A Bayesian network assessment of macroinvertebrate responses to nutrients and other factors in streams of the Eastern Corn Belt Plains, Ohio, USA

Douglas B. McLaughlin and Kenneth H. Reckhow

Ecological Modelling, 2017, vol. 345, issue C, 21-29

Abstract: Over the past several years, the United States Environmental Protection Agency has urged states to adopt numeric nutrient criteria to protect water quality. In a number of states, new numeric nutrient criteria have incorporated both a nutrient (nitrogen and/or phosphorus) criterion and a biological endpoint (e.g., chlorophyll a in lakes or benthic macroinvertebrates in streams). While the causal relationship between nutrient levels and chlorophyll in lakes is well-established, quantifying causal relationships between nutrients, chlorophyll a, and benthic macroinvertebrate communities in rivers and streams has been more elusive. This is especially true in highly agricultural ecoregions of the upper midwest United States where a number of confounding factors may be present. Predictive relationships derived from field-collected data can provide important support for setting numeric criteria and identifying management alternatives that can achieve and sustain water quality goals. In this paper, we examine the empirical basis for a causal relationship between nutrients, chlorophyll, and benthic macroinvertebrates in the context of other potential macroinvertebrate stressors in a highly agricultural region. We developed a Bayesian network (BN) model for the number of Ephemeroptera, Plecoptera, and Trichoptera taxa (EPT) present in streams of the Eastern Corn Belt Plains Ecoregion of Ohio using Ohio Environmental Protection Agency data collected over roughly a decade (2005–2013). For the data evaluated in this study, useful relationships between nutrients, chlorophyll a, and EPT were not found. An alternative BN model including total Kjeldahl nitrogen with habitat quality and dissolved oxygen appeared to reflect stronger causal influences on this indicator of stream macroinvertebrate quality. However, the predictive power of the BN was relatively low, suggesting that other factors not accounted for in the model may contribute significantly to EPT taxa abundance in these streams.

Keywords: Bayesian network models; Nutrients; Water quality; Macroinvertebrates; Habitat quality; Cause and effect (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:345:y:2017:i:c:p:21-29

DOI: 10.1016/j.ecolmodel.2016.12.004

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