A stochastic bioenergetics model based approach to translating large river flow and temperature in to fish population responses: The pallid sturgeon example
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Abstract
In managing fish populations, especially at-risk species, realistic mathematical models are needed to help predict population response to potential management actions in the context of environmental conditions and changing climate while effectively incorporating the stochastic nature of real world conditions. We provide a key component of such a model for the endangered pallid sturgeon (Scaphirhynchus albus) in the form of an individual-based bioenergetics model influenced not only by temperature but also by flow. This component is based on modification of a known individual-based bioenergetics model through incorporation of: the observed ontogenetic shift in pallid sturgeon diet from marcroinvertebrates to fish; the energetic costs of swimming under flowing-water conditions; and stochasticity. We provide an assessment of how differences in environmental conditions could potentially alter pallid sturgeon growth estimates, using observed temperature and velocity from channelized portions of the Lower Missouri River mainstem. We do this using separate relationships between the proportion of maximum consumption and fork length and swimming cost standard error estimates for fish captured above and below the Kansas River in the Lower Missouri River. Critical to our matching observed growth in the field with predicted growth based on observed environmental conditions was a two-step shift in diet from macroinvertebrates to fish.
Study Area
Publication type | Article |
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Publication Subtype | Journal Article |
Title | A stochastic bioenergetics model based approach to translating large river flow and temperature in to fish population responses: The pallid sturgeon example |
Series title | Geological Society of London Special Publications |
DOI | 10.1144/SP408.10 |
Volume | 408 |
Year Published | 2015 |
Language | English |
Publisher | The Geological Society of London |
Contributing office(s) | Columbia Environmental Research Center |
Description | 18 p. |
First page | 1 |
Last page | 17 |
Country | Canada, United States |
Other Geospatial | Missouri River |
Google Analytic Metrics | Metrics page |