Regular issues
Special Issues

Southeastern Naturalist
    SENA Home
    Range and Scope
    Board of Editors
    Editorial Workflow
    Publication Charges

Other EH Journals
    Northeastern Naturalist
    Caribbean Naturalist
    Urban Naturalist
    Eastern Paleontologist
    Eastern Biologist
    Journal of the North Atlantic

EH Natural History Home

Environmental Gradients and Overlapping Ranges of Dominant Coastal Wetland Plants in Weeks Bay, AL
Adam J. Constantin, Whitney P. Broussard III, and Julia A. Cherry

Southeastern Naturalist, Volume 18, Issue 2 (2019): 224–239

Full-text pdf (Accessible only to subscribers.To subscribe click here.)


Site by Bennett Web & Design Co.
Southeastern Naturalist A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 224 2019 SOUTHEASTERN NATURALIST 18(2):224–239 Environmental Gradients and Overlapping Ranges of Dominant Coastal Wetland Plants in Weeks Bay, AL Adam J. Constantin1, Whitney P. Broussard III2, and Julia A. Cherry1,3,* Abstract - Predicted changes in sea level and other environmental conditions may threaten the marginal occupancy of coastal wetlands. In a field survey conducted in Weeks Bay, AL, we investigated intertidal wetland plant zonation along environmental gradients. The results of this survey may have implications for coastal wetland resilience both locally and across the Northern Gulf of Mexico as changing environmental conditions exceed plant community tolerances, resulting in “coastal squeeze” phenomena. Within the coastal marsh transition of Weeks Bay, there was heterogeneous micro-topography with a large overlap of plant distributions along the elevation gradient (-0.474–0.661m NAVD 88). In addition to elevation, salinity was a primary indicator of plant zonation for the dominant species in the area: Spartina cynosuroides (Big Cordgrass), Juncus roemerianus (Black Needlerush), and Cladium mariscus ssp. jamaicense (Swamp Sawgrass). Based on our findings, the persistence of these plants in the intertidal zone of Weeks Bay may be especially susceptible to changes in flooding and salinity associated with sea-level rise and the presence of barriers to upslope migration. Introduction Coastal wetlands provide many valuable ecosystem services, including crucial habitat, water filtration, carbon sequestration, and shoreline stability (Gedan et al. 2010, Kirwan et al. 2010, McLeod et al. 2011, Mitsch and Gosselink 2015), yet they are among the most endangered ecosystems in the world (Dahl 1990, 2011), making their preservation and restoration a high priority for environmental managers. Because of their location at or near sea level, the accelerating rate of global sealevel rise (SLR) is among the greatest threats to these intertidal ecosystems (Wong et al. 2014). By altering inundation patterns and facilitating ecosystem-wide shifts in salinity, eustatic SLR threatens to radically alter coastal wetlands worldwide. Plant communities in coastal wetlands have many characteristics that may make them resilient to SLR. Flooding stress can alter species composition to favor more flood-tolerant species, and whole plant communities can migrate landward into new habitat. In fact, some estimates predict an increase in areas inhabitable by coastal wetlands as sea levels continue to rise and inundate new areas (Kirwan and Megonigal 2013). However, in the presence of a fixed upland barrier (e.g., a hard bulkhead shoreline, upland ridge, forested barrier), landward migration can be restricted, resulting in a phenomenon known as “coastal squeeze” (Borchert et al. 2017, English 1Department of Biological Sciences, The University of Alabama, Tuscaloosa, AL 35487. 2Institute for Coastal and Water Research, University of Louisiana at Lafayette, Lafayette, LA 70504. 