Factors influencing blue carbon accumulation across a 32-year chronosequence of created coastal marshes 1,2, 1 1 KATHERINE M. ABBOTT, TRACY ELSEY-QUIRK, AND RONALD D. DELAUNE

1Department of Oceanography and Coastal Sciences, College of the and Environment, Louisiana State University, Baton Rouge, Louisiana 70803 USA

Citation: Abbott, K. M., T. Elsey-Quirk, and R. D. DeLaune. 2019. Factors influencing blue carbon accumulation across a 32-year chronosequence of created coastal marshes. Ecosphere 10(8):e02828. 10.1002/ecs2.2828

Abstract. Saline coastal marshes are blue carbon ecosystems with relatively high soil carbon (C) stocks and high rates of soil C accumulation. Loss of saline wetlands due to relative sea-level rise, land-use change, and hydrologic alterations liberates previously stored C and reduces the capacity for future C sequestration. Widespread wetland loss has prompted marsh restoration and creation projects around the world; however, little is known about the timescale and capacity for created marshes to function as blue C sinks and the role of environmental conditions in mediating soil C accumulation in restoration sites. Using a chronosequence of five created saline marshes ranging in age from 5 to 32 yr and two adjacent natural reference marshes in southwest Louisiana, USA, short- and longer-term C accumulation rates (SCAR and LCAR, respectively) were determined using feldspar marker horizons and peat depth in cores at six loca- tions in each marsh. Created marshes ranged in elevation from À12 to 41 cm (NAVD88) and supported assorted community compositions driven by local environmental conditions. SCAR ranged from 75 À À to 430 g CÁm 2Áyr 1, which were comparable in the two youngest and two oldest marshes. Longer-term À À CAR ranged from 18 to 99 g CÁm 2Áyr 1 but did not significantly differ among marshes of different ages. Our findings indicate that LCAR in these created marshes were influenced by site-specific environmental conditions (i.e., stem density and mineral sediment) rather than marsh age. Results suggest that conditions appropriate for the establishment of vegetation with high stem densities, such as Distichlis spicata and Spar- tina patens, may facilitate higher LCAR in created marshes, which may be useful for restoration project planning and mitigation of climate change.

Key words: autochthonous production; carbon storage; Distichlis spicata; Louisiana; patens; stem density; vertical accretion; wetland creation; wetland restoration.

Received 4 January 2019; revised 13 June 2019; accepted 24 June 2019. Corresponding Editor: Noel Gurwick. Copyright: © 2019 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. 2 Present address: Department of Environmental Conservation, University of Massachusetts, Amherst, Massachusetts 01003 USA. E-mail: [email protected]

INTRODUCTION stored over short time periods as biomass and over longer periods as soil organic matter Wetlands play an important role in the global (McLeod et al. 2011). Coastal marshes, in partic- atmospheric carbon (C) cycle because of their ular, are considered important blue carbon ecosys- large soil C stocks, ability to sequester C through tems as they have environmental conditions that high rates of sediment accumulation and plant promote long-term C storage and high C accu- productivity, and low rates of microbial respira- mulation rates (CAR), with global estimates in tion. Coastal wetland macrophytes and algae CAR ranging from 4.6 up to 60.4 Tg C/yr (Love- assimilate carbon dioxide (CO2), which can be lock and Duarte 2019; Table 1). Additionally,

❖ www.esajournals.org 1 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

Table 1. Estimates of global carbon accumulation rates global coastline, wetlands along the coast may be (CAR) in saline marshes. subject to coastal squeeze (Nicholls 2004). Coastal marsh restoration provides the opportu- Global CAR (Tg C/yr) Source nity to mitigate some of the past and present loss 42.6 Æ 4 Chmura et al. (2003) of these systems and their associated functions. 60.4 Duarte et al. (2005) Coastal marsh restoration efforts are increasing 5.0 McLeod et al. (2011) in North America and globally (Craft et al. 1999, 87.0 McLeod et al. (2011) fi 10.1 Æ 1 Ouyang and Lee (2014) Zedler and Callaway 2000, Edwards and Prof tt 4.6 Bridgham et al. (2006) 2003, Cornell et al. 2007, Callaway et al. 2012). In Louisiana, marsh creation projects are increas- ingly prevalent due to large-scale conversion of saline marsh soils have abundant sulfate that previous wetland to open water caused by high hinders the production of methane (CH4; rates of sea-level rise, subsidence, erosion, and DeLaune et al. 1983, Poffenbarger et al. 2011), saltwater intrusion. The 2017 Louisiana Coastal and gas flux studies suggest that nitrous oxide Master Plan allocates nearly $18 billion to dredge emissions are negligible (Smith et al. 1983, sediment marsh creation projects over the next DeLaune et al. 1990). This allows coastal 50 yr (CPRA 2017). With such extensive marshes to function as a net sink for atmospheric resources devoted to creating marshes, it is nec- greenhouse gases, a critical ecosystem service essary to understand and quantify their ecosys- that can be harnessed for marsh protection and tem service provision, such as blue C restoration. accumulation potential. Additionally, identifying Widespread loss and degradation of marshes environmental drivers of C sequestration may due to anthropogenic and climatic changes affect provide important information for restoration their ability to function as blue C sinks, both project design and implementation. through the loss of area and through alterations Carbon accumulation rates have been shown in biogeochemical processes. Dredging and dik- to vary regionally, and even locally, within the ing, marsh filling, and river channelization have United States (Table 2). Marsh geomorphic set- severely altered hydrology, salinity, oxygen avail- ting, elevation, and hydrology, coupled with bio- ability, productivity, and vegetation community logical feedbacks, such as vegetation succession structure (Mitsch and Hernandez 2013). Global and microbial decomposition, may drive differ- warming-driven sea-level rise coupled with sub- ences in CAR (Allen 2000, Reddy and DeLaune sidence threatens to submerge many coastal 2008, Mudd et al. 2009, Saintilan et al. 2013). marshes, and with development of much of the Newly created dredge sediment marshes exhibit

Table 2. Estimates of regional carbon accumulation rates (CAR) in saline marshes measured using 137Cs dating.

Regional CAR À À (g CÁm 2Áyr 1) Location Dominant vegetation Source

39 Upper Bay of Fundy, New Brunswick, Canada – Low Spartina alterniflora Connor et al. (2001) 194 Upper Bay of Fundy, New Brunswick, Canada – High Plantago maritima 76 Outer Bay of Fundy, New Brunswick, Canada – Low S. alterniflora 188 Outer Bay of Fundy, New Brunswick, Canada – High P. maritima 147 Æ 14 Whale’s Tale, San Francisco Bay, Calif., USA – Low Spartina foliosa Callaway et al. (2012) 103 Whale’s Tale, San Francisco Bay, Calif., USA – High Spartina pacifica 142 Æ 44 China Camp, San Francisco Bay, Calif., USA – Low S. foliosa 87 Æ 5 China Camp, San Francisco Bay, Calif., USA – High S. pacifica 71–185 Barataria Basin, Louisiana, USA n/a In Chmura et al. (2003) 76 Æ 13 Reedy Creek, Barnegat Bay, New Jersey, USA S. alterniflora Unger et al. (2016) 250 Æ 12 Maurice River, Delaware Estuary, Delaware, USA S. alterniflora 159 Little Assawoman Bay, Delaware, USA S. alterniflora Elsey-Quirk et al. (2011) 119 Little Assawoman Bay, Delaware, USA Note: n/a, Not applicable.

