Mapping large areas for planning and conservation is a challenge undergoing rapid transformation. For centuries, the creation of broad-extent maps was the near-exclusive domain of expert specialist cartographers, who painstakingly delineated regions of relative homogeneity with respect to a given set of criteria. In the satellite era, it has become possible to rapidly create and update categorizations of Earth’s surface with improved speed and flexibility. Land cover datasets and landscape metrics offer a vast set of information for viewing and quantifying land cover across large areas. Comprehending the patterns revealed by hundreds of possibly relevant landscape metric values, however, remains a daunting task. We studied the information content of a large set of landscape pattern metrics across Quebec, Canada, asking whether they were capable of making consistent, spatially cohesive distinctions among patterns in landscapes. We evaluated the possibility of metrics to identify representative landscapes for efficient sampling or conservation, and determined areas where differences in nearby landscape patterns were the most and least pronounced. This approach can serve as a template for a landscape perspective on the challenges that will be faced in the near future by planners and conservationists working across large areas.
References
[1]
Olson, D.M.; Dinerstein, E.; Wikramanayake, E.D.; Burgess, N.D.; Powell, G.V.N.; Underwood, E.C.; D’Amico, J.A.; Itoua, I.; Strand, H.E.; Morrison, J.C.; et al. Terrestrial ecoregions of the worlds: A new map of life on Earth. BioScience 2001, 51, 933–938, doi:10.1641/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2.
[2]
Coops, N.C.; Wulder, M.A.; Iwanicka, D. An environmental domain classification of Canada using earth observation data for biodiversity assessment. Ecol. Inform. 2009, 4, 8–22, doi:10.1016/j.ecoinf.2008.09.005.
[3]
Robitaille, A.; Saucier, J.P. Paysages Régionaux du Québec Méridional; Les Publications du Québec: Québec, QC, Canada, 1998; p. 213.
[4]
Mackey, B.G.; Berry, S.L.; Brown, T. Reconciling approaches to biogeographical regionalization: A systematic and generic framework examined with a case study of the Australian continent. J. Biogeogr. 2008, 35, 213–229, doi:10.1111/j.1365-2699.2007.01822.x.
[5]
Hargrove, W.W.; Hoffman, F.M. Using multivariate clustering to characterize ecoregion borders. Comput. Sci. Eng. 1999, 1, 18–25, doi:10.1109/5992.774837.
[6]
Loveland, T.R.; Merchant, J.M. Ecoregions and ecoregionalization: Geographical and ecological perspectives. Environ. Manag. 2004, 34, S1–S13, doi:10.1007/s00267-003-5181-x.
[7]
Grandmont, K.; Fortier, D.; Cardille, J.A. Multi-Criteria Analysis with Geographic Information Systems in Changing Permafrost Environments: Opportunities and Limits. In Cold Regions Engineering 2012: Sustainable Infrastructure Development in a Changing Cold Environment; Morse, B., Dore, G., Eds.; American Society of Civil Engineers (ASCE): Reston, VA, USA, 2012; pp. 666–675.
Heikkinen, R.K.; Luoto, M.; Araujo, M.B.; Virkkala, R.; Thuiller, W.; Sykes, M.T. Methods and uncertainties in bioclimatic envelope modelling under climate change. Prog. Phys. Geogr. 2006, 30, 751–777, doi:10.1177/0309133306071957.
[10]
Allen, C.D.; Macalady, A.K.; Chenchouni, H.; Bachelet, D.; McDowell, N.; Vennetier, M.; Kitzberger, T.; Rigling, A.; Breshears, D.D.; Hogg, E.H.; et al. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For. Ecol. Manag. 2010, 259, 660–684, doi:10.1016/j.foreco.2009.09.001.
[11]
Millar, C.I.; Stephenson, N.L.; Stephens, S.L. Climate change and forests of the future: Managing in the face of uncertainty. Ecol. Appl. 2007, 17, 2145–2151, doi:10.1890/06-1715.1.
Turner, M.G. Landscape ecology: What is the state of the science? Annu. Rev. Ecol. Evol. Syst. 2005, 36, 319–344, doi:10.1146/annurev.ecolsys.36.102003.152614.
