Influence of the human perturbation on carbon, nitrogen, and oxygen biogeochemical cycles in the global coastal ocean

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1 Pergamon PII S (01) Geochimica et Cosmochimica Acta, Vol. 65, No. 21, pp , 2001 Copyright 2001 Elsevier Science Ltd Printed in the USA. All rights reserved /01 $ Influence of the human perturbation on carbon, nitrogen, and oxygen biogeochemical cycles in the global coastal ocean CHRISTOPHE RABOUILLE, 1 FRED T. MACKENZIE 2, and LEAH MAY VER 2 1 Laboratoire des Sciences du Climat et de l Environnement, Laboratoire Mixte CNRS-CEA, 1, Avenue de la Terrasse, Gif sur Yvette, France 2 Department of Oceanography, School of Ocean and Earth Science and Technology, University of Hawaii, Honolulu, HI 96822, USA (Received November 20, 2000; accepted in revised form July 20, 2001) Abstract The responses to human perturbations of the biogeochemical cycles of carbon (C), nitrogen (N), and oxygen (O) in the global coastal ocean were evaluated using a process-based model. In this model, the global coastal ocean is represented by two distinct zones: the proximal zone which includes large bays, the open water part of estuaries, deltas, inland seas, and salt marshes; and the distal zone which includes the open continental shelves down to a depth of 200 m. The biogeochemical model of the elemental cycles in the coastal ocean describes the dynamics of transfer processes and their interactions (primary production, mineralization, sediment deposition, and burial). The coastal sediment submodel describes element recycling in the sediments and allows the assessment of the evolution of denitrification under various environmental forcings. Initial values for the biogeochemical fluxes of carbon, nitrogen, and oxygen between the various reservoirs of the coastal ocean and the exchange of materials at the boundaries with the rivers and the open ocean are estimated based on current literature data. Before anthropogenic activities, the global coastal ocean was a net autotrophic system with a net export flux to sediments and open ocean of 20 Tmol organic C/yr. The magnitude and direction of this net flux is strongly dependent on the flux of organic carbon from the coastal ocean to adjacent reservoirs. The proximal coastal region was slightly heterotrophic at 8.4 Tmol C/yr, consistent with estimates by other authors; the distal coastal ocean was autotrophic at the rate of 28.4 Tmol C/yr. To simulate the evolution of the coastal ocean under human influence during the past 50 yr, the global coastal ocean model was perturbed by increasing the global riverine fluxes of dissolved inorganic nitrogen (DIN) and total organic matter (TOM) and the depositional flux of atmospheric nitrogen relative to the preanthropogenic condition. Model results show that over the past 50 yr, primary production in the coastal ocean has doubled, and resulted in an accumulation of biomass in all compartments of the system. The coastal ocean became more heterotrophic in response to the dominant perturbation of the increased flux of terrestrial organic matter via the rivers. Contrary to expectations, denitrification rates do not increase and the denitrification efficiency of the coastal ocean system decreases. This suggests that the coastal ocean is not likely to self-regulate the effects of human-induced perturbations on nutrient cycles. Finally, simulation results for a future condition where the rates of riverine organic and inorganic C and N inputs to the coastal ocean continue to increase at their current exponential growth patterns indicate that the proximal coastal ocean could become increasingly heterotrophic, the organic matter content could increase, and primary production could be enhanced. These changes could potentially cause noxious blooms to occur and become a generalized phenomenon of the proximal coastal ocean. There is a strong likelihood that unless human-derived inputs are regulated at the source, substantial biogeochemical modification of the global coastal ocean will occur because cyclic processes within the coastal ocean system are not rapid enough to dissipate the effects of the perturbations. Copyright 2001 Elsevier Science Ltd 1. INTRODUCTION In this paper we pay tribute to Harold C. Helgeson s contributions to the field of geochemistry by development of a quantitative model of the biogeochemical cycles of carbon, nitrogen, and oxygen in the global coastal zone. In the spirit of many of Hal s papers, our presentation is of a synthetic nature, is only a stepping stone toward reality, and probably will promote discussion by others. The coastal ocean is an important domain in the global biogeochemical cycles of carbon and nutrient elements in the ocean (Mantoura et al., 1991). This portion of the global ocean interacts closely and in a complex way with the continents, *Author to whom correspondence should be addressed (fredm@soest. hawaii.edu) atmosphere, and the open ocean. In the coastal zone, with a surface area of only 10% of the global ocean surface, approximately 25% of global oceanic primary production (PP) and 80% of global organic carbon burial take place (Berner, 1982; Smith and Hollibaugh, 1993). The coastal sediments are also the most important site for denitrification, a process that strongly regulates the oceanic nitrogen budget (Koike and Sorensen, 1988). During the last century, the coastal ocean has been exposed to large perturbations, mostly related to human activities on land. Prolonged and intensive use of inorganic fertilizer in agriculture, changes in land use patterns, deforestation, and discharge of industrial and municipal waste have all contributed to the eutrophication of river water and of the coastal ocean on a global scale. This phenomenon has led to severe degradation of water quality and alteration of the marine food