❖ www.esajournals.org 2 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL. highly variable abiotic conditions while sub- associated particle trapping (productivity + al- strates dewater, stabilize, and become colonized lochthonous inputs > respiration) that serve to by , but there is a paucity of information increase CAR toward a dynamic equilibrium regarding temporal and spatial drivers of blue C (productivity + allochthonous inputs  respira- accumulation in created marshes. In natural tion). We also hypothesized that CAR in created marshes, longer-term CAR is facilitated by min- marshes will vary due to differences in vegetation eral sedimentation through the settling and trap- and environmental characteristics (e.g., species ping of allochthonous materials (Mudd et al. composition, elevation, hydrology, and porewater 2004) and physical or biochemical stabilization of chemistry), which are indirectly affected by the the C pool (Six et al. 2002, Unger et al. 2016). age of the marsh through plant colonization and Vegetation communities with higher stem densi- succession. ties therefore may increase sedimentation rates by reducing flow velocity and increasing sedi- METHODS ment trapping, subsequently increasing CAR (Mudd et al. 2004). Additionally, macrophyte Study area species with different above- and belowground This study was conducted in Sabine National biomass stocks and productivities may con- Wildlife Refuge (SNWR) in the Chenier Plain in tribute to variability in the belowground C pool southwest Louisiana. Starting as early as the (Elsey-Quirk et al. 2011). Due to tight coupling 1800s, the Calcasieu River was successively between marsh hydrology, vegetation type and dredged and deepened, ultimately causing salt- productivity, and deposition rates (Morris et al. water intrusion and increased flooding in adja- 2002, Stagg and Mendelssohn 2010, Kirwan and cent wetlands (DeLaune et al. 1983). When Megonigal 2013, Snedden and Steyer 2013), teas- surveyed in 1949, saw-grass (Cladium jamaicense) ing apart direct and indirect drivers of CAR can marsh dominated this area, with abundant fresh be challenging. to intermediate wetlands and relatively little Ultimately, the long-term success and resiliency open water (O’Neil 1949). Subsurface fluid pro- of created marshes is dependent on the accretion duction in the 1950s was associated with minor, of sediments and soil organic matter (OM), to yet rapid, land-surface subsidence (Bernier et al. which C accumulation significantly contributes 2011), which, in concert with disturbance from (Mudd et al. 2009). Many subsiding coastal dredging, led to substantial marsh loss and con- marshes in Louisiana are subject to low allochtho- version to open water. In 1983, the Army Corps nous sediment availability and are therefore reli- of Engineers and the National Wildlife Refuge ant upon autochthonous organic inputs to system began to create marshes in SNWR by maintain marsh elevation in the face of high rates pumping channel dredge material into open of relative sea-level rise (RSLR; Turner and Stre- water areas bounded by low levees, which were ever 2002, DeLaune and Pezeshki 2002, Lane et al. naturally colonized with vegetation. Our study 2016). Recently, researchers have shown that ver- included a 32-yr chronosequence of five created tical accretion rates in the western Chenier Plain salt marshes representing a range of vegetation are an average of two times lower than in the Mis- communities, and two adjacent natural marshes sissippi Delta, which may be due to shallow sub- characterized by high marsh vegetation and sidence, distance from a fluvial sediment source, dominated by Distichlis spicata, , and the effects of Chenier ridges and impound- and Bolboschoenus robustus (Fig. 1). Six sampling ments (Jankowski et al. 2017). Created marshes in locations were selected in each created (5, 8, 13, this region may be especially impacted by such 20, and 32 yr old) and natural marsh areas. Three factors, and more information is necessary to created marshes (5, 8, and 13 yr old) and the nat- determine optimal environmental conditions for ural references are located west of Highway 27, greater surface accretion and blue C accumulation where tidal signals are dampened by water con- and storage rates. We hypothesized that total C trol structures at Hog Island Gully. The two east- stocks in created marshes increase with marsh ern created marshes (20 and 32 yr old) have age toward that of natural marshes, facilitated by greater influences from tides, barge traffic, and feedbacks between vegetation productivity and wave action. Space and age are, therefore,

❖ www.esajournals.org 3 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

Fig. 1. Map of created and natural marshes in Sabine National Wildlife Refuge. Points represent core and vege- tation plot locations. This map was created using ArcGIS software by Esri. ArcGIS and ArcMap are the intellec- tual property of Esri and are used herein under license. Copyright Esri. All rights reserved. confounded due to the spatial separation of the subsidence, saltwater intrusion, climatic shifts) as two oldest marshes from the younger and natu- adjacent created marshes. ral marshes. While this was inherent in the lay- out of marsh locations, it provides an Sample collection opportunity to evaluate marshes created under a Sampling locations were chosen remotely range of within- and among-marsh variability in using a 100-m spaced grid overlaid on a land- environmental conditions and to evaluate the rel- cover basemap (ESRI 2015) and by randomly ative roles of marsh age and environmental con- selecting intersections which corresponded with ditions in influencing CARs. Additionally, the specific GPS points in order to capture a range of reference marshes were selected to represent nat- variability in environmental characteristics urally established marshes within the geographic within marshes. At each sample location, one setting of SNWR in order to facilitate compar- PVC soil core was hand-extracted using a 35-cm isons between created marsh structure and func- polycarbonate tube with a diameter of 6.35 cm, tions; these reference marshes may not represent and a sharpened bottom edge to minimize com- optimal tidal marsh conditions, as they are sub- paction, then transported horizontally. A total of ject to similar environmental stressors (e.g., 36 cores were collected, six in each created and

❖ www.esajournals.org 4 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL. natural marshes. Next to three randomly selected percent loss on ignition (LOI), particle size distri- soil core locations in each created marsh, a 1.0- bution, total organic C (TOC), and for the natu- cm layer of white feldspar clay was deposited ral marsh samples, radionuclide analysis. within a 0.50-m2 quadrat to establish a marker Subsamples were ground and homogenized into horizon with which to measure short-term sur- a fine powder using a Wiley soil mill. Loss on face accretion, as described by Cahoon (1994). ignition was determined as the percentage of All plots were established in September and mass lost following combustion at 550°Cfor4h November of 2015, except the 20-yr-old marsh, (Heiri et al. 2001), and particle size distribution in which plots were established in Septem- was determined using the hydrometer method ber 2016, and therefore only sampled once. In (Bouyoucos 1962). Total organic C content was the natural sites, a total of six plots were estab- determined by weighing ~12 lg of each sample lished. into open Ag-foil capsules, adding 30 lL of deio- nized water, and fuming with 12 mol/L HCl for Soil processing and analyses 6 h to remove carbonates. The samples were then PVC soil cores were sectioned in 2 cm depth dried, and the capsules were sealed for analyzing intervals in the laboratory, with large (>20 mm), with Costech 1040 CHNOS Elemental Combus- rhizomatous tubers of B. robustus removed. tion system (Harris et al. 2001). Tubers occurred infrequently in sites where B. To estimate the depth of marsh above the origi- robustus occurred (<2 per core). All depth sec- nal surface of dredge sediment when created, tions were weighed wet and dried to a constant dredge sediment was visually identified as a weight at 60°C, and bulk densities (g/cm3) were dark gray clay layer and confirmed using bulk obtained by calculating the dry mass per unit densities in each 2-cm segment from the soil sur- volume of each depth section. Subsamples of face to 30 cm depth (Fig. 2). This will be here- each 2 cm depth interval were analyzed for after referred to as the dredge horizon, and the

Fig. 2. Examples of soil cores from natural and created marshes in Sabine National Wildlife Refuge. From left to right: Natural marsh, 32-yr-old created marsh, and 13-yr-old created marsh. Blue line indicates dredge horizon.

