Home range size estimates of red deer in Germany: environmental, individual and methodological correlates

Reinecke, Horst; Leinen, Loretta; Thißen, Ines; Meißner, Marcus; Herzog, S.; Schütz, Stefan; Kiffner, Christian

doi:10.1007/s10344-013-0772-1

Cited by 34 publications

(38 citation statements)

References 45 publications

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“…These small and inconclusive differences between the MCP and KDE methods can be attributed to the sensitivity of home range estimates to varying sample sizes, time scale, seasonal and behavioural variations, and other limitations associated with these methods (see Boulanger and White 1990;Girard et al 2002;Nilsen et al 2008). In view of this, we agree with previous work that support the use of more than one home range estimation method (see Biebouw 2009;Boyle et al 2009;Pebsworth et al 2012;Reinecke et al 2014). Despite this, it is clear there is much individual variation.…”

Section: Discussionsupporting

confidence: 86%

Home range and habitat use of Trumpeter Hornbills Bycanistes bucinator in an urban–forest mosaic, Eshowe, South Africa

Chibesa

Taylor

Ramesh

et al. 2017

Ostrich

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Despite the negative impacts of urbanisation, some species adapt to pressures of habitat loss and fragmentation. Trumpeter Hornbills Bycanistes bucinator are a large avian forest frugivore that uses urban environments in South Africa. Consequently, we used GPS/UHF transmitters to study their home range size, movement and habitat use in an urban-forest mosaic in Eshowe, South Africa from March to October 2014. We estimated the home range size using three methods: minimum convex polygon (MCP), kernel density estimation (KDE) and local convex hull (LoCoH). Our results showed that overall monthly home range size was 5.1 ± 1.28 km 2 (mean ± SE; 95% MCP), 4.6 ± 1.14 km 2 (95% KDE) and 1.9 ± 0. 46 km 2 (95% LoCoH). However, individual home range sizes varied monthly and seasonally. We found that all individuals tagged used mostly the indigenous forest and frequently utilised urban residential areas (gardens) with little or no use of cultivated land. Observed individual variations in monthly and seasonal home ranges could be a response to variations in availability of key fruit resources in the urban residential and indigenous forest mosaic. This study supports the use of more than one method of home range estimation for insight regarding home range and habitat use in urban-forest mosaics for this large forest frugivore. Aire de répartition et habitat utilisé par le Calao Trompette Bycanistes bucinator dans une forêt urbanisée, Eshowe, South Africa Malgré les impacts négatifs de l'urbanisation, certaines espèces s'adaptent à la pression de la perte et la fragmentation de leur habitat. Le Calao trompette Bycanistes bucinator est un grand oiseau frugivore et forestier, qui utilise l'environnement urbain de l'Afrique du Sud. Par conséquence, nous avons utilisé les transmissions du GPS/UHF pour étudier l'aire de répartition, les mouvements et l'habitat des individus de la forêt urbanisée de Eshowe (Afrique du Sud), entre Mars et Octobre 2014. Pour estimer leur aire de répartition nous utilisons trois méthodes : le polygone convexe minimum (Minimum Convex Polygon : MCP), estimation du noyau de densité (Kernel Density Estimation : KDE) et « Local Convex Hull » : LoCoH. Nos résultats ont montrés que sur un mois, l'ensemble des aires de répartitions étaient de 5,1 ± 1,28 km² (soit ± SE ; 95% MCP), 4,6 ± 1,14 km² (95% KDE) et 1,9 ± 0,46 km² (95% LoCoH). Cependant, l'aire de répartition individuelle varie selon les mois et les saisons. Nous avons trouvé que tous les individus marqués utilisaient principalement la forêt indigène et utilisent fréquemment les résidences urbaines (jardins), avec très peu, voire pas du tout, d'utilisation des terres cultivées. L'observation individuelle des variations mensuelles et saisonnières des aires de répartitions peuvent être expliquées par la disponibilité des ressources de fruits dans les résidences urbaines et la forêt indigène. Cette étude soutient l'utilisation de plus d'une méthode pour comprendre et estimer l'aire de répartition et l'habitat utilisé dans les forêts urbanisées pour cette g...