2 3616 C. Rabouille et al. web and community structure. Several estuarine and coastal regions showing such degradation are located in the North Sea, the Baltic Sea, the Adriatic Sea, and the east and south coast of North America (De Jonge et al., 1994; Richardson and Heilmann, 1995). Over the past 50 yr, the fluxes of natural and synthetic materials from the terrestrial environment to the coastal margin have increased by a factor of 1.5 to 2 because of humaninduced perturbations (Garrels et al., 1975; Meybeck, 1982; Meybeck and Ragu, 1995). There is much evidence that the natural stability of the coastal margin has been disrupted owing to the perturbational effects on the biogeochemical cycling of carbon and nutrient elements (Hu et al., 1998; Mackenzie et al., 2000; Smith and Hollibaugh, 1993; Smith and Mackenzie, 1987; Zhang et al., 1998). However, it is expected that the natural control mechanisms in the coastal margin system will serve to disperse the effects of the perturbation within a sufficiently short period and that these mechanisms are efficient enough to prevent accumulation of pollutants and their byproducts. Burial of organic matter, denitrification, and export of particulate organic matter (POM) to the open ocean are the natural regulatory mechanisms in the coastal margin. These processes remove excess carbon and nitrogen from the coastal ocean in organic and inorganic forms to the sediment, atmosphere, and open ocean reservoirs, respectively. An issue of concern then is: to what extent and over what time scale can the coastal margin system be burdened with carbon and nutrient perturbations before its natural regulatory system capacity is exceeded? We contend that because coupled elemental biogeochemical cycles in the coastal zone are very complex and interact very strongly with one another, the answer to our question on a worldwide basis is not readily predictable without numerical simulations. The study and understanding of elemental biogeochemical cycles and dynamics using numerical models are important to an understanding of the fate of anthropogenic fluxes and their partitioning between the different exogenic reservoirs of the Earth system. The awareness that biogeochemical processes are continuous across the adjacent domains of coastal ocean, ocean, sediments, land, and atmosphere provides strong justification to maintain coverage at the global spatial scale in model analysis. Our model analysis involves only those reservoirs and processes that would adequately represent the global coastal ocean, with due regard to the methodologic differences that characterize the oceanic models of other investigators. As in our past research into the 300-yr history of C-N-P biogeochemical cycling (Ver et al., 1999), our efforts are compatible with the sparse data that exist for some of the domains and the levels of accuracy that can be expected from simple, regionally aggregated global models. On the time scale of the human perturbation (centuries or less), a model defined by annually averaged parameters, ignoring seasonal variability, is often sufficient to illustrate trends in the response of various biogeochemical processes to perturbations from anthropogenic and climatic forcing functions (see, for example, Mackenzie et al., 2000 and references therein). Our general approach is to treat the smallest number of reservoirs that is consistent with the ability of the model to detect representative, average changes in the biogeochemical behavior of carbon, nitrogen, and oxygen, over the recent 50-yr period of progressively growing human perturbations of the environment and 50 yr into the future. In this work, we present a coupled biogeochemical model of the elemental cycles of these elements, emphasizing the coastal ocean domain and its interactions with processes on land, in the atmosphere, and in the open ocean. The model is a process-based kinetic model. The system is assumed to be operating in a quasi-steady-state condition before simulation. It undergoes sustained perturbation owing to human activities for the duration of the simulation. We determine the ability of the model to mimic the evolution of natural systems over the past 50 yr by comparing model outputs with observed historical trends of selected parameters for coastal margin areas. We develop scenarios of future conditions, focusing on the changing inputs of organic matter and nutrients to the coastal ocean as forcing functions, to predict and analyze the behavior of the coastal ocean system in response to these perturbations. 2. THE PREANTHROPOGENIC COASTAL OCEAN 2.1. Physical Description of the Global Coastal Ocean In our model, the coastal ocean is divided into two adjacent zones: proximal and distal (Fig. 1). Note that the coastal area north of 60 N latitude, except for portions of the Norwegian west coast 60 to 70 N latitude, is excluded from the system boundaries of the model. This approach is consistent with the methodology of other investigators (Smith and Hollibaugh, 1993; Wollast, 1993) whose coastal area estimates are ultimately based on the estimate of Woodwell et al. (1973). Exclusion of the high-latitude coastal areas is justified for our modeling effort because direct anthropogenic inputs to these areas are limited; it is anticipated however, that these areas will be significantly affected by climatic changes which are not accounted for in our model. The subdivision of the coastal ocean is necessary to account for the distinct differences in the observed biogeochemical processes between these two regions. In the proximal coastal zone, large inputs of particulate and dissolved, organic and inorganic materials are received from the rivers into a relatively small reservoir volume. In addition, there is a strong degree of coupling between the processes of sediment recycling and nutrient utilization in the photic layer of this zone. In the distal zone, material inputs are received from the open ocean and the adjacent proximal zone, and less importantly from the atmosphere. The coupling between the processes of benthic recycling and production is weaker relative to that in the proximal zone because of the greater depth of the water column and changes in the associated hydrologic processes of this part of the coastal ocean. Below, we highlight the important physical dimensions defining each of the coastal ocean zones in our model: (i) The global area of the proximal zone, including large bays, the open water part of estuaries, deltas, inland seas, and salt marshes, is estimated to be 1.8 Tm 2 ( m 2, Smith and Hollibaugh, 1993; Woodwell et al., 1973). The mean water depth is 20 m. This zone is treated as a single homogeneous reservoir where production and respiration occur concurrently. In this zone, sedimentation rates are estimated to be in the range of cm/yr (Heip et al., 1995).

