Landscape-Level Estimation of Nitrogen Removal in Coastal Louisiana Wetlands: Potential Sinks under Different Restoration Scenarios

Journal of Coastal Research

SI

67

75–87

Coconut Creek, Florida

Summer 2013

Landscape-Level Estimation of Nitrogen Removal in Coastal Louisiana Wetlands: Potential Sinks under Different Restoration Scenarios Victor H. Rivera-Monroy†, Benjamin Branoff†, Ehab Meselhe‡, Alex McCorquodale§, Mark Dortch††, Gregory D. Steyer‡‡, Jenneke Visser§§, and Hongqing Wang‡‡

† Louisiana State University Department of Oceanography and Coastal Sciences Baton Rouge, LA 70803, U.S.A. [email protected]

‡ The Water Institute of the Gulf 301 N Main Street, Suite 2000 Baton Rouge, LA 70825, U.S.A.

§ University of New Orleans Pontchartrain Institute for Environmental Sciences New Orleans, LA 70122, U.S.A.

††

‡‡

§§

Moffatt & Nichol 1905B Mission 66, Suite 1 Vicksburg, MS 39180, U.S.A.

U.S. Geological Survey National Wetlands Research Center c/o Livestock Show Office, Parker Coliseum Louisiana State University Baton Rouge, LA 70803, U.S.A.

University of Louisiana-Lafayette Institute for Coastal Ecology and Engineering, Lafayette, LA 70504, U.S.A.

ABSTRACT Rivera-Monroy, V.H.; Branoff, B.; Meselhe, E.; McCorquodale, A.; Dortch, M.; Steyer, G.D.; Visser, J., and Wang, H., 2013. Landscape-level estimation of nitrogen removal in coastal Louisiana wetlands: potential sinks under different restoration scenarios. In: Peyronnin, N. and Reed, D. (eds.), Louisiana’s 2012 Coastal Master Plan Technical Analysis, Journal of Coastal Research, Special Issue No. 67, 75–87. Coconut Creek (Florida), ISSN 0749-0208. Coastal eutrophication in the northern Gulf of Mexico (GOM) is the primary anthropogenic contributor to the largest zone of hypoxic bottom waters in North America. Although biologically mediated processes such as denitrification (Dn) are known to act as sinks for inorganic nitrogen, it is unknown what contribution denitrification makes to landscapescale nitrogen budgets along the coast. As the State of Louisiana plans the implementation of a 2012 Coastal Master Plan (MP) to help restore its wetlands and protect its coast, it is critical to understand what effect potential restoration projects may have in altering nutrient budgets. As part of the MP, a spatial statistical approach was developed to estimate nitrogen removal under varying scenarios of future conditions and coastal restoration project implementation. In every scenario of future conditions under which MP implementation was modeled, more nitrogen (NO 3 ) was removed from coastal waters when compared with conditions under which no action is taken. Overall, the MP increased coastwide average nitrogen removal capacity (NRC) rates by up to 0.55 g N m2 y1 compared with the ‘‘future without action’’  (FWOA) scenario, resulting in a conservative estimate of up to 25% removal of the annual NO 3 þ NO2 load of the Mississippi-Atchafalaya rivers (956,480 t y1). These results are spatially correlated, with the lower Mississippi River and Chenier Plain exhibiting the greatest change in NRC. Since the implementation of the MP can maintain, and in some regions increase the NRC, our results show the need to preserve the functionality of wetland habitats and use this ecosystem service (i.e. Dn) to decrease eutrophication of the GOM.

ADDITIONAL INDEX WORDS: Louisiana, denitrification, Mississippi River, hypoxia, nitrogen uptake, coastal modeling.

INTRODUCTION The potential for aquatic and estuarine ecosystems to mitigate and reduce increasing loads of inorganic nitrogen (N) has been recognized as one of the most relevant ecosystem services in the coastal region of Louisiana (DeLaune and Patrick, 1990; Rivera-Monroy et al., 2010) and other coastal ecosystems (Cook et al., 2006; Cornwell, Kemp, and Kana, 1999). The coastal Louisiana region encompasses the largest DOI: 10.2112/SI_67_6 received 16 November 2012; accepted in revision 4 February 2013; corrected proofs received 4 May 2013. Ó Coastal Education & Research Foundation 2013

deltaic system, at the mouth of the Mississippi River in the Gulf of Mexico (GOM), and the largest area of wetlands in the United States (Shaffer et al., 1992; Visser et al., 2000). Water quality conditions, particularly processes regulating N and phosphorous concentrations in the water column and intertidal wetlands, are expected to change as river diversions are implemented along coastal Louisiana under the 2012 Louisiana Comprehensive Master Plan (CPRA, 2012; Peyronnin et al., 2013). Given the importance of the functional role of the coastal wetlands in sequestering carbon and N (DeLaune and White, 2012) and regulating N export into adjacent coastal waters, assessing the potential role of wetlands as nitrogen

