Gabrielle Tomasky

Nitrogen loading from watersheds to estuaries: Verification of the Waquoit Bay Nitrogen Loading Model

World-wide eutrophication of estuaries has made accurate estimation ofland-derived nitrogen loads an important priority. In this paper we verifypredictions of nitrogen loads made by the Waquoit Bay Nitrogen LoadingModel (NLM). NLM is appropriate for watersheds with mixes of forested,agricultural, and residential land uses, and underlain by coarseunconsolidated sediments. NLM tracks the fate of nitrogen inputs byatmospheric deposition, fertilizer use, and wastewater disposal, and assignslosses of nitrogen from each source as the nitrogen is transported throughthe land use mosaic on the watershed surface, then through the underlyingsoils, vadose zones, and aquifers.We verified predictions of nitrogen loads by NLM in two independent ways.First, we compared NLM predictions to measured nitrogen loads in differentsubestuaries in the Waquoit Bay estuarine system. Nitrogen loads predictedby NLM were statistically indistinguishable from field-measured nitrogenloading rates. The fit of model predictions to measurements remained goodacross the wide range of nitrogen loads, and across a broad range in size(10–10,000 ha) of land parcels. NLM predictions were most precise whenspecific parcels were larger than 200 ha, and within factors of 2 for smallerparcels.Second, we used NLM to predict the percentage of nitrogen loads toestuaries contributed by wastewater, and compared this prediction to theδ15N signature distinguishable from N derived fromatmospheric or fertilizer sources. The greater the contribution ofwastewater, the heavier the δ15N value in groundwater. Thesignificant linear relation between NLM predictions of percent wastewatercontributions and stable isotopic signature corroborated the conclusionthat model outputs provide a good match to empirical measurements. Thegood agreement obtained in both verification exercises suggests that NLMis an useful tool to address basic and applied questions about how land usepatterns alter the fate of nitrogen traversing land ecosystems, and thatNLM provides verified estimates of the land-derived nitrogen exports thattransform receiving aquatic ecosystems.

OPERATIONALIZING SUSTAINABILITY: MANAGEMENT AND RISK ASSESSMENT OF LAND-DERIVED NITROGEN LOADS TO ESTUARIES

Sustainable coastal management requires that the goals and means of management be made operational and specific. We use Waquoit Bay, Massachusetts, as a case study, to suggest a decision-making process that brings updated scientific results forward while incorporating stakeholder concerns. Land-derived nitrogen loading is the major agent of change for receiving estuaries in the Waquoit Bay estuarine complex, so control of nitrogen loading rates is a principal goal of land management plans. We can establish the relationships of land use pattern to nitrogen loading rates, and of loading rates to mean annual concentrations of nitrogen in the estuaries. The latter, in turn, can be related quantitatively to mean annual production and biomass of phytoplankton, macroalgae, and eelgrass. We propose that phytoplankton, macroalgal, and eelgrass production and biomass are suitable end point measures that can be made meaningful to stakeholders. We define the relationship of agent of change vs. end point measure, and ...

ELM, An Estuarine Nitrogen Loading Model: Formulation and Verification of Predicted Concentrations of Dissolved Inorganic Nitrogen

ELM is an Estuarine Loading Model that calculates mean annual concentration of dissolved inorganic nitrogen (DIN) available to producers in shallow estuaries by considering how different processes modify pools of nitrogen provided by inputs (streams, groundwater flow, atmospheric deposition, N2 fixation, and regeneration), and losses (burial and denitrification), within components of the estuarine system (bare sediments, seagrass meadows, salt marshes, water column). ELM also considers the effect of flushing rate within an estuary. Its formulation was constrained to minimize demands of data needed to run the model. In spite of simplifications such as the use of loss coefficients instead of functional formulations of processes, and uncertainties in all the terms included in ELM, predictions of mean annual DIN in water were not significantly different than field measurements done in estuaries in Cape Cod, Massachusetts, subject to different rates of nitrogen (N) loading. This verification suggests that, in spite of its simple formulation, ELM captures the functioning of nutrient dynamics within estuaries. ELM may therefore be a reasonable tool for use in basic studies in nutrient dynamics and land/estuary coupling. Because of its simplicity and comprehensiveness in inclusion of components and processes, ELM may also be useful in efforts to manage N loads to estuaries and related management issues.

