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Sci Rep. 2020 Feb 6;10(1):2019. doi: 10.1038/s41598-020-58702-3.

Seasonal to Inter-Annual Variability of Primary Production in Chesapeake Bay: Prospects to Reverse Eutrophication and Change Trophic Classification.

Author information

1
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, California, 90095, United States. lharding@atmos.ucla.edu.
2
Interstate Commission on the Potomac River Basin, United States Environmental Protection Agency, Chesapeake Bay Program Office, 410 Severn Avenue, Annapolis, Maryland, 21403, United States.
3
Statistics Consultant, 377 Resolutions Rd., Colonial Beach, Virginia, 22443, United States.
4
U.S. Naval Research Laboratory, 4555 Overlook Ave., SW, Washington, D.C., 20375, United States.
5
Department of Biology, Monmouth University, West Long Branch, NJ, 07764, United States.
6
Smithsonian Institution, Smithsonian Environmental Research Center, 647 Contees Wharf Road, Edgewater, Maryland, 21037, United States.
7
Institute of Marine Sciences, University of North Carolina at Chapel Hill, 3431 Arendell Street, Morehead City, North Carolina, 28557, United States.

Abstract

Estuarine-coastal ecosystems are rich areas of the global ocean with elevated rates of organic matter production supporting major fisheries. Net and gross primary production (NPP, GPP) are essential properties of these ecosystems, characterized by high spatial, seasonal, and inter-annual variability associated with climatic effects on hydrology. Over 20 years ago, Nixon defined the trophic classification of marine ecosystems based on annual phytoplankton primary production (APPP), with categories ranging from "oligotrophic" to "hypertrophic". Source data consisting of shipboard measurements of NPP and GPP from 1982 to 2004 for Chesapeake Bay in the mid-Atlantic region of the United States supported estimates of APPP from 300 to 500 g C m-2 yr-1, corresponding to "eutrophic" to "hypertrophic" categories. Here, we developed generalized additive models (GAM) to interpolate the limited spatio-temporal resolution of source data. Principal goals were: (1) to develop predictive models of NPP and GPP calibrated to source data (1982 to 2004); (2) to apply the models to historical (1960s, 1970s) and monitoring (1985 to 2015) data with adjustments for nutrient loadings and climatic effects; (3) to estimate APPP from model predictions of NPP; (4) to test effects of simulated reductions of phytoplankton biomass or nutrient loadings on trophic classification based on APPP. Simulated 40% decreases of euphotic-layer chl-a or TN and NO2 + NO3 loadings led to decreasing APPP sufficient to change trophic classification from "eutrophic' to "mesotrophic" for oligohaline (OH) and polyhaline (PH) salinity zones, and from "hypertrophic" to "eutrophic" for the mesohaline (MH) salinity zone of the bay. These findings show that improved water quality is attainable with sustained reversal of nutrient over-enrichment sufficient to decrease phytoplankton biomass and APPP.

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