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Factors limiting our understanding of ecological scale
Authors:Matthew Wheatley  Chris Johnson
Affiliation:1. Geomatics and Landscape Ecology Laboratory, Department of Biology, Carleton University, Ottawa K1S 4B6, Canada;2. Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Autónoma de México, 58190 Morelia, Michoacán, Mexico;3. Département de biologie, Université de Sherbrooke, 2500, boul. de l''Université, Sherbrooke, (Québec) J1K 2R1, Canada;4. Laboratório de Ecologia Aplicada à Conservação, Departamento de Ciências Biológicas, Universidade Estadual de Santa Cruz, Rodovia Ilhéus-Itabuna, km 16, Ilhéus, BA, CEP 45662-900, Brazil;5. Department of Biology, University of Ottawa, Ottawa, Ontario, Canada;6. Geography and Environment, University of Southampton, Room 2078, Shackleton Building (B44), Highfield Campus, Southampton SO17 1BJ, UK;7. Department of Biology, University of British Columbia, Kelowna, British Columbia, Canada;8. Environmental Science and Policy, Wickson Hall, University of California, Davis, USA;9. Concordia University Montreal, Department of Geography, Planning and Environment, 1455 de Maisonneuve Blvd. West, Suite 1255, Montréal, QC H3G 1M8, Canada;10. Natural Resources Institute, University of Manitoba, Winnipeg, MB. R3T 2N2, Canada;11. Environment and Climate Change Canada, National Wildlife Research Centre, 1125 Colonel By Drive, Ottawa, Ontario, Canada;12. Centre d''Écologie Fonctionnelle et Évolutive UMR 5175, CNRS – Université de Montpellier – Université Paul Valéry Montpellier – EPHE - IRD, 1919 route de Mende, 34293 Montpellier Cedex 5, France;13. Dept. of Ecology, Institute of Bioscience, University of Sao Paulo, rua do Matao, 321, trv. 14, 05508-090 Sao Paulo, SP, Brazil;14. The University of Queensland, School of Earth and Environmental Sciences, Brisbane, QLD 4072, Australia;15. CSIRO Land & Water, Canberra, ACT, Australia;p. Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996, USA;q. Canadian Wildlife Service, Environment and Climate Change Canada, National Wildlife Research Centre, Ottawa, ON, Canada;r. ELUTIS Modelling and Consulting Inc., 681 Melbourne Ave., Ottawa, ON K2A 1X4, Canada;s. Département de biologie, Université de Sherbrooke, 2500 boulevard de l''Université, Sherbrooke, QC J1K 2R1, Canada;t. John Carroll University, 1 John Carroll Boulevard, University Heights, OH 44118, USA;1. School of Science, University of Waikato, Hamilton, New Zealand;2. Institute of Marine Science, University of Auckland, Auckland, New Zealand;3. National Institute of Water and Atmospheric Research Ltd., Hamilton, New Zealand
Abstract:Multi-scale studies ostensibly allow us to form generalizations regarding the importance of scale in understanding ecosystem function, and in the application of the same ecological principles across a series of spatial domains. Achieving such generalizations, however, requires consistency among multi-scale studies not only in across-scale sample design, but also in basic rationales used in the choice of observational scale, including both grain and extent. To examine the current state of this science, here we review 79 multi-scale wildlife-habitat studies published since 1993. We summarize rationales used in scale choice and also review key differences in scale-specific experimental design among studies. We found on average that 70% of the observational scales employed in wildlife-habitat research were chosen arbitrarily with no biological connection to the system of study, and with no consideration regarding domains of scale for either dependent or independent variables. Further, we found it common to change either both grain and extent, or the entire suite of independent variables across scales, making cross-scale extrapolations and generalizations impossible. We discuss these sampling limitations by clarifying the differences between multi-scale versus multi-design studies, including the distinction between spatial versus scalar observations, and how these may differ from the commonly cited “orders of resource selection”. We conclude by reviewing both existing and suggested alternatives to reduce the arbitrary nature of observational-scale choice prevalent in today's literature.
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