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sinks along salinity and hydrological gradients is a key process needed to construct and constrain landscape-level N budgets, especially since the Mississippi River currently drains ~41% of the conterminous United States, supplying an annual N flux of nearly 1.56 3 106 Mg N to the northern region of the GOM (Alexander, Smith, and Schwarz, 2000; Goolsby et al., 2000, 2001; Rabalais, Turner, and Wiseman, 2001, 2002). Hydrological and nutrient transport studies indicate that most of the N (~90%) dissolved in Mississippi River water travels conservatively through the main stem and ultimately is delivered to the GOM (Alexander, Smith, and Schwarz, 2000). This dissolved inorganic and organic nitrogen load exported into the GOM fuels a growing hypoxic zone (~21,000 km2; Hyfield et al., 2008; Rabalais, Turner, and Wiseman, 2001, 2002; Scavia, Justic, and Bierman, 2004; Turner, Rabalais, and Justic, 2008) negatively affecting water quality conditions and commercial fisheries (Craig, 2012; O’Connor and Whitall, 2007; Switzer, Chesney, and Baltz, 2009). Denitrification is a major biogeochemical pathway for the  þ removal of inorganic nitrogen (e.g. NO 3 , NO2 , NH4 ) in lakes, rivers, and coastal estuaries (Rivera-Monroy et al., 2010). This reduction is biologically mediated through a series of intermediate gaseous products to nitrogen gas (N2) representing a direct loss (i.e. ‘‘sink’’) of NO 3 to the atmosphere. This conversion of NO 3 to N2 gas is currently considered a critical ecosystem service for the removal of highly enriched N from anthropogenic sources (Day et al., 2004; Mitsch and Day, 2006; Mitsch et al., 2001, 2005). Since NO 3 is generally the dominant form of excessive nitrogen entering coastal regions, including coastal Louisiana, it is potentially viable to ameliorate water quality problems through the reduction of NO 3 via direct denitrification (Duncan and Groffman, 1994; Rivera-Monroy et al., 1995; Galloway et al., 2003; Mitsch et al., 2001; Mulholland et al., 2008). As nitrate-enriched water masses flow through the landscape, the presence of riparian areas, headwater streams, and coastal wetlands can efficiently remove reactive N. There is evidence that wetland and riparian ecosystems along the Mississippi River basin can retain up to 70% of NO 3 inflow (Mitsch and Day, 2006). However, large-scale managed input of nutrient-enriched Mississippi waters into wetlands and open waters has been controversial since its implementation in coastal Louisiana, particularly as part of coastal restoration projects (Darby and Turner, 2008; Kearney, Riter, and Turner, 2011; Turner et al., 2007, 2009; VanZomeren, White, and DeLaune, 2012). Presently, there is no clear consensus on whether restoring wetlands with sediment from the river will also enhance the capacity of NO 3 removal, thus reducing risks of eutrophication. Yet, given the ecological and economic importance of denitrification and associated N-process rates (e.g. fixation and nitrification) in waterbodies and wetlands, it is a priority to assess how denitrification rates from different types of habitats contribute to total N removal and identify optimal values when modeling nitrogen transformations at large temporal and spatial scales, particularly in diverse coastal geomorphological regions along the Louisiana coast (i.e. delta, chenier) that will be affected by hydrological and wetland restoration plans in the near future (Day et al., 2007, 2008; Hyfield et al., 2008; Lane et al., 2007).

In this paper, we present a landscape-level analysis of the amount of NO 3 that potentially can be spatially and explicitly removed by freshwater, brackish, and saline wetlands and benthic (open water) sediments along coastal Louisiana. Our nitrogen removal estimates are based on a combination of modeling output and actual denitrification rates reported for Louisiana ecosystems from 1981–2011 (Meselhe et al., 2013; Rivera-Monroy et al., 2010). Modeling output is obtained from linked predictive models simulating salinity, stage, and water quality variables of open waterbodies within estuaries (EcoHydrology model, Meselhe et al., 2013), as well as associated dynamic changes in wetland morphology (Couvillion et al., 2013) and vegetation (Visser et al., 2013). These models were developed for three distinct areas along coastal Louisiana (Chenier Plain region, Atchafalaya-Terrebonne region, and Pontchartrain-Barataria region), wherein the Eco-Hydrology model uses a mass balance approach in irregularly shaped cells or boxes with variable size (0.05–5844 km2; Figure 1). Using these model outputs, we estimated regional total N removal under different restoration scenarios and compared regional values to total N loading throughout the Mississippi and Atchafalaya Rivers to estimate how many metric tons could potentially be removed on an annual basis by wetlands and open water habitats under variable environmental and climatic conditions.

