Home range
{{Short description|The area in which an animal lives and moves on a periodic basis}}
File:Home range - simple schema.svg
A home range is the area in which an animal lives and moves on a periodic basis. It is related to the concept of an animal's territory which is the area that is actively defended. The concept of a home range was introduced by W. H. Burt in 1943. He drew maps showing where the animal had been observed at different times. An associated concept is the utilization distribution which examines where the animal is likely to be at any given time. Data for mapping a home range used to be gathered by careful observation, but in more recent years, the animal is fitted with a transmission collar or similar GPS device.
The simplest way of measuring the home range is to construct the smallest possible convex polygon around the data but this tends to overestimate the range. The best known methods for constructing utilization distributions are the so-called bivariate Gaussian or normal distribution kernel density methods. More recently, nonparametric methods such as the Burgman and Fox's alpha-hull and Getz and Wilmers local convex hull have been used. Software is available for using both parametric and nonparametric kernel methods.
History
The concept of the home range can be traced back to a publication in 1943 by W. H. Burt, who constructed maps delineating the spatial extent or outside boundary of an animal's movement during the course of its everyday activities.{{cite journal |last=Burt |first=W. H. |year=1943 |title=Territoriality and home range concepts as applied to mammals |journal=Journal of Mammalogy |volume=24 |issue=3 |pages=346–352 |doi= 10.2307/1374834|jstor=1374834 }} Associated with the concept of a home range is the concept of a utilization distribution, which takes the form of a two dimensional probability density function that represents the probability of finding an animal in a defined area within its home range.{{cite journal |last1=Jennrich |first1=R. I. |last2=Turner |first2=F. B. |year=1969 |title=Measurement of non-circular home range |journal=Journal of Theoretical Biology |volume=22 |issue=2 |pages=227–237 |doi=10.1016/0022-5193(69)90002-2 |pmid=5783911 |bibcode=1969JThBi..22..227J }}{{cite journal |last1=Ford |first1=R. G. |last2=Krumme |first2=D. W. |year=1979 |title=The analysis of space use patterns |journal=Journal of Theoretical Biology |volume=76 |issue=2 |pages=125–157 |doi=10.1016/0022-5193(79)90366-7 |pmid=431092 |bibcode=1979JThBi..76..125F }} The home range of an individual animal is typically constructed from a set of location points that have been collected over a period of time, identifying the position in space of an individual at many points in time. Such data are now collected automatically using collars placed on individuals that transmit through satellites or using mobile cellphone technology and global positioning systems (GPS) technology, at regular intervals.
Methods of calculation
The simplest way to draw the boundaries of a home range from a set of location data is to construct the smallest possible convex polygon around the data. This approach is referred to as the minimum convex polygon (MCP) method which is still widely employed,{{cite journal |last=Baker |first=J. |year=2001 |title=Population density and home range estimates for the Eastern Bristlebird at Jervis Bay, south-eastern Australia |journal=Corella |volume=25 |pages=62–67 }}{{cite book |last1=Creel |first1=S. |last2=Creel |first2=N. M. |year=2002 |title=The African Wild Dog: Behavior, Ecology, and Conservation |publisher=Princeton University Press |location=Princeton, New Jersey |isbn=978-0691016559 }}{{cite journal |last1=Meulman |first1=E. P. |last2=Klomp |first2=N. I. |year=1999 |title=Is the home range of the heath mouse Pseudomys shortridgei an anomaly in the Pseudomys genus? |journal=Victorian Naturalist |volume=116 |pages=196–201 }}{{cite journal |last1=Rurik |first1=L. |last2=Macdonald |first2=D. W. |year=2003 |title=Home range and habitat use of the kit fox (Vulpes macrotis) in a prairie dog (Cynomys ludovicianus) complex |journal=Journal of Zoology |volume=259 |issue=1 |pages=1–5 |doi=10.1017/S0952836902002959 }} but has many drawbacks including often overestimating the size of home ranges.