3 C, N, O biogeochemical cycles in the coastal ocean 3617 Fig. 1. Schematic diagram of the dynamic model including a description of the physical features and the fluxes of water between the defined reservoirs of the model. (ii) The distal zone includes the open continental shelves down to a depth of 200 m, which is considered as the mean depth of the shelf break. Its global surface area is estimated to be 27 Tm 2 (Smith and Hollibaugh, 1993; Woodwell et al., 1973). The mean depth is 130 m. This zone is divided into two subreservoirs: the upper water column, which receives substantial solar input and where PP is a dominant process; and the lower water column, which is dominated by mineralization and transfer of particles to the sediments. The sedimentation rate in the distal region is estimated to be between 0.01 and 0.1 cm/yr, an order of magnitude lower than that of the proximal zone (Wollast, 1998). (iii) Freshwater input to the coastal zone is estimated to be 37 Tm 3 /yr (Tm 3 /yr m 3 /yr, Berner and Berner, 1996). This discharge rate implies a mean water residence time with respect to river discharge of 1 yr in the proximal zone. The upwelling and onwelling fluxes of water and nutrients into the distal zone from the intermediate depths of the open ocean are not well quantified. Broecker and Peng (1982) calculated a transport flux of 600 Tm 3 /yr, which is higher than recent estimates of 400 Tm 3 /yr by Brink et al. (1995) and 215 Tm 3 /yr by Ver (1998). For our model, using the steady-state nitrate budget to constrain the estimate of the upwelling flux, a flux of 507 Tm 3 /yr is calculated. This flux magnitude implies a residence time of 6.4 yr for the water in the global distal zone The Elemental Cycles of Carbon, Nitrogen, and Oxygen There are very few estimates of the preanthropogenic global or regional coastal ocean carbon budgets based on field studies. Furthermore, extrapolation from widely scattered local or regional budgets to global cycles is prone to large and often unknown uncertainties. We rely on established values that accord reasonably well with present field studies to construct the carbon and nutrient budgets for the global coastal ocean. The procedure that we adopt here begins with the best estimates of the global fluxes in the system, such as those for riverine transport, sediment burial, and PP. Then, we reconstruct consistent internal element cycles (Figs. 2 4) using data and knowledge derived from regional studies because little global information exists for most of the internal processes, e.g., mineralization of organic carbon in the upper water column of the continental shelf, deposition of particles at the sedimentwater interface (SWI), and particulate export out of the coastal ocean to the open ocean. In Tables 1 through 3 we present a summary of the carbon, nitrogen, and oxygen reservoir and flux values adopted for our model. Where appropriate, we show various estimates considered during model development. Note that there are few independent estimates of fluxes for the global cycles of nitrogen and oxygen. Thus many of the fluxes were calculated from the carbon fluxes using the appropriate C:N and C:O 2 molar ratio. Figure 3 shows the fluxes and the adopted C:N ratios in parentheses. We use a Redfield C:N ratio of 6.6 for PP and recycling; however, we recognize that some decoupling may occur between the C and N cycles because of the more rapid recycling of nitrogen vs. carbon (Sambrotto et al., 1993). The C:N ratio for organic matter buried in coastal margin sediments is taken as 12 for the proximal zone and 14 for the distal zone. The oxygen cycle is intimately linked to the organic matter cycle, and almost all the fluxes involving oxygen are dependent on the production or degradation of particulate and dissolved

4 3618 C. Rabouille et al. Fig. 2. The organic carbon cycle in the global coastal ocean in its preanthropogenic state. A distinction is made between marine and riverine organic carbon. The boxes represent the reservoirs and the arrows represent the fluxes between the reservoirs. The processes occurring within each reservoir and their respective rate values are shown within each box. The NEM arrows indicate the trophic status of each compartment of the coastal zone but do not indicate the net flux of CO 2 because the carbonate system is not included in the budget. Fluxes in Tmol C/yr. organic matter (Fig. 4). The exchange fluxes between the atmosphere and the coastal ocean surface and the input fluxes from the rivers and upwelling from the intermediate depths of the ocean are dependent on physical and chemical parameters such as O 2 concentration, temperature, windspeed, and flux of water. In our model, the coupling between oxygen and the organic matter cycle is expressed in the average C:N ratio of organic matter relative to its O 2 consumption. Thus the rates of biologic production and consumption of oxygen are calculated from the magnitude of the associated carbon flux and the average C:N:O 2 ratio (106:16:138 for total marine organic matter and 106:6:118 for total riverine organic matter) Coastal Ocean Trophic Status Our modeled global coastal ocean is a net autotrophic system at the rate of 20 Tmol C/yr (Smith and Mackenzie, 1987), with the total output of 54 Tmol organic C/yr (export to the open ocean burial) exceeding the total input of 34 Tmol C/yr (riverine input). The flux of atmospheric CO 2 required to balance this net consumption of carbon is 20 Tmol C/yr. The high rate of autotrophy is mostly a result of the large export of particulate organic carbon (POC) from the shelf to the slope (a flux which is poorly known; see Table 1). It is noteworthy that flux estimates by Wollast (1998) and Walsh (1991), which are higher than those adopted for our model, would imply a more autotrophic coastal ocean system, and hence would require a CO 2 invasion flux of 2 to 4 times greater than 20 Tmol C/yr. Our analysis of the coastal ocean as an autotrophic system differs from that calculated by Mackenzie et al. (1998) and Ver et al. (1999). Based on their model (Terrestrial-Ocean-Atmosphere Ecosystem Model, TOTEM) results, the preanthropogenic coastal ocean is calculated to be a heterotrophic system with a net organic balance of 7.5 Tmol C/yr. The divergent conclusions are mainly due to the assumed value for the export flux of organic carbon at the coastal ocean open ocean boundary, and to the fact that TOTEM has as the initial steady-state condition the year 1700 A.D. However this difference in trophic status at initial conditions does not preclude comparison of the historical evolution of net ecosystem metabolism (NEM) between these two models. In this study, the proximal and distal zones of the global coastal ocean exhibit contrasting trophic status. The proximal zone is calculated to be net heterotrophic (at 8.4 Tmol C/yr) whereas the distal zone is calculated to be net autotrophic (at 28.4 Tmol C/yr). The calculated heterotrophy of the proximal zone is mainly due to the remineralization of terrestrially derived organic matter whereas the autotrophy of the distal zone

