Enhancing causal assessment of estuarine fishkills using graphical models

Abstract

It is not possible to determine the causal relationship between fishkills and the toxic dinoflagellate Pfiesteria piscicida in the Neuse River Estuary, North Carolina, using observational data on these two variables alone. However, consideration of a third variable, indicating the presence of a broader class of more easily measured Pfiesteria-like organisms (PLOs), leads to causal model structures from which the nature of this relationship can be distinguished. We use reported field data to evaluate alternative models and find that the suggestion that toxic Pfiesteria cause fishkills is inconsistent with observation. The data are more indicative of a model in which PLOs (including potentially toxic Pfiesteria) are stimulated to become actively toxic by the presence of already dead or dying fish. Laboratory experiments performed to date do not provide evidence contradictory to this finding. However, neither can the existence of a common cause of both Pfiesteria toxicity and fishkills be ruled out. The differing implications for ecosystem management suggest that these causal associations should be further investigated through additional modeling and data collection efforts. Graphical methods of model construction and evaluation can assist in this process.

DOI
10.1007/pl00021508
Year