3New College, The University of Alabama, Tuscaloosa, AL 35487. *Corresponding author - Manuscript Editor: Alvin Diamond Southeastern Naturalist 225 A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 Nature 1992, Pethick 1993). With SLR and pervasive anthropogenic development on or near the coast (Vitousek et al. 1997), this coastal squeeze phenomenon is being observed worldwide, and as such, is a topic of particular interest to environmental managers in highly developed/developing coastal regions (Enwright et al. 2016, Kirwan and Megonigal 2013). Coastal wetlands often exhibit conspicuous plant zonation patterns (Chapman 1974, Nixon 1982) that are driven by changes in hydro-edaphic conditions along an elevation gradient from the sea to upland environments (Earle and Kershaw 1989, Nixon, 1982, Zedler 1977). Ultimately, species’ distributions are determined by their physiological tolerances to changes in flooding and salinity occurring within the coastal transition (Brewer and Grace 1990, Chapman 1974, Cooper 1982, Earle and Kershaw 1989, La Peyre et al. 2001, Odum 1988). Plant zonation along environmental gradients also arises in response to trade-offs between competitive ability and stress tolerance; i.e., as stress declines, interspecific competition increases and has a greater influence on community structure (Grime 1977, 1979). Therefore, an increase in environmental stress along a coastal transition may favor more stress-tolerant species, potentially limiting species richness or plant diversity and reducing ecosystem resilience (Diaz and Cabido 2001, Elmqvist et al. 2003, Peterson et al. 1998, Stagg and Mendelssohn 2011). In the face of rapidly changing environmental conditions associated with SLR, changes in species’ distributions and subsequent impairment of wetland ecosystem resilience is an increasingly relevant topic for researchers and environmental managers. There are numerous ongoing efforts to model and predict the response of coastal ecosystems to SLR projections, each providing different strengths and weaknesses for managers tasked with conserving coastal habitats (McLeod et al. 2010). Some of these models utilize calculations of marsh loss/conversion based on general plant community categories across broad stress-tolerance ranges and do not incorporate important species-specific biological feedbacks to elevation maintenance, which can result in overestimates of total wetland loss in response to SLR (Kirwan and Guntenspergen 2009). To address these concerns, models are increasingly being refined to incorporate plant-mediated feedbacks to surface elevation (e.g., Hydro- MEM, in Alizad et al. 2016; WARMER, in Takekawa et al. 2013). Thus, surveying and monitoring plant species distributions along environmental stress gradients can provide high-resolution, site-specific data to inform models, thereby allowing managers to assess relative SLR impacts within specific habitats and to develop effective management strategies. To explore the environmental drivers of plant species zonation in a coastal wetland, we surveyed marsh plant dominance along elevation and salinity gradients in intertidal marsh habitat within the Weeks Bay National Estuarine Research Reserve (NERR), AL. Located in the most rapidly growing county (Baldwin County) in Alabama, the Weeks Bay estuary represents an important conservation area because of its relatively high upriver migration potential in response to rising seas (Enwright et al. 2016). Yet, coastal wetlands in the Bay occupy an already narrow transition and are therefore susceptible to changes in environmental conditions associated with Southeastern Naturalist A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 226 SLR and coastal squeeze. We provide information on local plant zonation in the Weeks Bay complex, which can inform future environmental management efforts in Mobile Bay and along the northern Gulf Coast. Field-site Description Weeks Bay is a part of the Bon Secour sub-estuary on the southeast corner of Mobile Bay in Baldwin County, AL. It covers 26.41 km2 and is fed primarily by 2 sources—the Magnolia River to the east and Fish River to the north—with nearly three quarters of the freshwater inflow coming from the Fish River (NERR 2008). The Weeks Bay Estuary is microtidal, with a tidal range of 0.3–0.5 m (NERR 2008). The focus of this study was on a narrow band of intertidal marshes near the mouth of the Fish River on the west side of the bay. In much of the vegetated marsh, we observed the presence of a slight, yet steep increase in elevation (~30 cm in most areas). This escarpment land feature, or berm, is common