In this paper we develop a model to estimate nitrogen loading to watersheds and receiving waters, and then apply the model to gain insight about sources, losses, and transport of nitrogen in groundwater moving through a coastal watershed. The model is developed from data of the Waquoit Bay Land Margin Ecosystems Research project (WBLMER), and from syntheses of published information. The WBLMER nitrogen loading model first estimates inputs by atmospheric deposition, fertilizer use, and wastewater to surfaces of the major types of land use (natural vegetation, turf, agricultural land, residential areas, and impervious surfaces) within the landscape. Then, the model estimates losses of nitrogen in the various compartments of the watershed ecosystem. For atmospheric and fertilizer nitrogen, the model allows losses in vegetation and soils, in the vadose zone, and in the aquifer. For wastewater nitrogen, the model allows losses in septic systems and effluent plumes, and it adds further losses that occur during diffuse transport within aquifers. The calculation of losses is done separately for each major type of land cover, because the processes and loss rates involved differ for different tesserae of the land cover mosaic. If groundwater flows into a freshwater body, the model adds a loss of nitrogen for traversing the freshwater body and then subjects the surviving nitrogen to losses in the aquifer. The WBLMER model is developed for Waquoit Bay, but with inputs for local conditions it is applicable to other rural to suburban watersheds underlain by unconsolidated sandy sediments. Model calculations suggest that the atmosphere contributes 56%, fertilizer 14%, and wastewater 27% of the nitrogen delivered to the surface of the watershed of Waquoit Bay. Losses within the watershed amount to 89% of atmospheric nitrogen, 79% of fertilizer nitrogen, and 65% of wastewater nitrogen. The net result of inputs to the watershed surface and losses within the watershed is that wastewater becomes the largest source (48%) of nitrogen loads to receiving estuaries, followed by atmospheric deposition (30%) and fertilizer use (15%). The nitrogen load to estuaries of Waquoit Bay is transported primarily through land parcels covered by residential areas (39%, mainly via wastewater), natural vegetation (21%, by atmospheric deposition), and turf (16%, by atmospheric deposition and fertilizers). Other land covers were involved in lesser throughputs of nitrogen. The model results have implications for management of coastal landscapes and water quality. Most attention should be given to wastewater disposal within the watershed, particularly within 200 m of the shore. Rules regarding setbacks of septic system location relative to shore and nitrogen retention ability of septic systems, will be useful in control of wastewater nitrogen loading. Installation of multiple conventional leaching fields or septic systems in high‐flow parcels could be one way to increase nitrogen retention. Control of fertilizer use can help to a modest degree, particularly...

Temporal patterns of nutrient input into a Southern California kelp forest were measured using traditional hydrocast sampling coupled with high frequency temperature profiling. Patterns of nutrient input were related to growth rates of Macrocystis pyrifera located in an adjacent kelp forest. There were 2 distinct components to the pattern of nutrient availability. The long term, or seasonal, component was consistent with large-scale storm-induced mixing and horizontal advection during winter months. In addition, vertical motions of the thermocline, bringing nutrients into the kelp forest, occurred throughout the year with a frequency of about 2 per day and were strongest during the summer months. Weekly hydrocast sampling methods were inadequate for measuring these episodic events, and high frequency sampling was required to resolve the pattern of nutrient input accurately. Although measurable, nutrient input from vertical thermocline motion was inadequate to sustain maximum growth of Macrocystis pyrifera at 10m depth during the summer months. Thus, the major component of nutrient input came during the winter. These results indicate that nitrate limitation of M. pyrifera is a likely cause of reduced summer growth. Further, high frequency sampling is necessary to predict nutrient availability in nearshore ecosystems dominated by benthic macrophytes where the pattern of nutrient input is dominated by episodic events of short duration.

A simple two-dimensional (z,t) model of first year sea ice structure and dynamics is coupled to a high resolution, time-dependent model of microalgal growth in which simulated physiological responses are determined by ambient temperature, specffal irradiance, nutrient concentration, and salinity. The physical component utilizes atmospheric d,•,ta to simulate congelation ice growth, initial brine entrapment, desalination, and nutrient flux. Tempefixture gradient, sea ice salinity, brine salinity, and brine volume are also computed. The biological component is based on the concept of a maximum temperature-dependent algal growth rate which is reduced by limitations imposed from insufficient light or nutrients, as well as suboptimal salinity. Estimated gross primary productivity is reduced by respiration and grazing terms. Preliminary simulations indicate that, during a bloom, microalgae are able to maintain their vertical position relative to the lower congelation ice margin and are not incorporated into the crystal matrix as the ice sheet thickens. Model results imply that land fast sea ice contains numerous microhabitats that are functionally distinct based upon the unique suite of processes that control microalgal growth and accumulation within each. In the early stages, of the spring bloom, high brine salinity inhibits microalgal growth at all depths within the congelation ice, except near the skeletal layer. Light is predicted to be the limiting resource throughout the congelation ice and platelet ice at this time. Later in the bloom when environmental conditions are more favorable for algal growth, model results suggest that biomass ac•cumulation in the upper congelation ice is controlled by microzooplankton grazing. Microalgae in the skeletal layer and upper platelet ice are susceptible to nutrient linfitation at this time due to diminished flux and high nutrient demand. Light limits microalgal gro•wth in the lower platelet ice throughout the bloom. Results indicate that land fast sea ice in McMurdo Sound can support a production rate of approximately 0.5 g C m -2 d -1 under optimal conditions, 76% of which is associated with the platelet layer where rates of nutrient exchange are relatively high. While adjustments in any biological coefficient will alter the magnitude of production in the model, the range of results permitted by uncertainty in their values is well within the bounds likely to result from normal variations in snow cover, or from the uncertainty in the rate of nutrient flux. INTRODUCTION The Southern Ocean, which extends from the continental margin of Antarctica northward to the subtropical convergence, encompasses an area equivalent to approximately 40% of the global ocean surface. A large but variable fraction of this area is covered by annually forming sea ice, ranging from 3 x 106 km 9-at the end of the austral summer to 20 x 106 km 9-in late winter [Zwally et al., 1979]. The advance and retreat of the ice sheet effectively divides the Southern Ocean into three provinces: the permanent open...

For over a thousand years, generations of Balinese farmers have gradually transformed the landscape of their island, clearing forests, digging irrigation canals, and terracing hillsides to enable themselves and their descendants to grow irrigated rice. Paralleling the physical system of terraces and irrigation works, the Balinese have also constructed intricate networks of shrines and temples dedicated to agricultural deities. Ecological modeling shows that water temple networks can have macroscopic effects on the topography of the adaptive landscape, and may be representative of a class of complex adaptive systems that have evolved to manage agroecosystems.