METHODS A numerical application was developed in Visual Basic programming language (Microsoft, 2010) to compile and analyze model output and prepare information for summary statistics and graphical display in maps (Figure 2). This application reads selected datasets (outputs) from the different models used in assessing regional differences in nutrient concentrations (Eco-Hydrology model), geomorphic changes (Wetland Morphology model), and vegetation diversity and spatial distribution (Vegetation model) under different management scenarios (see below). The application produces a raster dataset representing the nitrogen (NO 3 ) removal potential of each cell within the initial model areas (Figure 1). Data inputs to this process include outputs of water quality parameters from the Eco-Hydrology model, changes in land area distribution and elevation from the Wetland Morphology model, change in vegetation coverage and types from the Vegetation model, published denitrification rates reported for Louisiana wetlands, and a denitrification temperature correction factor (Rivera-Monroy et al., 2010). This factor was included because of the significant effect of seasonal changes in temperature range (10–308C) controlling nitrogen transformations on an annual basis in coastal Louisiana wetlands (Rivera-Monroy et al., unpublished data). We used a spatial statistical approach (SSA) wherein we explicitly partition nitrogen removal capacity (NRC; i.e. denitrification [Dn]) rates for vegetation and benthic (open water) sediments as wetlands are converted to open water. Total NRC was estimated by adding vegetation and benthic (open water) NRC values. The SSA uses only Dn rates published for vegetation and open water habitats in Louisiana (Rivera-Monroy et al., 2010) to avoid confounding factors (e.g.

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Figure 1. (A) Model boundaries represented by the Eco-Hydrology ‘‘boxes’’ of the Chenier Plain (red), Atchafalaya (blue), and Pontchartrain-Barataria (green) regions (left). (B) Example of a 0.25 km2 vegetation and nitrogen removal grid cell within one of the Eco-Hydrology boxes.

latitude, geomorphology, hydrology, water management regimes), which occur when including rates obtained in other coastal and freshwater ecosystems. Dn rates in the SSA were grouped using the habitat categories selected by the vegetation

model—saline, brackish, intermediate, fresh marshes—although in this work we combined the intermediate and freshwater vegetation groups into one category (fresh marsh). Experimental Dn rates obtained by direct methods (e.g. 15N

Figure 2. Flow diagram showing modeling process. Initial steps include analyzing water quality outputs from the Eco-Hydrology model (salinity, temperature) and the Vegetation model (vegetation coverage and types) in conjunction with denitrification rates experimentally estimated for each type of habitat. Nitrogen removal is estimated for each 0.25 km2 cell within the vegetation grid (see Figure 1).

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Table 1. Ranges and associated median denitrification (Dn) rates estimated for wetland vegetation habitats and open water sediments used for final estimations of nitrogen (i.e. NO3) removal capacity (NRC). (Data from Rivera-Monroy et al., 2010.) Rate (Dn, lmol m2 h1) Habitat Wetland

