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Journal article 1268 views

Could you please phrase “home range” as a question?

John Fieberg, Luca Borger Orcid Logo

Journal of Mammalogy, Volume: 93, Issue: 4, Pages: 890 - 902

Swansea University Author: Luca Borger Orcid Logo

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DOI (Published version): 10.1644/11-MAMM-S-172.1

Abstract

Statisticians frequently voice concern that their interactions with applied researchers start only after data have been collected. The same can be said for our experience with home-range studies. Too often, conversations about home range begin with questions concerning estimation methods, smoothing...

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Published in: Journal of Mammalogy
Published: 2012
URI: https://cronfa.swan.ac.uk/Record/cronfa16625
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spelling 2021-07-16T14:56:10.9133357 v2 16625 2013-12-14 Could you please phrase “home range” as a question? 8416d0ffc3cccdad6e6d67a455e7c4a2 0000-0001-8763-5997 Luca Borger Luca Borger true false 2013-12-14 SBI Statisticians frequently voice concern that their interactions with applied researchers start only after data have been collected. The same can be said for our experience with home-range studies. Too often, conversations about home range begin with questions concerning estimation methods, smoothing parameters, or the nature of autocorrelation. More productive efforts start by asking good (and interesting) research questions; once these questions are defined, it becomes possible to ask how various design and analysis strategies influence one's ability to answer these questions. With this process in mind, we address key sample-design and data-analysis issues related to the topic of home range. The impact of choosing a particular home-range estimator (e.g., minimum convex polygon, kernel density estimator, or local convex hull) will be question dependent, and for some problems other movement or use-based metrics (e.g., mean step lengths or time spent in particular areas) may be worthy of consideration. Thus, we argue the need for more question-driven and focused research and for clearly distinguishing the biological concept of an animal's home range from the statistical quantities one uses to investigate this concept. For comparative studies, it is important to standardize sampling regimes and estimation methods as much as possible, and to pay close attention to missing data issues. More attention should also be given to temporally changing space-use patterns, with biologically meaningful time periods (e.g., life-history stages) used to define sampling periods. Last, we argue the need for closer connections between theoretical and empirical researchers. Advances in ecological theory, and its application to natural resources management, will require carefully designed research studies to test theoretical predictions from more mechanistic modeling approaches. Journal Article Journal of Mammalogy 93 4 890 902 home range, kernel density estimation, animal movements, movement ecology 31 12 2012 2012-12-31 10.1644/11-MAMM-S-172.1 COLLEGE NANME Biosciences COLLEGE CODE SBI Swansea University 2021-07-16T14:56:10.9133357 2013-12-14T01:31:27.0242940 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences John Fieberg 1 Luca Borger 0000-0001-8763-5997 2
title Could you please phrase “home range” as a question?
spellingShingle Could you please phrase “home range” as a question?
Luca Borger
title_short Could you please phrase “home range” as a question?
title_full Could you please phrase “home range” as a question?
title_fullStr Could you please phrase “home range” as a question?
title_full_unstemmed Could you please phrase “home range” as a question?
title_sort Could you please phrase “home range” as a question?
author_id_str_mv 8416d0ffc3cccdad6e6d67a455e7c4a2
author_id_fullname_str_mv 8416d0ffc3cccdad6e6d67a455e7c4a2_***_Luca Borger
author Luca Borger
author2 John Fieberg
Luca Borger
format Journal article
container_title Journal of Mammalogy
container_volume 93
container_issue 4
container_start_page 890
publishDate 2012
institution Swansea University
doi_str_mv 10.1644/11-MAMM-S-172.1
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Biosciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Biosciences
document_store_str 0
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description Statisticians frequently voice concern that their interactions with applied researchers start only after data have been collected. The same can be said for our experience with home-range studies. Too often, conversations about home range begin with questions concerning estimation methods, smoothing parameters, or the nature of autocorrelation. More productive efforts start by asking good (and interesting) research questions; once these questions are defined, it becomes possible to ask how various design and analysis strategies influence one's ability to answer these questions. With this process in mind, we address key sample-design and data-analysis issues related to the topic of home range. The impact of choosing a particular home-range estimator (e.g., minimum convex polygon, kernel density estimator, or local convex hull) will be question dependent, and for some problems other movement or use-based metrics (e.g., mean step lengths or time spent in particular areas) may be worthy of consideration. Thus, we argue the need for more question-driven and focused research and for clearly distinguishing the biological concept of an animal's home range from the statistical quantities one uses to investigate this concept. For comparative studies, it is important to standardize sampling regimes and estimation methods as much as possible, and to pay close attention to missing data issues. More attention should also be given to temporally changing space-use patterns, with biologically meaningful time periods (e.g., life-history stages) used to define sampling periods. Last, we argue the need for closer connections between theoretical and empirical researchers. Advances in ecological theory, and its application to natural resources management, will require carefully designed research studies to test theoretical predictions from more mechanistic modeling approaches.
published_date 2012-12-31T03:19:00Z
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score 11.012924

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