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Assessing habitat connectivity for ground‐dwelling animals in an urban environment
Abstract
To ensure viable species populations in fragmented landscapes, individuals must be able to move between suitable habitat patches. Despite the increased interest in biodiversity assessment in urban environments, the ecological relevance of habitat connectivity in highly fragmented landscapes remains largely unknown. The first step to understanding the role of habitat connectivity in urban ecology is the challenging task of assessing connectivity in the complex patchwork of contrasting habitats that is found in cities. We developed a data‐based framework, minimizing the use of subjective assumptions, to assess habitat connectivity that consists of the following sequential steps: (1) identification of habitat preference based on empirical habitat‐use data; (2) derivation of habitat resistance surfaces evaluating various transformation functions; (3) modeling of different connectivity maps with electrical circuit theory (Circuitscape), a method considering all possible pathways across the landscape simultaneously; and (4) identification of the best connectivity map with information‐theoretic model selection. We applied this analytical framework to assess habitat connectivity for the European hedgehog Erinaceus europaeus , a model species for ground‐dwelling animals, in the city of Zurich, Switzerland, using GPS track points from 40 individuals. The best model revealed spatially explicit connectivity “pinch points,” as well as multiple habitat connections. Cross‐validation indicated the general validity of the selected connectivity model. The results show that both habitat connectivity and habitat quality affect the movement of urban hedgehogs (relative importance of the two variables was 19.2% and 80.8%, respectively), and are thus both relevant for predicting urban animal movements. Our study demonstrates that even in the complex habitat patchwork of cities, habitat connectivity plays a major role for ground‐dwelling animal movement. Data‐based habitat connectivity maps can thus serve as an important tool for city planners to identify habitat corridors and plan appropriate management and conservation measures for urban animals. The analytical framework we describe to model such connectivity maps is generally applicable to different types of habitat‐use data and can be adapted to the movement scale of the focal species. It also allows evaluation of the impact of future landscape changes or management scenarios on habitat connectivity in urban landscapes.
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Circuit theory has been found suitable for characterizing relative frequency of routine movements along multiple potential paths through urban and other fragmented landscapes.
“Still, circuit theory has been found suitable for characterizing relative frequency of routine movements along multiple potential paths through urban and other fragmented landscapes (e.g., Braaker et al. 2014; Rödder et al. 2016; Grafius et al. 2017).”
From Circuit‐theory applications to connectivity science and conservation (2019) · cites this paper as Braaker et al. 2014
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USING CIRCUIT THEORY TO MODEL CONNECTIVITY IN ECOLOGY, EVOLUTION, AND CONSERVATION
McRae, B. H., Dickson, B. G., Keitt, T. H., & Shah, V. B. (2008) · Ecology · doi:10.1890/07-1861.1 · Cited by 2,244
McRae, B. H. (2006) · Evolution · doi:10.1111/j.0014-3820.2006.tb00500.x · Cited by 1,081
The city-fox phenomenon: genetic consequences of a recent colonization of urban habitat
Wandeler, P., Funk, S. M., Largiadèr, C. R., Gloor, S., & Breitenmoser, U. (2003) · Molecular Ecology · doi:10.1046/j.1365-294x.2003.01768.x · Cited by 189 · cited 1×
“…in urban areas and was explained by isolation by fragmentation (lizards and birds; Delaney et al. 2010) or by multiple independent colonization events and consequent founder effects combined with limited gene flow due to fragmentation (foxes and birds; Wandeler et al. 2003, Evans et al. 2009).”
BackgroundThe effect of map boundary on estimates of landscape resistance to animal movement
Koen, E. L., Garroway, C. J., Wilson, P. J., & Bowman, J. (2010) · PLoS ONE · doi:10.1371/journal.pone.0011785 · Cited by 148
Flagged first, then by citations