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Section: Discussionsupporting

confidence: 86%

Home range and habitat use of Trumpeter Hornbills Bycanistes bucinator in an urban–forest mosaic, Eshowe, South Africa

Chibesa

Taylor

Ramesh

et al. 2017

Ostrich

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“…Although a variety of more home sophisticated home-range estimators have been developed in recent years, MCPs and KDEs are the simplest and most widely applied approaches [14,21]. We also included LoCoH because previous studies (e.g., [9,22]) found that home-range estimates from LoCoH may be more useful for wildlife managers, because of their ability to better detect sharp boundaries. For KDE, we used bivariate normal kernels on a 100 by 100 grid with a resolution of 1 unit.…”

Section: Discussionmentioning

confidence: 99%

“…Because of their accessibility, home-range estimators are frequently used to compare space-use patterns for animals living in different landscapes (e.g., [8,9]) or along spatial gradients (e.g., [10]). With the increase of fine-scale spatio-temporal data afforded by Global Positioning Technology (GPS), short-term (weekly, monthly) estimates of home-range size are now also commonly used to explore changes in space-use patters over time (e.g., [3,11,12]).…”

Section: Introductionmentioning

confidence: 99%

Does estimator choice influence our ability to detect changes in home-range size?

et al. 2015

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Background: Estimates of home-range size are frequently used to compare areal requirements of animals over time or space. Comparative studies of home-range estimators have highlighted extreme differences among general classes of methods (e.g., polygon-based and kernel density-based estimators) and sensitivity to the choice of various tuning parameters (e.g., amount of smoothing). These studies, however, have largely failed to consider how estimates of home-range size are typically used in applied research. We illustrate simulation-based methods for comparing estimators, which focus on relative differences in home-range size (over time or space), rather than their absolute magnitude. We also consider Global Positioning Technology (GPS) location data from a black bear (Ursus americanus) from northwestern Minnesota, USA, to illustrate the relevance to real-world data applications. Results: In our examples, estimates of home-range size often differed considerably in absolute magnitude. Yet, for relative differences, the choice of home-range estimator was often negligible. Furthermore, choosing the right estimator was less important than other aspects of study design (e.g., number of animals followed). Conclusion: Many questions in ecology focus on changes in space-use patterns (over space or time). For these types of questions, home-range estimators should be evaluated in terms of their ability to detect these spatial and temporal patterns. More importantly, home-range estimation should be seen as a means to an end-i.e., estimators provide indices useful for addressing interesting biological questions or hypotheses-rather than as an end to itself.

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“…Despite the importance of the home range concept, there is no consensus among scientists studying animal movements on how to estimate the home range size of animals (Reinecke et al, 2014). However, in this paper, we estimate the home range of elephant in Amboseli ecosystem using the MCP and KDE methods.…”

Section: Introductionmentioning

confidence: 99%

Home range sizes and space use of African elephants (Loxodonta africana) in the Southern Kenya and Northern Tanzania borderland landscape

Ngene¹,

Okello²,

Mukeka³

et al. 2017

Int. J. Biodivers. Conserv.

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The African elephant (Loxodonta africana) require vast areas to meet their survival needs such as food, mates, water, resting sites, and look up positions; the area referred to as home range. We collared 9 bull and 3 female elephants using satellite-linked Geographic Positioning System (GPS) collars in February 2013. Their movements were monitored up to April 2016 in the wider Amboseli landscape. We estimated their home ranges using 100% minimum convex polygon (MCP) and 95% Fixed Kernel Density Estimator (KDE) methods. A total of 48,852 GPS points were used representing 77% of the expected GPS points. This study revealed that bulls had a larger total home range size (MCP = 32,110 km²; KDE = 3,170 km² compared to females (MCP = 10,515 km²; KDE = 3,070 km²). The 95% confidence interval of the monthly range (95% KDE) for all elephants was 6,130 to 7,025 km² with the minimum and maximum range being 5,200 and 7,790 km² respectively. Females had smaller home ranges during the dry and wet season (MCP: dry = 2,974 km²; wet = 1,828 km²; KDE: dry = 2,810 km²; wet = 3,070 km²) than bulls (MCP: dry = 3,312 km²; wet = 13,288 km²; KDE: dry = 2,960 km²; wet = 3,720 km²). The variations of the elephant home range could have been influenced by an interaction of factors including rainfall, human disturbances and land use (e.g., farms, settlements, road network, and fences), water availability, bush cover, food availability, and tracking period. The most important areas that had key habitats for elephants were scattered throughout the Kenya/Tanzania borderland. The Amboseli-TsavoMagadi-Natron-West Kilimanjaro elephant population roams within specific areas of the landscape. Trans-boundary efforts should be enhanced to ensure sound management of the elephant-habitatpeople interface for continued well-being of the elephant population.

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Home range size estimates of red deer in Germany: environmental, individual and methodological correlates

Cited by 34 publications

References 45 publications

Home range and habitat use of Trumpeter Hornbills Bycanistes bucinator in an urban–forest mosaic, Eshowe, South Africa

Home range and habitat use of Trumpeter Hornbills Bycanistes bucinator in an urban–forest mosaic, Eshowe, South Africa

Does estimator choice influence our ability to detect changes in home-range size?

Home range sizes and space use of African elephants (Loxodonta africana) in the Southern Kenya and Northern Tanzania borderland landscape

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