Abstract
Assessments of large-scale changes in habitat are a priority for management and conservation. Traditional approaches use land use and land cover data (LULC) that focus mostly on “structural” properties of landscapes, rather than “functional” properties related to specific ecological processes. Here, we contend that designing functional analyses of LULC can provide important and complementary information to traditional, structural analyses. We substantiate this perspective with an example of functional changes in habitat due to industrial anthropogenic footprints in Alberta’s boreal forest, where there has been little overall forest loss (~ 6% structural change), but high levels of functional change (up to 93% functional change) for species’ habitat, biodiversity, and wildfire ignition. We discuss the methods needed to achieve functional LULC analyses, when they are most appropriate to add to structural assessments, and conclude by providing recommendations for analyses of LULC in a future of increasingly high-resolution, dynamic remote sensing data.
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References
Abdi, A.M. 2013. Integrating open access geospatial data to map the habitat suitability of the declining corn bunting (Miliaria calandra). ISPRS International Journal of Geo-Information 2 (4): 935–954. https://doi.org/10.3390/ijgi2040935.
Arienti, M.C., S.G. Cumming, M.A. Krawchuk, and S. Boutin. 2009. Road network density correlated with increased lightning fire incidence in the Canadian western boreal forest. International Journal of Wildland Fire 18: 970–982. https://doi.org/10.1071/WF08011.
Bayne, E.M., S.L. Van Wilgenburg, S. Boutin, and K.A. Hobson. 2005. Modeling and field-testing of Ovenbird (Seiurus aurocapillus) responses to boreal forest dissection by energy sector development at multiple spatial scales. Landscape Ecology 20: 203–216. https://doi.org/10.1007/s10980-004-2265-9.
Borra, S., R. Thanki, and N. Dey. 2019. Satellite image analysis: Clustering and classification., SpringerBriefs in applied sciences and technology Singapore: Springer. https://doi.org/10.1007/978-981-13-6424-2.
Campbell, M.A., B. Kopach, P.E. Komers, and A.T. Ford. 2019. Quantifying the impacts of oil sands development on wildlife: perspectives from impact assessments. Environmental Reviews 9: 1–9. https://doi.org/10.1139/er-2018-0118.
Coops, N.C., and M.A. Wulder. 2019. Breaking the habit(at). Trends in Ecology and Evolution 34: 585–587. https://doi.org/10.1016/j.tree.2019.04.013.
Cousins, S.A.O., A.G. Auffret, J. Lindgren, and L. Tränk. 2015. Regional-scale land-cover change during the 20th century and its consequences for biodiversity. Ambio 44: 17–27. https://doi.org/10.1007/s13280-014-0585-9.
Crooks, K.R., C.L. Burdett, D.M. Theobald, S.R.B. King, M. Di Marco, C. Rondinini, and L. Boitani. 2017. Quantification of habitat fragmentation reveals extinction risk in terrestrial mammals. Proceedings of the National academy of Sciences of the United States of America 114: 7635–7640. https://doi.org/10.1073/pnas.1705769114.
Curtis, J.T. 1956. The modification of mid-latitude grasslands and forests by man. In Man’s role in changing the face of the earth, ed. W.L. Thomas Jr., 721–736. Chicago: University of Chicago Press.
Dabros, A., H.E. James Hammond, J. Pinzon, B. Pinno, and D. Langor. 2017. Edge influence of low-impact seismic lines for oil exploration on upland forest vegetation in northern Alberta (Canada). Forest Ecology and Management 400: 278–288. https://doi.org/10.1016/j.foreco.2017.06.030.
Dabros, A., M. Pyper, and G. Castilla. 2018. Seismic lines in the boreal and arctic ecosystems of North America: Environmental impacts, challenges, and opportunities. Environmental Reviews 16: 1–16. https://doi.org/10.1139/er-2017-0080.
Daskalova, G.N., I.H. Myers-Smith, A.D. Bjorkman, S.A. Blowes, S.R. Supp, A.E. Magurran, and M. Dornelas. 2020. Landscape-scale forest loss as a catalyst of population and biodiversity change. Science 368: 1341–1347. https://doi.org/10.1126/science.aba1289.
Dennis, R.L.H., T.G. Shreeve, and H. Van Dyck. 2003. Towards a functional resource-based concept for habitat: A butterfly biology viewpoint. Oikos 102: 417–426.
