Hydrologic Versus Biogeochemical Controlsof Denitrification in Tidal Freshwater Wetlands

Scott Ensign & Kaylyn Siporin & Mike Piehler &

Martin Doyle & Lynn Leonard

Received: 4 April 2011 /Revised: 7 February 2012 /Accepted: 16 February 2012 /Published online: 16 March 2012# Coastal and Estuarine Research Federation 2012

Abstract Tidal freshwater wetlands (TFW) alter nitrogenconcentrations in river water, but the role of these processeson a river’s downstream nitrogen delivery is poorly under-stood. We examined spatial and temporal patterns in deni-trification in TFWof four rivers in North Carolina, USA andevaluated the relative importance of denitrification rate andinundation on ecosystem-scale N2 efflux. An empiricalmodel of TFW denitrification was developed to predict N2

efflux using a digital topographic model of the TFW, a timeseries of water level measurements, and a range of denitri-fication rates. Additionally, a magnitude-frequency analysiswas performed to investigate the relative importance ofstorm events on decadal patterns in N2 efflux. Spatially,inundation patterns exerted more influence on N2 effluxthan did the range of denitrification rate used. Temporalvariability in N2 efflux was greatest in the lower half ofthe tidal rivers (near the saline estuary) where inundation

dynamics exerted more influence on N2 efflux than denitri-fication rate. N2 efflux was highest in the upper half of therivers following storm runoff, and under these conditionsvariation in denitrification rate had a larger effect on N2

efflux than variability in inundation. The frequency-magnitude analysis predicted that most N2 efflux occurredduring low flow periods when tidal dynamics, not stormevents, affected TFW inundation. Tidal hydrology and ri-parian topography are as important as denitrification rate incalculating nitrogen loss in TFW; we present a simpleempirical model that links nitrogen transport in rivers withloss due to denitrification in TFW.

Keywords Tidal freshwater wetland . Tidal forestedwetland . Tidal river . Denitrification . LIDAR . Nitrogencycling

Introduction

The tidal exchange of water and solutes between tidal fresh-water wetlands (TFW) and rivers affects solute concentra-tions in the river, which in turn affects broader-scale soluteflux from watersheds to the coastal ocean. While TFWconstitute a small part of the landscape, they play a dispro-portionately large role in biogeochemical cycling because oftheir high degree of hydrologic connectivity with their ad-joining rivers. Nitrogen is particularly reactive in TFW, andthe downstream flux of river-borne nitrogen can be reduced20–35% by TFW processes in large rivers (Seitzinger 1988),2–15% in smaller rivers (Ensign et al. 2008), or about 1%/river km (Bowden et al. 1991). Knowledge of how tidesaffect marsh flooding is necessary for prediction of nutrientconcentrations in saline estuaries (Vörösmarty and Loder1994), and the same information on hydrologic coupling

S. Ensign (*)Curriculum for the Environment and Ecology,University of North Carolina at Chapel Hill,Chapel Hill, NC, USAe-mail: sensign@usgs.gov

K. Siporin :M. PiehlerInstitute of Marine Sciences,University of North Carolina at Chapel Hill,Morehead City, NC, USA

M. DoyleDepartment of Geography,University of North Carolina at Chapel Hill,Chapel Hill, NC, USA

L. LeonardDepartment of Geography and Geology,University of North Carolina at Wilmington,Wilmington, NC, USA

Estuaries and Coasts (2013) 36:519–532DOI 10.1007/s12237-012-9491-1

between river channels and adjoining TFW is needed tobetter understand solute flux in tidal rivers.

Daily inundation of TFW by tides is necessary for the twoprocesses which permanently sequester river-borne nitrogen:denitrification and long term burial by sediment accretion.This study focused on the process of denitrification: the mi-crobial reduction of NO3

− to N2 (a non-reactive gas that isemitted to the atmosphere) that occurs in the absence of O2 inriparian sediments. Total N2 efflux at the scale of an entiretidal river is the product of the rate of denitrification, the areaover which it occurs, and the duration of denitrifying condi-tions. Ultimately, it is this landscape-scale N2 efflux which isnecessary for predicting the delivery of terrestrially derivednitrogen to the ocean (Davidson and Seitzinger 2006, andaccompanying articles).

Efforts to extrapolate landscape-scale N2 efflux are com-plicated by the spatial and temporal variability in denitrifi-cation rate (Cornwell et al. 1999; Kulkarni et al. 2008), andthis variability has garnered much attention in the biogeo-chemical “hot spots” literature (Groffman et al. 2009). Add-ing to the high variability in denitrification rate is thevariability in inundation across a landscape, particularly inTFW where inundation continually changes due to tidalinfluence. While the spatial and temporal variation in deni-trification rate has been studied extensively in TFW toimprove the accuracy of landscape-scale extrapolations(Neubauer et al. 2005; Gribsholt et al. 2006, 2007; Ensignet al. 2008; Hopfensperger et al. 2009), less attention hasbeen given to how the variability in inundation along a TFWtidal gradient affects these extrapolations. With two sourcesof variation affecting the calculation of N2 efflux, denitrifi-cation rate, and inundated area, a fundamental questionremains: is N2 efflux more sensitive to the temporal andspatial variation in microbial processing or variation ininundation? How does TFW topography along a tidal gra-dient and associated inundation patterns affect where, when,and how much N2 efflux occurs along a tidal river? More-over, is there a predominant driver that can be used to scaleN2 efflux occurring in TFW over broad spatial and temporalscales? These questions are the focus of the current study.