{{cite journal |last1=Burgman |first1=M. A. |last2=Fox |first2=J. C. |year=2003 |title=Bias in species range estimates from minimum convex polygons: implications for conservation and options for improved planning |journal=Animal Conservation |volume=6 |issue=1 |pages=19–28 |doi=10.1017/S1367943003003044 |bibcode=2003AnCon...6...19B |s2cid=85736835 |url=http://espace.library.uq.edu.au/view/UQ:39112/Bias_species_ranges_2003.pdf }}
The best known methods for constructing utilization distributions are the so-called bivariate Gaussian or normal distribution kernel density methods.{{cite book |last=Silverman |first=B. W. |year=1986 |title=Density estimation for statistics and data analysis |publisher=Chapman and Hall |location=London |isbn=978-0412246203 |url-access=registration |url=https://archive.org/details/densityestimatio00silv_0 }}{{cite journal |last=Worton |first=B. J. |year=1989 |title=Kernel methods for estimating the utilization distribution in home-range studies |journal=Ecology |volume=70 |issue=1 |pages=164–168 |doi=10.2307/1938423 |jstor=1938423 |bibcode=1989Ecol...70..164W }}{{cite journal |last1=Seaman |first1=D. E. |last2=Powell |first2=R. A. |year=1996 |title=An evaluation of the accuracy of kernel density estimators for home range analysis |journal=Ecology |volume=77 |issue=7 |pages=2075–2085 |doi=10.2307/2265701 |jstor=2265701 |bibcode=1996Ecol...77.2075S |url=http://www.lib.ncsu.edu/resolver/1840.2/302 }} This group of methods is part of a more general group of parametric kernel methods that employ distributions other than the normal distribution as the kernel elements associated with each point in the set of location data.
Recently, the kernel approach to constructing utilization distributions was extended to include a number of nonparametric methods such as the Burgman and Fox's alpha-hull method {{cite journal |last1=Burgman |first1=M. A. |last2=Fox |first2=J. C. |year=2003 |title=Bias in species range estimates from minimum convex polygons: implications for conservation and options for improved planning |journal=Animal Conservation |volume=6 |issue=1 |pages=19–28 |doi=10.1017/S1367943003003044 |bibcode=2003AnCon...6...19B |s2cid=85736835 |url=http://espace.library.uq.edu.au/view/UQ:39112/Bias_species_ranges_2003.pdf }} and Getz and Wilmers local convex hull (LoCoH) method.{{cite journal |last1=Getz |first1=W. M. |first2=C. C. |last2=Wilmers |year=2004 |title=A local nearest-neighbor convex-hull construction of home ranges and utilization distributions |journal=Ecography |volume=27 |issue=4 |pages=489–505 |doi=10.1111/j.0906-7590.2004.03835.x |bibcode=2004Ecogr..27..489G |s2cid=14592779 |url=http://www.cnr.berkeley.edu/%7Egetz/Reprints04/Getz&WilmersEcoG_SF_04.pdf }} This latter method has now been extended from a purely fixed-point LoCoH method to fixed radius and adaptive point/radius LoCoH methods.{{cite journal |last1=Getz |first1=W. M |first2=S. |last2=Fortmann-Roe |first3=P. C. |last3=Cross |first4=A. J. |last4=Lyonsa |first5=S. J. |last5=Ryan |first6=C. C. |last6=Wilmers |year=2007 |title=LoCoH: nonparametric kernel methods for constructing home ranges and utilization distributions |url=http://www.cnr.berkeley.edu/%7Egetz/Reprints06/GetzEtAlPLoSLoCoH07.pdf |journal=PLoS ONE |volume=2 |issue=2 |pages=e207 |doi=10.1371/journal.pone.0000207 |pmid=17299587 |pmc=1797616|bibcode=2007PLoSO...2..207G |doi-access=free }}
Although, currently, more software is available to implement parametric than nonparametric methods (because the latter approach is newer), the cited papers by Getz et al. demonstrate that LoCoH methods generally provide more accurate estimates of home range sizes and have better convergence properties as sample size increases than parametric kernel methods.
