St Andrews Research Repository

St Andrews University Home
View Item 
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  • Login
JavaScript is disabled for your browser. Some features of this site may not work without it.

Quantifying spatial-temporal interactions from wildlife tracking data : issues of space, time, and statistical significance

Thumbnail
View/Open
Long_2015_PES_Quantifying_CC.pdf (414.8Kb)
Date
2015
Author
Long, Jed A.
Keywords
Telemetry
Contacts
Encounters
Dynamic interaction
Movement ecology
G Geography (General)
QL Zoology
NDAS
Metadata
Show full item record
Altmetrics Handle Statistics
Altmetrics DOI Statistics
Abstract
New tracking technologies are allowing researchers to study wildlife movements at unprecedented spatial and temporal resolutions. Researchers now routinely deploy tracking sensors on multiple individual animals simultaneously, offering new opportunities to study the spatial-temporal interactions (often termed dynamic interaction) in the movements of these animals. The objective of this paper is to examine the statistical properties of a suite of currently available methods aimed at measuring spatial-temporal interactions and the ability of each method to characterize and capture different patterns of spatial-temporal interaction encountered in practice. Specifically, this paper examines issues relating to the spatial arrangement of interactions across a study area, temporal patterns in interactions over a tracking period, and the effectiveness of different statistical testing procedures used to identify significant spatial-temporal interaction. Simulations using biased correlated random walks are used to emulate different patterns of spatial-temporal interaction encountered in empirical data. The results demonstrate the challenges of statistical testing of interaction patterns with several methods having high rates of type I and/or type II error. More problematic is that, in practice, spatial-temporal interactions exhibit underlying spatial and/or temporal patterns, for example with key watering holes revisited daily, which can cause problems for statistics that use permutation tests from the original data to test for significance. The need to consider statistical significance in the context of biological significance, which relates to quantifying the spatial locations and temporal patterns of interaction events and types of interactions, is emphasized. Methods that can be adapted to facilitate spatial and temporally ‘local’ analysis are advantageous with high resolution tracking data currently being collected. An R package–wildlifeDI–provides the computational tools for performing the analysis described herein and is made openly available to other researchers.
Citation
Long , J A 2015 , ' Quantifying spatial-temporal interactions from wildlife tracking data : issues of space, time, and statistical significance ' , Procedia Environmental Sciences , vol. 26 , pp. 3-10 . https://doi.org/10.1016/j.proenv.2015.05.004
Publication
Procedia Environmental Sciences
Status
Peer reviewed
DOI
https://doi.org/10.1016/j.proenv.2015.05.004
ISSN
1878-0296
Type
Journal article
Rights
© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Collections
  • University of St Andrews Research
URI
http://hdl.handle.net/10023/6775

Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

Advanced Search

Browse

All of RepositoryCommunities & CollectionsBy Issue DateNamesTitlesSubjectsClassificationTypeFunderThis CollectionBy Issue DateNamesTitlesSubjectsClassificationTypeFunder

My Account

Login

Open Access

To find out how you can benefit from open access to research, see our library web pages and Open Access blog. For open access help contact: openaccess@st-andrews.ac.uk.

Accessibility

Read our Accessibility statement.

How to submit research papers

The full text of research papers can be submitted to the repository via Pure, the University's research information system. For help see our guide: How to deposit in Pure.

Electronic thesis deposit

Help with deposit.

Repository help

For repository help contact: Digital-Repository@st-andrews.ac.uk.

Give Feedback

Cookie policy

This site may use cookies. Please see Terms and Conditions.

Usage statistics

COUNTER-compliant statistics on downloads from the repository are available from the IRUS-UK Service. Contact us for information.

© University of St Andrews Library

University of St Andrews is a charity registered in Scotland, No SC013532.

  • Facebook
  • Twitter