The temporal and spatial patterns in N2 efflux from TFWhave implications beyond the challenges they pose tolandscape-scale models of nitrogen cycling. TFW are ad-vancing inland as sea level rises, thus changing the spatialconfiguration of the landscape itself. A rough approximationof this rate of tidal migration highlights the importance ofthis process over contemporary timescales: the quotient ofcoastal river slope in NC (0.0009 on average, Sweet andGeratz 2003) and the current rate of sea level rise in NC(0.003 m year−1; NOAA 2004) results in a landward migra-tion of 3.3 m year−1. Over the coming decade, the spatialpatterns we observe in N2 efflux today may shift inland33 m (depending on patterns of sediment accretion), thereby

changing broader-scale patterns in TFW nitrogen cycling(Craft et al. 2009). Predicting how this process will affectnitrogen cycling as sea level rises requires knowledge of thetemporal and spatial patterns in N2 efflux and theirlandscape-scale controls in TFW.

This study investigated the dynamics of TFW inundationand their potential influence on N2 efflux. Our objective wasto identify the relative importance of the two components ofN2 efflux: denitrification rate and inundation extent. Weused a modeling approach wherein field observations ofwater level were merged with digital topographic data topredict inundation along the entire length of tidal rivers ofwidely varying watershed area. N2 efflux was calculatedusing rate measurements previously reported for one ofthese rivers (Ensign et al. 2008). The model allowed exam-ination of the relative influence of inundation versus deni-trification on N2 efflux given the spatio-temporal variationin both variables.

Methods

Summary of Analytical Approach Since both inundationand denitrification are variable in space and time, our studyfocused on analyzing the effect of variation in these driverson N2 efflux. We assumed that denitrification only occurredunder reduced conditions when a floodplain was inundated,and thus the variation in N2 efflux in space and time wasproportional to the variation in inundation; spatio-temporalvariation in N2 efflux was further modified by the denitrifi-cation rate. If variation in denitrification rate was high andvariation in inundation was low, variation in N2 efflux mayprimary reflect the variation in denitrification rate. Alterna-tively, if variation in denitrification rate was low and varia-tion in inundation was high, variation in N2 efflux mayprimarily reflect variation in inundation. We quantifiedspatio-temporal patterns of floodplain inundation in a tidalriver and used a range of denitrification rates to calculate therange of potential N2 efflux. If the resultant ranges of pre-dicted N2 efflux overlapped spatially or temporally, thendenitrification rate was considered equal to, or more impor-tant than, inundation in predicting N2 efflux. When thepredicted ranges of N2 efflux did not overlap, this indicatedthat the dynamics of inundation were more important thanvariation in denitrification in predicting N2 efflux.

This comparative analysis of the predicted range in N2

efflux examined both the spatial and temporal variations ininundation (the spatial and temporal variation in denitrifica-tion rate is discussed in N2 Efflux below). River reacheswere subdivided into 1- or 3-km segments to examinespatial patterns of inundation along four rivers drainingadjoining watersheds. We compared topographic patternsbetween these rivers to help distinguish between the effects

520 Estuaries and Coasts (2013) 36:519–532

of topography and water level variation on inundation dy-namics. We examined temporal variation in N2 efflux ineach river by modeling inundation for one month, therebycapturing temporal variability due to both spring-neap tidalcycles and river discharge variation due to watershed runoff.The temporal variability in river discharge (and its influenceon inundation) during a month is small relative to annualvariability, and thus an important question was the extent towhich large watershed runoff events (that may not be cap-tured in a single month of inundation measurement) affectlong-term cumulative N2 efflux. We performed a frequency-magnitude analysis to address this question using our N2

efflux predictions and 10 years of water level data from aUS Geological Survey (USGS) gage (described in Frequen-cy-Magnitude Analysis below).

Study Area Our study investigated the tidal freshwater (<0.5psu) and oligohaline (<5 psu) portion of four coastal plainrivers in North Carolina of varying lengths and watershedareas (Fig. 1; Table 1). We included the oligohaline portionof the river since the position of the freshwater-oligohalineboundary varies several kilometers due to seasonality inriver discharge. The National Wetlands Inventory (NWI;U.S. Fish and Wildlife Service 2010) categorizes the pre-dominant riparian vegetation community as freshwater for-ested/shrub wetland in all rivers, followed by estuarine andmarine wetland in the Newport and White Oak Rivers(Table 1). Emergent freshwater wetlands were only reportedby the NWI as occurring in Newport River (Table 1), butpersonal observation revealed that small areas (100–1,000 m2) of emergent freshwater wetlands do occur alongthe margins of the White Oak and Northeast Cape FearRivers, as well.

