A multidimensional density dependent matrix population model for assessing risk of stressors to fish populations.

Abstract

Modeling exposure and recovery of fish and wildlife populations after stressor mitigation serves as a basis for evaluating remediation success. Herein, we develop a novel multidimensional density dependent matrix population model that analyzes both size-structure and age class-structure simultaneously. This 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 stressors to outcomes in populations. We applied the model to investigate Atlantic killifish (Fundulus heteroclitus) exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin with effects on fertility and survival rates. The Atlantic killifish is an important and well-studied model organism for understanding the effects of pollutants and other stressors in estuarine and marine ecosystems. For each exposure concentration, the corresponding plots of total population size, population size structure, and age structure over time were generated. The present study serves as an example of how a multidimensional matrix population model can 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 multiple generations.