❖ www.esajournals.org 5 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL. depth of this horizon was used to calculate described above. Mineral, organic, and C content longer-term surface accretion and C accumula- of feldspar samples were determined using pore- tion rates in created marshes. The known cre- water content, percent LOI, and dry bulk density ation dates of the marshes from the Army Corps of the feldspar sample and calculating percent were used to determine age at time of sampling. organic C using the equation described by Craft Carbon density (g C/cm3) was calculated by mul- et al. (1991). The product of percent organic, tiplying the respective percent TOC by the total mineral, or C content and bulk density was mul- dry bulk density (g/cm3) of each sample, and tiplied by the short-term surface accretion rate at CAR was calculated by multiplying the total C each feldspar plot to obtain short-term accumula- density above the dredge horizon by the respec- tion rates. tive surface accretion rate. Literature values were used for accretion, organic, and mineral accumu- Vegetation and environmental measurements lation rates in the Chenier Plain region (Table 3; In August 2016, stem densities, average shoot Smith 2012). Carbon densities for natural marsh height, and aboveground biomass were obtained literature values were calculated using the equa- within 0.01-, 0.10-, or 0.25-m2 quadrats at all core tion described by Craft et al. (1991; sample locations, depending on species density. OC = 0.40ÃOM + 0.0025ÃOM2) and multiplying The 0.01-m2 quadrats were used for S. patens and by the bulk densities provided (Smith 2012). D. spicata dominated plots, and the 0.10- and Longer-term CAR in natural marshes were deter- 0.25-m2 quadrats were used for Spartina alterni- mined by multiplying calculated C densities by flora and B. robustus dominated plots, respec- respective accretion rates. tively. All were scaled to 1.0 m2 for calculations. Short-term surface accretion at each feldspar Aboveground biomass was sorted into live and horizon plot was calculated using the change in dead standing biomass and dried to a constant height of the marsh surface above the top of the weight at 60°C. Shoot height was measured on feldspar layer along three sides of a square plug live herbaceous plants only (S. patens, D. spicata, over time. Feldspar plots were sampled every 4– S. alterniflora, and B. robustus). Elevation 6 months. Samples of soil accumulated above (NAVD88) was surveyed at each core location marker horizons were collected, dried to a con- using Leica GS14, and horizontal and vertical stant weight at 60°C, and processed for LOI as accuracies were 1 and 2 cm, respectively. Water depth relative to the marsh surface was deter- Table 3. Natural marsh accretion and C accumulation mined from 2 April to 8 July 2016 using continu- rates (CAR) in Chenier Plain saline marshes. ous water level and salinity monitors (Aqua TROLL 200, In situ) deployed in vented PVC Accretion wells ~60 cm deep. Water level data were rate CAR† À À Location (cm/yr) (gÁm 2Áyr 1) Source recorded every 15 min, and salinity data were recorded every 30 min. Average salinity (psu) Rockefeller Wildlife 0.51 70.31 Smith (2012) was determined for each deployment period, Refuge 0.33 56.28 0.51 104.95 with anomalous data removed prior to averag- 0.69 147.70 ing, as conductivity sensors are easily affected by 0.78 146.40 suspended sediments. 0.60 153.46 0.42 113.35 Data analyses 0.38 99.15 Water depth from 2 April to 8 July 2016 was 0.51 79.83 estimated for each core location (n = 6) using the Rockefeller Wildlife 0.90 n/a DeLaune Refuge et al. (1992) elevation difference (NAVD88) between the Mermentau River– 0.69 n/a marsh surface at the core location and the water Grand Lake level recorder. Mean high water (MHW), mean Lower Calcasieu 0.70 n/a Marshes low water (MLW), and percentage of time flooded were calculated for each core location Notes: n/a, Not applicable. † CAR calculated after Craft et al. (1999) from bulk den- (MATLAB 9.0.0; The MathWorks, Inc. 2016), and sity and organic matter values provided in Smith 2012. average salinities were determined at each logger

❖ www.esajournals.org 6 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL. location. Aboveground biomass and stem den- and 99.8% of the time, with the 8-yr-old marsh sity data were square -transformed prior to most frequently inundated. The natural marshes analysis to attain normality and homogeneity of were flooded an average of 85.3% of the time. variance. Differences among marshes were tested Because water level recorders were installed only using one-way ANOVA, and post hoc differences through the spring and early summer, typically a were analyzed with Tukey’s honest significant time of seasonally high water, annual flooding of difference test (R Core Team 2017). To examine the marsh may be overestimated; however, these vegetation community compositions of core loca- data were useful for examining relative differ- tions, we used non-metric multi-dimensional ences in flooding dynamics within and among scaling. The adonis function in the vegan package marshes. Mean high water ranged from À9.6 to (Oksanen et al. 2017) was used to test for 42.2 cm in the created marshes and 12.1 to between-marsh variation. Differences in short- 22.0 cm in the natural marshes. The large range and longer-term surface accretion rates and in MHW reflected the range of elevations from CARs within and between created salt marshes À12 to 41 cm, NAVD88 in the created marshes, and natural reference marshes were tested using and 5–15 cm, NAVD88 in the natural marshes one-way ANOVA (R Core Team 2017). Rates (Fig. 3). The 5-yr-old marsh contained highly were log-transformed if assumptions of normal- variable topography, with an elevation range of ity or homogeneity of variances were not met, 27 cm, while the natural site had the most uni- which were tested using Shapiro-Wilk’s method form within-marsh elevations, with a range of and normality plots of residuals, and Levene’s 10 cm. The natural marsh had the lowest salinity test, respectively. of 10.6 psu, while the highest salinity averaged To elucidate the nature of the relationship 22.1 psu in the 32-yr-old marsh adjacent to the between environmental variables and surface shipping channel (Table 4). Mean high water, accretion and accumulation rates, two statistical MLW, percent of time flooded, average water approaches were used. The predictor variables depth, and salinity were highly correlated with were first tested for significant correlations; then, elevation (P < 0.01), and therefore, we selected stepwise multiple regressions using minimum elevation as a representative parameter for Akaike’s information criterion corrected for sam- regression analyses. ple sizes were used to identify important explanatory variables on accumulation rates. For Vegetation the second approach, hierarchical partitioning Vegetation plots contained seven total species: was used to minimize the influence of multi-col- Batis maritima, B. robustus, Borrichia frutescens, linearity among environmental variables and to D. spicata, S. alterniflora (reclassified in 2014 as assess the independent effects of environmental alterniflorus; Peterson et al. 2014), factors on surface accretion and accumulation S. patens, and Symphyotrichum tenuifolium. S. rates. Hierarchical partitioning is a regression alterniflora was present in varying abundances in technique in which all possible linear models are all marshes. Young created marshes (≤8 yr old) jointly considered to identify the most likely were dominated by S. alterniflora, though it was explanatory factors, providing a measure of the also abundant at lower elevations in the 13- and effect of each factor that is largely independent 32-yr-old marshes. B. maritima, B. frutescens, and from that of others (Walsh and Mac Nally 2013). S. tenuifolium were only found in the older cre- This analysis was completed using the hier.part ated marshes east of Highway 27 and dominated package in R (Walsh and Mac Nally 2013, R Core the highest elevations. Species richness generally Team 2017). For all statistical analyses, tests of increased with marsh age and elevation. Four significance were based on a = 0.05. species (live and dead) were present in the natu- ral marsh plots, three in the 13- and 5-yr-old RESULTS plots, and two in the 8-yr-old marsh. In contrast, seven total species were found in both the 20- Environmental conditions and 32-yr-old marshes. While total live and dead From 2 April to 8 July 2016, created marshes aboveground biomass was similar among were flooded to the soil surface between 68.1% marshes (P = 0.27; Fig. 4a), stem densities varied

❖ www.esajournals.org 7 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

Fig. 3. Average elevations measured within each created and natural marsh of Sabine NWR (n = 6). Standard error bars are shown.

Table 4. Environmental characteristics of study marshes (ÆSE).

