Complexity in ecology and conservation : mathematical, statistical, and computational challenges Green, Jessica L. Hastings, Alan Arzberger, Peter Ayala, Francisco J. Cottingham, Kathryn L. Cuddingham, Kim Davis, Frank Dunne, Jennifer A. Fortin, Marie-Josee Gerber, Leah Neubert, Michael G. 2006-12-06T16:56:00Z 2006-12-06T16:56:00Z 2005-06
dc.description Author Posting. © American Institute of Biological Sciences, 2005. This article is posted here by permission of American Institute of Biological Sciences for personal use, not for redistribution. The definitive version was published in BioScience 55 (2005): 501–510, doi:10.1641/0006-3568(2005)055[0501:CIEACM]2.0.CO;2. en
dc.description.abstract Creative approaches at the interface of ecology, statistics, mathematics, informatics, and computational science are essential for improving our understanding of complex ecological systems. For example, new information technologies, including powerful computers, spatially embedded sensor networks, and Semantic Web tools, are emerging as potentially revolutionary tools for studying ecological phenomena. These technologies can play an important role in developing and testing detailed models that describe real-world systems at multiple scales. Key challenges include choosing the appropriate level of model complexity necessary for understanding biological patterns across space and time, and applying this understanding to solve problems in conservation biology and resource management. Meeting these challenges requires novel statistical and mathematical techniques for distinguishing among alternative ecological theories and hypotheses. Examples from a wide array of research areas in population biology and community ecology highlight the importance of fostering synergistic ties across disciplines for current and future research and application. en
dc.description.sponsorship This paper is the result of a National Science Foundation (NSF) workshop on quantitative environmental and integrative biology (DEB-0092081). J. L. G. would like to acknowledge financial support from the NSF (DEB-0107555). en
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dc.identifier.citation BioScience 55 (2005): 501–510 en
dc.identifier.doi 10.1641/0006-3568(2005)055[0501:CIEACM]2.0.CO;2
dc.language.iso en_US en
dc.publisher American Institute of Biological Sciences en
dc.subject Ecological complexity en
dc.subject Quantitative conservation biology en
dc.subject Cyberinfrastructure en
dc.subject Metadata en
dc.subject Semantic Web en
dc.title Complexity in ecology and conservation : mathematical, statistical, and computational challenges en
dc.type Article en
dspace.entity.type Publication
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