Dickie, M., R.S. McNay, G.D. Sutherland, M. Cody, and T. Avgar. 2019. Corridors or risk? Movement along, and use of, linear features vary predictably among large mammal predator and prey species. Journal of Animal Ecology 1365–2656: 13130. https://doi.org/10.1111/1365-2656.13130.
Dungan, J.L., J.N. Perry, M.R.T.T. Dale, P. Legendre, S. Citron-Pousty, M.-J.J. Fortin, A. Jakomulska, M. Miriti, et al. 2002. A balanced view of scale in spatial statistical analysis. Ecography 25: 626–640. https://doi.org/10.1034/j.1600-0587.2002.250510.x.
Environment Canada. 2011. Recovery Strategy for the Woodland Caribou, Boreal population (Rangifer tarandus caribou) in Canada. Species at Risk Act, Recovery Strategy Series. Environment Canada, Ottawa. xi + 138 pp.
Fahrig, L. 2020. Why do several small patches hold more species than few large patches? Edited by David Storch. Global Ecology and Biogeography. https://doi.org/10.1111/geb.13059.
Fahrig, L., J. Baudry, L. Brotons, F.G. Burel, T.O. Crist, R.J. Fuller, C. Sirami, G.M. Siriwardena, et al. 2011. Functional landscape heterogeneity and animal biodiversity in agricultural landscapes. Ecology Letters 14: 101–112. https://doi.org/10.1111/j.1461-0248.2010.01559.x.
Farwell, L.S., P.R. Elsen, E. Razenkova, A.M. Pidgeon, and V.C. Radeloff. 2020. Habitat heterogeneity captured by 30-m resolution satellite image texture predicts bird richness across the United States. Ecological Applications In Press. https://doi.org/10.1002/eap.2157.
Fisher, J.T., and A.C. Burton. 2018. Wildlife winners and losers in an oil sands landscape. Frontiers in Ecology and the Environment 16: 323–328. https://doi.org/10.1002/fee.1807.
Flannigan, M.D., M.A. Krawchuk, W.J. de Groot, M.B. Wotton, and L.M. Gowman. 2009. Implications of changing climate for global wildland fire. International Journal of Wildland Fire 18: 483–507. https://doi.org/10.1071/WF08187.
Gustafson, E.J. 2018. How has the state-of-the-art for quantification of landscape pattern advanced in the twenty-first century? Landscape Ecology. https://doi.org/10.1007/s10980-018-0709-x.
Haddad, N.M., L.A. Brudvig, J. Clobert, K.F. Davies, A. Gonzalez, R.D. Holt, T.E. Lovejoy, J.O. Sexton, et al. 2015. Habitat fragmentation and its lasting impact on Earth’s ecosystems. Science Advances 1: 1–10. https://doi.org/10.1126/sciadv.1500052.
Hanski, I. 1998. Metapopulation dynamics. Nature 396: 41–49. https://doi.org/10.1016/0169-5347(89)90061-X.
Jacob, F. 1988. The statue within: An autobiography. New York: Cold Spring Harbor Laboratory Press.
Jetz, W., M.A. McGeoch, R. Guralnick, S. Ferrier, J. Beck, M.J. Costello, M. Fernandez, G.N. Geller, et al. 2019. Essential biodiversity variables for mapping and monitoring species populations. Nature Ecology and Evolution 3: 539–551. https://doi.org/10.1038/s41559-019-0826-1.
Jordaan, S.M. 2012. Land and water impacts of oil sands production in Alberta. Environmental Science and Technology 46: 3611–3617. https://doi.org/10.1021/es203682m.
Kareiva, P., and M. Marvier. 2012. What is conservation science? BioScience 62: 962–969. https://doi.org/10.1525/bio.2012.62.11.5.
Kattenborn, T., F.E. Fassnacht, and S. Schmidtlein. 2019. Differentiating plant functional types using reflectance: Which traits make the difference? Remote Sensing in Ecology and Conservation 5: 5–19. https://doi.org/10.1002/rse2.86.