in intertidal marshes along the northern Gulf of Mexico (Fig. 1). The survey area also included 3 main vegetative zones typical of northern Gulf Coast marshes that are dominated by Cladium mariscus ssp. jamaicense (Swamp Sawgrass) in freshwater and higher elevation areas, Juncus roemerianus (Black Needlerush) in the brackish to intermediate salinity and elevation zone, and Spartina alterniflora (Smooth Cordgrass) in the high salinity and low-elevation fringe/shoreline marsh. Other key species in these areas include Spartina cynosuroides (Big Cordgrass), Spartina patens (Salt Meadow Cordgrass), Sagittaria lancifolia (Bulltongue), Symphyotrichum subulatum (Salt Marsh Aster), and Distichlis spicata (Saltgrass) (A.J. Constantin, pers. observ.; NERR 2008) reflecting local elevation and salinity conditions. Methods We conducted vegetation and elevation surveys in July 2014 along transects running perpendicular to the shoreline in an intertidal marsh at Weeks Bay (Fig. 1). We chose the specific survey area based on accessibility and the presence of representative, contiguous marsh. The Weeks Bay NERR walkway and observation deck allowed access to and from the survey site. We created a field map for reference during surveys that included approximate transect locations. To create parallel transects that were approximately perpendicular to the shoreline, we established a 350° bearing from the southwest piling of the observation deck as the initial reference transect from which we based all other transect lines. Initially, we took survey points every 20 m along 9 transects, with a 40-m interval between transects (Fig. 1). We took this approach to ensure that our survey would capture a representative profile of the emergent marsh within the area of interest. After this initial survey, we sampled 4 intermediate transects at a 10-m frequency (Fig. 1) to ensure that we fully recorded plant species zones. We measured elevation and percent cover of marsh plants at each sampling point along all transects. To measure elevation, we used a GPS real-time kinetic Southeastern Naturalist 227 A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 (RTK) solution in which a Trimble Geo7x witha Zephyr2 antenna acquired corrections from the Alabama Department of Transportation (ALDOT) Continuously Operating Reference Stations (CORS) network. This approach provided real-time, auto-corrected elevation readings for each survey point. We tested the GPS RTK at an elevation benchmark near the sampling area, from which we determined that we could consistently acquire a less than 3-cm vertical accuracy within 180 epochs (GPS-coordinate readings). We recorded elevation readings using the NAVD88 datum based on Geoid12A. Dauphin Island was the closest tide station with available NAVD88 data relative to local mean sea level (MSL), which showed that local MSL was +1.8 cm NAVD88. We then employed a transformation coefficient of -1.8 cm to convert NAVD88 elevation to relative MSL. We visually determined percent cover of vascular plant species using a 1-m2 quadrat at each sampling point, for a total of 101 cover readings throughout the sampling area. We recorded percent cover of live standing aboveground biomass by a single observer over a 4-day sampling period. To estimate cover, we randomly placed the sampling quadrat within 1 m of the RTK device while elevation was being recorded, and recorded the proportion of marsh surface covered by the aerial parts of the plants emerging from within the plot (Brower et al. 1990). We recorded unvegetated, exposed groundcover as “bare”. We also recorded additional plant Figure 1. Sampling locations for surveys of percent cover of plant species, elevation readings, and subsequent salinity measurements along transects established within Weeks Bay NERR, AL. Each white circle represents a survey point. The location of the berm is denoted by the sharp transition to a lighter shade of gray along the shoreline. Southeastern Naturalist A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 228 species that were not in the quadrat but were observed within ~3 m of the sampling location; these observations were not included in the analysis. We collected