Environmental variable 5 yr 8 yr 13 yr 20 yr 32 yr Natural

MHW (cm) 10 Æ 4b 33 Æ 3s 9 Æ 2b 9 Æ 2b 10 Æ 2b 17 Æ 2b MLW (cm) 6 Æ 4b 29 Æ 3a 7 Æ 2b 3 Æ 2b 3 Æ 2b 14 Æ 2b Time flooded (%) 68 Æ 11b 100 Æ 0a 71 Æ 4b 68 Æ 10b 81 Æ 4ab 85 Æ 4ab Elevation (cm, NAVD88) 14 Æ 4bc À3 Æ 3d 9 Æ 2c 36 Æ 2a 35 Æ 2a 10 Æ 2bc Salinity (psu) 14 16 16 n/a 22 11 % Clay 48 Æ 3ab 54 Æ 5a 38 Æ 3bcd 44 Æ 2abc 33 Æ 2 cd 29 Æ 3d % Silt 30 Æ 2a 28 Æ 2ab 36 Æ 1a 29 Æ 1a 35 Æ 2a 19 Æ 3b % Sand 23 Æ 3b 18 Æ 4b 26 Æ 2b 26 Æ 2b 32 Æ 4b 52 Æ 6a Notes: Values represent an average of core locations (n = 6), except for salinity. Water depth and salinity were measured in one location between 2 April 2016 and 8 July 2016. Mean high water/mean low water (MHW/MLW) is relative to surface. Parti- cle size distribution is average to 10 cm depth. Superscripts of different letters indicate significant differences among marshes. n/a, not applicable. significantly among marshes (P = 0.01; Fig. 4b). yr-old marshes were dominated by S. alterniflora The natural and 13-yr-old marshes were domi- and associated with early successional stage, nated by D. spicata and S. patens and had an aver- lower elevations, and greater percent of time À age of 2483 and 2866 more stems m 2 than the 5- flooded (Fig. 5). Conversely, the 20-yr-old marsh yr-old marsh where S. alterniflora was dominant. had high elevations and was dominated by B. All marshes contained at least one plot with S. frutescens and B. maritima. Within the alterniflora and D. spicata with shoot heights rang- 32-yr-old marsh, there were distinct communities ing from 25 to 85 cm, though where present, B. of S. alterniflora as well as higher-marsh species. robustus was the tallest species, up to 95 cm (Table 5). Plant community composition varied Soil properties significantly among marshes (P < 0.01), with dis- Soil bulk densities were generally lower and tinct groupings of species (Fig. 5). The 5- and 8- organic carbon densities higher in the natural

❖ www.esajournals.org 8 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

Fig. 4. (a) Average aboveground biomass by species in created and natural marshes in late summer, 2016 (n = 6). Standard errors for total biomass were 501, 398, 253, 89, 366, and 371 for the 5-, 8-, 13-, 20-, 32-yr-old, and natural marshes, respectively. (b) Average stem density by species in created and natural marshes in late summer, 2016 (n = 6). Standard errors for total stem densities were 176, 528, 963, 293, 891, and 740 for the 5-, 8-, 13-, 20-, 32-yr-old, and natural marshes, respectively.

Table 5. Average shoot height for dominant plant spe- yr-old marshes had lower bulk densities than the Æ cies (cm SE). 20-yr-old marsh, reflecting higher organic matter Marsh accumulation. age Spartina Distichlis Spartina Bolboschoenus (yr) alterniflora spicata patens robustus

585Æ 7 35 n/a 95 Longer-term accretion and accumulation rates 858Æ 10 59 n/a n/a Total C stocks above the dredge horizons 13 73 Æ 37 40 Æ 7 n/a 85 Æ 30 increased linearly with created marsh age 20 25 46 Æ 3 49 n/a within the observed range of values, as hypoth- Æ Æ Æ 32 59 3546624 n/a esized (Fig. 7). Longer-term surface accretion Natural 25 37 Æ 843Æ 12 85 Æ 5 rates ranged from 0.2 to 0.8 cm/yr. Accretion rates in the 20-yr-old marsh were significantly lower than rates found in the 8-yr-old marsh marsh as compared to the created marshes, par- (P < 0.01; Fig. 8a, Table 6), likely due to its high ticularly at depth (Fig. 6a). Carbon densities elevation (Fig. 3). Marsh elevation explained from 0 to 30 cm were relatively uniform in cre- approximately 33% of the variation in longer- ated marshes (Fig. 6b) with a slight increase with term accretion rate in created marshes, with marsh age (Fig. 6b). Age since creation, however, higher accretion rates at lower elevations was not the only factor influencing bulk soil and (R2 = 0.33; P < 0.01). Organic matter accumula- organic C densities. For example, the 8- and 13- tion rates were similar among created and

❖ www.esajournals.org 9 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

Fig. 5. Vegetation community compositions in created and natural marshes as determined by non-metric mul- ti-dimensional scaling using Bray distance. Vectors indicate dominant plant species and associated environmen- tal variables. natural marshes (P = 0.94), while mineral accu- stem density and sediment deposition, LCAR was mulation rates in the 5-yr-old marsh were sig- positively associated with OM accumulation rates nificantly higher than in the natural marshes (R2 = 0.51; P < 0.01), but not mineral sedimenta- (P < 0.01; Table 6). Despite differences in tion rates (R2 < 0.01; P = 0.95). Within created longer-term accretion rates among marshes, marshes, environmental contributors to LCAR LCAR did not significantly differ among created were variable (Table 7). In the 13- and 32-yr-old marshes of different ages (Fig. 8b). Natural marshes, stem density remained the most impor- marshes, however, had LCAR which were sig- tant predictor, but in the 8-yr-old low-elevation nificantly higher than those in the 20- and 5-yr- marsh, LCAR was strongly and positively related old created marshes (P < 0.05). to marsh elevation (R2 = 0.92; P < 0.01). Within Across created marshes, stem density was the the oldest and youngest marshes, mineral sedi- most important contributor to LCAR (I = 62.4%), ment density was found to contribute to LCAR, with mineral sediment density, age, elevation, and with stem density and biomass secondary vegetation biomass having smaller contributions contributors. (I = 27.8%; I = 4.2%; I = 3.6%, I = 2.1%). These findings were supported by stepwise multiple Short-term surface accretion and accumulation regression, where stem density was also identified rates as the most important overall predictor of LCAR Short-term surface accretion rates measured in created marshes (R2 = 0.24; P < 0.01; Fig. 9). using feldspar marker horizons ranged from an Contrary to hypothesized relationships between average of 0.4–1.6 cm/yr in created marshes,

❖ www.esajournals.org 10 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

Fig. 6. (a) Average bulk densities in created and natural marsh cores. (b) Average organic carbon densities in created and natural marsh cores. Standard error bars indicated in gray. averaged 0.9 Æ 0.2 cm/yr in natural marshes, accumulation rates were over 7 times lower in and did not significantly differ among marshes the 8-yr-old marsh than those found in the 32-, (P=0.16; Fig. 8a, Table 6). Accretion rates above 20-, and 13-yr-old marshes, with the 8-yr-old feldspar horizons were not associated with any marsh being the lowest in elevation and domi- measured vegetation or environmental variable nated by low-density S. alterniflora. (P > 0.05), and no significant relationship between short- and longer-term surface accretion DISCUSSION rates was found (P > 0.05). Although short-term accretion rates were similar among marshes, Influence of marsh age on C stocks, accretion, OM, mineral sediment, and SCAR varied signifi- and accumulation rates cantly (Table 6), with both OM and mineral As hypothesized, C stocks increased with cre- contributions significantly related to SCAR ated marsh age, to a maximum of 1973 g C/m2 (P < 0.01). The 13-yr-old marsh had OM and in the 32-yr-old marsh but remained less than the short-term C accumulation rates from 3.3 to 5.7 natural marsh average of 2246 g C/m2, a trend times higher than those found in the 5-, 8-, and also found in other created wetlands (Osland 20-yr-old marshes (P < 0.05; Fig. 8b). Higher et al. 2012, Radabaugh et al. 2018). While it is SCAR was positively but weakly associated with not possible to have negative C stocks, or posi- plant stem densities (P = 0.07). Mineral tive stocks with no sediment present, the linear

❖ www.esajournals.org 11 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

Fig. 7. Relationship between carbon stock above dredge horizon and created marsh age. 95% confidence inter- val indicated in gray.