Benthic sediment

Class

Low

Medium

High

Low Median

Medium Median

High Median

Fresh and intermediate Brackish Saline Fresh and intermediate Brackish Saline

0–30 0–29.8 0–13.9 0–19.9 0–15 0–11.4

30–200 29.8–80 14–55 19.9–50 15–38.2 11.4–23.6

200–800 80–500 55–241 50–145.4 38.2–74.2 33.6–47.9

15 14.9 6.95 9.95 7.5 5.7

115 54.9 34.5 34.95 26.6 17.5

500 290 148 97.7 56.2 40.7

isotope techniques) were preferentially selected and used; values obtained from indirect methods (e.g. NO 3 disappearance, and nitrous oxide fluxes) were only used when no direct estimates were available for either habitat. After selection of Dn rates, values were ranked in high, medium, and low ranges (Table 1) on the basis of reported experimental conditions reflecting enrichment treatments (i.e. laboratory or field incubations using high NO 3 enrichment or loading rates). Only medium values were applied within the SSA in this particular case to provide a conservative estimate of potential NO 3 removal; however, additional analyses were performed using high and low rates to set bounds for nitrogen removal within the system (data not shown, but see the ‘‘Discussion’’ section). The numerical application locates appropriate files according to user-defined parameters that include scenarios and simulation years. Scenarios represent plausible future environmental conditions, including projected sea level rise, changes in Mississippi River discharge, and storms. Groups represent either a future without action (FWOA) or a future in which the Master Plan (MP) is implemented (CPRA, 2012). Simulation years covered a 50 year time span from 2010 to 2060. The modeled scenarios were evaluated using a planning tool, which is an ‘‘objective function computer program designed to provide an analytical and objective basis for comparing different risk reduction and restoration projects and for developing groups of projects, or alternatives, for consideration in the Master Plan’’ (Peyronnin et al., 2013). This interactive tool compares several of possible risk reductions and restoration projects for three environmental scenarios designed to evaluate the robustness of project and plan outcomes over 50 years (Peyronnin et al., 2013). The scenarios are: Moderate scenario, Moderate with High Sea Level Rise scenario, and Less Optimistic scenario (Table 2). In each scenario, the same variables are taken into consideration, but ranges vary to reflect a set of environmental uncertainties as reflected in different values. These variables include: sea level rise (mm), subsidence (m), storm intensity (%), storm frequency (%), Mississippi River discharge (ft3 s1), rainfall (%), evapotranspiration (6 historic monthly mean), Mississippi River nutrient concentration (N and phosphorous, mg L1), and marsh collapse threshold (salinity and inundation depth) (Table 2). The Moderate with High Sea Level Rise scenario was added specifically for the plan comparison based on input from an external review board and the latest scientific predictions (Peyronnin et al., 2013). The formulation of the MP focused on the selection of high-performing projects on the basis of their

individual outcomes, particularly related to size (.500 acres) and sediment diversions with variable discharges. By focusing on individual project outcomes, the MP was able to compare projects objectively while considering resource and funding constraints. On the basis of these criteria, 397 projects were evaluated using this strategy. Our NRC results are not focused on individual projects; rather, they are focused on overall changes in NRC at the landscape level by region (Figure 1) to determine large spatial scale of NO 3 fate as modified by the different scenarios. For a further description about project characteristics (e.g. discharge) and screening criteria, see the paper by Peyronnin et al. (2013).

Nitrogen Removal Algorithm Estimation Sequence The numerical processes algorithm starts with mining of water salinity and temperature data from the Eco-Hydrology model outputs (Figure 2). Once the appropriate salinity input file is found and selected, a reader process is initiated and the application reads monthly salinity values over a period of 1 year for each of the irregularly shaped ‘‘box’’ delineations (Figure 1). Monthly salinity values are then averaged for each ‘‘box’’ to produce a yearly mean. The corresponding temperature file is then read from the Eco-Hydrology model output in a fashion similar to the salinity data file. However, the temperature values are not just averaged, they are converted into a denitrification correction factor (using a piecewise function; Rivera-Monroy and Branoff, 2012) on the basis of experimental results (Rivera-Monroy et al., unpublished data); this factor reduces potential denitrification rates accordingly, and these correction factors are then averaged into a yearly mean. Annual water quality means for each irregularly shaped box in the Eco-Hydrology model are then translated into the finer resolution of 500 3 500 m (0.25 km2) vegetation grid using a conversion file. After this step, a two-dimensional array is produced for both the salinity and temperature correction factor, representing values for each 0.25 km2 cell within the vegetation grid. A reader file registers the first half of the vegetation file for the appropriate year, which is a raster dataset of the individual CELL IDs; this dataset is then stored in a two-dimensional array for later use. The reader then begins the second half of the vegetation file, which is the aerial coverage of different vegetation classes found within each of the cells labeled CELL ID. A number of one-dimensional arrays are created, each representing the area of a particular habitat type found within a given cell of name CELL ID. Once completed, the program analyzes all resulting data for the appropriate

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Table 2. Environmental and climatic conditions used as criteria to implement modeling scenarios (CPRA 2012, p. 85).

Environmental Uncertainty Sea level rise (m over 50 y) Subsidence (mm y1)a Storm intensity (% current intensities) Storm frequency (% current frequency) Mississippi River discharge % Annual mean Mean annual discharge (ft3 s1) Rainfall

Evapotranspirationa Mississippi River nutrient concentration

Plausible Range 0.16–0.8 0–35 Current intensities to þ30 20 to þ10

Less Optimistic Value

0.27 0–19 þ10

0.78 0–19 þ10

0.45 0–25 þ20

Current frequencyb

Current frequencyb

þ2.5c

534,000 Variable percent historical monthly mean Historical monthly mean 12% of current concentrationse

534,000 Variable percent historical monthly mean Historical monthly mean 12% of current concentrationsf

5 509,000 Variable percent historical monthly mean þ0.4 SD from historical monthly mean Current concentrationsg

Midrange values of salinity and inundation result in collapse

Midrange values of salinity and inundation result in collapse

Lower 25th percentile values of salinity and inundation result in collapse

4–7 6–8

6 7

6 7

5 7

31–38 20–26 16–23

34 23 21

34 23 21

33 21 18

7 to 14d Historical monthly range; varies spatially Historical monthly range (61 SD) 45% to þ20% of current nitrogen and phosphorus concentrations

