Cost distances and least cost paths respond differently to cost scenario variations: a sensitivity analysis of ecological connectivity modeling

References

• Adriaensen, F., et al. 2003. The application of least-cost modelling as a functional landscape model. Landscape and Urban Planning, 64 (4), 233–247. doi:10.1016/S0169-2046(02)00242-6
   Web of Science ®Google Scholar
• Balbi, M., et al., 2019. Ecological relevance of least cost path analysis: an easy implementation method for landscape urban planning. Journal of Environmental Management, 244, 61–68. doi:10.1016/j.jenvman.2019.04.124
   PubMed Web of Science ®Google Scholar
• Balkenhol, N., et al. 2013. Landscape-level comparison of genetic diversity and differentiation in a small mammal inhabiting different fragmented landscapes of the Brazilian Atlantic Forest. Conservation Genetics, 14 (2), 355–367. doi:10.1007/s10592-013-0454-2
   Web of Science ®Google Scholar
• Beier, P., Majka, D.R., and Newell, S.L., 2009. Uncertainty analysis of least-cost modeling for designing wildlife linkages. Ecological Applications, 19 (8), 2067–2077. doi:10.1890/08-1898.1
   PubMed Web of Science ®Google Scholar
• Beier, P., Majka, D.R., and Spencer, W.D., 2008. Forks in the road: choices in procedures for designing wildland linkages. Conservation Biology, 22 (4), 836–851. doi:10.1111/j.1523-1739.2008.00942.x
   PubMed Web of Science ®Google Scholar
• Bowman, J., et al., 2020. Effects of cost surface uncertainty on current density estimates from circuit theory. PeerJ, 8, e9617. doi:10.7717/peerj.9617
   PubMed Web of Science ®Google Scholar
• Breiman, L., et al., 1984. Classification and regression trees. Boca Raton: CRC press.
   Google Scholar
• Burnham, K.P. and Anderson, D.R., 2004. Multimodel inference: understanding AIC and BIC in model selection. Sociological Methods & Research, 33 (2), 261–304. doi:10.1177/0049124104268644
   Web of Science ®Google Scholar
• Carrascal, L.M., Galván, I., and Gordo, O., 2009. Partial Least Squares regression as an alternative to current regression methods used in ecology. Oikos, 118 (5), 681–690. doi:10.1111/j.1600-0706.2008.16881.x
   Web of Science ®Google Scholar
• Carroll, C., McRae, B., and Brookes, A., 2012. Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America. Conservation Biology, 26 (1), 78–87. doi:10.1111/j.1523-1739.2011.01753.x
   PubMed Web of Science ®Google Scholar
• Clevenger, A.P., et al. 2002. GIS-generated, expert-based models for identifying wildlife habitat linkages and planning mitigation passages. Conservation Biology, 16 (2), 503–514. doi:10.1046/j.1523-1739.2002.00328.x
   Web of Science ®Google Scholar
• Cushman, S.A., Shirk, A.J., and Landguth, E.L., 2013. Landscape genetics and limiting factors. Conservation Genetics, 14 (2), 263–274. doi:10.1007/s10592-012-0396-0
   Web of Science ®Google Scholar
• de La Torre, J.A., et al., 2019. Using elephant movements to assess landscape connectivity under peninsular Malaysia’s central forest spine land use policy. Conservation Science and Practice, 1 (12), e133.