Research works printed but not linked: 74
- 10.1016/S0169-2046(02)00242-6 · DOI · Paper page
- 10.2307/1940062 · DOI
- 10.1111/j.1523-1739.2008.00942.x · DOI · Paper page
- 10.1098/rstb.2010.0083 · DOI
- Biotoptypenkartierung der Stadt Zurich, 2010, Naturschutz-Inventar und Kartierungen
- Bontadina F, 1991, Strassenüberquerungen von Igeln (Erinaceus europaeus)
- Bontadina F, 1994, Igel in der Stadt. Zürich: Wildbiologie, 6
- 10.1016/S0304-3800(02)00200-4 · DOI
- Burnham K. P, 2002, Model selection and multimodel inference: a practical information-theoretic approach
- 10.1890/1540-9295(2004)002[0529:ACGTCM]2.0.CO;2 · DOI · Paper page
- 10.1016/j.ecolmodel.2006.03.017 · DOI
- 10.1016/j.ecoinf.2008.10.002 · DOI
- 10.1890/0012-9658(2006)87[2349:EOSRFA]2.0.CO;2 · DOI
- Carey V. J, 2004, yags: yet another GEE solver. Version 4.0-2.1
- 10.1002/bimj.200610379 · DOI
- 10.1086/506976 · DOI · Paper page
- Delaney K. S, 2010, A rapid, strong, and convergent genetic response to urban habitat fragmentation in four divergent and widespread vertebrates, PLoS ONE, 5, 10.1371/journal.pone.0012767 · DOI
- 10.1007/s10592-004-7748-3 · DOI
- 10.1111/j.1365-2664.2010.01899.x · DOI
- 10.1046/j.1365-2656.2001.00471.x · DOI
- 10.1016/j.anbehav.2010.04.007 · DOI
- ESRI, 2009, ArcMap version 9.3.1
- 10.1098/rspb.2008.1712 · DOI
- 10.1098/rstb.2010.0079 · DOI
- 10.1111/j.1365-2664.2009.01692.x · DOI
- 10.1111/j.1466-8238.2007.00287.x · DOI
- 10.1111/j.1365-2664.2004.00869.x · DOI
- 10.1016/j.tree.2009.07.016 · DOI · Paper page
- 10.1126/science.1150195 · DOI
- 10.18637/jss.v015.i02 · DOI
- Hardin J. W, 2003, Generalized estimating equations
- 10.1016/j.ppees.2011.03.003 · DOI
- 10.1111/j.1365-2664.2009.01695.x · DOI
- 10.1890/06-0957.1 · DOI
- 10.1111/j.1365-2664.2009.01642.x · DOI
- 10.1111/j.1365-2656.2012.01955.x · DOI
- 10.1007/s10980-011-9620-4 · DOI
- 10.1093/biomet/73.1.13 · DOI · Paper page
- Manly B. F. J, 2002, Resource selection by animals. Statistical design and analysis for field studies
- Morris P. A, 2008, Mammals of the British Isles: handbook, 241
- 10.1890/1051-0761(2002)012[0900:HWDEBP]2.0.CO;2 · DOI
- 10.1111/j.0006-341X.2001.00120.x · DOI
- 10.1371/journal.pone.0049390 · DOI · Paper page
- 10.1111/j.1365-2656.2010.01736.x · DOI
- R Development Core Team, 2011, R: a language and environment for statistical computing. Reference index version 2.13.0
- 10.1016/j.tree.2011.10.008 · DOI
- 10.1890/09-2190.1 · DOI · Paper page
- 10.1017/S1367943004001313 · DOI
- Reeve N. J, 1994, Hedgehogs
- 10.1007/BF03195183 · DOI
- 10.1111/j.1365-2664.2010.01806.x · DOI
- 10.1046/j.1365-2435.2002.00651.x · DOI
- 10.1007/s10980-010-9473-2 · DOI
- 10.1016/j.landurbplan.2007.03.005 · DOI
- Savicky P, 2009, pspearman: Spearman's rank correlation test. Version 0.2-5
- 10.1111/j.1365-2664.2011.01970.x · DOI
- 10.1890/11-0815.1 · DOI
- 10.1111/j.1365-294X.2010.04745.x · DOI · Paper page
- 10.1007/s10531-004-5014-0 · DOI
- 10.1111/j.1365-294X.2010.04657.x · DOI · Paper page
- 10.1007/s00442-006-0500-6 · DOI
- Swisstopo, 2011, Vector25. Das digitale Landschaftsmodell der Schweiz
- 10.1046/j.1365-294X.2003.02040.x · DOI
- 10.2307/3544927 · DOI · Paper page
- 10.1017/CBO9780511754821.003 · DOI
- 10.1007/s10980-013-9861-5 · DOI
- 10.18356/08b807d4-en · DOI
- 10.1890/0012-9658(2001)082[1205:LCAGTP]2.0.CO;2 · DOI
- 10.1111/j.1461-0248.2008.01271.x · DOI · Paper page
- White G. C, 1990, Analysis of wildlife radio-tracking data
- 10.1023/A:1016223907962 · DOI
- 10.1016/S0169-7439(00)00122-2 · DOI
- 10.1111/j.1469-7998.2006.00078.x · DOI
- Zingg R, 1994, Aktivität sowie Habitat- und Raumnutzung von Igeln (Erinaceus eruopaeus) in einem ländlichen Siedlungsgebiet
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Circuit‐theory applications to connectivity science and conservation
Dickson, B. G., Albano, C. M., Anantharaman, R., Beier, P., Fargione, J., Graves, T. A., Gray, M. E., Hall, K. R., Lawler, J. J., Leonard, P. B., et al. (2019) · Conservation Biology · doi:10.1111/cobi.13230 · Cited by 461
Metadata
- Authors
- Braaker, S., Moretti, M., Boesch, R., Ghazoul, J., Obrist, M. K., & Bontadina, F.
- Venue
- Ecological Applications
- Publisher
- Wiley
- Published
- 2014-10
- Volume
- 24
- Issue
- 7
- Pages
- 1583-1595
- ISSN
- 1051-0761
- 1939-5582
- Cited by
- 121
- References
- 4
- Language
- en
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