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dc.contributor.authorPeterson, A. Townsend
dc.contributor.authorBodbyl-Roels, Sarah Ann
dc.contributor.authorXiao, Xiangming
dc.date.accessioned2014-01-17T15:53:50Z
dc.date.available2014-01-17T15:53:50Z
dc.date.issued2011-03-28
dc.identifier.citationBaumann, Diana, Malcolm Cook, Limei Ma, Arcady Mushegian, Erik Sanders, Joel Schwartz, and C Ron Yu. 2008. “A Family of GFP-like Proteins with Different Spectral Properties in Lancelet Branchiostoma Floridae.” Biology Direct 3: 28. http://dx.doi.org/10.1186/1476-072X-10-21
dc.identifier.urihttp://hdl.handle.net/1808/12762
dc.description.abstractEcological niche modeling integrates known sites of occurrence of species or phenomena with data on environmental variation across landscapes to infer environmental spaces potentially inhabited (i.e., the ecological niche) to generate predictive maps of potential distributions in geographic space. Key inputs to this process include raster data layers characterizing spatial variation in environmental parameters, such as vegetation indices from remotely sensed satellite imagery. The extent to which ecological niche models reflect real-world distributions depends on a number of factors, but an obvious concern is the quality and content of the environmental data layers.
dc.language.isoen_US
dc.publisherBioMed Central
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.urihttp://creativecommons.org/licenses/by/2.0
dc.titleComparative analysis of remotely-sensed data products via ecological niche modeling of avian influenza case occurrences in Middle Eastern poultry.
dc.typeArticle
kusw.kuauthorPeterson, A. Townsend
kusw.kuauthorBodbyl-Roels, Sarah
kusw.kudepartmentEcology & Evolutionary Biology
kusw.oastatusfullparticipation
dc.identifier.doi10.1186/1476-072X-10-21
dc.identifier.orcidhttps://orcid.org/0000-0001-7590-677X
kusw.oaversionScholarly/refereed, publisher version
kusw.oapolicyThis item meets KU Open Access policy criteria.
dc.rights.accessrightsopenAccess


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This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as: This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.