Floodplain Topography A digital topographic model of thetidal river’s riparian zone was developed using geographicinformation software (ArcGIS, ESRI, Redlands, CA) andLight Image Detection and Ranging (LIDAR) data. Com-parison of these topographic models with other digital datasources is described in Rayberg et al. (2009), and a similartopographic analysis of floodplain inundation was per-formed by Diefenderfer et al. (2008). The LIDAR data wereobtained from the North Carolina Floodplain Mapping Pro-gram (NCFMP), and have a vertical accuracy of ≤0.2 mRMS (NCDEM 2002; 2004a and b). The location and shapeof river channels was represented using digital line andpolygon files of surface hydrology distributed by theNCFMP. LIDAR data within 60 m of the channels wereextracted for analysis, and a triangulated irregular network(TIN) was created to provide a continuous representation oftopography (based on the NAVD88 datum) across the flood-plain. A 50-m width of the original 60 m-wide TIN wasanalyzed to eliminate edge artifacts created by the

topographic modeling process. This 50 m floodplain widthwas chosen based on personal observation that inundationcan extend at least this far into the floodplain. Elevation ofthe TIN was summarized in segments (1 river km in theNewport, New, and White Oak Rivers and 3 river km in theNortheast Cape Fear River) using a function within ArcGISwhich computes the three-dimensional area inundated at agiven water level. A series of elevations between 0 and1.5 m were used to generate hypsometric curves for thefloodplain area inundated within each river segment.

Water Level Measurements Water level was measured in thefour rivers over a 29.5-day period (one lunar month) toencompass one spring-neap tidal sequence. The NewportRiver was monitored from December 2009 through January2010, a winter period when high river discharge is common.Three HOBO water level loggers (Onset Computer Corpo-ration, Pocasset, MA) were installed in the subtidal river bedat 6-, 11-, and 19-km upstream from the oligohaline–meso-haline transition (34.75368° N, 76.77309° W). Water levelmeasurements (accuracy±3 mm) were logged every 5 minand subsequently corrected to NAVD88 datum using eleva-tion benchmarks measured with a Trimble RTK-GPS (Trim-ble Navigation Limited, Sunnyvale, CA).

The White Oak River was monitored from June throughJuly 2009, a period when river discharge is typically low.Four HOBO water level loggers were installed in the sub-tidal river bed at locations 8, 12, 15, and 17 km upstreamfrom the oligohaline–mesohaline transition (34.76808° N,77.15074° W), and water level was logged every 5 min.River discharge during this period was near base flow, so weassumed that the average water level at each of the four siteswas mean local sea level. This average was subtracted fromeach water level measurement to calculate the water elevationrelative to local mean sea level (LMSL), and LMSL wasconverted to NAVD88 by subtracting 0.134 m (the offsetdetermined using NOAA’s Vdatum model (http://vdatum.noaa.gov/) at the mouth of the White Oak River, 34.6379 N,77.1037 W).

The New River was monitored from May 2010 throughJune 2010. Water level data (NAVD88) recorded at 15-minintervals were obtained from the USGS gages at Jackson-ville (#0209303205) and Gum Branch (#02093000). TheJacksonville gage is located in the mesohaline portion ofthe estuary 2 km downstream from the study area, and GumBranch marks the upstream extent of tidal influence.

The Northeast Cape Fear River water level was moni-tored from March through April 2010. Water level at 15-minintervals was obtained from the USGS gage at Burgaw(#02108566), located 73 km from the mesohaline estuary.These measurements were converted from NGVD29 datumto NAVD88 using the NOAA VERTCON model, whichresulted in subtracting 0.293 m from the NGVD29 values

Estuaries and Coasts (2013) 36:519–532 521

Fig. 1 The location of the rivers studied in North Carolina. The thick black lines indicate the extent of the tidal freshwater zone, and the shadedgray indicates the extent of the watershed

522 Estuaries and Coasts (2013) 36:519–532

(http://www.ngs.noaa.gov/cgi-bin/VERTCON/vert_con.prl). Water level in the lower Northeast Cape Fear Riverwas measured at NAVD88 every 6 min at gages 4 and 15 kmfrom the oligohaline–mesohaline transition (34.32576° N,77.96791° W). These gages consisted of a UNIDATA (Uni-data Pty Ltd, Perth, Australia) shaft-encoded water levelrecorder housed in an aluminum stilling well.

Wetland Inundation Inundation in each river segment (1 kmin the Newport and White Oak Rivers, 3 km in the NortheastCape Fear River) was calculated from hypsometric curves(inundated TFW area versus water level) and the water levelmeasured closest to that segment. Water levels less than 0 m(NAVD88) was assumed to equate to zero inundated flood-plain area. All calculations of inundation and denitrificationthat follow were conducted in the R software program (RDevelopment Core Team 2009).

Spatio-temporal Variation in Denitrification Rate Analysisof the relative importance of inundation versus denitrifica-tion rate on N2 efflux requires a spatial and temporal rangeof denitrification rate. In a previous study, we measureddenitrification rates in three riparian zone habitat types(hardwood forest, emergent marsh, and mudflat) over an11-month period in the Newport River (Ensign et al.2008). In these experiments, sediment cores with overlyingriver water were incubated in the laboratory at in-situ tem-perature with river water flowing over the sediment. Deni-trification was calculated from the difference between N2

concentrations in the inflow versus outflow water from thecore. Denitrification rates in the forested site were statisti-cally greater than in the mudflat during autumn, but therewere no other significant differences between habitats dur-ing the same month. There were no significant differencesbetween the average monthly denitrification rates for allsites combined.