Marsh collapse threshold

Salinity (ppt) Swamp Fresh marsh Inundation (water depth, cm) Intermediate marsh Brackish marsh Saline marsh

Moderate with High Sea Level Rise Value

Moderate Value

a

Values vary spatially. One Category 3 or greater every 19 y. c One Category 3 or greater every 18 y. d Adjusted for seasonality. e In mg L1: phosphorus ¼ 0.19; nitrate þ nitrate ¼ 1.1; ammonium ¼ 0.038; organic nitrogen ¼ 0.67. f In mg L1: phosphorus ¼ 0.19; nitrate þ nitrate ¼ 1.1; ammonium ¼ 0.038; organic nitrogen ¼ 0.68. g In mg L1: phosphorus ¼ 0.22; nitrate þ nitrate ¼ 1.3; ammonium ¼ 0.044; organic nitrogen ¼ 0.77. b

year, and an output file is created and a writer process is initiated to write the results to the file. The algorithm begins by analyzing each cell within the vegetation grid to determine its annual nitrogen removal based on areal coverage of each habitat type within the cell and the salinity and temperature of that cell during that year. The output is determined as follows: If the value found within the input vegetation file is the NODATA_value, then the output is also NODATA_value, meaning that the cell is not represented in the model. If the cell in question contains open water, the salinity of that water is determined by using the corresponding value from the salinity array created in the first part of the process. Once the salinity is determined, the appropriate nitrogen removal rate from Table 1 is multiplied by the corresponding temperature correction value (Figure 2). The new nitrogen removal value is applied by multiplying it by the open water area; the result is the nitrogen removed by the open water habitat within that cell. This value accumulates for each cell to create an estimate for the total nitrogen removed for each region. The individual values are converted to a rate comparable to the Eco-Hydrology model output units (g N m2), and the value is stored in the raster dataset. A similar process continues if the vegetation array contains vegetation as well as, or instead of, open water. The nitrogen removed by the

vegetation within that cell is determined by multiplying the area of each fresh, brackish, and saline habitat type by their respective temperature-reduced nitrogen removal rates. Results for each habitat type are added to determine the nitrogen removed by vegetation within that cell, and the output displays either open water removal, vegetation removal, or both (Figure 2). Percent change in NRC values was also calculated for each cell over the 50 y simulation period under each scenario. This percentage was obtained by subtracting the year 1 NRC value from the year 50 NRC value and taking this difference over the year 1 NRC value, as indicated by Equation (1): %Change ¼

NRCYear 50  NRCYear 1 3 100 NRCYear 1

ð1Þ

This calculation provides a positive percent change value for ‘‘positive,’’ or more desirable, outcomes and a negative percent change for ‘‘negative,’’ or less desirable, outcomes. For instance, if the NRC increases in the future, this is considered a more desirable outcome, and the result is a positive percent change, allowing us to determine those areas most affected by various management decisions and environmental scenarios.

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Figure 3. Nitrogen (NO 3 ) removal capacity (NRC) in benthic and vegetation habitats under Moderate and Less Optimistic Future scenarios from 2010 to 2060. Simulations include runs for a Future Without Action (FWOA) and implementation of the Master Plan (MP).

RESULTS AND DISCUSSION Published in situ and experimental denitrification rates for coastal Louisiana show a consistently lower rate (2–3 times) for benthic habitats compared with wetland habitats, and this difference is reflected in the total NRC values (Table 1, Figure 3). In all scenarios where the master plan was implemented, estimated total NRC values were higher for vegetation habitats (Figures 3–6). For example, in the Moderate scenario (Table 2), total NRC (benthic þ vegetation) under FWOA (220,269 tonnes [metric tons, t]; Figures 4A and B) is less than under the MP implementation (241,062 t; Figures 4G and H) in 2010; a similar trend was observed for year 2060, for which the difference in NRC values between FWOA (Figures 4C and D) and MP (Figures 4I and J) is 35,293 t. This trend is similar in the Less Optimistic scenario, in which the total NRC differences between FWOA and the MP in years 2010 and 2060 are 23,224 and 29,816 t, respectively (Figures 5A–J). Similarly, in the Moderate with High Sea Level Rise scenario, total NRC difference between simulation years is 21,549 t (2010) and 34,159 t (2060), with consistently higher values for