and pressed unknown plants for later identification with Godfrey and Wooten (1979, 1981) and the USDA Plants database ( or Larry Allain at the USGS National Wetland and Aquatic Research Center in Lafayette, LA. We plotted plant survey data by elevation and distance from shoreline. We calculated distance from shoreline in ESRI ArcMap (ArcGIS 10.3.1, ESRI, Redlands, CA) using a created vector shoreline shapefile and a NAD83/UTM zone16N (North American Datum of 1983/Universal Transverse Mercator) projected coordinate system. Plotting plant data by elevation and distance from shoreline provided spatial representations of marsh plant species’ distributions along vertical and horizontal planes. Elevation generally increased from shore to inland, but with micro-topographic variations that resulted in a lack of clear delineations between plant zones by elevation. Following preliminary examination of relationships between elevation and plant cover, we sampled porewater salinity in early October 2014 along the same transects as the surveys of elevation and percent cover to determine if observed zonation patterns corresponded to relative differences in salinity among plots. We used a sipper tube inserted vertically into the soil to a depth of 15 cm to collect samples of at least 40 mL of porewater, from which salinity (psu) was subsequently determined in the lab using a YSI conductivity meter (YSI 3100, YSI Inc., Yellow Springs, OH). We followed established transects as closely as possible and took samples at a 10-m frequency and recorded GPS points for all new sample sites. We imported GPS points and associated salinity values into ArcMap as a point shapefile. Although the points from the salinity survey did not match the timing or exact locations of the prior plant surveys, they captured relative differences in salinity along transects and were collected generally no more than 5 m from original survey locations. To determine soil salinity at sites we surveyd for elevation and percent cover, we used an inverse distance-weighted (IDW) interpolation to create a 2D surface model of salinity. Salinity values were then sampled from the resulting raster using the previous survey points. Each survey point then had an associated value for species percent cover, elevation, salinity, and distance from shoreline. We examined how environmental conditions (elevation, salinity, distance from shoreline) related to each other and to species percent cover using separate correlation analyses for the 3 dominant species: Swamp Sawgrass, Black Needlerush, and Big Cordgrass. We included data from all 101 survey points across the full ranges of elevation, salinity, and distance from shoreline to examine correlations with percent cover and to detect general patterns of species distributions within the coastal transition. We also examined correlations between species using data from all 101 survey points to elucidate relationships of cohabitation between species. Data for all correlations violated the normality assumption for parametric tests, necessitating the use of non-parametric Spearman’s rho correlations. We conducted all analyses in JMP v10.0 (SAS Institute, Cary, NC) and tested at the α = 0.05 level. Southeastern Naturalist 229 A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 Results In the surveyed vegetated marsh, elevation varied from -0.474 m to +0.661 m (NAVD 88), with the lowest elevation occurring along the shoreline (Table 1, Fig. 2). Inland of the subtidal area, there was an ~0.3-m increase in elevation, marking the berm which ran parallel to the shore (Figs. 1, 2). Inland of the berm, elevation varied between 0.2 m and 0.6 m, generally increasing with increasing distance from shoreline (ρ = 0.47, P < 0.0001); there was heterogeneous microtopography throughout the coastal transition (Fig. 2). We observed a total of 18 vascular plant species in the study area (Table 1). We identified 3 dominant plant species from the 14 transects: Big Cordgrass (17.9% of observations), Black Needlerush (12.3%), and Swamp Sawgrass (12.3%) (Table 1). Combined, the 3 species contributed to 42.5% of the total observations across 101 survey plots, with the other 15 