The TFW habitats examined by Ensign et al. (2008) inthe Newport River are very similar to the other rivers in-cluded in this study (Table 1). For the current analyses, we

estimated the range in denitrification rate due to spatialvariability as the mean of the monthly range in rates be-tween the three habitats, which was 12 μg m−2 min−1. Thetemporal variability in denitrification rates was estimated asthe range in mean values for each habitat over an annualperiod, which was 17 μg m−2 min−1. The overall meandenitrification rate of all measurements made in the New-port River was 29 μg m−2 min−1, and therefore our spatialrange in denitrification rate was 23 to 35 μg m−2 min−1, andthe temporal range was 21 to 38 μg m−2 min−1.

N2 Efflux The spatial and temporal ranges of denitrificationrates were multiplied by inundated area at the time-step ofwater level measurement in each river to calculate N2 effluxwithin each river segment. Previous research found that a4.6-h lag (L) occurred between inundation of wetland sedi-ments and an oxidation-reduction potential conducive fordenitrification in the surficial sediments (Ensign et al. 2008).Since our objective was to examine the influence of ripariandenitrification on nitrogen concentration in the overlyingriver water, we incorporated this 4.6-h lag between inunda-tion and the onset of N2 efflux. During each low-to-high tidecycle, N2 efflux in each river segment was calculated for thearea of sediment that had been inundated for at least 4.6 hduring the period of inundation (p) using the formula:

N2efflux ¼Z t2

t1

At;s � RþZ t4

t3

At;s � R ð1Þ

where t1 is the beginning of floodplain inundation, t20 t1+((p-L)/2), t30t2+L, t40t1+p, At,s is the area inundated during eachtime step in a given river segment, and R is the denitrificationrate. A simple hypothetical example illustrates how we deter-mined the relative importance of A and R on N2 efflux. Con-sider two locations along a tidal river, X and Y, where locationX exhibits much greater inundation than Y. Does this differencein inundation result in a substantially different prediction of N2

efflux given the expected spatial variability in denitrification?Using Eq. 1 with two values of R (representing the range in

Table 1 Aquatic and marine surface area and riparian vegetation type as represented in the National Wetlands Inventory (U.S. Fish and WildlifeService 2010)

River Lengthstudied (km)

Watershedarea (km2)

Vegetation type

Estuarine and marinewetland (%)

Freshwateremergent wetland (%)

Freshwater forestedand shrub wetland (%)

Riverine (%) Estuarine and marinedeepwater (%)

Newport 17 178 41 0 57 1 2

White Oak 23 551 14 14 68 3 1

New 12 431 0 0 98 2 0

NECF 64 4513 0 0 93 7 0

Classification of wetland vegetation habitat type follows that of Cowardin et al.’s (1979)

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denitrification rate we expect could occur) we calculate aminimum and maximum N2 efflux at each location. We findthat despite the greater inundation at station X, the minimumN2 efflux calculated there is less than the maximum N2 effluxcalculated at Y. We conclude that the inherent spatial variationin denitrification rate exerted more influence on the range in N2

efflux than the difference in inundation between locations.Alternatively, if the minimum N2 efflux at station X exceededthe maximum value at station Y, we would conclude thatdifferences in inundation exerted more influence on N2 effluxthan the spatial variation in denitrification rate. A similarcomparison can be made using differences in inundation at asingle location over time and the inherent temporal variation indenitrification. We present these comparisons of N2 effluxgraphically, both spatially along a river and temporally at onelocation, by showing the predicted minimum and maximumN2 efflux expected given a range in denitrification rate.

Sensitivity of the estimated N2 efflux to variation in lagtime was not examined, although a shorter lag time wouldresult in greater N2 efflux while a longer lag time wouldresult in less N2 efflux. Our calculations assume that deni-trification within the surficial (∼1 cm depth) reduced sedi-ment layer utilizes NO3

− from the overlying water. Whiledenitrification likely occurs in sediments below 5 cm, wedid not consider this N2 production would directly affect theNO3

- concentration in the water column.

Frequency-Magnitude Analysis The variability in river dis-charge, water level, and consequent floodplain inundationduring one month is limited relative to the variationoccurring over decadal time scales, and this may limitour ability to generalize our findings to longer time scales.This is a common problem in fluvial geomorphology(Wolman and Miller 1960) and fluvial biogeochemistry(Doyle et al. 2005), where prediction of dominant pro-cesses over long time scales is limited by observationsmade over shorter time scales. One method for predictinghow N2 efflux may be governed by long term hydrologicpatterns is to perform a frequency-magnitude analysis. Inthis case, an empirical relationship is developed betweenN2 efflux and an independent variable (water level) forwhich a long term record exists. Multiplying the frequen-cy distribution of water level by the respective N2 effluxresults in a prediction of the proportion of the overall N2

efflux that occurred across the range of water levelsobserved.

A three parameter sigmoid model was developed to relatethe average daily predicted N2 efflux on the Northeast CapeFear River with the average daily water level (H) from allthree sites on the Northeast Cape Fear River:

N2efflux ¼ x

1þ y� exp�z�Hð Þ ð2Þ

Estimation of x, y, and z was performed by least squaresregression in R. The distribution of mean daily water levelover a 10-year period at the USGS gaging station at Burgawon the Northeast Cape Fear River (#02108566) was multi-plied by the sigmoid model. The resulting peak value indi-cated the water level at which most N2 efflux occurred overthe 10-year period. The discharge regime (storm flow versusbase flow) at which this water level occurred was deter-mined by plotting the 760 records of mean daily discharge atthis station by their corresponding mean daily water level.