Lechner, A.M., W.T. Langford, S.D. Jones, S.A. Bekessy, and A. Gordon. 2012. Investigating species–environment relationships at multiple scales: Differentiating between intrinsic scale and the modifiable areal unit problem. Ecological Complexity 11: 91–102. https://doi.org/10.1016/j.ecocom.2012.04.002.
Lechner, A.M., C.M. Raymond, V.M. Adams, M. Polyakov, A. Gordon, J.R. Rhodes, M. Mills, A. Stein, et al. 2014. Characterizing spatial uncertainty when integrating social data in conservation planning. Conservation Biology 28: 1497–1511. https://doi.org/10.1111/cobi.12409.
Mahon, C.L., G.L. Holloway, E.M. Bayne, and J.D. Toms. 2019. Additive and interactive cumulative effects on boreal landbirds: Winners and losers in a multi-stressor landscape. Ecological Applications. https://doi.org/10.1002/eap.1895.
McGarigal, K. 2014. Landscape Pattern Metrics. In Wiley StatsRef: Statistics Reference Online, ed. J.N. Rao. Chichester: Wiley.
Meijer, J.R., M.A.J. Huijbregts, K.C.G.J. Schotten, and A.M. Schipper. 2018. Global patterns of current and future road infrastructure. Environmental Research Letters 13: 1–10. https://doi.org/10.1088/1748-9326/aabd42.
Mendoza-Ponce, A., R.O. Corona-Núñez, L. Galicia, and F. Kraxner. 2019. Identifying hotspots of land use cover change under socioeconomic and climate change scenarios in Mexico. Ambio 48: 336–349. https://doi.org/10.1007/s13280-018-1085-0.
Newbold, T., L.N. Hudson, S.L.L. Hill, S. Contu, I. Lysenko, R.A. Senior, L. Börger, D.J. Bennett, et al. 2015. Global effects of land use on local terrestrial biodiversity. Nature 520: 45–50. https://doi.org/10.1038/nature14324.
Nielsen, S.E., M.S. Boyce, and G.B. Stenhouse. 2004. Grizzly bears and forestry: I. Selection of clearcuts by grizzly bears in west-central Alberta, Canada. Forest Ecology and Management. https://doi.org/10.1016/j.foreco.2004.04.014.
Nielsen, S.E., E.M. Bayne, J. Schieck, J. Herbers, and S. Boutin. 2007. A new method to estimate species and biodiversity intactness using empirically derived reference conditions. Biological Conservation 137: 403–414. https://doi.org/10.1016/j.biocon.2007.02.024.
Oeser, J., M. Heurich, C. Senf, D. Pflugmacher, E. Belotti, and T. Kuemmerle. 2020. Habitat metrics based on multi-temporal Landsat imageryfor mapping large mammal habitat. Remote Sensing in Ecology and Conservation 6: 52–69. https://doi.org/10.1002/rse2.122.
O’Neill, R.V., J.R. Krummel, R.H. Gardner, G. Sugihara, B. Jackson, D.L. DeAngelis, B.T. Milne, M.G. Turner, et al. 1988. Indices of landscape pattern. Landscape Ecology 1: 153–162. https://doi.org/10.1007/BF00162741.
Pindozzi, S., E. Cervelli, A. Capolupo, C. Okello, and L. Boccia. 2016. Using historical maps to analyze two hundred years of land cover changes: Case study of Sorrento peninsula (south Italy). Cartography and Geographic Information Science 43: 250–265. https://doi.org/10.1080/15230406.2015.1072736.
Sadoti, G., A.L. Jones, W.G. Shriver, and P.D. Vickery. 2017. Employing landscape metrics in an open population model to estimate demographic parameters of a grassland bird. Landscape Ecology 32: 1553–1562. https://doi.org/10.1007/s10980-017-0535-6.
Riitters, K.H., J.D. Wickham, and J.W. Coulston. 2004. A preliminary assessment of Montréal process indicators of forest fragmentation for the United States. Environmental Monitoring and Assessment 91: 257–276. https://doi.org/10.1023/B:EMAS.0000009240.65355.92.
Riva, F., and S.E. Nielsen. 2020. Six key steps for functional landscape analyses of habitat change. Landscape Ecology. https://doi.org/10.1007/s10980-020-01048-y.
Riva, F., J.H. Acorn, and S.E. Nielsen. 2018a. Localized disturbances from oil sands developments increase butterfly diversity and abundance in Alberta’s boreal forests. Biological Conservation 217: 173–180. https://doi.org/10.1016/j.biocon.2017.10.022.