5 C, N, O biogeochemical cycles in the coastal ocean 3619 Fig. 3. The nitrogen cycle in the global coastal ocean in its preanthropogenic state, represented as in the carbon cycle (Fig. 2). The C:N ratios adopted for this model are also shown. Fluxes in Tmol N/yr. results from the large export of marine organic matter to the open ocean. This partitioning of the trophic status between proximal and distal zones agrees with the conclusion of Smith and Hollibaugh (1993), who state that the nearshore coastal region is heterotrophic due to the input of riverine total organic carbon (TOC). 3. DYNAMICS OF BIOGEOCHEMICAL REACTIONS The dynamic coastal ocean model conceptualized in this paper can be used to reconstruct the evolution of the coastal ocean on the time scale of major human perturbations of the environment, i.e., decades to centuries. The effect of seasonal variability can be very pronounced, especially in certain coastal regions (Nixon and Pilson, 1983) owing to the seasonality of the forcings involved (e.g., changes in photosynthetically available radiation, upwelling, river discharge, temperature, and precipitation). However, over the temporal and spatial scales of interest in the numerical experiments described below, we have established by sensitivity analysis that on a global scale, the seasonal changes do not significantly affect the results of the longer-term simulations. Thus, mean annual biogeochemical flux rates are adopted, ignoring the seasonal variations. In our model, the various transfer and transformation fluxes are expressed dynamically, employing parameterizations of geochemical, physical, and biological processes. The kinetic constants are assumed to remain unchanged over the time course of the simulation and are calculated from the initial values of the stocks and fluxes which are assumed to be at steady state. This implies that the physical features and biologic community structure of the system do not evolve over the century time scale of perturbation. This constraint may be debatable, especially for biologic systems in highly eutrophicated coastal regions where minor (and sometimes toxic) specific plankton types have been observed to develop uncharacteristically large blooms. These processes, however, appear to be the exception rather than the rule on a global scale. Thus, the intrinsic properties of a system described by unchanging rate constants would not be altered substantially over the time scale of our numerical simulations. Mineralization processes can be described by first-order rate laws with respect to the organic phase (Emerson and Hedges, 1988; Murray and Kuivila, 1990; Otsuki and Hanya, 1972; Westrich and Berner, 1984). This allows us to express the processes of respiration, mineralization, and denitrification using first-order kinetics, as in the following equation: F dm dt k fm (1) In the above equation, the kinetic constant k f can be determined from the initial steady-state values for the reservoir M and the flux F, where F may be respiration, mineralization, or denitrification. Denitrification is one of the major processes that serve to remove nitrogen from the coastal ocean system. It occurs

6 3620 C. Rabouille et al. Fig. 4. The oxygen cycle in the global coastal ocean in its preanthropogenic state, represented as in the carbon cycle (Fig. 2). Fluxes in Tmol O 2 /yr. mostly in oxygen-depleted waters and in the suboxic zone of sediments. During denitrification, biologically available N in the form of nitrate is transformed into the biologically inert gases N 2 and N 2 O, which are then exported to the atmosphere. Thus the process of denitrification plays a significant role in the inorganic nitrogen and organic matter budgets in the coastal ocean. Hence dynamic models such as ours must be able to model rigorously the effects and feedbacks on denitrification owing to changing environmental conditions. In our model, we are able to parameterize the effect on the partitioning of particulate organic nitrogen (PON) between the degradation pathways of mineralization (to NO 3 and NH 4 ) and denitrification (to N 2 or N 2 O) owing to changes in the flux of PON and in the water column concentrations of NO 3 and O 2. Using a diagenetic model similar to that of Soetaert et al. (1996), we investigated the variation in denitrification efficiency (defined as the ratio of the rate of denitrification to the deposition flux of PON) with respect to changes in the NO 3 or O 2 concentrations in the bottom water and the PON deposition flux into the sediment. For the kinetic constant term in Eqn. (1), three factors (fo 2, fno 3, fpon) are defined for each of the zones within the coastal margin system. These factors represent the deviation with respect to a standard case (i.e., initial steady state) of the calculated denitrification efficiency when environmental parameters are modified. In the dynamic model, these factors are used in parameterizing the rate of denitrification to adapt the rate constants to altered environmental conditions. In the standard case, denitrification efficiency when calculated with respect to the flux of reactive PON is 32% in the proximal zone and 44% in the distal zone. Therefore a 0.1 increase in f-factor corresponds to a variation in denitrification efficiency of 3.2% (0.13 Tmol/yr) and 4.4% (0.6 Tmol/yr) for the proximal and distal zones, respectively. Important variations of the f-factor are expected with different environmental parameters (Fig. 5). One of the most interesting variations concerns that of fpon with respect to the rain rate of organic nitrogen. Indeed, large increases of PP and particulate export are expected during human perturbation on the coastal zone. This would imply a significant reduction of denitrification efficiency, which would be the consequence of increased anoxic conditions that favor the flux of NH 4 out of the sediment relative to its nitrification to NO 3. Transfer fluxes are assumed to be proportional to the content of the source reservoir. The transfer rate constants are assumed invariant throughout time, implying a stable rate of physical transport on a global scale over century time scales. Dissolved inorganic nitrogen transfer from the proximal to the distal zone or from the lower to the upper water column in the distal zone is assumed to occur during the exchange of water containing DIN between the different reservoirs. This assumption also applies to the POM transfer between the proximal and the distal zone. The rate equation for the POM export to deep waters or to the sediments is expressed with the same formulation as described above. This implies that a constant fraction of the standing stock is removed by export processes. Fluxes generated by the river discharge of terrigenous organic matter (e.g., riverine TOC and total organic nitrogen