   Google Scholar
• Duflot, R., et al., 2018. Combining habitat suitability models and spatial graphs for more effective landscape conservation planning: an applied methodological framework and a species case study. Journal for Nature Conservation, 46, 38–47. doi:10.1016/j.jnc.2018.08.005
   Web of Science ®Google Scholar
• Etherington, T.R. and Holland, E.P., 2013. Least-cost path length versus accumulated-cost as connectivity measures. Landscape Ecology, 28 (7), 1223–1229. doi:10.1007/s10980-013-9880-2
   Web of Science ®Google Scholar
• Etherington, T.R. and Perry, G.L., 2016. Visualising continuous intra-landscape isolation with uncertainty using least-cost modelling based catchment areas: common brushtail possums in the Auckland isthmus. International Journal of Geographical Information Science, 30 (1), 36–50. doi:10.1080/13658816.2014.926365
   Web of Science ®Google Scholar
• Foltête, J.C., Girardet, X., and Clauzel, C., 2014. A methodological framework for the use of landscape graphs in land-use planning. Landscape and Urban Planning, 124, 140–150. doi:10.1016/j.landurbplan.2013.12.012
   Web of Science ®Google Scholar
• Ford, A.T., et al. 2020. Effective corridor width: linking the spatial ecology of wildlife with land use policy. European Journal of Wildlife Research, 66 (4), 1–10. doi:10.1007/s10344-020-01385-y
   Web of Science ®Google Scholar
• Gonzales, E.K. and Gergel, S.E., 2007. Testing assumptions of cost surface analysis - a tool for invasive species management. Landscape Ecology, 22 (8), 1155–1168. doi:10.1007/s10980-007-9106-6
   Web of Science ®Google Scholar
• Graves, T.A., et al. 2012. The influence of landscape characteristics and home-range size on the quantification of landscape-genetics relationships. Landscape Ecology, 27 (2), 253–266. doi:10.1007/s10980-011-9701-4
   Web of Science ®Google Scholar
• Graves, T.A., Beier, P., and Royle, J.A., 2013. Current approaches using genetic distances produce poor estimates of landscape resistance to interindividual dispersal. Molecular Ecology, 22 (15), 3888–3903. doi:10.1111/mec.12348
   PubMed Web of Science ®Google Scholar
• Gurrutxaga, M., Lozano, P.J., and Del Barrio, G., 2010. GIS-based approach for incorporating the connectivity of ecological networks into regional planning. Journal for Nature Conservation, 18 (4), 318–326. doi:10.1016/j.jnc.2010.01.005
   Web of Science ®Google Scholar
• Hanski, I., Moilanen, A., and Gyllenberg, M., 1996. Minimum viable metapopulation size. The American Naturalist, 147 (4), 527–541. doi:10.1086/285864
   Web of Science ®Google Scholar
• Hoover, B., Yaw, S., and Middleton, R., 2020. CostMAP: an open-source software package for developing cost surfaces using a multi-scale search kernel. International Journal of Geographical Information Science, 34 (3), 520–538. doi:10.1080/13658816.2019.1675885
   Web of Science ®Google Scholar
• Inglada, J., et al. 2017. Operational high resolution land cover map production at the country scale using satellite image time series. Remote Sensing, 9 (1), 95. doi:10.3390/rs9010095
   Web of Science ®Google Scholar
• James, G., et al. 2013. An introduction to statistical learning. Vol. 112. New York: Springer.
   Google Scholar
• Kadoya, T., 2009. Assessing functional connectivity using empirical data. Population Ecology, 51 (1), 5–15. doi:10.1007/s10144-008-0120-6
   Web of Science ®Google Scholar
• Khimoun, A., et al. 2017. Landscape genetic analyses reveal fine-scale effects of forest fragmentation in an insular tropical bird. Molecular Ecology, 26 (19), 4906–4919. doi:10.1111/mec.14233
   PubMed Web of Science ®Google Scholar
• Koen, E.L., Bowman, J., and Walpole, A.A., 2012. The effect of cost surface parameterization on landscape resistance estimates. Molecular Ecology Resources, 12 (4), 686–696. doi:10.1111/j.1755-0998.2012.03123.x
   PubMed Web of Science ®Google Scholar
• Lechner, A.M. and Rhodes, J.R., 2016. Recent progress on spatial and thematic resolution in landscape ecology. Current Landscape Ecology Reports, 1 (2), 98–105. doi:10.1007/s40823-016-0011-z
   Google Scholar
• Mantel, N., 1967. The detection of disease clustering and a generalized regression approach. Cancer Research, 27 (2), 209–220.
   PubMed Web of Science ®Google Scholar
• Marrotte, R.R., Bowman, J., and Shi, Y., 2017. The relationship between least-cost and resistance distance. Plos One, 12 (3), e0174212. doi:10.1371/journal.pone.0174212
   PubMed Web of Science ®Google Scholar
• McGarigal, K., 1995. Fragstats: spatial pattern analysis program for quantifying landscape structure. Vol. 351. Portland, Oregon, US: US Department of Agriculture, Forest Service, Pacific Northwest Research Station.