Results

Hydrology and Floodplain Topography Temporal changesin water level in the four rivers were related to upstreamdischarge and tidal influence. Water level measurements inthe Newport River were made during a period of high riverdischarge following a 4-cm rain event that occurred 25 Dec2009 (Fig. 2a). Tidal amplitude in the upper river dimin-ished immediately after this rain event as water level rose,and slowly resumed a semi-diurnal frequency through therest of the period as water level decreased. In the lower tidalriver, the semi-diurnal tidal range was briefly suppressed bythis event, but water level did not increase as it did up-stream. The range in water level throughout the White OakRiver was remarkably consistent throughout the period,indicating that any changes in upstream discharge that oc-curred did not influence water level in the river (Fig. 2c).Changes in tidal amplitude and water level in the White OakRiver corresponded with the spring-neap tidal sequence,with spring tides occurring 6 and 23 June, and neap tidesoccurring 15 June and 2 July. Water level in the upper NewRiver reflected a small runoff event on 17 June, but this didnot influence water level in the lower tidal river (Fig. 2e).Water level in the upper Northeast Cape Fear River approx-imated the tail of a storm hydrograph and semi-diurnal tidalamplitude increased as the flood wave receded (Fig. 2g).The lower Northeast Cape Fear River tidal amplitude andwater level reflected neap tides on 22 March and 7 April andspring tides on 31 March and 15 April.

Digital topographic models revealed similarities and dif-ferences in the hypsometric curves of the four rivers. TheNewport (Fig. 2b) and White Oak Rivers (Fig. 2d) exhibitedgreater potential for inundation in the upper portion of thetidal river, while the Northeast Cape Fear River (Fig. 2h)showed greater potential for inundation in the lower river.The New River showed greater potential inundation down-stream when water level was greater than 0.1 m (Fig. 2f).

Floodplain Inundation We present the inundation data thatreflect a 4.6-h lag (as measured in Ensign et al. 2008) to

524 Estuaries and Coasts (2013) 36:519–532

more effectively compare and discuss the relative impor-tance of inundation versus denitrification rate. Consequent-ly, the TFW area inundated for less than 4.6 h is not shownin the graphs presented, and thus the actual inundated areaduring tidal flooding is greater than that shown. The New-port River showed much greater inundation in the upperthan lower river, and the upper river was continually inun-dated to some extent throughout the month of study(Fig. 3a). The riparian zone in the lower half of the NewportRiver drained completely on all but one day of the month(Fig. 3b). A general decline in inundation occurred overtime in the upper river that reflected the decrease in waterlevel (Fig. 3c).

The White Oak River displayed greater inundation in theupper than lower portion of the tidal river, despite nearlyequal water level along the river (Fig. 4a). The daily rangeof inundation in both the upper and lower river corre-sponded with the spring-neap tidal sequence (Figs. 4b, cand 2c). Complete drainage of the riparian zone occurreddaily, and on days 9 and 26 the floodplain was inundated forless than 4.6 h (as represented by gaps in inundation inFig. 4b, c).

The New River displayed greatest inundation in themiddle portion of the tidal river (Fig. 5a), contributingto a peak inundation occurring in the middle of thestudy period in the lower river (Fig. 5b). Continual

Dec 17 Dec 22 Dec 27 Jan 01 Jan 06 Jan 11

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Fig. 2 Water level andhypsometric curves in theNewport River (a, b), WhiteOak River (c, d), New River(e, f), and Northeast Cape FearRiver (g, h). The “estuary”endpoint represents theoligoholine–mesohalinetransition zone

Estuaries and Coasts (2013) 36:519–532 525

Fig. 3 Range in inundation andN2 efflux along the NewportRiver over a 1-month period(a), and range in inundation andN2 efflux each day in the lower(b) and upper (c) tidal river. Thehorizontal axis in (a) begins atthe oligohaline–mesohalinetransition zone. Scale on theprimary vertical axis in (c) isidentical to (b)

Fig. 4 Range in inundation andN2 efflux along the White OakRiver over a one month period(a), and range in inundation andN2 efflux each day in the lower(b) and upper (c) tidal river. Thehorizontal axis in (a) begins atthe oligohaline–mesohalinetransition zone

526 Estuaries and Coasts (2013) 36:519–532

Fig. 5 Range in inundation andN2 efflux along the New Riverover a 1-month period (a), andrange in inundation and N2

efflux each day in the lower (b)and upper (c) tidal river. Thehorizontal axis in (a) begins atthe oligohaline–mesohalinetransition zone. Scale on theprimary vertical axis in (c)is identical to (b)

Fig. 6 Range in inundation andN2 efflux along the NortheastCape Fear River over a onemonth period (a), and range ininundation and N2 efflux eachday in the lower (b) and upper(c) tidal river. The horizontalaxis in (a) begins at theoligohaline–mesohalinetransition zone

Estuaries and Coasts (2013) 36:519–532 527

inundation of the upper river occurred throughout thestudy period (Fig. 5c).

Inundation in the Northeast Cape Fear River was domi-nated by the lower half of the river (Fig. 6a), despite the highwater level upstream (Fig. 2g). The lower half of the riverdrained completely almost every day (Fig. 6b), while theupper half of the river was continually inundated to someextent throughout the study period due to storm runoff(Fig. 6c).