7 C, N, O biogeochemical cycles in the coastal ocean 3621 Table 1. Carbon reservoirs (Tmol C) and fluxes (Tmol C/yr) in the coastal zone. Reservoir Mass (Tmol C) Residence time (yr) Biota in the proximal water column mol C/m 2 (Ajtay et al., 1979) Organic carbon in proximal sediments Benthic biota in proximal sediments mol C/m 2 (Ajtay et al., 1979) Biota in the distal upper water column mol C/m 2 (Ajtay et al., 1979) Organic debris in the distal lower water column Organic carbon in distal sediments Flux Tmol C/yr k, 1/yr TOC River input Gt C/yr (Meybeck, 1982; Smith and Hollibaugh, 1993, this study) 50% POC and 50% DOC (Smith and Hollibaugh, 1993, this study) 32 Tmol C/yr, 55% DOC (Ludwig et al., 1996) 20.5 Tmol C/yr (Ittekkot, 1988) 33.5 Tmol C/yr (Schlesinger and Melack, 1981) Mineralization of the riverine TOC in proximal water column 17 Primary production in the proximal water column 40 See N, Table g C/m 2 -yr (Wollast, 1998) 500 Tmol C/yr (whole coastal ocean) (Wollast, 1998) 270 g C/m 2 -yr (estuaries/proximal coastal ocean) (Smith and Hollibaugh, 1993) g C/m 2 -yr (total) (Smith and Hollibaugh, 1993) 270 g C/m 2 -yr 1.8 Tm 2 (this study) Mineralization of marine OC in the proximal water column Tmol/yr (Wollast, 1998) Deposition of marine OC in proximal sediments Tmol/yr (based on burial efficiency and data, Canfield, 1993) 28 Tmol/yr (based on mineralization rate, Canfield, 1993) 27 Tmol/yr (based on remineralization rate, Nixon and Pilson, 1983) Benthic primary production % of total production (Smith and Hollibaugh, 1993) 50 g C/m 2 -yr 1.8 Tm 2 (this study) Total mineralization in proximal sediments Burial of marine OC in proximal sediments Tmol organic C/yr (total sediments) (Wollast, 1998) 11.5 Tmol/yr; 50% proximal zone, 50% distal zone (Hedges and Keil, 1995) 18,500 Tg sediment discharge/yr (Milliman, 1991) 90% (burial in coastal ocean, Garrels and Mackenzie, 1971; Hedges and Keil, 1995) 1% (organic carbon content) (this study) Burial of riverine OC in proximal sediments 3 6 Tmol/yr (total) (Keil et al., 1995) Transfer of marine OC from proximal to distal zone Tmol organic N/yr (Nixon et al., 1996) Transfer of riverine TOC from proximal to distal zone 14 Mineralization of the riverine TOC in distal water column 6 Primary production in distal water column 320 See N, Table g C/m 2 -yr 25 Tm 2 (Walsh, 1988) 160 g C/m 2 -yr (Smith and Hollibaugh, 1993) 140 g C/m 2 -yr 27 Tm 2 (this study) Mineralization in distal upper water column f-ratio 0.5 (Paasche, 1988) Export of OC from the distal upper to the distal lower water column Mineralization of OC in the distal lower water column Deposition of POC in distal sediments Tmol/yr (based on burial efficiency and data, Canfield, 1993) 93 Tmol/yr (based on mineralization rate, Canfield, 1993) Mineralization in distal sediments Burial of marine OC in distal sediments 4 Burial of riverine OC in distal sediments 3 6 Tmol/yr (total) (Keil et al., 1995) Export of marine OC from the distal zone to the open ocean 35 10% of PP (Vertex data, Wollast, 1991) 5 10% of PP (SEEP II, Bacon et al., 1994; Falkowski et al., 1994) 6% of PP (KEEP, Chen et al., 1996) Export of riverine organic matter to the open ocean 5

8 3622 C. Rabouille et al. Table 2. Nitrogen reservoirs (Tmol N) and fluxes (Tmol N/yr) adopted in the model. a Reservoir Mass (Tmol N) Residence time (yr) DIN in the proximal water column Biota in the proximal water column Organic nitrogen in proximal sediments Benthic biota in proximal sediments DIN in the distal upper water column DIN in the distal lower water column Biota in the distal upper water column Organic debris in the distal lower water column Organic nitrogen in distal sediments Flux Tmol N/yr k, 1/yr River input of TON Tmol DON/yr (Meybeck, 1982) 1.5 Tmol PON/yr (Wollast, 1993) 2 3 Tmol N/yr (total organic inorganic) (Mackenzie et al., 1993) River input of DIN Tmol N/yr (Meybeck, 1982) Mineralization of riverine TON in proximal water column 1.3 Primary production in the proximal water column K s 2 M Mineralization of marine ON in the proximal water column Deposition of marine PON in proximal sediments Benthic N 2 fixation (Benthic ON production) 1 1 Tmol N/yr (Capone, 1988) Total mineralization in proximal sediments Denitrification in proximal sediments Tmol N/yr (Christensen et al., 1987) Tmol N/yr (total coastal ocean) (Seitzinger, 1988) 7.25 Tmol N/yr (total coastal ocean) (Seitzinger and Giblin, 1996) 1.5 Tmol N/yr (this study), using regression equation from Nixon et al. (1996) Burial of marine ON in proximal sediments Tmol N/yr (total coastal zone) (Wollast, 1993) 1.1 Tmol N/yr (total coastal zone) (Garrels et al., 1975) 1.1 Tmol N/yr (total coastal zone) (Mackenzie et al., 1993) Burial of riverine ON in proximal sediments 0.3 Transfer of marine ON from proximal to distal zone Tmol N/yr (total export) (Nixon et al., 1996) Transfer of DIN from proximal to distal zone Tmol N/yr (total export) (Nixon et al., 1996) Transfer of riverine ON from proximal to distal zone Tmol N/yr (total export) (Nixon et al., 1996) Mineralization of the riverine TON in distal water column 0.25 Atmospheric deposition of N in the distal zone Tmol N/yr (Wollast, 1993) Primary production in the distal water column K s 1 M Mineralization in the distal upper water column Export of ON from the distal upper to the distal lower water column Mineralization of ON in the distal lower water column Deposition of PON in distal sediments Mineralization in distal sediments Denitrification in distal sediments Tmol N/yr (Christensen et al., 1987) 6 Tmol N/yr (this study) 7.25 Tmol N/yr (total coastal ocean) (Seitzinger and Giblin, 1996) Tmol N/yr (proximal) Burial of marine ON in distal sediments 0.3 Burial of riverine ON in distal sediments 0.2 Export of marine ON from the distal zone to the open ocean 5 Export of riverine organic matter to the open ocean 0.15 Upwelling of DIN to the distal upper water column Tmol N/yr (Wollast, 1993) 7.5 Tmol N/yr (Brink et al., 1995) 40 Tmol N/yr (Walsh, 1991) Exchange of DIN from the distal lower to the distal upper water column 14.1 a Primary production is expressed using the Monod rate law, Eqn. (2).

