) collected in Oklahoma, USA. Our results demonstrate the ability of the jPPA to identify and map jPPA sub-areas of the home range. We show how jPPA maps can be used to identify habitat differences (using percent tree canopy cover as a habitat indicator) between areas of spatial-temporal overlap and the overall home range in each of the three deer dyads.Conclusions: The value of the jPPA approach within current wildlife habitat analysis workflows is highlighted along with its simple and straightforward implementation and interpretation. Given the current emphasis on remote tracking in wildlife movement and habitat research, new approaches capable of leveraging both the spatial and temporal information content contained within these data are warranted. We make code (in the statistical software R)for implementing the jPPA approach openly available for other researchers.

Original languageEnglish (US)
Article number38
JournalMovement Ecology
Volume3
Issue number1
DOIs
StatePublished - 2015
Externally publishedYes

Fingerprint

wildlife
Odocoileus virginianus
habitats
home range
habitat
deer
wildlife habitats
methodology
researchers
canopy
GPS
software
method
sampling

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics

Cite this

Mapping areas of spatial-temporal overlap from wildlife tracking data. / Long, Jed A.; Webb, Stephen L.; Nelson, Trisalyn; Gee, Kenneth L.

In: Movement Ecology, Vol. 3, No. 1, 38, 2015.

Research output: Contribution to journalArticle

Long, Jed A. ; Webb, Stephen L. ; Nelson, Trisalyn ; Gee, Kenneth L. / Mapping areas of spatial-temporal overlap from wildlife tracking data. In: Movement Ecology. 2015 ; Vol. 3, No. 1.
@article{1a463449e1e5416fac8b41f6b6a46573,
title = "Mapping areas of spatial-temporal overlap from wildlife tracking data",
abstract = "Background: The study of inter-individual interactions (often termed spatial-temporal interactions, or dynamic interactions) from remote tracking data has focused primarily on identifying the presence of such interactions.New datasets and methods offer opportunity to answer more nuanced questions, such as where on the landscape interactions occur. In this paper, we provide a new approach for mapping areas of spatial-temporal overlap in wildlife from remote tracking data. The method, termed the joint potential path area (jPPA) builds from the time-geographic movement model, originally proposed for studying human movement patterns.Results: The jPPA approach can be used to delineate sub-areas of the home range where inter-individual interaction was possible. Maps of jPPA regions can be integrated with existing geographic data to explore landscape conditions and habitat associated with spatial temporal-interactions in wildlife. We apply the jPPA approach to simulated biased correlated random walks to demonstrate the method under known conditions. The jPPA method is then applied to three dyads, consisting of fine resolution (15 minute sampling interval) GPS tracking data of white-tailed deer (Odocoileus virginianus) collected in Oklahoma, USA. Our results demonstrate the ability of the jPPA to identify and map jPPA sub-areas of the home range. We show how jPPA maps can be used to identify habitat differences (using percent tree canopy cover as a habitat indicator) between areas of spatial-temporal overlap and the overall home range in each of the three deer dyads.Conclusions: The value of the jPPA approach within current wildlife habitat analysis workflows is highlighted along with its simple and straightforward implementation and interpretation. Given the current emphasis on remote tracking in wildlife movement and habitat research, new approaches capable of leveraging both the spatial and temporal information content contained within these data are warranted. We make code (in the statistical software R)for implementing the jPPA approach openly available for other researchers.",
author = "Long, {Jed A.} and Webb, {Stephen L.} and Trisalyn Nelson and Gee, {Kenneth L.}",
year = "2015",
doi = "10.1186/s40462-015-0064-3",
language = "English (US)",
volume = "3",
journal = "Movement Ecology",
issn = "2051-3933",
publisher = "BioMed Central",
number = "1",

}

TY - JOUR

T1 - Mapping areas of spatial-temporal overlap from wildlife tracking data

AU - Long, Jed A.

AU - Webb, Stephen L.

AU - Nelson, Trisalyn

AU - Gee, Kenneth L.

PY - 2015

Y1 - 2015

N2 - Background: The study of inter-individual interactions (often termed spatial-temporal interactions, or dynamic interactions) from remote tracking data has focused primarily on identifying the presence of such interactions.New datasets and methods offer opportunity to answer more nuanced questions, such as where on the landscape interactions occur. In this paper, we provide a new approach for mapping areas of spatial-temporal overlap in wildlife from remote tracking data. The method, termed the joint potential path area (jPPA) builds from the time-geographic movement model, originally proposed for studying human movement patterns.Results: The jPPA approach can be used to delineate sub-areas of the home range where inter-individual interaction was possible. Maps of jPPA regions can be integrated with existing geographic data to explore landscape conditions and habitat associated with spatial temporal-interactions in wildlife. We apply the jPPA approach to simulated biased correlated random walks to demonstrate the method under known conditions. The jPPA method is then applied to three dyads, consisting of fine resolution (15 minute sampling interval) GPS tracking data of white-tailed deer (Odocoileus virginianus) collected in Oklahoma, USA. Our results demonstrate the ability of the jPPA to identify and map jPPA sub-areas of the home range. We show how jPPA maps can be used to identify habitat differences (using percent tree canopy cover as a habitat indicator) between areas of spatial-temporal overlap and the overall home range in each of the three deer dyads.Conclusions: The value of the jPPA approach within current wildlife habitat analysis workflows is highlighted along with its simple and straightforward implementation and interpretation. Given the current emphasis on remote tracking in wildlife movement and habitat research, new approaches capable of leveraging both the spatial and temporal information content contained within these data are warranted. We make code (in the statistical software R)for implementing the jPPA approach openly available for other researchers.

AB - Background: The study of inter-individual interactions (often termed spatial-temporal interactions, or dynamic interactions) from remote tracking data has focused primarily on identifying the presence of such interactions.New datasets and methods offer opportunity to answer more nuanced questions, such as where on the landscape interactions occur. In this paper, we provide a new approach for mapping areas of spatial-temporal overlap in wildlife from remote tracking data. The method, termed the joint potential path area (jPPA) builds from the time-geographic movement model, originally proposed for studying human movement patterns.Results: The jPPA approach can be used to delineate sub-areas of the home range where inter-individual interaction was possible. Maps of jPPA regions can be integrated with existing geographic data to explore landscape conditions and habitat associated with spatial temporal-interactions in wildlife. We apply the jPPA approach to simulated biased correlated random walks to demonstrate the method under known conditions. The jPPA method is then applied to three dyads, consisting of fine resolution (15 minute sampling interval) GPS tracking data of white-tailed deer (Odocoileus virginianus) collected in Oklahoma, USA. Our results demonstrate the ability of the jPPA to identify and map jPPA sub-areas of the home range. We show how jPPA maps can be used to identify habitat differences (using percent tree canopy cover as a habitat indicator) between areas of spatial-temporal overlap and the overall home range in each of the three deer dyads.Conclusions: The value of the jPPA approach within current wildlife habitat analysis workflows is highlighted along with its simple and straightforward implementation and interpretation. Given the current emphasis on remote tracking in wildlife movement and habitat research, new approaches capable of leveraging both the spatial and temporal information content contained within these data are warranted. We make code (in the statistical software R)for implementing the jPPA approach openly available for other researchers.

UR - http://www.scopus.com/inward/record.url?scp=85010262500&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85010262500&partnerID=8YFLogxK

U2 - 10.1186/s40462-015-0064-3

DO - 10.1186/s40462-015-0064-3

M3 - Article

VL - 3

JO - Movement Ecology

JF - Movement Ecology

SN - 2051-3933

IS - 1

M1 - 38

ER -