Using a temperature-dependent population model to predict the population growth rates of grass carp across North America

• With available data models predict increased population growth with temperature. • Temperature dependence in other traits alters the direction of change in growth rate. • Adult survival is likely a good target for management action. • More temperature-dependent, species-specific data is needed for future research. Invasion risk and impact are related to the population growth rate of newly introduced species. We parameterized a temperature dependent age- and size-structured integral projection model (IPM) to predict the population growth rate of invasive grass carp ( Ctenopharyngodon idella ) in North America. We formulated models using available data on temperature dependence in the age at maturity and fecundity for grass carp and found a small increase in population growth rate at higher temperatures. However, these models did not include potential temperature-dependence in other life history variables (e.g., somatic growth rate, maximum size, and survival) for which there is no data specific to grass carp. Inclusion of simulated temperature dependence in these important variables can reverse the trend in population growth rate and temperature, depending on which combination of life history traits are temperature-dependent. Elasticity analysis highlighted adult survival as a good management target to keep population growth rates small in all cases. We suggest that future studies regarding climate impacts on population growth will require detailed study of the impacts of temperature dependence on various life history traits in order to reach robust conclusions.

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Publication Details

Journal
Ecological Modelling
Published
2024-11-23
DOI
https://doi.org/10.1016/j.ecolmodel.2024.110945
Primary Topic
Fish Ecology and Management Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Using a temperature-dependent population model to predict the population growth rates of grass carp across North America

Madison E. Brook, Kim Cuddington
Ecological Modelling
Fish Ecology and Management Studies
article

Using a temperature-dependent population model to predict the population growth rates of grass carp across North America

Madison E. Brook, Kim Cuddington
article en

Abstract

• With available data models predict increased population growth with temperature. • Temperature dependence in other traits alters the direction of change in growth rate. • Adult survival is likely a good target for management action. • More temperature-dependent, species-specific data is needed for future research. Invasion risk and impact are related to the population growth rate of newly introduced species. We parameterized a temperature dependent age- and size-structured integral projection model (IPM) to predict the population growth rate of invasive grass carp ( Ctenopharyngodon idella ) in North America. We formulated models using available data on temperature dependence in the age at maturity and fecundity for grass carp and found a small increase in population growth rate at higher temperatures. However, these models did not include potential temperature-dependence in other life history variables (e.g., somatic growth rate, maximum size, and survival) for which there is no data specific to grass carp. Inclusion of simulated temperature dependence in these important variables can reverse the trend in population growth rate and temperature, depending on which combination of life history traits are temperature-dependent. Elasticity analysis highlighted adult survival as a good management target to keep population growth rates small in all cases. We suggest that future studies regarding climate impacts on population growth will require detailed study of the impacts of temperature dependence on various life history traits in order to reach robust conclusions.

Ecological ModellingVol. 500
University of Waterloo (CA)
Natural Sciences and Engineering Research Council of Canada
Zero hunger
Openalex Percentile: Top 80%
Fish Ecology and Management Studies
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