Fig. 8. (a) Short- and longer-term accretion rates in created and natural marshes in Sabine NWR. (b) Short- and longer-term carbon accumulation rates in created marshes and natural marshes. Standard error bars are shown. † Letters indicate significant differences. Short-term rates for natural marshes were obtained from this study, and longer-term rates for natural marshes were obtained from Smith (2012). prediction is based on our observed range of val- rapid accretion as newly created marshes (<5 yr) ues in created marshes. The true relationship colonize. Similarly, rapid increases in soil OM between C stocks and marsh age is likely nonlin- content as created marshes age (Zedler and Call- ear near the origin, which may be due to initial away 1999, Edwards and Proffitt 2003) suggest

❖ www.esajournals.org 12 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

Table 6. Short- and longer-term accretion and accumulation rate averages (ÆSE) in created and natural marshes.

Accretion Organic matter Mineral OC rate accumulation accumulation accumulation À À À À À À À Marsh age (cm yr 1) (g m 2 yr 1) (g m 2 yr 1) (g m 2 yr 1)

Short-term 5 0.77 Æ 0.5a 327 Æ 226b 2748 Æ 1524ab 131 Æ 91b 8 0.43 Æ 0.1a 188 Æ 18b 377 Æ 44b 75 Æ 7b 13 1.60 Æ 0.2a 1073 Æ 66a 3649 Æ 1183a 430 Æ 26a 20 0.48 Æ 0.2a 310 Æ 121b 2832 Æ 311a 124 Æ 48b 32 0.85 Æ 0.3a 534 Æ 179ab 3407 Æ 1616a 214 Æ 72ab Natural 0.89 Æ 0.2a 584 Æ 95ab 1071 Æ 216ab 234 Æ 38ab Longer-term 5 0.47 Æ 0.1ab 222 Æ 33a 2741 Æ 471a 47 Æ 12a 8 0.63 Æ 0.1a 222 Æ 32a 1698 Æ 341ab 64 Æ 12ab 13 0.54 Æ 0.0ab 253 Æ 16a 1586 Æ 206ab 73 Æ 5ab 20 0.35 Æ 0.0b 219 Æ 25a 2038 Æ 236ab 50 Æ 6a 32 0.44 Æ 0.0ab 245 Æ 19a 1933 Æ 267ab 62 Æ 7ab Natural† 0.53 Æ .05ab 239 Æ 28a 984 Æ 213b 108 Æ 12b Notes: Superscript letters indicate significant differences between marshes. Short-term natural marsh rates were obtained from this study. † Longer-term rates for Chenier Plain natural marshes were calculated from Smith (2012).

Fig. 9. Relationship between stem densities and carbon accumulation rates in created marshes, with marsh age indicated by color and dominant vegetation communities indicated by shape.

the potential for created marshes to sequester variability. While the 20-yr-old marsh had signifi- carbon at relatively high rates before stabilizing cantly lower longer-term accretion rates than at a rate that is dependent on site-specific condi- other created marshes, and the 13-yr-old marsh tions. Contrary to the first hypothesis, however, had the highest SCAR, there was no clear trend short-term surface accretion rates and LCAR in in accretion or C accumulation rates due to SNWR did not vary among created marshes of marsh age. Additionally, the range of longer- different ages, owing to high within-marsh term accretion rates in created marshes (0.2–

❖ www.esajournals.org 13 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

Table 7. Environmental variables contributing to C increasing the potential for erosion (Watson et al. accumulation rates within created marshes. 2017, Feher and Hester 2018). Thus, short-term settling and long-term subsidence in created Environmental variable 5 yr 8 yr 13 yr 20 yr 32 yr marshes may have dramatic impacts on produc- Elevation 12.6 3.9 10.7 19.1 5.3 tivity and ultimately, soil accretion. In SNWR, Total biomass 10.0 57.7 3.1 21.7 23.1 the low short-term accretion rates estimated in Total stem density 24.0 25.3 76.9 20.2 68.2 the 20- and 8-yr-old marshes suggest a similar Mineral sediment density 53.4 13.1 9.3 39.1 3.5 trend as detailed by Stagg and Mendelssohn Notes: Value (%I) indicates percent independent contribu- (2010), in which above- and belowground pro- tion based on hierarchical partitioning. Dominant variables fl are in bold. duction of S. alterni ora at intermediate eleva- tions was greater than productivity measured at very low or high elevations within marshes 0.8 cm/yr) were similar to those reported for restored through sediment addition. nearby natural marshes (0.3–0.8 cm/yr; Smith 2012), suggesting that all marshes in this area are Role of vegetation and environmental factors in responding similarly to environmental, climatic, accretion and CAR dynamics and geomorphic conditions, regardless of age. In Site-specific environmental conditions influ- a study of created marshes planted with S. enced LCAR and surface accretion rates across alterniflora, Davis et al. (2015) found CAR to created marshes to a greater extent than marsh decline with marsh age; however, high estimates age, which supported the second hypothesis, to in younger marshes may reflect the planting of an extent. Successional trajectories of created this carbon-rich species. In SNWR marshes, both marshes varied at the site level and thus young marshes and low-elevation areas in older obscured effects of marsh age on accretion and marshes are dominated with S. alterniflora; thus, CAR. Longer-term surface accretion rates in cre- a similar declining trend in CAR may be compli- ated marshes were inversely related to elevation, cated by variable initial elevations and the subse- likely associated with greater inundation, and quent succession of diverse plant communities. greater sedimentation deposition, as well as colo- nization by more productive, flood tolerant plant Short- vs. longer-term accretion rates species, such as S. alterniflora (Morris et al. 2002, We anticipated longer-term surface accretion Kirwan and Megonigal 2013). Within-marsh vari- rates to be lower than short-term accretion rates ability in environmental conditions is likely dri- due to compaction and decomposition over time ven by microtopography, as younger marshes (Neubauer et al. 2002). We found this trend to had the greatest ranges in elevations and may hold true in all marshes except the 8-yr-old exhibit more abiotic variability than older marsh, which contained the highest longer-term marshes because of the timescale of settlement accretion rates, but the lowest short-term rates. and consolidation of dredge sediment. It is these Because soil cores represent an integration of abiotic conditions that subsequently drive plant marsh conditions over time, longer-term accre- community compositions and accretion pro- tion rates may not represent current accretion cesses, as has been found in other restored rates, especially in created marshes. Dredge sedi- marshes (Shafer and Streever 2000, Stagg and ment marshes can decrease in elevation from a Mendelssohn 2011, Kongchum et al. 2017). On few centimeters to meters after creation, as the average, we found the lowest short-term accre- sediment consolidates and dewaters (Turner and tion rates in both the lowest and highest eleva- Streever 2002). The 8-yr-old marsh may have tion marshes. These sites may represent the been created at an initial elevation that sup- lower and upper boundaries in the parabolic ported rapid vegetation colonization and growth model of inundation developed by Morris et al. of S. alterniflora, but later settled to a sub-optimal (2002), in which aboveground production is elevation for high rates of marsh accretion; this reduced at both high and low water depths, cou- marsh now experiences prolonged inundation pled with changes in species composition. In such that productivity is reduced, reducing vege- SNWR, the overall low accretion rates compared tation contributions to surface elevation and to RSLR suggest that this parabola will shift over