[14]
Turner, M.G.; Gardner, R.H.; O’Neil, R.V. Landscape Ecology in Theory and Practice: Pattern and Process, 1st ed. ed.; Springer-Verlag: New York, NY, USA, 2001; p. 404.
[15]
Bergeron, Y.; Gauthier, S.; Kafka, V.; Lefort, P.; Lesieur, D. Natural fire frequency for the eastern Canadian boreal forest: Consequences for sustainable forestry. Can. J. For. Res. 2001, 31, 384–391, doi:10.1139/x00-178.
[16]
Boucher, Y.; Arseneault, D.; Sirois, L.; Blais, L. Logging pattern and landscape changes over the last century at the boreal and deciduous forest transition in Eastern Canada. Landsc. Ecol. 2009, 24, 171–184, doi:10.1007/s10980-008-9294-8.
[17]
Boucher, Y.; Arseneault, D.; Sirois, L. Logging-induced change (1930–2002) of a preindustrial landscape at the northern range limit of northern hardwoods, eastern Canada. Can. J. For. Res. 2006, 36, 505–517, doi:10.1139/x05-252.
[18]
Boucher, Y.; Grondin, P. Impact of logging and natural stand-replacing disturbances on high-elevation boreal landscape dynamics (1950–2005) in eastern Canada. For. Ecol. Manag. 2012, 263, 229–239, doi:10.1016/j.foreco.2011.09.012.
[19]
Lillesand, T.M.; Kiefer, R.W.; Chipman, J.W. Remote Sensing and Image Interpretation, 6th ed. ed.; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2008; p. 756.
[20]
Loveland, T.R.; Reed, B.C.; Brown, J.F.; Ohlen, D.O.; Zhu, Z.; Yang, L.; Merchant, J.W. Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data. Int. J. Remote Sens. 2000, 21, 1303–1330, doi:10.1080/014311600210191.
[21]
Latifovic, R.; Zhu, Z.L.; Cihlar, J.; Giri, C.; Olthof, I. Land cover mapping of north and central America—Global land cover 2000. Remote Sens. Environ. 2004, 89, 116–127, doi:10.1016/j.rse.2003.11.002.
[22]
Prince, S.D.; Steininger, M.K. Biophysical stratification of the Amazon basin. Glob. Chang. Biol. 1999, 5, 1–22, doi:10.1046/j.1365-2486.1998.00220.x.
[23]
Chen, G.; Hay, G.J.; St-Onge, B. A GEOBIA framework to estimate forest parameters from lidar transects, Quickbird imagery and machine learning: A case study in Quebec, Canada. Int. J. Appl. Earth Obs. Geoinf. 2012, 15, 28–37, doi:10.1016/j.jag.2011.05.010.
[24]
Chen, G.; Hay, G.J. An airborne lidar sampling strategy to model forest canopy height from Quickbird imagery and GEOBIA. Remote Sens. Environ. 2011, 115, 1532–1542, doi:10.1016/j.rse.2011.02.012.
[25]
Hay, G.J.; Blaschke, T. Special issue: Geographic Object-Based Image Analysis (GEOBIA) foreword. Photogramm. Eng. Remote Sens. 2010, 76, 121–122.
[26]
Ramankutty, N.; Evan, A.T.; Monfreda, C.; Foley, J.A. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Glob. Biogeochem. Cycle. 2008, doi:10.1029/2007GB002952.
[27]
Monfreda, C.; Ramankutty, N.; Foley, J.A. Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Glob. Biogeochem. Cycle. 2008, doi:10.1029/2007GB002947.
[28]
Girvetz, E.H.; Thorne, J.H.; Berry, A.M.; Jaeger, J.A.G. Integration of landscape fragmentation analysis into regional planning: A statewide multi-scale case study from California, USA. Landsc. Urban Plan. 2008, 86, 205–218, doi:10.1016/j.landurbplan.2008.02.007.
[29]
Cardille, J.A.; Foley, J.A. Agricultural land-use change in Brazilian Amazonia between 1980 and 1995: Evidence from integrated satellite and census data. Remote Sens. Environ. 2003, 87, 551–562, doi:10.1016/j.rse.2002.09.001.