9 C, N, O biogeochemical cycles in the coastal ocean 3623 Table 3. Oxygen reservoirs (Tmol O 2 ) and fluxes (Tmol O 2 /yr) adopted in the model. Reservoir Mass (Tmol O 2 ) Residence time (yr) Oxygen in the proximal water column Oxygen in the distal upper water column Oxygen in the distal lower water column Flux Tmol O 2 /yr O 2 river input km 3 /yr (global river water discharge rate) (Berner and Berner, 1996) Oxygen production by primary production in the proximal water column 52 Respiration of marine organic matter in the proximal water column 11.7 Respiration of riverine organic matter in the proximal water column 19 Oxygen production by benthic primary production 10 Total respiration in proximal sediments 39.2 O 2 flux from atmosphere to proximal zone 5.9 Transfer of O 2 from proximal to distal zone 11 Oxygen production by primary production in the distal water column 416 Oxygen consumption in the distal upper water column 195 Respiration of marine organic matter in the distal lower water column 56 Respiration of riverine organic matter in the distal upper water column 6.6 Total respiration in distal sediments 121 Transfer of O 2 from upper to lower distal upper water column 177 Export of O 2 from the distal zone to the open ocean O 2 flux from atmosphere to distal zone 11.6 Upwelling flux of O [TON]) are prescribed in the model. Very little is known about the fate of riverine organic matter in the coastal zone, and the dynamics of transfer and transformation processes are largely unknown. Therefore the partitioning of riverine POM between the various reservoirs is assumed to remain constant over the time course of the simulations. The fraction of riverine organic Fig. 5. Variations in the f-factor with changes in oxygen concentration in bottom waters O 2 bw, nitrate concentration in bottom waters NO 3 bw, and the flux of PON. Variations are relative to the initial state and are different for each zone due to the nonlinear response of the model parameters to the perturbations. An increase in the value of the f-factor implies an increase in the denitrification efficiency.

10 3624 C. Rabouille et al. matter mineralized in the proximal zone is assumed to be 50% of the total input and 17% in the distal zone. These fractions are kept constant throughout the model simulation time. Burial of riverborne organic matter is equally partitioned between the two zones and amounts to 9% of the total input for each zone. Export of riverine TOM occurs at the boundary between the coastal and open ocean and represents 15% of the total river input. The approach described above for various flux parameterizations is also applied to the burial flux of sedimentary POC and PON. The reservoir of sedimentary organic matter, assumed as reactive, is thus completely remineralized. Organic matter burial occurs from the large pool of refractory matter in the sediments. The burial flux is assumed to constitute a constant fraction of the deposition flux: 15% of the POC flux from the water column in the proximal zone, and 4% from that in the distal zone. It should be noted that the use of zeroth-order parameterization imposes a response time for burial equal to that of the depositional flux variations. Primary production is formulated using the Monod rate law with the DIN component as the limiting nutrient: G G max DIN (DIN K s ) where G is the growth rate in divisions per day, G max is the maximum growth rate, DIN is the DIN concentration, and K s is the half-saturation concentration. The growth of the phytoplankton community (biomass per day) is represented by: R G max PON DIN (DIN K s ) where PON represents an approximation of the living biomass (expressed in nitrogen units) and K s is taken as 2 M for the proximal zone and 1 M for the distal zone (Kremer and Nixon, 1978). The growth flux R represents the dynamic PP in the proximal and distal zones for C and N. 4. MODEL SENSITIVITY We investigated the sensitivity of the model to the assumed initial values of the reservoir sizes and fluxes adopted for our model, recognizing the large uncertainty in these values and in the values of derived rate constants. Note that for our model, an uncertainty in the rate constants by a factor of 2 to 3 translates to time constants that are short relative to the time period of human perturbation. To illustrate this point for the global coastal system under the effects of sustained anthropogenic perturbations over a period of 50 to 100 yr, consider that when an uncertainty factor of 2 is applied to one of the largest time constants (7 yr for mineralization of C in the sediments, Table 1), the result is a time constant whose value would still be short relative to the timescale of the perturbation. Generally, our model showed internal robustness and stability over the range of known values of the important parameters used. The following analysis illustrates the sensitivity of the model to the magnitude of the export flux of POM from the coastal zone to the open ocean, the parameter with the largest uncertainty in the organic carbon budget (Table 1). In the (2) (3) standard run, the export flux is set to 35 Tmol/yr (approximately 10% of the PP in the distal region of the coastal zone). This value lies in the middle of the range of 5 to 30% of coastal zone PP (Bacon et al., 1994; Chen et al., 1996; Walsh, 1991). Results from this standard run are compared with those from two other model simulations using export values of 10 Tmol/yr (3% of PP, case 1) and 80 Tmol/yr (25% of PP, case 2). Here we discuss model results for scenarios of increasing river discharge of inorganic nitrogen and organic matter and increasing deposition of DIN from the atmosphere over the past 50 yr. Under a scenario of increased riverine delivery of nutrient, model response for both cases and the standard run is maintained in the same direction. However, the amplitude of the response is modulated by the unique parameters of the model. Primary production in the distal zone increased from its initial value in both cases and the standard run (Fig. 6A). However the increase in PP was larger under case 1 relative to the increase under case 2 and the standard run. This is related to the loss of a potential source of nutrients in the distal region by particle export (Fig. 6B). In case 2, the high proportion of PP lost by export (25%) limits the increase in PP from regenerated nutrients. Denitrification in distal sediments also increases for all three model simulations (Fig. 6C). The increase is modulated such that in case 1, more denitrification occurs at the final stage from organic matter deposited in the sediments. The overall model behavior illustrated above for PP and denitrification is also reflected by changes in NEM (Fig. 6D). The initial value of NEM is different for the standard run and both cases because of its dependence on the magnitude of the export flux of organic matter to the open ocean. Thus the system under case 1 is initially a slightly heterotrophic coastal ocean (see TOTEM, Mackenzie et al., 1998; Ver et al., 1999) whereas the system under case 2 is highly autotrophic. NEM decreases owing to the perturbation in both cases and the standard run, with a larger decrease in case 1 ( 8.4 Tmol/yr) relative to that of case 2 ( 6 Tmol/yr). Note that regardless of the assumed initial magnitude of NEM, the calculated overall trend towards increasing heterotrophy for the past 50 yr is maintained. 5. NUMERICAL SIMULATIONS OF GLOBAL CHANGE IN THE COASTAL OCEAN In this section we address several relevant changes in the environment that affect the global coastal ocean. Riverine and atmospheric transport link the coastal ocean to the terrestrial domain; gas exchange and deposition are the process links with the atmosphere; advective transport of water, dissolved and particulate matter link it with the open ocean; and deposition and burial of organic and inorganic matter are its links with the sediment domain. Thus the past behavior of the coastal ocean under stress from natural and human-induced perturbations owing to its interactions with the adjacent domains of land, atmosphere, open ocean, and sediments may provide some clues as to its future course under sustained pressure from increasing human activities. These include changes in the export fluxes of material from the terrestrial realm to the coastal zone and changes in the coastal upwelling rate which might occur naturally or due to human-induced global warming (Mackenzie et al., 2000; Manabe and Stouffer, 1999; Sarmiento et al., 1998).