N2 Efflux The model-predicted range in N2 efflux gener-ally reflected the temporal and spatial trends in floodplaininundation from which they were calculated. The majorityof the N2 efflux occurred in the upstream portion of allrivers (Figs. 3, 4, 5, and 6), regardless of the dischargecondition of the river (storm flow versus base flow) andhypsometric curves (Fig. 2). The lack of overlap in therange of potential N2 efflux along this spatial gradient(e.g., the black bars representing N2 efflux from the rangeof denitrification rates specified above) indicated that N2

efflux was more sensitive to variation in inundation alongthis spatial gradient (Figs. 3a, 4a, 5a, and 6a). The range inpotential N2 efflux differed over time in the lower portionof all rivers (e.g., the black bars do not all overlap),indicating that the variation in inundation had a greatereffect on N2 efflux than the temporal variability in deni-trification rate (Figs., 3b, 4b, 5b, and 6b). In contrast, therange in potential N2 efflux in the upper Newport, New,and Northeast Cape Fear Rivers did not differ over time(e.g., the black bars all overlap), indicating that N2 effluxwas more sensitive to the temporal variation in denitrifi-cation rate than inundation (Figs. 3c, 5c, and 6c). TheWhite Oak River, the only river in which we assumedthat upstream runoff did not affect tidal amplitude,showed similar temporal variability in N2 efflux up-stream and downstream. This pattern indicates that tem-poral variation in inundation exerted greater influence on N2

efflux than did the temporal variation in denitrification rate(Fig. 4b, c).

Frequency-Magnitude Analysis The water level calculatedfrom the frequency-magnitude analysis for the NortheastCape Fear River was 0.45 m, which represents the waterlevel where most N2 efflux occurs in the upper NortheastCape Fear River (Fig. 7a). To put this water level in contextwith the flow regime of the river, we compared water levelto discharge at this gaging station. The maximum dischargethat occurred at a water level of 0.45 m was 26.4 m3 s−1,indicating that high river discharge had a minimal effect onN2 efflux over an inter-annual period (Fig. 7b). Most N2

efflux in the upper tidal river occurred when tides, not highriver discharge, were the predominant influence on TFWinundation.

Discussion

Water level and inundation were measured during differenthydrologic regimes (baseflow versus stormflow) in eachriver, yet general patterns in inundation emerged from thesedifferent conditions. One pattern that emerged was thatgreater inundation occurred in the upper tidal zone of theNewport and White Oak Rivers whose topography wassimilar but whose flow regimes differed (Newport Riverexperienced storm events while the White Oak River wasat low flow). The greater range in inundation in the uppertidal zone of both rivers was apparently more a function oftheir similar topography and less a function of flow regime.A second pattern that emerged was that inundation wasmore temporally variable in the lower tidal zone than uppertidal zone of rivers which experienced storm events, regard-less of the rivers’ topographic characteristics. The first pat-tern indicates that rivers with similar riparian topographyexhibit similar spatial gradients in inundation regardless oftheir flow regime; the second pattern indicates that tidalrivers experiencing storm runoff exhibit similar spatial gra-dients in inundation regardless of their topography. Thesespatial and temporal patterns in inundation allowed us toinfer general patterns in N2 efflux in the four rivers, despitethe different periods in which they were studied.

Fig. 7 Frequency-magnitude plot of water level and N2 efflux in thetidal Northeast Cape Fear River at Burgaw (a), and the relationshipbetween water level and discharge at this site (b). In (a), the histogramshows the distribution of mean daily water level at Burgaw from 1 Jan2000 to 1 Jan 2010, the line shows the regression developed in Fig. 8and the dots show the product of the N2 efflux and the proportion of allwater level measurements represented by each histogram bar. Thewater level at which most N2 efflux occurred over a decadal period(0.65 m) is shown as a dashed line in (b)

528 Estuaries and Coasts (2013) 36:519–532

Two Modes of N2 Efflux The temporal contrasts in the rangeof potential N2 efflux can be summarized as occurring intwo dominant modes of efflux. High river discharge andwater level caused continual inundation of the upper half ofthe tidal rivers regardless of their topography (as demon-strated by the opposite hypsometric curves in the Newportand Northeast Cape Fear Rivers (Fig. 2b, h) but similarpatterns in inundation (Figs. 3c and 6c)). During theseperiods of continual inundation, the variation in day-to-dayN2 efflux was highly sensitive to factors controlling biogeo-chemical rates (as indicated by the overlap in the potentialN2 efflux). We refer to these periods as exhibiting a biogeo-chemical mode of N2 efflux since the temporal variation inbiogeochemical rates most strongly affected N2 efflux(Fig. 8). In contrast, when river discharge and water levelwere low, N2 efflux was governed more by temporal pat-terns in tidal inundation than temporal variability in denitri-fication rate. We refer to these periods as exhibiting ahydrologic mode of N2 efflux. Biogeochemical mode wasmore common in the upper portion of all rivers, whilehydrologic mode was most common in the lower portionof all rivers (Fig. 8).

Strong spatial gradients in N2 efflux were also observed,with higher N2 efflux upstream than downstream due topatterns in hydrology and topography. This pattern in N2

efflux was consistent for all rivers regardless of river length,watershed size, topography, or flow regime (storm flowversus base flow). These physical gradients had a greaterinfluence on N2 efflux than did the spatial variation indenitrification rate, as indicated by the lack of overlap inbars representing the N2 efflux along the length of the rivers(Figs. 3, 4, 5, and 6). Overall, the upper portion of all riverswas the major contributor of N2 efflux due to larger spatialextent of inundation.