[30]
Cardille, J.A.; Foley, J.A.; Costa, M.H. Characterizing patterns of agricultural land use in Amazonia by merging satellite classifications and census data. Glob. Biogeochem. Cycle. 2002, doi:10.1029/2000GB001386.
[31]
Ellis, E.C.; Ramankutty, N. Putting people in the map: Anthropogenic biomes of the world. Front. Ecol. Environ. 2008, 6, 439–447, doi:10.1890/070062.
[32]
Gustafson, E.J. Quantifying landscape spatial pattern: What is the state of the art? Ecosystems 1998, 1, 143–156, doi:10.1007/s100219900011.
[33]
Peng, J.; Wang, Y.; Zhang, Y.; Wu, J.; Li, W.; Li, Y. Evaluating the effectiveness of landscape metrics in quantifying spatial patterns. Ecol. Indic. 2010, 10, 217–223, doi:10.1016/j.ecolind.2009.04.017.
[34]
Li, H.B.; Wu, J.G. Use and misuse of landscape indices. Landsc. Ecol. 2004, 19, 389–399, doi:10.1023/B:LAND.0000030441.15628.d6.
[35]
Kupfer, J.A. National assessments of forest fragmentation in the US. Glob. Environ. Chang. 2006, 16, 73–82, doi:10.1016/j.gloenvcha.2005.10.003.
[36]
Wulder, M.A.; White, J.C.; Han, T.; Coops, N.C.; Cardille, J.A.; Holland, T.; Grills, D. Monitoring Canada’s forests. Part 2: National forest fragmentation and pattern. Can. J. Remote Sens. 2008, 34, 563–584, doi:10.5589/m08-081.
[37]
Riitters, K.H.; Wickham, J.D.; O’Neill, R.V.; Jones, K.B.; Smith, E.R.; Coulston, J.W.; Wade, T.G.; Smith, J.H. Fragmentation of continental United States forests. Ecosystems 2002, 5, 815–822, doi:10.1007/s10021-002-0209-2.
[38]
Riitters, K.; Wickham, J.; O’Neill, R.; Jones, B.; Smith, E. Global-scale patterns of forest fragmentation. Conserv. Ecol. 2000, 4, 3.
[39]
Wade, T.G.; Riitters, K.H.; Wickham, J.D.; Jones, K.B. Distribution and causes of global forest fragmentation. Conserv. Ecol. 2003, 7, 7.
Cardille, J.; Turner, M.; Clayton, M.; Gergel, S.; Price, S. Metaland: Characterizing spatial patterns and statistical context of landscape metrics. BioScience 2005, 55, 983–988, doi:10.1641/0006-3568(2005)055[0983:MCSPAS]2.0.CO;2.
[42]
Long, J.; Nelson, T.; Wulder, M. Regionalization of landscape pattern indices using multivariate cluster analysis. Environ. Manag. 2010, 46, 134–142, doi:10.1007/s00267-010-9510-6.
[43]
Kupfer, J.A.; Gao, P.; Guo, D. Regionalization of forest pattern metrics for the continental United States using contiguity constrained clustering and partitioning. Ecol. Inform. 2012, 9, 11–18, doi:10.1016/j.ecoinf.2012.02.001.
[44]
Hargrove, W.W.; Hoffman, F.M. Potential of multivariate quantitative methods for delineation and visualization of ecoregions. Environ. Manag. 2004, 34, S39–S60, doi:10.1007/s00267-003-1084-0.
[45]
Frey, B.J.; Dueck, D. Clustering by passing messages between data points. Science 2007, 315, 972–976, doi:10.1126/science.1136800.
[46]
Cardille, J.A.; Lambois, M. From the redwood forest to the Gulf Stream waters: Human signature nearly ubiquitous in representative US landscapes. Front. Ecol. Environ. 2010, 8, 130–134, doi:10.1890/080132.
[47]
Cardille, J.A.; White, J.C.; Wulder, M.A.; Holland, T. Representative landscapes in the forested area of Canada. Environ. Manag. 2012, 49, 163–173, doi:10.1007/s00267-011-9785-2.