   Google Scholar
• McRae, B.H., 2006. Isolation by resistance. Evolution, 60 (8), 1551–1561. doi:10.1111/j.0014-3820.2006.tb00500.x
   PubMed Web of Science ®Google Scholar
• McRae, B.H. and Beier, P., 2007. Circuit theory predicts gene flow in plant and animal populations. Proceedings of the National Academy of Sciences, 104 (50), 19885–19890. doi:10.1073/pnas.0706568104
   PubMed Web of Science ®Google Scholar
• McRae, B.H. and Kavanagh, D.M., 2011. Linkage mapper connectivity analysis software. Seattle WA: The Nature Conservancy.
   Google Scholar
• Mimet, A., Clauzel, C., and Foltête, J.C., 2016. Locating wildlife crossings for multispecies connectivity across linear infrastructures. Landscape Ecology, 31 (9), 1955–1973. doi:10.1007/s10980-016-0373-y
   Web of Science ®Google Scholar
• Mony, C., et al. 2018. Effects of connectivity on animal-dispersed forest plant communities in agriculture-dominated landscapes. Journal of Vegetation Science, 29 (2), 167–178. doi:10.1111/jvs.12606
   Web of Science ®Google Scholar
• Murekatete, R.M. and Shirabe, T., 2018. A spatial and statistical analysis of the impact of transformation of raster cost surfaces on the variation of least-cost paths. International Journal of Geographical Information Science, 32 (11), 2169–2188. doi:10.1080/13658816.2018.1498504
   Web of Science ®Google Scholar
• Panzacchi, M., et al. 2016. Predicting the continuum between corridors and barriers to animal movements using step selection functions and randomized shortest paths. Journal of Animal Ecology, 85 (1), 32–42. doi:10.1111/1365-2656.12386
   PubMed Web of Science ®Google Scholar
• Pérez-Espona, S., et al. 2008. Landscape features affect gene flow of Scottish Highland red deer (Cervus elaphus). Molecular Ecology, 17 (4), 981–996. doi:10.1111/j.1365-294X.2007.03629.x
   PubMed Web of Science ®Google Scholar
• Peterman, W.E., et al. 2019. A comparison of popular approaches to optimize landscape resistance surfaces. Landscape Ecology, 34 (9), 2197–2208. doi:10.1007/s10980-019-00870-3
   Web of Science ®Google Scholar
• Peterman, W.E. and Pope, N.S., 2020. The use and misuse of regression models in landscape genetic analyses. Molecular Ecology, 30 (1), 37–47. doi:10.1111/mec.15716
   PubMed Web of Science ®Google Scholar
• Pinto, N. and Keitt, T.H., 2009. Beyond the least-cost path: evaluating corridor redundancy using a graph-theoretic approach. Landscape Ecology, 24 (2), 253–266. doi:10.1007/s10980-008-9303-y
   Web of Science ®Google Scholar
• Pressey, R., 2004. Conservation planning and biodiversity: assembling the best data for the job. Conservation Biology, 18 (6), 1677–1681. doi:10.1111/j.1523-1739.2004.00434.x
   Web of Science ®Google Scholar
• Pullinger, M.G. and Johnson, C.J., 2010. Maintaining or restoring connectivity of modified landscapes: evaluating the least-cost path model with multiple sources of ecological information. Landscape Ecology, 25 (10), 1547–1560. doi:10.1007/s10980-010-9526-6
   Web of Science ®Google Scholar
• Rayfield, B., Fortin, M.J., and Fall, A., 2010. The sensitivity of least-cost habitat graphs to relative cost surface values. Landscape Ecology, 25 (4), 519–532. doi:10.1007/s10980-009-9436-7
   Web of Science ®Google Scholar
• Rayfield, B., Fortin, M.J., and Fall, A., 2011. Connectivity for conservation: a framework to classify network measures. Ecology, 92 (4), 847–858. doi:10.1890/09-2190.1
   PubMed Web of Science ®Google Scholar
• Ricketts, T.H., 2001. The matrix matters: effective isolation in fragmented landscapes. The American Naturalist, 158 (1), 87–99. doi:10.1086/320863
   PubMed Web of Science ®Google Scholar
• Roy, K., Kar, S., and Das, R.N., 2015. Statistical methods in QSAR/QSPR. In: A primer on QSAR/QSPR modeling. Cham: Springer, 37–59.