The spatio-temporal patterns we observed in N2 effluxwere based on 1 month of water level measurement, andwhile there was significant variation in water level due torainfall-runoff events and tides during this period, greaterwater level variation occurs over annual and decadal timescales. What is the cumulative effect of the infrequent, highmagnitude floodplain inundation events caused by stormson long term N2 efflux from a tidal river? We addressed thisquestion using a frequency-magnitude analysis that reliedon an empirical summary of our data and a decade of waterlevel observations from a USGS stream gage on the North-east Cape Fear River. The frequency-magnitude analysispredicted that most N2 efflux over a 10-year period occurredat a relatively low water level (0.45 m). This water levelcorresponded with a discharge of 26.4 m3 s−1, slightly lessthan the mean discharge of 27.5 m3 s−1 for the 2 years ofrecord. Therefore, most N2 efflux in the Northeast CapeFear River was predicted to occur during low and moderatedischarge, not high discharge associated with storm runoffevents that led to continual inundation of the floodplain(Fig. 8). Moreover, this analysis for the Burgaw gagingstation on the Northeast Cape Fear River represents theupstream end member of the tidal continuum, and our dataindicate that storm events influence inundation less in thelower than upper portion of tidal rivers. Thus we expect thathigh river discharge would have even less influence oninundation and N2 efflux in the lower portion of the North-east Cape Fear River.

Modeling Denitrification in TFW Accounting for the tem-poral and spatial variability in denitrification rate has beenidentified as the foremost challenge in denitrification mod-eling (Groffman et al. 2009), but our analysis suggests thisissue may be of secondary importance in TFW. While theenvironmental factors regulating denitrification are of pri-mary importance during the biogeochemical mode of N2

efflux, they are equally or less important than inundationdynamics during the hydrologic mode. The frequency-magnitude analysis we performed showed that most N2

efflux occurred during the hydrologic mode, indicating thatdenitrification rate is of secondary importance (given therange of rates our analysis was based on). From a landscape-scale perspective, we suggest that equal, and sometimesgreater, emphasis be given to characterizing the inundationof TFW instead of the biogeochemical mechanisms regulat-ing denitrification rate.

Our calculation of N2 efflux was based on three assump-tions which generated a characteristic response to variationin water level. First, N2 efflux was not expected to occuruntil after a 4.6-h lag time to account for the time necessaryfor the sediment-water interface to become reduced anddenitrification of NO3

− in the overlying water to begin.Second, N2 efflux occurring after this lag period was

base flow

uppe

r tid

al r

iver

hydrologicmode

biogeochemicalmode

temporal variation

spat

ial v

aria

tion

low

er ti

dal r

iver

storm flow

Fig. 8 Generalized, qualitative model of the temporal and spatialvariation in N2 efflux in a tidal river showing the periods of hydrologicand biogeochemically driven modes of N2 efflux. The sizes of the foursections of the figure show the relative N2 efflux over an annual period

Estuaries and Coasts (2013) 36:519–532 529

calculated directly from the TFW area inundated. Third, theriparian area considered in the model was limited to 20 ha/river km, thereby limiting the maximum N2 efflux. Theseassumptions lead to the expectation that N2 efflux shouldscale as a sigmoid function of water level. This response isapparent from a plot of the daily mean water level from eachriver against the corresponding daily N2 efflux per river km(Fig. 9). When the Newport, White Oak, and NortheastCape Fear River are considered together, over 99% of thevariance in the relationship between water level (L) anddaily N2 efflux (per river km) can be accounted for withthe model.

The New River differed from the other rivers in Fig. 9for two reasons. First, water level in the lower tidal riverexhibited irregular patterns and periods of continuouswater level less than 0 m (NAVD88) that may have beendue to wind-affected water level in the wide channel(>1 km) of the New River estuary downstream. Second,most N2 efflux occurred in the upper river which wascontinually inundated due to storm runoff and high waterlevel. The combination of these two factors resulted inlower average water levels than the other rivers but com-parable N2 efflux. These patterns in the New River may beindicative of tidal rivers whose water levels are strongly

influenced by wind-driven changes in estuarine water lev-el, such as tributaries of the Albemarle and PamlicoSounds in North Carolina. Therefore, the model of N2

efflux based on a mean daily water level may only beapplicable to tidal rivers with predominantly lunar-driventides.

The strength of the relationship between daily N2

efflux and mean daily water level is striking consideringthe inter- and intra-river variations in topography andhydrology. While some degree of auto-correlation isexpected between model output (N2 efflux) and a sum-mary measure of the data input (water level), most of thevariance in N2 efflux can be explained by this relativelysimple 3 parameter model. Despite the different spatialpatterns in topography among rivers and differences intheir tidal and fluvial dynamics, water level aloneexplained a substantial portion of the inundation dynam-ics of three tidal rivers.