❖ www.esajournals.org 14 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL. time, with increasing accretion in high-elevation therefore remain in the substrate for longer peri- areas as subsidence and compaction occur, and ods than S. alterniflora litter, which is readily mid- to low-elevation marshes ultimately sub- decomposed (Lonard et al. 2010, 2013). In con- merging. trast, the 8-yr-old marsh, with a low SCAR of À À In a natural marsh, elevations tend to 75.3 gÁm 2Áyr 1, may be sub-optimal in the eleva- increase in response to sea-level rise as the tion-growth range for S. alterniflora. That is, it marsh ages and vertically accrete, reaching a floods at a depth and frequency that suppresses dynamic equilibrium controlled by tidal max- vegetative growth and decreases overall vertical ima (Pethick 1981). However, variable initial accretion and organic C accumulation rates, conditions of each created marsh may obscure which were 3.7 and 5.7 times lower than rates typical patterns of natural marsh evolution, found in the 13-yr-old marsh. Field observations and it is coincidental that the oldest sites in support this suggestion, as we noted large this area were also highest in elevation. Due to patches of vegetative die-off in the 8-yr-old marsh their high elevations and locations near the over the duration of this study. Within the 8-yr- shipping channel, the 20- and 32-yr-old marsh old marsh dominated by low-density S. alterni- edges were subject to higher salinities as well flora, vegetative biomass was found to have the as storm and wave impacts that may promote greatest percent contribution to LCAR. Marsh the growth of more resilient, but lower stem areas with bare sediment and very low stem den- density, shrub and forb species such as B. mar- sity may be subject to higher turbulence and sedi- itima, B. frutescens, and S. tenuifolium (Lonard ment erosion, further reducing measured short- et al. 2011). Increased wave action due to term surface accretion and CAR (Reed and barge wakes may cause increased erosion rates Cahoon 1992, Greiner et al. 2013). Although pre- near the marsh edges, but random selection of vious studies have demonstrated the ability of core locations should capture a representative dense vegetation to trap sediment and slow water accretion rate that includes erosion. We attri- velocity to increase particle settling (Mudd et al. bute the relatively low LCAR to low overall 2004, Fagherazzi et al. 2012), we found that over- accretion rates and the paradoxical interactions all, mineral sediment accumulation rate was not of elevation and high-density plant species. correlated with LCAR in these created marshes. Lower accretion rates were found at higher ele- Mineral sediment contributed to CAR to a greater vations, and higher LCAR were found within extent than other variables within the 5- and 20- in older, higher elevation marshes with high yr-old marshes, suggesting a greater dependency stem densities. Therefore, interactions between on mineral inputs. In the youngest marsh, this the differential drivers of surface accretion and may be due to reworking of mineral-dense accumulation rates counteract major differences dredge material in sparsely vegetated areas. In in LCAR among marshes. Thus, we suggest the 20-yr-old marsh, which contained woody, that marsh elevation, coupled with vegetation high-elevation species, allochthonous inputs from successional processes and tidal flushing, is infrequent flooding and storm surges may be biologically important factors that indirectly contributing more to accretion and CAR than influence rates. productivity. Within the 13- and 32-yr-old In this system, stem density was determined to marshes, however, stem density remained the be the most important predictor of both short- most important predictor of LCAR, suggesting and longer-term CAR across created marshes, these marshes remain dependent upon auto- while the within-marsh predictors varied. Both chthonous, rather than allochthonous contribu- the highest short- and longer-term CAR were tions to sustain soil C accumulation rates found in the 13-yr-old marsh, which was compa- (Jankowski et al. 2017). This variability in factors rable to surrounding natural marshes. The 13-yr- that contribute to C accumulation points to com- old marsh had abundant D. spicata, which, along plex and site-specific feedbacks between marsh with S. patens, exhibit high stem densities, and elevation, mineral sediment availability, and veg- may be more resistant to decomposition due to etation type and structure, even within a limited high lignin content (Lonard et al. 2010, 2013). geomorphic setting such as the Chenier Plain Aboveground litter from these species may (Fig. 10).

❖ www.esajournals.org 15 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

Created marsh persistence Additionally, SNWR marshes have relatively low LCAR in SNWR created marshes aver- short- and longer-term CAR as compared with À À aged 59.0 g CÁm 2Áyr 1, less than the 107.9 g other regions in Louisiana but were maximized in À À CÁm 2Áyr 1 natural marsh average calculated the 13-yr-old marsh. This site may serve as a use- from Smith (2012). In Cameron Parish, CARs ful model for future dredge sediment creation À À ranged from 41 to 115 g CÁm 2Áyr 1 (Chmura projects that seek to both sequester blue C and et al. 2003); in contrast, rates in the Mississippi maintain elevation in the face of RSLR, though we Delta were found between 131 and note the potential need for future sediment À À 265 g CÁm 2Áyr 1 (Markewich et al. 2007). In this amendments to maintain marsh stability over a setting, vegetation contributes to overall accre- long period (Stagg and Mendelssohn 2011). tion more than mineral sedimentation, and despite relatively high short-term surface accre- Implications for marsh creation and restoration tion rates, created marshes may not persist over Our results point to complex and dynamic time without additional mineral sediment feedbacks between created marsh age, elevation, sources (Morris et al. 2016). Rogers et al. (2019) and vegetation stem density, with stem density recently suggested that an increase in vertical ultimately the most important factor influencing accommodation space driven by RSLR may lead CAR in SNWR. Our results suggest that invest- to increasing sedimentation and C sequestration; ing greater resources in refining project design however, the limited tidal exchange and reduced and implementation may prove invaluable; if sediment availability in this region may contradict high stem density species are targeted based on this trend. Mean observed RSLR in this area is the geomorphic setting, vertical accretion and 9.5 mm/yr (Æ6.33 mm/yr, n = 89; Jankowski et al. CAR may be optimized, ultimately increasing 2017), which is 1.5 times higher than even the the beneficial lifespan of the marsh. In assessing highest longer-term accretion rate we measured in post-creation progress, relying solely upon the this study, suggesting both created and natural age of a created marsh to infer rates of blue C marshes are at risk of drowning in SNWR. Our accumulation may prove inappropriate (Zedler results support and augment these findings by and Callaway 1999). This study, among others, demonstrating a substantial accretion deficit in points to the necessity for long-term marsh moni- created marshes in the western Chenier Plain, irre- toring and modeling under potential sea-level, spective of environmental conditions or age. sediment availability, and climate scenarios

Fig. 10. Conceptual diagram illustrating site-specific feedback processes influencing accretion and carbon accumulation in created dredge sediment wetlands.