11 C, N, O biogeochemical cycles in the coastal ocean 3625 Fig. 6. An illustration of the sensitivity of the model to the magnitude of the export flux of POM from the coastal zone to the open ocean, showing the response of selected processes in the global coastal ocean to increasing river discharge of inorganic nitrogen and organic matter and increasing deposition of DIN from the atmosphere over the past 50 yr: (A) PP; (B) N export to the open ocean; (C) denitrification; and (D) NEM. The global coastal zone is being heavily impacted directly and indirectly by human activities, disproportionately more than the open ocean. Among the myriad of human activities on land, the following have substantially affected coastal zone biogeochemistry: deforestation and conversion of forest land to pasture, grazing land, and urban centers, enhancing the export of organic matter, sediment, and nutrients to the coastal zone; application of N and phosphorus (P) fertilizers and pesticides to croplands, which subsequently leach to the coastal zone via river and groundwater flows; discharge of municipal and industrial sewage and detergents into the coastal zone; and combustion of fossil fuels and atmospheric emissions mostly of carbon and smaller amounts of nitrogen and sulfur, affecting the flux of substances from the atmosphere onto coastal surface waters. Fossil fuel combustion and the subsequent increased emission of CO 2 to the atmosphere are significant factors in the global warming of the past century and its probable continuance into the 21st century, which can affect the carbon chemistry and temperature of coastal waters and possibly alter species composition and community structure as well as rates of organic productivity and calcification of carbonate-secreting organisms in coastal marine ecosystems. ACO 2 -induced global warming is also anticipated to effect changes in ocean circulation which might immediately and strongly affect the nature of CO 2 exchange between the atmosphere and ocean (Mackenzie et al., 2000). Coupled atmosphere-ocean model simulations of climate change (Manabe and Stouffer, 1994) indicate that global warming of the planet could greatly strengthen the vertical stratification of the ocean because of warming in the low latitudes and freshening of ocean waters in the high latitudes. These changes could lead to a substantial weakening of the thermohaline circulation of the ocean, as well as vertical mixing in general (Sarmiento and Wofsy, 1999). As a result, the transport of water mass and of dissolved inorganic carbon (DIC) to the deep ocean would be reduced, affecting the delivery of DIC and nutrients from intermediate waters to the coastal ocean via upwelling. Model analyses of this scenario indicate that the coastal waters could become a greater sink for atmospheric CO 2, as opposed to the conditions in the past and present, when coastal waters are believed to be a source of CO 2 to the atmosphere (Mackenzie et al., 2000). In addition, our dynamic model allows us to analyze the response of the global coastal ocean to changes in the fluxes of DIN and TOC to the ocean during the past 50 yr and to speculate on the future role of the coastal ocean undergoing climatic change. Several numerical experiments of the dynamic model were performed imposing selected perturbations on the model. These perturbations can be subdivided into three categories: (1) enhanced organic matter flux from the rivers; (2) increased inorganic nutrient concentration in the riverine input fluxes; and (3) increased atmospheric deposition of nutrients. The numerical experiments allowed for the analysis of the separate effects of the different components of the human perturbation as well as the effects owing to all the perturbations applied simultaneously Decrease in the Coastal Upwelling Rate In this numerical experiment, the rate of upwelling (UPW) was reduced by a factor of 2 (from 507 to 250 Tm 3 /yr) following a semigaussian function with a sigma of 20 yr: UPW(t) UPW final (UPW init UPW final )e ( t2 /20 2 ) (4) where UPW final is the final upwelling rate, UPW init is the initial upwelling rate, and t is time in years. Using this time scale,

12 3626 C. Rabouille et al. Fig. 7. Response of selected processes in the global coastal ocean to a decrease in the upwelling rate by 50% over a period of 100 yr: (A) POC export; (B) NEM, sediment mineralization, and PP. The vertical dashed lines indicate the point in time when 50% and 90% of the perturbation are achieved. 98% of the decrease is achieved within 40 yr (Fig. 7). In the simulation, the only zone affected by the change in upwelling rate was the distal coastal zone. Before disturbance, the net transfer of material between the two zones of the coastal ocean was from the proximal to the distal zone. Throughout the simulation, this net flux was not affected by changes in the rate of upwelling, thus confining the effects of the perturbation to the distal zone. The reduction in the rate of upwelling of intermediate waters decreased the input flux of new nutrients to the distal zone consequently affecting a decrease in PP. This response caused the reduction in the export of POM from the coastal ocean to the open ocean. NEM decreased significantly during the simulation from a state of net autotrophy to roughly that of organic balance. The change in NEM is linked to the relatively significant decrease in POM export to the open ocean. The response of the distal zone was extremely rapid; a new steady state was attained after 70 yr, only 30 yr after the perturbation reached its climax. Analysis of model results shows that the rapid response time was strongly influenced by the sediment dynamics adopted in our model, where only the reactive fraction of the deposited POM is considered. The residence time of POM in the sediment of the distal zone is 7 yr Increase in the Riverine Flux of DIN The flux of riverine DIN was doubled to mimic the anthropogenic eutrophication of the coastal zone during the past 50