Home range estimation methods that have been developed since 2005 include:
- LoCoH{{cite journal |last1=Getz |first1=W. M. |first2=C. C. |last2=Wilmers |year=2004 |title=A local nearest-neighbor convex-hull construction of home ranges and utilization distributions |journal=Ecography |volume=27 |issue=4 |pages=489–505 |doi=10.1111/j.0906-7590.2004.03835.x |bibcode=2004Ecogr..27..489G |s2cid=14592779 |url=http://www.cnr.berkeley.edu/%7Egetz/Reprints04/Getz&WilmersEcoG_SF_04.pdf }}
- Brownian Bridge{{cite journal |last1=Horne |first1=J. S. |first2=E. O. |last2=Garton |first3=S. M. |last3=Krone |first4=J. S. |last4=Lewis |year=2007 |title=Analyzing animal movements using Brownian Bridges |journal=Ecology |volume=88 |issue=9 |pages=2354–2363 |doi=10.1890/06-0957.1 |pmid=17918412 |bibcode=2007Ecol...88.2354H |s2cid=15044567 }}
- Line-based Kernel{{cite journal |last1=Steiniger |first1=S. |first2=A. J. S. |last2=Hunter |title=A scaled line-based kernel density estimator for the retrieval of utilization distributions and home ranges from GPS movement tracks |journal=Ecological Informatics |volume= 13|year=2012 |pages=1–8 |doi=10.1016/j.ecoinf.2012.10.002 }}
- GeoEllipse{{cite journal |last1=Downs |first1=J. A. |first2=M. W. |last2=Horner |first3=A. D. |last3=Tucker |year=2011 |title=Time-geographic density estimation for home range analysis |journal=Annals of GIS |volume=17 |issue=3 |pages=163–171 |doi=10.1080/19475683.2011.602023 |s2cid=7891668 |doi-access=free |bibcode=2011AnGIS..17..163D }}{{cite journal |last1=Long |first1=J. A. |first2=T. A. |last2=Nelson |year=2012 |title=Time geography and wildlife home range delineation |journal=Journal of Wildlife Management |volume=76 |issue=2 |pages=407–413 |doi=10.1002/jwmg.259 |bibcode=2012JWMan..76..407L |hdl=10023/5424 |hdl-access=free }}
- Line-Buffer{{cite journal |last1=Steiniger |first1=S. |first2=A. J. S. |last2=Hunter |year=2012 |title=OpenJUMP HoRAE – A free GIS and Toolbox for Home-Range Analysis |journal=Wildlife Society Bulletin |volume=36 |issue=3 |pages=600–608 |doi=10.1002/wsb.168 |bibcode=2012WSBu...36..600S }} (See also: [http://146.155.17.19:21080/mediawiki-1.22.7/index.php/Movement_Analysis OpenJUMP HoRAE - Home Range Analysis and Estimation Toolbox])
Computer packages for using parametric and nonparametric kernel methods are available online.[http://locoh.cnr.berkeley.edu/ LoCoH: Powerful algorithms for finding home ranges] {{webarchive|url=https://web.archive.org/web/20060912083122/http://locoh.cnr.berkeley.edu/ |date=2006-09-12 }}{{Cite web |url=http://www.faunalia.it/animov/ |title=AniMove – Animal movement methods |access-date=2007-01-12 |archive-date=2007-01-04 |archive-url=https://web.archive.org/web/20070104210509/http://www.faunalia.it/animov/ |url-status=dead }}[http://146.155.17.19:21080/mediawiki-1.22.7/index.php/Movement_Analysis OpenJUMP HoRAE - Home Range Analysis and Estimation Toolbox (open source; methods: Point-Kernel, Line-Kernel, Brownian-Bridge, LoCoH, MCP, Line-Buffer)][http://cran.univ-lyon1.fr/web/packages/adehabitat/index.html adehabitat for R (open source; methods: Point-Kernel, Line-Kernel, Brownian-Bridge, LoCoH, MCP, GeoEllipse)] In the appendix of a 2017 JMIR article, the home ranges for over 150 different bird species in Manitoba are reported.{{Cite journal|last1=Nasrinpour|first1=Hamid Reza|last2=Reimer|first2=Alex A.|last3=Friesen |first3=Marcia R.|last4=McLeod|first4=Robert D.| date=July 2017 | title = Data preparation for West Nile Virus agent-based modelling: protocol for processing bird population estimates and incorporating ArcMap in AnyLogic| journal = JMIR Research Protocols |volume=6|issue=7|pages=e138| url=http://www.researchprotocols.org/article/downloadSuppFile/6213/54909 | doi=10.2196/resprot.6213 |pmid=28716770|pmc=5537560 |doi-access=free }}
See also
References
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