conditions in which the MP was implemented (Figures 6A–J). Figure 3 shows the particular time series trend of NRC values for benthic and vegetation habitats (million kg N and g N m2 y1) for different years of simulation under the Moderate and Less Optimistic scenarios. The greater contribution of NRC corresponds to the vegetation habitat with consistent differences for all years. In contrast, the benthic NRC values are slightly higher in both conditions for FWOA compared with the MP. This difference is apparently the result of an increase in benthic habitat under the FWOA condition, wherein wetland habitat is constantly lost as a result of changes in sedimentation patterns and lack of sediment input in more vulnerable areas in the Pontchartrain-Barataria modeling region. Spatial changes in nitrogen removal rates are strongly associated with the dominant regional geomorphological setting (chenier vs. delta). In the Moderate scenario under the MP, the major changes in NRC are observed along inland wetlands, particularly in freshwater wetlands in the Pontchartrain-Barataria region (Figure 4). High N removal rates are as high as 13 g N m2 y1 for both 2010 and 2060, which is close to observed NR rate (14.7 g N m2 y1) by a freshwater marsh

Journal of Coastal Research, Special Issue No. 67, 2013

Figure 4. Nitrogen removal capacity (NRC, g m2 y1) values and 50 y NRC percent change estimated for the Moderate scenario. The numbers in parentheses are the total NRC (metric tons) for the entire coastal region for each scenario combination; see Table 2 for scenario description.

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Figure 5. Nitrogen removal capacity (NRC, g m2 y1) values and 50 y NRC percent change estimated for the Less Optimistic scenario. The numbers in parentheses are the total NRC (metric tons) for the entire coastal region for each scenario combination; see Table 2 for scenario description.

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Figure 6. Nitrogen removal capacity (NRC, g m2 y1) values and 50 y NRC percent change estimated for the Moderate with High Sea Level Rise scenario. The numbers in parentheses are the total NRC (metric tons) for the entire coastal region for each scenario combination; see Table 2 for scenario description.

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Table 3. Variation in coast-wide nitrogen (NO 3 ) removal capacity (NRC) values for wetlands (see Figure 4) under the Moderate Future Conditions scenario (Table 2) and based on the range of denitrification rates measured in Louisiana (Table 1). Only median values were used in this study as a conservative estimation of NRC (FWOA ¼ Future Without Action; MP ¼ Master Plan). FWOA

MP

Scenario

N Removal (t N)

N Removal Rate (gN m2 y1)

% Median Value

N Removal (t N)

N Removal Rate (gN m2 y1)

% Median Value

Low Median High

24,735 190,050a 802,734

1.30 9.31 42.27

13 100 422

26,751 211,720b 870,249

1.34 9.76 43.75

13 100 411

a b

Figure 4B. Figure 4H.

receiving diverted Mississippi River water with a typical nitrate concentration of 1 mg L1 (Yu, DeLaune, and Boeckx, 2006). The 50 year NRC percent change between those years is more evident in the benthic habitat, where changes are more apparent in the Chenier Plain (Figures 4E, F, K, L). Even when the MP is implemented, the environmental uncertainties (Table 2) used in the modeling exercise strongly influence the spatial differences (Table 3) in NRC rates. For example, when the MP is implemented under both Less Optimist and Moderate scenarios, total vegetation NRC is much higher in the Moderate scenario (208,651 t; Figure 4J) than under the Less Optimistic scenario (184,264 t; Figure 5J) conditions by year 2060. In a FWOA in year 2010, the coast-wide total (benthic þ vegetation) NRC is 220,269 t (Figures 4A and B), which decreases by 9% over the 50 years if no restoration actions are implemented. Most of the reduction occurs around Lake Pontchartrain and the Chenier Plain regions, particularly for benthic habitats. Overall, the MP increased the coastwide average nitrogen removal rate by 0.55 g N m2 y1 under the Moderate scenario and by 0.51 g N m2 y1 under the Less Optimistic scenario compared with the rate under FWOA over the 50 year simulation period (Figure 3). The overall annual nitrogen removal rates under both FWOA and MP at vegetated areas (i.e. 7–9 g N m2 y1) are within the range of 4.5–9.0 g N m2 y1 reported in a cross-GOM estuarine study (Twilley et al., 1999), indicating that the medium-range Dn rates used in this study provide reasonable estimates of total NR values for different environmental scenarios under both FWOA and MP. Although NR rates for benthic areas under the MP decreased under both environmental scenarios by 0.022 and 0.02 g N m2 y1, respectively, they increased by 1.12 and 1.06 g N m2 y1 for vegetated areas. The large NRC spatial variation across coastal Louisiana underlines the dynamic change triggered by the implementation of restoration measures at different scales, particularly in the Atchafalaya-Terrebonne and Pontchartrain-Barataria regions. Considering all scenarios used in our analysis, the coast-wide total (benthic þ vegetation) NRC ranges from 183,514 to 241,062 t y1. In general, these values are twice the value of the monthly NO 3 loading rate (~100,000 t) entering the GOM directly through the Mississippi and Atchafalaya Rivers (Goolsby and Battaglin, 2001; Turner, Rabalais, and Justic, 2012). Furthermore, the mean annual total N flux into the GOM has been estimated as 1,568,000 t y1, of which  approximately 61% (956,480 t y1) is NO 3 þ NO2 (Goolsby et al., 2001). Thus, coastal wetlands and open water habitats

