Downstream Effects of Upstream Causes

Abstract

The United States Environmental Protection Agency considers nutrient pollution in stream ecosystems one of the United States’ most pressing environmental challenges. But limited independent replicates, lack of experimental randomization, and space- and time-varying confounding handicap causal inference on effects of nutrient pollution. In this article, the causal g-methods are extended to allow for exposures to vary in time and space in order to assess the effects of nutrient pollution on chlorophyll a—a proxy for algal production. Publicly available data from North Carolina’s Cape Fear River and a simulation study are used to show how causal effects of upstream nutrient concentrations on downstream chlorophyll a levels may be estimated from typical water quality monitoring data. Estimates obtained from the parametric g-formula, a marginal structural model, and a structural nested model indicate that chlorophyll a concentrations at Lock and Dam 1 were influenced by nitrate concentrations measured 86 to 109 km upstream, an area where four major industrial and municipal point sources discharge wastewater. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

Keywords:

• g-formula
• Marginal structural models
• Potential outcomes
• Structural nested models

Supplementary Materials

Appendices: Four appendices containing additional explication of the g-formula, derivation of the closed form structural nested model estimators, details on simulations parameterizations, and additional analyses of Cape Fear River data. (PDF file)

R-package updown: R-package updown containing code to perform the simulations and analyses described in this article. (GNU zipped tar file)

R-package geex: R-package geex containing code necessary for sandwich variance estimators used in updown package. (GNU zipped tar file)

R-package capefear: R-package capefear containing data from the Cape Fear River obtained by the North Carolina Nature Conservancy. Also contains discharge data from USGS stream gauges for the period of the study. (GNU zipped tar file)

Acknowledgments

We would like to thank Dr. Rebecca Benner and the Nature Conservancy of North Carolina for compiling and providing the data. We would also like to thank all those who collected and collated these data in order to protect the Cape Fear watershed. The causal inference with interference research group at UNC (Brian Barkley, Sujatro Chakladar, and Wen Wei Loh) plus Mary Kirk Wilkinson provided helpful feedback and critical support throughout this project. We also thank the Associate Editor and two anonymous reviewers for helpful comments. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Additional information

Funding

This work was partially supported by NIH grant R01 AI085073 and the Lower Cape Fear River Program.