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dc.contributor.authorLacy, Robert C.en
dc.contributor.authorMiller, Philip S.en
dc.contributor.authorNyhus, Philip J.en
dc.contributor.authorPollak, J. P.en
dc.contributor.authorRaboy, Becky E.en
dc.contributor.authorZeigler, Sara L.en
dc.date.accessioned2018-10-16T16:41:24Zen
dc.date.available2018-10-16T16:41:24Zen
dc.date.issued2013-12-13en
dc.identifier.othere84211en
dc.identifier.urihttp://hdl.handle.net/10919/85380en
dc.description.abstractWildlife population models have been criticized for their narrow disciplinary perspective when analyzing complexity in coupled biological – physical – human systems. We describe a “metamodel” approach to species risk assessment when diverse threats act at different spatiotemporal scales, interact in non-linear ways, and are addressed by distinct disciplines. A metamodel links discrete, individual models that depict components of a complex system, governing the flow of information among models and the sequence of simulated events. Each model simulates processes specific to its disciplinary realm while being informed of changes in other metamodel components by accessing common descriptors of the system, populations, and individuals. Interactions among models are revealed as emergent properties of the system. We introduce a new metamodel platform, both to further explain key elements of the metamodel approach and as an example that we hope will facilitate the development of other platforms for implementing metamodels in population biology, species risk assessments, and conservation planning. We present two examples – one exploring the interactions of dispersal in metapopulations and the spread of infectious disease, the other examining predator-prey dynamics – to illustrate how metamodels can reveal complex processes and unexpected patterns when population dynamics are linked to additional extrinsic factors. Metamodels provide a flexible, extensible method for expanding population viability analyses beyond models of isolated population demographics into more complete representations of the external and intrinsic threats that must be understood and managed for species conservation.en
dc.format.mimetypeapplication/pdfen
dc.language.isoen_USen
dc.publisherPLOSen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleMetamodels for Transdisciplinary Analysis of Wildlife Population Dynamicsen
dc.typeArticle - Refereeden
dc.description.versionPeer Revieweden
dc.contributor.departmentBiological Sciencesen
dc.title.serialPLOS ONEen
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0084211en
dc.identifier.volume8en
dc.identifier.issue12en
dc.type.dcmitypeTexten
dc.identifier.pmid24349567en
dc.identifier.eissn1932-6203en


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Creative Commons Attribution 4.0 International
License: Creative Commons Attribution 4.0 International