Non-monotonic Responses of Phytoplankton Biomass Accumulation to Hydrologic Variability: A Comparison of Two Coastal Plain North Carolina Estuaries |
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| Authors: | Benjamin L Peierls Nathan S Hall Hans W Paerl |
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| Institution: | 1. Institute of Marine Sciences, University of North Carolina at Chapel Hill, 3431 Arendell St., Morehead City, NC, 28557, USA
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| Abstract: | Freshwater inputs often play a more direct role in estuarine phytoplankton biomass (chlorophyll a) accumulation than nitrogen (N) inputs, since discharge simultaneously controls both phytoplankton residence time and N loading. Understanding this link is critical, given potential changes in climate and human activities that may affect discharge and watershed N supply. Chlorophyll a (chla) relationships with hydrologic variability were examined in 3-year time series from two neighboring, shallow (<5?m), microtidal estuaries (New and Neuse River estuaries, NC, USA) influenced by the same climatic conditions and events. Under conditions ranging from drought to floods, N concentration and salinity showed direct positive and negative responses, respectively, to discharge for both estuaries. The response of chla to discharge was more complex, but was elucidated through conversion of discharge to freshwater flushing time, an estimate of transport time scale. Non-linear fits of chla to flushing time revealed non-monotonic, unimodal relationships that reflected the changing balance between intrinsic growth and losses through time and along the axis of each estuary. Maximum biomass occurred at approximately 10-day flushing times for both systems. Residual analysis of the fitted data revealed positive relationships between chla and temperature, suggesting enhanced growth rates at higher temperatures. N loading and system-wide, volume-weighted chla were positively correlated, and biomass yields per N load were greater than other marine systems. When combined with information on loss processes, these results on the hydrologic control of phytoplankton biomass will help formulate mechanistic models necessary to predict ecosystem responses to future climate and anthropogenic changes. |
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