Riva, F., J.H. Acorn, and S.E. Nielsen. 2018b. Narrow anthropogenic corridors direct the movement of a generalist boreal butterfly. Biology Letters. https://doi.org/10.1098/rsbl.2017.0770.
Riva, F., J. Pinzon, J.H. Acorn, and S.E. Nielsen. 2020. Composite effects of cutlines and wildfire result in fire refuges for plants and butterflies in boreal treed peatlands. Ecosystems 23: 485–497. https://doi.org/10.1007/s10021-019-00417-2.
Roberts, D., S. Ciuti, Q.E. Barber, C. Willier, and S.E. Nielsen. 2018. Accelerated seed dispersal along linear disturbances in the Canadian oil sands region. Scientific Reports. https://doi.org/10.1038/s41598-018-22678-y.
Rooney, R.C., S.E. Bayley, and D.W. Schindler. 2012. Oil sands mining and reclamation cause massive loss of peatland and stored carbon. Proceedings of the National academy of Sciences of the United States of America 109: 4933–4937. https://doi.org/10.1073/pnas.1.
Rosa, L., K.F. Davis, M.C. Rulli, and P. D’Odorico. 2017. Environmental consequences of oil production from oil sands. Earth’s Future 5: 158–170. https://doi.org/10.1002/2016EF000484.
Soulé, M.E. 1985. What is Conservation Biology? A new synthetic discipline addresses the dynamics and problems of perturbed species, communities, and ecosystems. BiosSience. https://doi.org/10.2307/1310054.
Stern, E., F. Riva, and S. Nielsen. 2018. Effects of narrow linear disturbances on light and wind patterns in fragmented boreal forests in Northeastern Alberta. Forests 9: 486. https://doi.org/10.3390/f9080486.
Taubert, F., R. Fischer, J. Groeneveld, S. Lehmann, M.S. Müller, E. Rödig, T. Wiegand, and A. Huth. 2018. Global patterns of tropical forest fragmentation. Nature 554: 519–522. https://doi.org/10.1038/nature25508.
Tigner, J., E.M. Bayne, and S. Boutin. 2015. American Marten respond to seismic lines in Northern Canada at two spacial scales. PLoS ONE 10: e0118720. https://doi.org/10.1371/journal.pone.0118720.
Tingley, M.W., E.S. Darling, and D.S. Wilcove. 2014. Fine- and coarse-filter conservation strategies in a time of climate change. Annals of the New York Academy of Sciences 1322: 92–109. https://doi.org/10.1111/nyas.12484.
Tischendorf, L., and L. Fahrig. 2000. On the usage and measurement of landscape connectivity. Oikos 90: 7–19. https://doi.org/10.1034/j.1600-0706.2000.900102.x.
Tuanmu, M.N., and W. Jetz. 2014. A global 1-km consensus land-cover product for biodiversity and ecosystem modelling. Global Ecology and Biogeography 23: 1031–1045. https://doi.org/10.1111/geb.12182.
van Rensen, C.K., S.E. Nielsen, B. White, T. Vinge, and V.J. Lieffers. 2015. Natural regeneration of forest vegetation on legacy seismic lines in boreal habitats in Alberta’s oil sands region. Biological Conservation 184: 127–135. https://doi.org/10.1016/j.biocon.2015.01.020.
Watling, J.I., V. Arroyo-Rodríguez, M. Pfeifer, L. Baeten, C. Banks-Leite, L.M. Cisneros, R. Fang, A.C. Hamel-Leigue, et al. 2020. Support for the habitat amount hypothesis from a global synthesis of species density studies. Ecology Letters 23: 674–681. https://doi.org/10.1111/ele.13471.
Wickham, J., and K.H. Riitters. 2019. Influence of high-resolution data on the assessment of forest fragmentation. Landscape Ecology. https://doi.org/10.1007/s10980-019-00820-z.
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Riva, F., Nielsen, S.E. A functional perspective on the analysis of land use and land cover data in ecology. Ambio 50, 1089–1100 (2021). https://doi.org/10.1007/s13280-020-01434-5
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DOI: https://doi.org/10.1007/s13280-020-01434-5