Abstract

Hypoxia, or low dissolved oxygen (DO), is a widespread water quality problem affecting estuaries and coastal waters around the world. Water quality criteria for DO have been established for every estuary in the US and are an important part of the regulatory response to nutrient pollution and associated anthropogenic eutrophication. Experimental studies examining effects of low DO exposure have been to quantify outcomes based on hypoxia effects observed in individuals, such as increased mortality or growth impairment. Although laboratory exposure tests provide useful benchmarks for policy development, most of those considered in policy development did not consider behavioral responses to low DO. However, experimental research has shown that behavioral responses occur, and that behavior modifies exposure to low DO conditions. Here we begin development of a spatially explicit individual based model (SEIBM) intended to project behavioral outcomes of exposure to spatially variable hypoxia in estuaries. Our goal is to consider the responsiveness of an SEIBM to both different behavioral hypotheses, as well as realistic spatial patterns in hypoxia. A sensitivity analysis was used to explore responsiveness based on two movement strategies: avoidance and behavioral switching. We tested the sensitivity of a suite of movement parameters to changes in spatial patterns representative of an index estuary. The sensitivity analysis demonstrated that model responses to changes in movement strategies include biologically meaningful changes in site occupancy and movement distance centered on individual behavior near a normoxic–hypoxic boundary. Further, the model demonstrated important sensitivity to realistic changes in movement parameters, including the size and shape of the individual neighborhood describing knowledge useful for movement decisions. These results support the utility of the developed SEIBM for exploring behavioral responses of fish to hypoxia in estuaries. The sensitivity analysis also demonstrates parameter values that must be set based on empirical data and are sensitive to data quality. These results will be used to further develop the model and to plan field and laboratory studies to support model parametrization. The end goal is a model framework that can inform policy decisions regarding hypoxia resulting from anthropogenic nutrient loading in estuaries.

Full Text
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