❖ www.esajournals.org 16 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

(Kulawardhana et al. 2015, Propato et al. 2018). Bernier, J. C., R. A. Morton and K.W. Kelso. 2011. Several questions remain to be resolved; in par- Trends and Causes of Historical Wetland Loss, ticular, whether the influence of stem density on Sabine National Wildlife Refuge, Southwest Louisi- LCAR extends to created marshes in different ana. U.S. Geological Survey Open File Report – geomorphic settings or with greater sediment 2011 1169. U.S. Geological Survey, Reston, Virgi- nia, USA. availabilities. Longer-term studies are required to Bouyoucos, G. J. 1962. Hydrometer method improved evaluate created marsh development over time for making particle size analysis of soils. Agron- in order to quantify feedbacks of elevation and omy Journal 54:464–465. vegetation species on CAR. Bridgham, S. D., J. P. Megonigal, J. K. Keller, N. B. Bliss, and C. Trettin. 2006. The carbon balance of CONCLUSIONS North American wetlands. Wetlands 26:889–916. Cahoon, D. R. 1994. Recent accretion in two managed Across the 32-yr chronosequence of created marsh impoundments in coastal Louisiana. Ecolog- marshes, CARs were most influenced by plant ical Applications 4:166–176. stem densities, maximized in S. patens and D. spi- Callaway, J. C., E. L. Borgnis, R. E. Turner, and C. S. cata communities. This has implications for the Milan. 2012. Carbon sequestration and sediment planning and design of dredge sediment accretion in San Francisco Bay tidal wetlands. Estu- aries and 35:1163–1181. marshes, and points to the importance of creat- Chmura, G. L., S. C. Anisfeld, D. R. Cahoon, and J. C. ing marshes at optimal elevations for the estab- Lynch. 2003. Global carbon sequestration in tidal, lishment and growth of high-density species saline wetland soils. Global Biogeochemical Cycles such as D. spicata and S. patens, particularly in 17:1111. settings where allochthonous sediment inputs Coastal Protection and Restoration Authority of may be low or variable. Designing marshes to Louisiana. 2017. Louisiana’s comprehensive master promote high-density species may have multiple plan for a sustainable coast. Coastal Protection and benefits, as the higher elevations that support Restoration Authority of Louisiana, Baton Rouge, these species may also increase project longevity Louisiana, USA. in the face of RSLR and serve to increase C accu- Connor, R. F., G. L. Chmura, and C. B. Beecher. 2001. mulation. Further research on the ecological Carbon accumulation in Bay of Fundy salt marshes: implications for restoration of reclaimed marshes. development of created marshes will provide Global Biogeochemical Cycles 15:943–954. critical insights on marsh restoration in the con- Cornell, J. A., C. B. Craft, and J. P. Megonigal. 2007. text of a high projected RSLR that will likely be Ecosystem gas exchange across a created salt experienced globally in the future. marsh chronosequence. Wetlands 27:240–250. Craft, C. B., J. Reader, J. N. Sacco, and S. W. Broome. ACKNOWLEDGMENTS 1999. Twenty-five years of ecosystem development of constructed Spartina alterniflora (Loisel) marshes. – This project was supported by NOAA-Louisiana Ecological Applications 9:1405 1419. Sea Grant no.: NA140AR4170099. This work was pos- Craft, C. B., E. D. Seneca, and S. W. Broome. 1991. Loss sible thanks to collaboration with Sabine National on ignition, and Kjeldahl digestion for estimating Wildlife Refuge staff. We thank two anonymous organic carbon and total nitrogen in estuarine reviewers whose comments helped improve this marsh soils: calibration with dry combustion. Estu- – manuscript and acknowledge A. Muench, C. LeSieur, aries 14:175 179. ’ S. Matzke, A. McClellan, W. Quirk, T. Blanchard, and Davis, J. L., C. A. Currin, C. O Brien, C. Raffenburg, K. Maiti, who assisted in data collection and provided and A. Davis. 2015. Living shorelines: coastal resili- fi laboratory support for this project. ence with a blue carbon bene t. PLOS ONE 10: e0142595. DeLaune, R. D., R. H. Baumann, and J. G. Gosselink. LITERATURE CITED 1983. Relationships among vertical accretion, coastal submergence, and erosion in a Louisiana Allen, J. R. L. 2000. Morphodynamics of Holocene salt Gulf coast marsh. Journal of Sediment Petrology marshes: a review sketch from the Atlantic and 53:0147–0157. Southern North Sea coasts of Europe. Quaternary DeLaune, R. D., W. H. Patrick Jr, and C. J. Smith. 1992. Science Reviews 19:1155–1231. Marsh aggradation and sediment distribution

❖ www.esajournals.org 17 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

along rapidly submerging Louisiana Gulf Coast. Kirwan, M. L., and J. P. Megonigal. 2013. Tidal wetland Environmental and Geological Water Science stability in the face of human impacts and sea-level 20:57–64. rise. Nature 504:53–60. DeLaune, R. D., and S. R. Pezeshki. 2002. The role of Kongchum, M., M. D. Materne, G. B. Williamson, and soil organic carbon in maintaining surface eleva- L. Bissett. 2017. Effect of elevation on soil proper- tion in rapidly subsiding U.S. Gulf of Mexico ties in reconstructed back barrier island coastal coastal marshes. Water, Air, and Soil Pollution marsh using dredge materials. Wetlands 37:301– 3:167–179. 311. DeLaune, R. D., S. R. Pezeshki, J. H. Pardue, J. H. Whit- Kulawardhana, R. W., R. A. Feagin, S. C. Popescu, T. comb, and W. H. Patrick Jr. 1990. Some influences W. Boutton, K. M. Yeager, and T. S. Bianchi. 2015. of sediment addition to a deteriorating The role of elevation, relative sea-level history and in the Mississippi River deltaic plain: a pilot study. vegetation transition in determining carbon distri- Journal of Coastal Research 6:181–188. bution in Spartina alterniflora dominated salt Duarte, C. M., J. J. Middelburg, and N. Caraco. 2005. marshes. Estuarine, Coastal and Shelf Science Major role of marine vegetation on the oceanic car- 154:48–57. bon cycle. Biogeosciences 2:1–8. Lane, R. R., S. K. Mack, J. W. Day, R. D. DeLaune, M. J. Edwards, K. R., and C. E. Proffitt. 2003. Comparison of Madison, and P. R. Precht. 2016. Fate of soil organic wetland structural characteristics between created carbon during wetland loss. Wetlands 36:1167– and natural salt marshes in southwest Louisiana, 1181. USA. Wetlands 23:344–356. Lonard, R. I., F. W. Judd, and R. Stalter. 2010. The bio- Elsey-Quirk, T., D. M. Seliskar, C. K. Sommerfield, and logical flora of coastal dunes and wetlands: Spar- J. L. Gallagher. 2011. Salt marsh carbon pool distri- tina patens (W. Aiton) G. H. Muhlenberg. Journal of bution in a mid-Atlantic lagoon, USA: sea level rise Coastal Research 26:935–946. implications. Wetlands 31:87–99. Lonard, R. I., F. W. Judd, and R. Stalter. 2011. The bio- ESRI (Environmental Systems Resource Institute). 2015. logical flora of coastal dunes and wetlands: Batis ArcMap 10.3.1. ESRI, Redlands, California, USA. maritima (C. Linnaeus). Journal of Coastal Research Fagherazzi, S., et al. 2012. Numerical models of salt 27:441–449. marsh evolution: ecological, geomorphic, and Lonard, R. I., F. W. Judd, and R. Stalter. 2013. The bio- climatic factors. Reviews of Geophysics 50: logical flora of coastal dunes and wetlands: Distich- RG1002. lis spicata (C. Linnaeus) E Greene. Journal of Feher, L. C., and M. W. Hester. 2018. The interactive Coastal Research 29:107–117. effects of created salt marsh substrate type, hydrol- Lovelock, C. E., and C. M. Duarte. 2019. Dimensions of ogy, and nutrient regime on Spartina alterniflora blue carbon and emerging perspectives. Biology and Avicennia germinans productivity and soil Letters 15:20180781. development. Wetlands Ecology and Management Markewich, H. W., G. R. Buell, L. D. Britsch, J. P. 26:715–728. McGeehin, J. A. Robbins, J. H. Wrenn, D. L. Dillon, Greiner, J. T., K. J. McGlathery, J. Gunnell, and B. A. T. L. Fries, and N. R. Morehead. 2007. Organic-car- McKee. 2013. Seagrass restoration enhances “blue bon sequestration in soil/sediment of the Missis- carbon” sequestration in coastal waters. PLOS sippi River deltaic plain- Data; landscape ONE 8:e72469. distribution, storage, and inventory; accumula- Harris, D., W. R. Horwath, and C. van Kessel. 2001. tion rates; and recent loss, including a post- Acid fumigation of soils to remove carbonates Katrina preliminary analysis. In H. W. Marke- prior to total organic carbon or carbon-13 isotopic wich, editor. Soil carbon storage and inventory analysis. Soil Science Society of America Journal for the Continental United States. Professional 65:1852–1856. Paper 1686-B. U.S. Geological Survey, Reston, Heiri, O., A. F. Lotter, and G. Lemcke. 2001. Loss on Virginia, USA. ignition as a method for estimating organic content McLeod, E., G. L. Chmura, S. Bouillon, R. Salm, M. in sediments: reproducibility and comparability of Bjork,€ C. M. Duarte, C. E. Lovelock, W. H. Sch- results. Journal of Paleolimnology 25:101–110. lesinger, and B. R. Sillman. 2011. A blueprint for Jankowski, K. L., T. E. Tornqvist,€ and A. M. Fernandes. blue carbon: toward an improved understanding 2017. Vulnerability of Louisiana’s coastal wetlands of the role of vegetated coastal in seques- to present-day rates of relative sea-level rise. Nat- tering CO2. Frontiers in Ecology and the Environ- ure Communications 8:14792. ment 9:552–560.

