Monitoring data compilations can be leveraged to highlight relationships between estuarine and watershed factors influencing eutrophication in estuaries
Citation:
Pelletier, Peg, Jim Latimer, B. Rashleigh, C. Tilburg, AND Mike Charpentier. Monitoring data compilations can be leveraged to highlight relationships between estuarine and watershed factors influencing eutrophication in estuaries. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, 197(1):80, (2025). https://doi.org/10.1007/s10661-024-13564-4
Impact/Purpose:
Estuaries are bodies of water fed by land and connected with the sea. Nutrient loads to these waterbodies have increased, resulting in excess algal blooms and low oxygen conditions. In order to understand the processes impacting these waters, so that we can better predict and control adverse impacts, monitoring data are needed. In this study we leveraged data from 28 monitoring programs in the northeastern U.S. to explore the relationships between eutrophication response variables and watershed and estuarine variables. We focused on summer total nitrogen and chlorophyll, and summer bottom dissolved oxygen. We analyzed these data using a machine learning technique, random forest. All models showed the importance of variables related to nutrient loading such as population density and % development and variables related to flushing rate such as tidal range, length:width at mouth, and estuary openness. Future work will examine the impacts of climate on eutrophication response variables. This study demonstrates the utility of combining data from multiple unrelated routine monitoring programs to understand eutrophication impacts at regional scales.
Description:
Estuaries have been adversely impacted by increased nutrient loads. Eutrophication impacts from these loads include excess algal blooms and low oxygen conditions. In this study, we leveraged data from 28 monitoring programs in the northeastern US to explore the relationships between eutrophication response variables and watershed and estuarine variables. Extensive effort was needed to locate, harmonize, and assure the quality of the data. Random forest regression allowed us to identify the most important variables that could predict summer total nitrogen (TN), chlorophyll (chl), and bottom dissolved oxygen (DO). Several different summaries of the data were assessed. The best models for TN and chl used data summarized by estuary and year, explaining > 70% and > 60% of the variation, respectively. The best model for DO used data that were averaged by estuary across all years and explained > 55% of the variation. All models showed the importance of variables related to nutrient loading, such as population density and % development, and variables related to flushing rate, such as tidal range, length:width at mouth, and estuary openness. Future work will examine the impacts of climate on eutrophication response variables. This study demonstrates the utility of combining data from multiple unrelated routine monitoring programs to understand eutrophication impacts at regional scales.
URLs/Downloads:
DOI: Monitoring data compilations can be leveraged to highlight relationships between estuarine and watershed factors influencing eutrophication in estuaries