| Dose-structured population dynamics. | |
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MedLine Citation:
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PMID: 17296208 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Applied population dynamics modeling is relied upon with increasing frequency to quantify how human activities affect human and non-human populations. Current techniques include variously the population's spatial transport, age, size, and physiology, but typically not the life-histories of exposure to other important things occurring in the ambient environment, such as chemicals, heat, or radiation. Consequently, the effects of such 'abiotic' aspects of an ecosystem on populations are only currently addressed through individual-based modeling approaches that despite broad utility are limited in their applicability to realistic ecosystems [V. Grimm, Ten years of individual-based modeling in ecology: what have we learned and what could we learn in the future? Ecol. Model. 115 (1999) 129-148][1]. We describe a new category of population dynamics modeling, wherein population dynamical states of the biotic phases are structured on dose, and apply this framework to demonstrate how chemical species or other ambient aspects can be included in population dynamics in three separate examples involving growth suppression in fish, inactivation of microorganisms with ultraviolet irradiation, and metabolic lag in population growth. Dose-structuring is based on a kinematic approach that is a simple generalization of age-structuring, views the ecosystem as a multi-component mixture with reacting biotic/abiotic components. The resulting model framework accommodates (a) different memories of exposure as in recovery from toxic ambient conditions, (b) differentiation between exogenous and endogenous sources of variation in population response, and (c) quantification of acute or sub-acute effects on populations arising from life-history exposures to abiotic species. Classical models do not easily address the very important fact that organisms differ and have different experiences over their life cycle. The dose structuring is one approach to incorporate some of these elements into the existing structures of the classical models, while retaining many of the features (and other limitations) of classical models. |
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Authors:
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Timothy R Ginn; Frank J Loge |
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Publication Detail:
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Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S. Date: 2006-12-24 |
Journal Detail:
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Title: Mathematical biosciences Volume: 208 ISSN: 0025-5564 ISO Abbreviation: Math Biosci Publication Date: 2007 Jul |
Date Detail:
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Created Date: 2007-06-04 Completed Date: 2007-08-15 Revised Date: 2009-11-11 |
Medline Journal Info:
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Nlm Unique ID: 0103146 Medline TA: Math Biosci Country: United States |
Other Details:
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Languages: eng Pagination: 325-43 Citation Subset: IM |
Affiliation:
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Department of Civil and Environmental Engineering, University of California, Davis, CA 95616, USA. trginn@ucdavis.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Animals Biodegradation, Environmental Demography Disinfection / methods Ecosystem* Humans Models, Biological* Population Density Population Dynamics Population Growth Salmon / growth & development Stochastic Processes Water Pollutants, Chemical / analysis, toxicity Water Purification / methods |
| Chemical | |
Reg. No./Substance:
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0/Water Pollutants, Chemical |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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