13 C, N, O biogeochemical cycles in the coastal ocean 3627 yr. The DIN flux increased following a semigaussian function with a sigma of 30 yr. DIN(t) DIN final (DIN init DIN final )e (t2 /30 2 ) (5) where DIN init is the DIN flux from the river before the perturbation (0.3 Tmol N/yr), DIN final is the riverine DIN flux after the perturbation (0.6 Tmol N/yr), and t is time in years. This type of semigaussian function has a steep increase in the early part of the simulation representing an increase in nutrient discharge from the rivers during the past 50 yr. The system is then allowed to return to a new steady state after the perturbation is removed, which simulates a scenario of a possible abatement in the increase in river DIN discharge. The experiment provides an opportunity to investigate system behavior during and after the imposition of a perturbation. In the experiment, 93% of the increase in DIN discharge was achieved within 50 yr. The increase essentially follows the increase in fertilizer use from World War II to the present. The initial and final flux values of DIN were adopted from a report by the Joint Group of Experts on the Scientific Aspects of Marine Environmental Protection (GESAMP, 1987) on the analysis of the anthropogenic impact on the riverine flux of dissolved nitrogen. GESAMP determined the natural riverine flux of dissolved nitrogen to be 1 Tmol/yr and the anthropogenic flux as Tmol/yr. We then imposed a doubling of the DIN flux to the coastal ocean up to the present time. This estimate is a conservative estimate of the impact relative to that estimated by the United Nations Food and Agricultural Organization (FAO, various years). In the simulation, the increased riverine DIN flux was discharged directly to the proximal zone, significantly affecting the processes within its system. Although there was enhanced export of material from the proximal zone, the distal zone biogeochemical dynamics was affected on a smaller scale. In the proximal zone, the biomass increased by 20% due to the increase in PP induced by the increased flux of nutrients (Fig. 8A). The increase in biomass in the distal zone was small (less than 2%). Due to the increased input of nutrients, the NEM of the coastal ocean as a whole was driven towards a more autotrophic state (Fig. 8B). The proximal zone became less heterotrophic because of increased PP, burial of organic matter, and export of organic matter to the distal zone. The distal zone became slightly less autotrophic because of the increased input of POC from the proximal zone. The change in the distal zone NEM was calculated to be very small because the increased import of organic matter was accompanied by a slight increase in PP. Model simulation results show that the effect of anthropogenically induced eutrophication is small compared to the effect of changes in upwelling that may occur on short (e.g. during an El Niño, or under human-induced global warming) or longer (glacial/ interglacial) time scales. However with respect to the whole ocean, changes in the upwelling flux of intermediate ocean waters to the coastal ocean and in the export of organic matter from the coastal to the open ocean are internal fluxes that modulate autotrophy (or heterotrophy) between the adjacent oceanic realms, whereas changes in the riverine flux of DIN comprise an external perturbation that creates autotrophy in the coastal ocean. The doubling of the riverine nutrient flux imposes a net change in NEM of the whole oceanic system of 1.3 Tmol C/yr. The effect on the coastal zone of an increased upwelling flux is an order of magnitude larger at 18 Tmol C/yr. However most of this effect is mainly due to the redistribution of NEM between the coastal and open ocean. A smaller component of this NEM change is attributed to the increased burial of organic carbon within coastal sediments owing to an increase in productivity. Significantly, this term represents only 1.5 Tmol C/yr, the same order of magnitude as the NEM change owing to an increase in riverine DIN discharge. Another interesting result of the simulation concerns the fate of the additional input of DIN during eutrophication. In response to the perturbation, PON production and sedimentation increase, which in turn increases the rates of recycling into DIN and denitrification into N 2 or N 2 O. In the model, the f-factor parameterizes the partitioning between denitrification and recycling. During the numerical simulation, this factor decreased from 1 to 0.94 in the proximal zone because of changes in environmental conditions (Fig. 8C): PON deposition in the sediment increased whereas oxygen and nitrate concentrations in the water column remained constant. These changes led to the net decrease observed in the f-factor, i.e., the denitrification efficiency (see Fig. 5). These results suggest that the role of the proximal coastal ocean in regulating DIN discharged by the rivers is weak. Indeed, denitrification increases by only 0.1 Tmol/yr, which is approximately one-third of the increase of the riverine DIN flux caused by human activities Increase in the Riverine Flux of TOM This numerical experiment simulated the increase in the flux of riverine TOM (RTOM) with time while the other inputs were kept constant. The evolution with time of RTOM was described using the following function: RTOM(t) RTOM final (RTOM init RTOM final )e (t2 /30 2 ) where RTOM final is the final flux (68 Tmol C/yr), RTOM init is the initial flux (34 Tmol C/yr), and t is time. This equation simulates the increase of RTOM flux during the last 50 yr and a relaxation of the perturbation allowing a new steady state to be achieved. In the simulation, the flux of riverine organic matter was doubled (Fig. 9B). There is some uncertainty as to the magnitude of the anthropogenic perturbation on the riverine flux of organic matter. Wollast (1993) indicates that the natural flux of dissolved organic nitrogen has increased by a factor of 2.5 and that of PON by only 30% because of human activity. However, Smith and Hollibaugh (1993) estimate that the POM flux may have doubled since preindustrial times following the rise in riverborne material discharge to the coastal ocean whereas the dissolved organic carbon (DOC) flux did not change greatly. These authors provide different estimates (ranging from 50 to 64 Tmol C/yr) of the present flux of RTOM. Thus, it appears that an estimated doubling of the TOM flux over the past 50 yr might be at the upper bound of the range in estimations. An increase of 50 70% would probably be a more reasonable approximation. Biomass and PP increased substantially in the proximal zone ( 100%) and less so in the distal zone (4%) during the perturbation. The nitrogen derived from the remineralization of the (6)