The Influence of TFW on Riverine Nitrogen Transport Alimitation of current models of riverine denitrification is thedifficulty of connecting in-channel processes with riparianprocesses that affect nitrogen transport (Boyer et al. 2006).Our analysis revealed that water level fluctuation alone maybe sufficient to link TFW riparian processes with riverinetransport in a manner similar to other aquatic denitrificationmodels (reviewed by Boyer et al. 2006). The nitrogen load(mass time−1) exiting a river reach (Nout) of length b couldbe estimated as the difference between the load entering thereach (Nin) and the riparian processes contributing to deni-trification:

Nout ¼ Nin � a� vf � C

1þ k � exp�r�Hð Þ � b ð3Þ

where a is the total TFW area along a river, vf is thedenitrification mass-transfer coefficient, C is the NO3

- con-centration in the river, k is the water level at half the value ofthe numerator, r is the rate of increase in N2 efflux withwater level, and H is mean daily water level. This equationreflects the combined influence of biogeochemical process(expressed as vf and C) and the degree of hydrologic inter-action between the river and TFW (expressed as a sigmoidfunction of H with the fitted constants y and z). Thus, boththe biogeochemical and hydrologic processes represented inequation three can be tailored for specific river reaches. Thismodel may provide a generalized and widely applicablemethod of accounting for riparian zone processes in riverinenitrogen transport models, and bridging the gap betweenwetland and riverine processes in current modelingapproaches (Boyer et al. 2006; Seitzinger et al. 2006).

Shifting Landscapes and Denitrification During Sea LevelRise The spatial patterns in TFW topography and hydrology

Fig. 9 Predicted N2 efflux versus the mean daily water level in eachriver over the month of study. Model predictions represented by sym-bols are for those calculated using the grand mean denitrification rate(29 μg m−2 min−1). The solid line shows a three parameter logisticregression curve fit to all data except the New River, with x, y, and z inEq. 1 equal to 2.6 kg N lunar day−1 river km−1, 0.4, and 0.1, respec-tively. The R2 value of this regression is 99.9

530 Estuaries and Coasts (2013) 36:519–532

in the North Carolina rivers we studied were similar to otherTFW in the eastern USA. Elevation was lower upstreamthan downstream in the Newport and White Oak Rivers, apattern similar to that observed in the Suwannee River, FL(Light et al. 2007) and Nanticoke River, MD (Baldwin2007). Inundation extent was greater upstream than down-stream, a pattern also seen in tributaries of the Cape FearRiver, NC (Hackney et al. 2007). These spatial gradientsalong tidal rivers are the combined result of long termtemporal changes in topography and tidal amplitude as sealevel rises. One explanation for this spatial gradient ininundation is that sediment accretion is more rapid in thelower than upper tidal zone, thereby restricting tidal inun-dation in the lower tidal zone (e.g., Darke and Megonigal2003; see Pasternack 2009 for review; Neubauer et al.2002). Additionally, tidal amplitude can be greater upstreamthan downstream in some tidal rivers, thus drivinggreater inundation in the upstream reaches (see Dalrympleand Choi 2007 for review of tidal river hydrology andgeomorphology).

As sea level rises, the balance between TFW accretionand the simultaneous landward advance of tidal influencegovern the net change in N2 efflux from tidal rivers. Ourdata indicate that most N2 efflux occurs in the upper regionof tidal rivers. Thus, if the rate of downstream accretion isproportionally faster than the advance of tidal inundationupstream, total N2 efflux from the tidal river may declineover time. Alternatively, if tidal inundation extends up-stream faster than downstream TFW accrete, total N2 effluxmay increase as sea level rises. The hypothetical landwardtidal migration rate of 33 m/decade calculated earlier couldbe detectable in multi-year study of a tidal river. Measuringthese shifts in tidal inundation and associated biogeochem-ical cycling is an exciting prospect for long term environ-mental monitoring, particularly since the rate of sea levelrise may be increasing and accelerating these landscape-scale ecosystem processes.

Riparian forested TFW were the location of most N2

efflux in this study (Table 1). These habitats have re-ceived less attention than emergent tidal marshes withrespect to nitrogen cycling and denitrification, yet appearto be crucial to the overall N2 efflux in tidal rivers.Forested riparian wetlands in non-tidal rivers sequesternitrogen through both denitrification (Brinson et al.1984) and burial (Noe and Hupp 2005, 2009), but mayalso be a source of nitrogen during short hydroperiodfloods (Noe and Hupp 2007). Broad-scale comparisonshave been made between tidal and non-tidal forestedriparian habitats (Verhoeven et al. 2001), but how thebiogeochemistry of these habitats changes upon conver-sion to a tidal hydroperiod is unknown. These tidally-induced biogeochemical transformations in tidal forestedwetlands are another topic in need of future research in

the broader effort to understand nitrogen dynamics intidal rivers and wetlands.

Acknowledgments We thank Stacy Davis, Claude Lewis, Dr. RobinMattheus, Jeff Muehlbauer, Nicholas Politte, Dr. Tony Rodriguez, Dr.Kyle Shertzer, Ashley Smyth, and Suzanne Thompson for field, labo-ratory, and modeling support. Hermann Godwin and David Wilkeprovided access to field sites on their property. This project was fundedby NSF REU # 0441504 (M. W. D.), EPA STAR Graduate Fellowship#FP-91686901-0 (S. H. E.), NSF EAR-0815627 (M.F.P.), and NOAAEcological Effects of Sea Level Rise Program grants (M.F.P.). Theresearch described in this paper has been funded in part by the USEnvironmental Protection Agency (EPA) under the Science to AchieveResults Graduate Fellowship Program. EPA has not officially endorsedthis publication and the views expressed herein may not reflect theviews of the EPA.

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