❖ www.esajournals.org 18 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

Mitsch, W. J., and M. E. Hernandez. 2013. Landscape Pethick, J. S. 1981. Long-term accretion rates on tidal and climate change threats to wetlands of North salt marshes. Journal of Sedimentary Petrology and Central America. Aquatic Sciences 75:133–149. 51:571–577. Morris, J. T., P. V. Sundareshwar, C. T. Nietch, B. Kjer- Poffenbarger, H. J., B. A. Needleman, and J. P. Megoni- fve, and D. R. Cahoon. 2002. Responses of coastal gal. 2011. Salinity influence on methane emissions wetlands to rising sea level. Ecology 83:2869–2877. from tidal marshes. Wetlands 31:831–842. Morris, J. T., et al. 2016. Contributions of organic and Propato, M., J. S. Clough, and A. Polaczyk. 2018. Eval- inorganic matter to sediment volume and accretion uating the costs and benefits of marsh-management in tidal wetlands at steady state. Earth’s Future strategies while accounting for uncertain sea-level rise 4:110–121. and ecosystem response. PLOS ONE 13:e0200368. Mudd, S. M., S. Fagherazzi, J. T. Morris, and D. J. Fur- R Core Team. 2017. R: a language and environment for bish. 2004. Flow, sedimentation, and biomass pro- statistical computing. R Foundation for Statistical duction on a vegetated salt marsh in South Computing, Vienna, Austria. Carolina: toward a predictive model of marsh mor- Radabaugh, K. R., R. P. Moyer, A. R. Chappel, C. E. phologic and ecologic evolution. Pages 165–188 in Powell, I. Bociu, B. C. Clark, and J. M. Smoak. 2018. S. Fagherazzi, M. Marani, and L. K. Blum, editors. Coastal blue carbon assessment of mangroves, salt The Ecogeomorphology of Tidal Marshes, Coastal marshes, and salt barrens in Tampa Bay, Florida, and Estuarine Studies. Volume 59. AGU, Washing- USA. Estuaries and Coasts 41:1496–1510. ton, D.C., USA. Reddy, K. R., and R. D. DeLaune. 2008. Biogeochem- Mudd, S. M., S. M. Howell, and J. T. Morris. 2009. istry of wetlands: science and applications. Taylor Impact of dynamic feedbacks between sedimenta- and Francis Group, CRC Press, Boca Raton, Flor- tion, sea–level rise, and biomass production on ida, USA. near–surface marsh stratigraphy and carbon accu- Reed, D. J., and D. R. Cahoon. 1992. The relationship mulation. Estuarine, Coastal and Shelf Science between marsh surface topography, hydroperiod, 82:377–389. and growth of Spartina alterniflora in a deteriorating Neubauer, S. C., I. C. Anderson, J. A. Constantine, and Louisiana salt marsh. Journal of Coastal Research S. A. Kuehl. 2002. Sediment deposition and accre- 8:77–87. tion in a mid-Atlantic (U.S.A.) tidal freshwater Rogers, K., et al. 2019. Wetland carbon storage con- marsh. Estuarine, Coastal, and Shelf Science trolled by millennial-scale variation in relative sea- 54:713–727. level rise. Nature 567:91–95. Nicholls, R. J. 2004. Coastal flooding and wetland loss Saintilan, N., K. Rogers, D. Mazumder, and C. Woo- in the 21st century: changes under the SRES cli- droffe. 2013. Allochthonous and autochthonous mate and socio–economic scenarios. Global Envi- contributions to carbon accumulation and carbon ronmental Change 14:69–86. store in southeastern Australia coastal wetlands. Oksanen, J., et al. 2017. vegan: Community Ecology Estuarine, Coastal and Shelf Science 128:84–92. Package. R package version 2.4-3. 2017. https:// Shafer, D. J., and W. J. Streever. 2000. A comparison of cran.r-project.org 28 natural and dredged material salt marshes in O’Neil, T. 1949. The muskrat in the Louisiana coastal Texaswithanemphasisongeomorphologicalvari- marshes; a study of the ecological, geological, bio- ables. Wetlands Ecology and Management 8:353–366. logical, tidal and climatic factors governing the Six, J., R. T. Conant, E. A. Paul, and K. Paustian. 2002. production and management of the muskrat indus- Stabilization mechanisms of soil organic matter: try in Louisiana. Federal Aid Section, Fish and implications for C-saturation of soils. Plant and Soil Game Division, Louisiana Department of Wildlife 241:155–176. and Fisheries, New Orleans, Louisiana, USA. Smith, K. E. L. 2012. Paleoecological study of coastal Osland, M. J., et al. 2012. Ecosystem development after marsh in the Chenier Plain, Louisiana: investigat- mangrove wetland creation: plant-soil change ing the diatom composition of hurricane-deposited across a 20-year chronosequence. Ecosystems 15: sediments and a diatom-based quantitative recon- 848–866. struction of sea-level characteristics. Dissertation. Ouyang, X., and S. Y. Lee. 2014. Updated estimates of University of Florida, Gainesville, Florida, USA. carbon accumulation rates in coastal marsh sedi- Smith, C. J., R. D. DeLaune, and W. H. Patrick. 1983. ments. Biogeosciences 11:5057–5071. Carbon dioxide emission and carbon accumulation Peterson, P. M., K. Romaschenko, Y. H. Arrieta, and J. in coastal wetlands. Estuarine, Coastal and Shelf M. Saarela. 2014. A molecular phylogeny and new Science 17:21–29. subgeneric classification of Sporobolus (: Snedden, G. A., and G. D. Steyer. 2013. Predictive Chloridoideae: Sporobolinae). Taxon 63:1212–1243. occurrence models for coastal wetland plant

❖ www.esajournals.org 19 August 2019 ❖ Volume 10(8) ❖ Article e02828 ABBOTT ET AL.

communities: delineating hydrologic response sur- accumulating in Spartina alterniflora-dominated salt faces with multinomial logistic regression. Estuar- marshes of the Mid-Atlantic U.S. Estuarine. Coastal ine, Coastal and Shelf Science 118:11–23. and Shelf Science 182:179–189. Stagg, C. L., and I. A. Mendelssohn. 2010. Restoring Walsh, C. and R. Mac Nally. 2013. hier.part: hierarchi- ecological function to a submerged salt marsh. cal Partitioning. R package version 1.0-4. https:// Restoration Ecology 18:10–17. CRAN.R-project.org/package=hier.part Stagg, C. L., and I. A. Mendelssohn. 2011. Controls on Watson, E. B., C. Wigand, E. W. Davey, H. M. resilience and stability in a sediment-subsidized salt Andrews, J. Bishop, and K. B. Raposa. 2017. Wet- marsh. Ecological Applications 21:1731–1744. land loss patterns and inundation-productivity The MathWorks, Inc. 2016. MATLAB User’s Guide relationships prognosticate widespread salt marsh (R2016a). The MathWorks, Natick, Massachusetts, loss for southern New England. Estuaries and USA. Coasts 40:662–681. Turner, R. E., and B. Streever. 2002. Approaches to Zedler, J. B., and J. C. Callaway. 1999. Tracking wet- coastal wetland restoration: Northern Gulf of Mex- land restoration: Do mitigation sites follow desired ico. SPB Academic Publishing, Den Hague, The trajectories? Restoration Ecology 7:69–73. Netherlands. Zedler, J. B., and J. C. Callaway. 2000. Evaluating the Unger, V., T. Elsey-Quirk, C. Sommerfield, and D. progress of engineered tidal wetlands. Ecological Velinsky. 2016. Stability of organic carbon Engineering 15:211–225.

❖ www.esajournals.org 20 August 2019 ❖ Volume 10(8) ❖ Article e02828