across coastal Louisiana could potentially remove from 19% to 25% of the total NO 3 load into the GOM. This estimated range is based on medium denitrification rates (Table 1) and therefore represents a conservative estimate. If maximum denitrification values are included for fresh and intermediate, brackish, and saline water for both vegetation (148–500 lmol m2 h1) and benthic sediments (41–97 lmol m2 h1; Table 1), these removal percentage ranges can increase to 45%–75% of the total NO 3 load into the GOM. We acknowledge that the current delivery of N loads into coastal Louisiana is constrained by channelization of water flow that delivers most of the inorganic nitrogen directly into GOM coastal waters (Alexander, Smith, and Schwarz, 2000; Clark et al., 2002; McIsaac et al., 2002; Twilley and RiveraMonroy, 2009; White et al., 2009), particularly during the dry season when water levels are low and when there is a lack of flooding into adjacent wetlands along the channels. However, our calculations are aimed to underline the functional role, at large spatial scales (hundreds of km2), of natural biogeochemical transformations (i.e. denitrification) in reducing eutrophication in the coastal zone as a result of excess inorganic nitrogen, especially NO 3 . Since the 2012 Louisiana MP includes a wide arrangement of small- and large-scale water/ sediment diversions, it is critical to incorporate engineering designs that would allow discharge of water into coastal wetlands and that increase residence time of water masses over these systems to promote N2 gas production through denitrification (Dettmann, 2001). Achieving this conversion represents a net loss of excess N from the system, thus reducing at least between 50,000 and 100,000 t N y1 in areas where wetlands are developing as a result of large-scale sediment inputs. For example, current estimates of in situ net and direct denitrification rates in recently formed wetlands in the Wax Lake delta indicate that denitrification rates are .100 lmol m2 h1 (.12 t km2 y1; e.g. Henry, 2012). Similarly, recent experimental studies showed that under large NO 3 loading rates reflecting high NO 3 concentration during peak river 1 discharge (1–2 mg NO 3 L ; VanZomeren, White, and DeLaune, 2012), marsh soils receiving freshwater diversions can remove up to 81 t km2 y1. Because of the significant spatial differences in denitrification rates that are associated with wetland spatial distribution (Table 1) along salinity and tidal gradients, it is expected that wetland and benthic habitat NRC rates will show major spatial differences across the coast under restoration measures. Our analysis shows that the potential NRC of wetlands across the

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entire wetland and open water Louisiana coast for a Less Optimistic FWOA 2010 scenario (no MP implemented) is 207, 283 t (vegetation þ benthic; Figures 5A and B). This value represents the potential removal of inorganic nitrogen (NO 3) by freshwater, brackish, and saline wetlands and benthic sediments in open water areas under current conditions. Moreover, this number also implies that direct denitrification is the only biological process involved in the transformation of inorganic nitrogen to N2. Overall, denitrification is a form of anaerobic respiration performed only by certain genera of  bacteria, in which NO 3 (or NO2 ) is used as a terminal electron acceptor for the oxidation of organic compounds and is ultimately reduced to gaseous end products like N2O (nitrous oxide) and N2. This loss of N from the coastal region represents a true sink (Boynton et al., 2008; Cornwell, Kemp, and Kana, 1999; Jenkins and Kemp, 1984; Kemp et al., 1982; RiveraMonroy and Twilley, 1996) because N is totally removed from the system into the atmosphere, unless it returns via biological nitrogen fixation (Fulweiler et al., 2007). Another potential process to remove inorganic nitrogen is coupled denitrification,  where NHþ 4 is transformed to NO3 by nitrification and then converted to N2 (Rivera-Monroy and Twilley, 1996). Because a limited number of studies assess coupled denitrification rates in all types of wetland habitats in Louisiana, this transformation was not taken into consideration when assessing N removal. If coupled denitrification is considered, total removal could slightly increase by 2%–10% given the low observed NHþ 4 1 loading rates (31,360 t y1) in contrast to NO 3 (953,000 t y ; Goolsby et al., 2001). Our estimated NRC values do not consider other gases produced during denitrification (e.g. nitrous oxide) and ANaerobic AMMonium OXidation (ANAMMOX), another bacteria-mediated N biogeochemical transformation producing N2; although, it has been estimated that ANAMMOX is less than 5% of the total N2 production in reduced marsh sediments and other shallow systems, particularly in brackish and saline wetlands (Dalsgaard et al., 2012; Humbert, Zopfi, and Tarnawski, 2012; Koop-Jakobsen and Giblin, 2009, 2010). Comparatively, all scenarios analyzed in this work show that the annual wetland NRC value (e.g. 190,050 t y1; Figure 4B) is about six times greater than the value for benthic sediments (e.g. 30,219 t y1; Figure 4A), underscoring the large spatial scale role wetlands perform in regulating N-cycle transformations in the Louisiana coastal zone. However, this estimation does not include the temporal removal of inorganic nitrogen from water and sediments by plant uptake, which represents a conversion of dissolved inorganic nitrogen to organic nitrogen. Storage of N in plant tissues above and below ground should also be considered when assessing the total N budget in wetland habitats, particularly in the Louisiana coastal region (DeLaune and Patrick, 1990; DeLaune, Patrick, and Smith, 1992; DeLaune, Pezeshki, and Jugsujinda, 2005; DeLaune, Smith, and Patrick, 1983). Plant uptake is actually not considered a net N sink because of the N stored in plant tissues (as organic nitrogen) that remains in the wetland and sediments, whereas denitrification is a net sink because N is converted to gas (N2). Nevertheless, plants on a seasonal basis remove a large amount of dissolved inorganic nitrogen that can result in similar N percentage loss (~10%–20%) compared with

