globalchange  > 气候变化与战略
DOI: 10.1016/j.rse.2019.111626
论文题名:
Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models
作者: Randin C.F.; Ashcroft M.B.; Bolliger J.; Cavender-Bares J.; Coops N.C.; Dullinger S.; Dirnböck T.; Eckert S.; Ellis E.; Fernández N.; Giuliani G.; Guisan A.; Jetz W.; Joost S.; Karger D.; Lembrechts J.; Lenoir J.; Luoto M.; Morin X.; Price B.; Rocchini D.; Schaepman M.; Schmid B.; Verburg P.; Wilson A.; Woodcock P.; Yoccoz N.; Payne D.
刊名: Remote Sensing of Environment
ISSN: 344257
出版年: 2020
卷: 239
语种: 英语
英文关键词: Anthropocene ; Monitoring ; Remote sensing ; Species distribution models ; Sustainable development ; Terrestrial ecosystems
Scopus关键词: Biodiversity ; Decision making ; Ecosystems ; Monitoring ; Planning ; Population distribution ; Sustainable development ; Anthropocene ; Comprehensive assessment ; Ecological modeling ; Management strategies ; Remote sensing data ; Spatiotemporal information ; Species distribution models ; Terrestrial ecosystems ; Remote sensing ; Anthropocene ; anthropogenic effect ; biodiversity ; ecological modeling ; environmental monitoring ; mountain environment ; remote sensing ; sustainable development ; terrestrial ecosystem
英文摘要: In the face of the growing challenges brought about by human activities, effective planning and decision-making in biodiversity and ecosystem conservation, restoration, and sustainable development are urgently needed. Ecological models can play a key role in supporting this need and helping to safeguard the natural assets that underpin human wellbeing and support life on land and below water (United Nations Sustainable Development Goals; SDG 15 & 14). The urgency and complexity of safeguarding forest (SDG 15.2) and mountain ecosystems (SDG 15.4), for example, and halting decline in biodiversity (SDG 15.5) in the Anthropocene requires a re-envisioning of how ecological models can best support the comprehensive assessments of biodiversity and its change that are required for successful action. A key opportunity to advance ecological modeling for both predictive and explanatory purposes arises through a collaboration between ecologists and the Earth observation community, and a close integration of remote sensing and species distribution models. Remote sensing products have the capacity to provide continuous spatiotemporal information about key factors driving the distribution of organisms, therefore improving both the use and accuracy of these models for management and planning. Here we first survey the literature on remote sensing data products available to ecological modelers interested in improving predictions of species range dynamics under global change. We specifically explore the key biophysical processes underlying the distribution of species in the Anthropocene including climate variability, changes in land cover, and disturbances. We then discuss potential synergies between the ecological modeling and remote sensing communities, and highlight opportunities to close the data and conceptual gaps that currently impede a more effective application of remote sensing for the monitoring and modeling of ecological systems. Specific attention is given to how potential collaborations between the two communities could lead to new opportunities to report on progress towards global agendas - such as the Agenda 2030 for sustainable development of the United Nations or the Post-2020 Global Biodiversity Framework of the Convention for Biological Diversity, and help guide conservation and management strategies towards sustainability. © 2020 Elsevier Inc.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/158704
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作者单位: Dept. of Ecology and Evolution (DEE), University of Lausanne, Biophore, Lausanne, CH-1015, Switzerland; Centre Alpien de Phytogéographie (CAP), Route de l'Adray 27, Champex-Lac, CH-1938, Switzerland; Interdisciplinary Centre for Mountain Research (ICMR), University of Lausanne, Case postale 4176, Sion 4, CH-1950, Switzerland; Centre for Sustainable Ecosystem Solutions, University of WollongongNSW 2522, Australia; Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, Birmensdorf, 8903, Switzerland; University of Minnesota, Department of Ecology, Evolution and Behavior, 1475 Gortner Ave, Saint Paul, MN 55108, United States; University of British Columbia, Department of Forest Resource Management, 2424 Main Mall, Vancouver, BC, Canada; University of Vienna, Division of Conservation Biology, Vegetation Ecology and Landscape Ecology, Department of Botany & Biodiversity Research, Rennweg 14, Vienna, 1030, Austria; Department for Ecosystem Research and Environmental Information Management, Environment Agency Austria, Spittelauer Lände 5, Vienna, Austria; Center for Development and Environment, Mittelstrasse 43, Bern, 3012, Switzerland; University of Maryland Baltimore County, Geography and Environmental Systems, 211 Sondheim Hall, Baltimore, MD 21250, United States; German Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, Leipzig, 04103, Germany; Institute of Biology, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, Halle (Saale), 06108, Germany; University of Geneva, Institute for Environmental Sciences/enviroSPACE, 66 Boulevard Carl-Vogt, Geneva, 1205, Switzerland; Institute of Earth Surface Dynamics, Géopolis Building, University of Lausanne, Lausanne, CH-1015, Switzerland; Yale University, Department of Ecology and Evolutionary Biology, 165 Prospect Street, New Haven, CT 06520-8106, United States; Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, 1015, Switzerland; University of Antwerp, Campus Drie Eiken, Universiteitsplein 1, D.C.007, Wilrijk, 2610, Belgium; UR “Ecologie et dynamique des systèmes anthropisés” (EDYSAN, UMR 7058 CNRS-UPJV), Université de Picardie Jules Verne, 1 rue des Louvels, Amiens Cedex 1, 80037, France; University of Helsinki, Department of Geosciences and Geography, P.O. Box 33 (Yliopistonkatu 4), Helsinki, 00014, Finland; CEFE, CNRS - Université de Montpellier - Université Paul-Valéry Montpellier - EPHE, 1919 Route de Mende, Montpellier Cedex 5, F-34293, France; Alma Mater Studiorum University of Bologna, Department of Biological, Geological and Environmental Sciences, via Irnerio 42, Bologna, 40126, Italy; University of Trento, Department of Cellular, Computational and Integrative Biology (CIBIO), Via Sommarive, 9, Povo, TN 38123, Italy; Fondazione Edmund Mach, Research and Innovation Centre, Department of Biodiversity and Molecular Ecology, Via E. Mach 1, S. Michele all'Adige, TN 38010, Italy; Czech University of Life Sciences Prague, Faculty of Environmental Sciences, Department of Applied Geoinformatics and Spatial Planning, Kamycka 129, Praha - Suchdol, 16500, Czech Republic; University of Zurich, Department of Geography, Remote Sensing Laboratories, Winterthurerstrasse 190, Zurich, 8057, Switzerland; University of Zurich, Department of Evolutionary Biology and Environmental Studies, Ecology & Environment, Biology of Species Interactions, Winterthurerstrasse 190, Zurich, 8057, Switzerland; Vrije University Amsterdam, Faculty of Science, Institute for Environmental Studies, de Boelelaan 1105, Amsterdam, 1081 HV, Netherlands; University at Buffalo, Department of Geography, 120 Wilkeson Quad, Ellicott Complex, North Campus, Buffalo, NY 14261, United States; Joint Nature Conservation Committee, Monkstone House, City Road, Peterborough, PE1 1JY, United Kingdom; The Arctic University of Norway, Department of Arctic and Marine Biology, Tromsø, 9037, Norway; Global Mountain Biodiversity Assessment, University of Bern, Institute of Plant Sciences, Altenbergrain 21, Bern, 3013, Switzerland

Recommended Citation:
Randin C.F.,Ashcroft M.B.,Bolliger J.,et al. Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models[J]. Remote Sensing of Environment,2020-01-01,239
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