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Development and application of a multidimensional density dependent matrix population model for Atlantic killifish (Fundulus heteroclitus)
Citation:
Miller, D., B. Clark, AND D. Nacci. Development and application of a multidimensional density dependent matrix population model for Atlantic killifish (Fundulus heteroclitus). SETAC North America, Sacramento, CA, November 04 - 08, 2018.
Impact/Purpose:
The Atlantic killifish (Fundulus heteroclitus) has a range including the Atlantic coast from Florida to the Maritime Provinces of Canada, and is an important model organism for understanding the effects of pollutants and other stressors in estuarine and marine ecosystems. Herein, we develop a multidimensional density dependent matrix population model for Atlantic killifish that analyzes both size class structure and age class structure of the population simultaneously over time. This population modeling approach emphasizes application in conjunction with field monitoring efforts (e.g., through effects-based monitoring programs) and/or laboratory analysis to link effects due to chemical and/or nonchemical stressors to adverse outcomes in whole organisms and populations. We applied the model to investigate population trajectories for Atlantic killifish exposed to 112, 296, and 875 pg/g of 2,3,7,8-tetrachlorodibenzop-dioxin with effects on fertility and survival rates. For each exposure concentration of 2,3,7,8-tetrachlorodibenzop-dioxin, the corresponding plots of total population size, population size class structure, and population age class structure over time were generated. For example, exposure to 875 pg/g of 2,3,7,8-tetrachlorodibenzop-dioxin resulted in a 13.1% decline in population size after 2 years, a 19.9% decline in population size after 5 years, and a 27.9% decline in population size over 10 years with plots of all size classes and age classes exhibiting declines. As this model accounts for both size class structure and age class structure of the fish population over time, it can readily incorporate output from a dynamic energy budget (DEB) model. This study serves as an example of how multidimensional density dependent matrix population models are useful for ecological risk assessment because they integrate effects across the life cycle, provide a linkage between endpoints observed in the individual and ecological risk to the population as a whole, and project outcomes forfuture generations.
Description:
Modeling exposure and recovery of fish and wildlife populations after stressor mitigation serves as a basis for evaluating population status and remediation success. The Atlantic killifish (Fundulus heteroclitus) is an important and well-studied model organism for understanding the effects of pollutants and other stressors in estuarine and marine ecosystems. Herein, we develop a multidimensional density dependent matrix population model for Atlantic killifish that analyzes both size class structure and age class structure of the population simultaneously over time. This population modeling approach emphasizes application in conjunction with field monitoring efforts (e.g., through effects-based monitoring programs) and/or laboratory analysis to link effects due to chemical and/or nonchemical stressors to adverse outcomes in whole organisms and populations. We applied the model to investigate population trajectories for Atlantic killifish exposed to 112, 296, and 875 pg/g of 2,3,7,8-tetrachlorodibenzop-dioxin with effects on fertility and survival rates. For each exposure concentration of 2,3,7,8-tetrachlorodibenzop-dioxin, the corresponding plots of total population size, population size class structure, and population age class structure over time were generated. For example, exposure to 875 pg/g of 2,3,7,8-tetrachlorodibenzop-dioxin resulted in a 13.1% decline in population size after 2 years, a 19.9% decline in population size after 5 years, and a 27.9% decline in population size over 10 years with plots of all size classes and age classes exhibiting declines. The present study serves as an example of how multidimensional density dependent matrix population models are useful tools for ecological risk assessment because they integrate effects across the life cycle, provide a linkage between endpoints observed in the individual and ecological risk to the population as a whole, and project outcomes for future generations.