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N loss via denitrification. Further work is needed to estimate the large-scale N storage, both annually and seasonally, by wetland biomass both above and below under all scenarios.

CONCLUSIONS Our results are closely related to current and future changes in vegetation composition and distribution (Visser et al., 2013). The vegetation model simulation analysis indicates that the implementation of the MP could decrease the extension of saline and brackish areas, but increase freshwater vegetation areas. Since the denitrification potential of freshwater vegetation is higher than for other types of wetlands (Table 1), it is expected that in any location where freshwater expands, as a result of the MP (e.g. river diversions), large ‘‘hot spots’’ of N removal will be developed. Indeed, freshwater marshes receiving diverted Mississippi River water could denitrify up to 110 t km2 y1 (Yu, DeLaune, and Boeckx, 2006). Additionally, ‘‘cool spots’’ could also develop where NRC is inhibited or reduced because of environmental factors such as temperature and salinity. Depending on the distribution and abundance of these spots, coast-wide NRC in a FWOA scenario for vegetation could vary from 13% to 422% of the values presented here (Table 3); this range of variation is also similar in scenarios when the MP is implemented (13%–411%). This wide range in NRC is directly related, among other environmental variables, to the direct relationship between NO 3 loading and denitrification rates (e.g. Mulholland et al., 2008, 2009; Rivera-Monroy and Twilley, 1996). Specific analysis by location at smaller scales (,10 km2; the vegetation grid has a cell resolution of 5003500 m) is needed; however, it is apparent that in areas where freshwater diversions are already present (e.g. Breton Sound, Davis Pond/Barataria Bay; e.g. DeLaune, Pezeshki, and Jugsujinda, 2005) or planned, total NRC will be among the highest values. NRC hot spots can be observed in Figures 4K, 5K, and 6K, where the MP promotes major changes in benthic NRC at the boundary between the Chenier and Atchafalaya regions and in wetland areas in the Chenier Plain and Pontchartrain-Barataria regions (Figures 4L, 5L, and 6L). Because the implementation of the MP can maintain, and in some regions increase the NRC, our results show the need to preserve the functionality of wetland habitats (saline, brackish, and freshwater) and use this ecosystem service (i.e. denitrification) to decrease eutrophication of the GOM under current conditions and with future implementation of the Master Plan.

ACKNOWLEDGMENTS Funding was provided for this effort by the Coastal Protection and Restoration Authority (CPRA) of Louisiana, through the development of the 2012 Coastal Master Plan and the Louisiana State University NOAA–Sea Grant Program (agreement R/MMR-33/2010–2012). Special thanks to Kristin DeMarco (CPRA), A. ‘‘Carol Parsons’’ Richards (CPRA), and Alaina Owens (The Water Institute of the Gulf) for their support and constructive comments during the development of the modeling approach to analyze nutrient data. The authors thank Dr. Jeffrey Cornwell, Dr. Michael Osland, two anonymous reviewers for comments and suggestions to earlier versions of the original algorithm used in this work. Any use of trade, product, or firm names is for

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descriptive purposes only and does not imply endorsement by the U.S. Government.

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