Processing arctic eddy-flux data using a simple carbon-exchange model embedded in the ensemble Kalman filter

Continuous time-series estimates of net ecosystem carbon exchange (NEE) are routinely made using eddy covariance techniques. Identifying and compensating for errors in the NEE time series can be automated using a signal processing filter like the ensemble Kalman filter (EnKF). The EnKF compares each measurement in the time series to a model prediction and updates the NEE estimate by weighting the measurement and model prediction relative to a specified measurement error estimate and an estimate of the model-prediction error that is continuously updated based on model predictions of earlier measurements in the time series. Because of the covariance among model variables, the EnKF can also update estimates of variables for which there is no direct measurement. The resulting estimates evolve through time, enabling the EnKF to be used to estimate dynamic variables like changes in leaf phenology. The evolving estimates can also serve as a means to test the embedded model and reconcile persistent deviations between observations and model predictions. We embedded a simple arctic NEE model into the EnKF and filtered data from an eddy covariance tower located in tussock tundra on the northern foothills of the Brooks Range in northern Alaska, USA. The model predicts NEE based only on leaf area, irradiance, and temperature and has been well corroborated for all the major vegetation types in the Low Arctic using chamber-based data. This is the first application of the model to eddy covariance data. We modified the EnKF by adding an adaptive noise estimator that provides a feedback between persistent model data deviations and the noise added to the ensemble of Monte Carlo simulations in the EnKF. We also ran the EnKF with both a specified leaf-area trajectory and with the EnKF sequentially recalibrating leaf-area estimates to compensate for persistent model-data deviations. When used together, adaptive noise estimation and sequential recalibration substantially improved filter performance, but it did not improve performance when used individually. The EnKF estimates of leaf area followed the expected springtime canopy phenology. However, there were also diel fluctuations in the leaf-area estimates; these are a clear indication of a model deficiency possibly related to vapor pressure effects on canopy conductance.

Nutrient limitation of phytoplankton growth in Waquoit Bay, Massachusetts, USA: a nutrient enrichment study

We conducted nutrient enrichment experiments and field sampling to address three questions: (1) is there nutrient limitation of phytoplankton accumulation within an estuary whose waters are exposed to relatively high nitrogen loading rates, (2) where in the salinity gradient from fresh to seawater (0 to 32‰) is there a shift from phosphorus to nitrogen limitation of phytoplankton accumulation, and (3) is there a seasonal shift in limiting function of phosphorus and nitrogen anywhere in the estuarine gradient. Nitrogen and phosphorus enrichment experiments in the Childs River, an estuary of Waquoit Bay, Massachusetts, USA, showed that the accumulation of phytoplankton biomass in brackish and saline water was limited by supply of nitrate during warm months. The effects of enrichment were less evident in fresh water, with short-lived responses to phosphate enrichment. There was no specific point along the salinity gradient where there was a shift from phosphorus- to nitrogen-limited phytoplankton accumulation; rather, the relative importance of nitrogen and phosphorus changed along the salinity gradient in the estuary and with season of the year. There was no response to nutrient additions during the colder months, suggesting that some seasonally-varying factor, such as light, temperature or a physiological mechanism, restricted phytoplankton accumulation during months other than May-Aug. There was only slight evidence of a seasonal shift between nitrogen- and phosphorus-limitation of chlorophyll accumulation. Phytoplankton populations in nutrient-rich estuaries with short flushing times grow fast, but at the same time the cells may be advected out of the estuaries while still rapidly dividing, thereby providing an important subsidy to production in nearby deeper waters.

Relationship of Reproductive Output in Acartia tonsa, Chlorophyll Concentration, and Land-Derived Nitrogen Loads in Estuaries of Waquoit Bay, Massachusetts

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