Population modeling using harpacticoid copepods Bridging the gap between individual-level effects and protection goals of environmental risk assessment

Abstract: To protect the environment from contaminants, environmental risk assessment (ERA) evaluates the risk of adverse effects to populations, communities and ecosystems. Environmental management decisions rely on ERAs, which commonly are based on a few endpoints at the individual organism level. To bridge the gap between what is measured and what is intended for protection, individual-level effects can be integrated in population models, and translated to the population level. The general aim of this doctoral thesis was to extrapolate individual-level effects of harpacticoid copepods to the population level by developing and using population models. Matrix models and individual based models were developed and applied to life-history data of Nitocra spinipes and Amphiascus tenuiremis, and demographic equations were used to calculate population-level effects in low- and high-density populations. As a basis for the population models, individual-level processes were studied. Development was found to be more sensitive compared to reproduction in standard ecotoxicity tests measuring life-history data. Additional experimental animals would improve statistical power for reproductive endpoints, but at high labor and cost. Therefore, a new test-design was developed in this thesis. Exposing animals in groups included a higher number of animals without increased workload. The number of reproducing females was increased, and the statistical power of reproduction was improved. Individual-level effects were more or equally sensitive compared to population-level effects, and individual-level effects were translated to the population level to various degrees by population models of different complexities. More complex models showed stronger effects at the population level compared to the simpler models. Density dependence affected N. spinipes populations negatively so that toxicant effects were stronger at higher population densities. The tools presented here can be used to assess the toxicity of environmental contaminants at the individual and population level, improve ERA, and thereby the basis for environmental management.