[48]
Van der Laan, M.J.; Pollard, K.S.; Bryan, J. A new partitioning around medoids algorithm. J. Stat. Comput. Simul. 2003, 73, 575–584, doi:10.1080/0094965031000136012.
[49]
Wulder, M.A.; White, J.C.; Cranny, M.; Hall, R.J.; Luther, J.E.; Beaudoin, A.; Goodenough, D.G.; Dechka, J.A. Monitoring Canada’s forests. Part 1: Completion of the EOSD land cover project. Can. J. Remote Sens. 2008, 34, 549–562, doi:10.5589/m08-066.
[50]
Institut de la statistique du Québec (ISQ). Le Québec Chiffres en Main—Québec Handy Numbers; Institut de la Statistique du Québec, Gouvernement du Québec: Québec, QC, Canada, 2011; p. 72.
[51]
Zones de Végétation et Domaines Biolimatiques du Québec. Ministère des Ressources Naturelles et de la Faune du Québec (MRNF). Available online: http://www.mrnf.gouv.qc.ca/forets/connaissances/connaissances-inventaire-zones-carte.jsp (accessed on 18 October 2013).
[52]
Pan, D.; Domon, G.; de Blois, S.; Bouchard, A. Temporal (1958 to 1993) and spatial patterns of land use changes in Haut-Saint-Laurent (Quebec, Canada) and their relation to landscape physical attributes. Landsc. Ecol. 1999, 14, 35–52, doi:10.1023/A:1008022028804.
[53]
System of Agents for Forest Observation Research with Automation Hierarchies. SAFORAH. Available online: http://www.saforah.org (accessed on 29 October 2013).
[54]
Cushman, S.A.; McGarigal, K.; Neel, M.C. Parsimony in landscape metrics: Strength, universality, and consistency. Ecol. Indic. 2008, 8, 691–703, doi:10.1016/j.ecolind.2007.12.002.
[55]
McGarigal, K.; Cushman, S.A.; Neel, M.C.; Ene, E. FRAGSTATS: Spatial Pattern Analysis Program for Categorical Maps (Version 3.3); The University of Massachusetts: Amherst, MA, USA, 2002.
[56]
Riitters, K.H.; Oneill, R.V.; Hunsaker, C.T.; Wickham, J.D.; Yankee, D.H.; Timmins, S.P.; Jones, K.B.; Jackson, B.L. A factor-analysis of landscape pattern and structure metrics. Landsc. Ecol. 1995, 10, 23–39, doi:10.1007/BF00158551.
[57]
O’Neill, R.V.; Riitters, K.H.; Wickham, J.D.; Jones, K.B. Landscape pattern metrics and regional assessment. Ecosyst. Health 1999, 5, 225–233, doi:10.1046/j.1526-0992.1999.09942.x.
[58]
Cain, D.H.; Riitters, K.; Orvis, K. A multi-scale analysis of landscape statistics. Landsc. Ecol. 1997, 12, 199–212, doi:10.1023/A:1007938619068.
[59]
Bodenhofer, U.; Kothmeier, A.; Hochreiter, S. APCluster: An R package for affinity propagation clustering. Bioinformatics 2011, 27, 2463–2464, doi:10.1093/bioinformatics/btr406.
[60]
R Development Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2011.
[61]
Sarr, D.A.; Hibbs, D.E.; Huston, M.A. A hierarchical perspective of plant diversity. Q. Rev. Biol. 2005, 80, 187–212, doi:10.1086/433058.
[62]
Ministère des Ressources Naturelles du Québec (MRN). La Limite Nordique des Forêts Attribuables; Ministère des Ressources Naturelles, Gouvernement du Québec: Québec, QC, Canada, 2000; p. 101.
[63]
Keller, M.; Schimel, D.S.; Hargrove, W.W.; Hoffman, F.M. A continental strategy for the National Ecological Observatory Network. Front. Ecol. Environ. 2008, 6, 282–284, doi:10.1890/1540-9295(2008)6[282:ACSFTN]2.0.CO;2.