   Google Scholar
• Ruiz-González, A., et al. 2014. Landscape genetics for the empirical assessment of resistance surfaces: the European pine marten (Martes martes) as a target-species of a regional ecological network. Plos One, 9 (10), e110552. doi:10.1371/journal.pone.0110552
   PubMed Web of Science ®Google Scholar
• Savary, P., et al., 2021. graph4lg: a package for constructing and analysing graphs for landscape genetics in R. Methods in Ecology and Evolution, 12 (3), 539–547 doi:10.1111/2041-210X.13530. : .
   Web of Science ®Google Scholar
• Sawyer, S.C., Epps, C.W., and Brashares, J.S., 2011. Placing linkages among fragmented habitats: do least-cost models reflect how animals use landscapes? Journal of Applied Ecology, 48 (3), 668–678. doi:10.1111/j.1365-2664.2011.01970.x
   Web of Science ®Google Scholar
• Schadt, S., et al. 2002. Rule-based assessment of suitable habitat and patch connectivity for the Eurasian lynx. Ecological Applications, 12 (5), 1469–1483. doi:10.1890/1051-0761(2002)012[1469:RBAOSH]2.0.CO;2
   Web of Science ®Google Scholar
• Shirabe, T., 2016. A method for finding a least-cost wide path in raster space. International Journal of Geographical Information Science, 30 (8), 1469–1485. doi:10.1080/13658816.2015.1124435
   Web of Science ®Google Scholar
• Shirk, A., et al. 2010. Inferring landscape effects on gene flow: a new model selection framework. Molecular Ecology, 19 (17), 3603–3619. doi:10.1111/j.1365-294X.2010.04745.x
   PubMed Web of Science ®Google Scholar
• Simpkins, C.E., et al., 2017. Effects of uncertain cost-surface specification on landscape connectivity measures. Ecological Informatics, 38, 1–11. doi:10.1016/j.ecoinf.2016.12.005
   Web of Science ®Google Scholar
• Simpkins, C.E., et al., 2018. Assessing the performance of common landscape connectivity metrics using a virtual ecologist approach. Ecological Modelling, 367, 13–23. doi:10.1016/j.ecolmodel.2017.11.001
   Web of Science ®Google Scholar
• Spackman, S.C. and Hughes, J.W., 1995. Assessment of minimum stream corridor width for biological conservation: species richness and distribution along mid-order streams in Vermont, USA. Biological Conservation, 71 (3), 325–332. doi:10.1016/0006-3207(94)00055-U
   Web of Science ®Google Scholar
• Spear, S.F., et al. 2010. Use of resistance surfaces for landscape genetic studies: considerations for parameterization and analysis. Molecular Ecology, 19 (17), 3576–3591. doi:10.1111/j.1365-294X.2010.04657.x
   PubMed Web of Science ®Google Scholar
• Tenenhaus, M., 1998. La régression pls: théorie et pratique. Paris: Editions TECHNIP.
   Google Scholar
• Therneau, T.M., Atkinson, B., and Ripley, M.B., 2010. The rpart package.
   Google Scholar
• Wang, Y.H., et al., 2008. Habitat suitability modelling to correlate gene flow with landscape connectivity. Landscape Ecology, 23 (8), 989–1000.
   Web of Science ®Google Scholar
• Wold, S., Sjöström, M., and Eriksson, L., 2001. PLS-regression: a basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems, 58 (2), 109–130. doi:10.1016/S0169-7439(01)00155-1
   Web of Science ®Google Scholar
• Zeller, K.A., et al. 2016. Using simulations to evaluate Mantel-based methods for assessing landscape resistance to gene flow. Ecology and Evolution, 6 (12), 4115–4128. doi:10.1002/ece3.2154
   PubMed Web of Science ®Google Scholar
• Zeller, K.A., et al. 2018. Are all data types and connectivity models created equal? validating common connectivity approaches with dispersal data. Diversity & Distributions, 24 (7), 868–879. doi:10.1111/ddi.12742
   Web of Science ®Google Scholar
• Zeller, K.A., McGarigal, K., and Whiteley, A.R., 2012. Estimating landscape resistance to movement: a review. Landscape Ecology, 27 (6), 777–797. doi:10.1007/s10980-012-9737-0
   Web of Science ®Google Scholar