species collectively comprising 53%, and none making up more than 8.8% cover. Of the dominant plant species, Big Cordgrass had the second largest elevation span (-0.066 to +0.636 m), with higher percent cover in areas along and near the berm (Table 1; Figs. 2, 3). Its cover throughout the coastal transition was not significantly related to elevation (ρ = 0.32, P = 0.75; Fig. 3a), although it did occupy elevations up to 0.05 m higher than Black Needlerush. Big Cordgrass cover increased with increasing salinity (ρ = 0.29, P = 0.003; Fig. 3b) and declined with increasing distance from shoreline (ρ = -0.45, P < 0.0001; Fig. 3c). Black Needlerush had the largest elevation span (-0.228 to +0.586 m), with higher percent cover in lower elevation, saltier areas nearer the shore (Table 1, Figs. 2–4). Generally, its distribution throughout the coastal transition declined Figure 2. Change in elevation with increasing distance from shoreline and corresponding distributions of dominant marsh plant species by elevation and distance from shoreline. Big Cordgrass, Black Needlerush, and Swamp Sawgrass distributions are illustrated by the shaded boxes, with the vertical extent of each box indicating elevation ranges and the horizontal extent of each box indicating the range in distance from shoreline. Each point on the elevation line signifies a survey point, conveying the heterogeneous micro-topography of the coastal transition in the survey area. Southeastern Naturalist A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 230 Table 1. Plant species identified during surveys of marsh transects listed in order of frequency (n) in which they were observed out of 101 total plots. Range (min/max), mean, and median of elevation (m), salinity (psu), and distance from shoreline (m) are provided for observed plant species. % = percent of total observed. Elevation is relative to MSL. [Table continued on following page.] Elevation (m) Salinity (psu) Distance to shoreline (m) Scientific name Common name n % Min Max Mean Median Min Max Mean Median Min Max Mean Median Spartina cynosuroides Big Cordgrass 55 17.9 -0.07 0.64 0.43 0.44 1.04 12.18 6.68 6.55 1.39 92.79 35.25 35.49 (L.) Roth Juncus roemerianus Black Needlerush 38 12.3 -0.23 0.59 0.34 0.38 1.04 13.82 6.68 6.47 0.82 105.27 45.33 44.01 Scheele Cladium mariscus (L.) Swamp Sawgrass 38 12.3 0.33 0.59 0.47 0.47 1.67 7.33 4.34 3.88 18.26 156.92 89.47 86.54 Pohl ssp. jamaicense. (Crantz) Kük Spartina patens (Aiton) Saltmeadow 27 8.8 0.19 0.59 0.47 0.49 2.66 8.59 6.23 6.53 8.73 87.73 43.28 39.65 Muhl. Cordgrass Sagittaria lancifolia L. Bulltongue 25 8.1 0.25 0.64 0.46 0.47 1.04 7.91 3.40 2.86 4.15 156.92 70.04 74.67 Arrowhead Distichlis spicata (L.) Saltgrass 22 7.1 0.29 0.59 0.46 0.47 2.66 13.82 7.07 6.95 16.72 74.05 41.86 40.41 Greene Schoenoplectus robustus Sturdy Bulrush 21 6.8 0.29 0.61 0.47 0.48 1.26 10.24 5.91 6.00 8.27 92.79 43.19 39.69 (Pursh) M.T. Strong Kosteletzyka virginica (L.) Virginia Saltmarsh 16 5.2 0.42 0.59 0.50 0.51 1.04 7.25 4.11 3.80 63.17 156.92 100.60 96.41 C. Presl Mallow Eleocharus rostellata Beaked Spikerush 13 4.2 0.30 0.61 0.47 0.47 1.26 7.59 4.09 3.67 19.07 99.83 63.62 70.28 (Torr.) Torr. Southeastern Naturalist 231 A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 Table 1, continued. Elevation range (m) Salinity (psu) Distance to shoreline (m) Scientific name Common name n % Min Max Mean Median Min Max Mean Median Min Max Mean Median Osmunda regalis L. Royal Fern 10 3.2 0.36 0.53 0.45 0.45 1.70 4.86 3.64 3.64 70.28 156.92 111.16 111.13 Ipomoea sagittata Poir. Saltmarsh Morning 9 2.9 0.36 0.59 0.47 0.47 2.86 6.89 5.22 5.39 28.28 118.59 72.07 67.88 Glory Zizaniopsis miliacea Giant Cutgrass 7 2.3 0.41 0.66 0.54 0.52 1.20 7.38 3.98 3.73 46.13 97.35 64.10 55.65 (Michx.) Döll and Asch. Spartina alterniflora Smooth Cordgrass 5 1.6 -0.47 0.51 -0.15 -0.33 6.09 6.89 6.43 6.34 0.09 77.84 16.59 1.27 Loisel. Baccharus halimifolia L. Eastern Baccharis 2 0.6 0.43 0.48 0.46 0.46 3.16 6.85 5.00 5.00 80.99 89.10 85.04 85.04 Typha domingensis Pers. Southern Cattail 2 0.6 0.49 0.52 0.51 0.50 6.00 6.53 6.47 6.53 57.28 87.73 67.78 58.32 Hypericum hypericoides St. Andrew’s Cross 2 0.6 0.43 0.44 0.44 0.44 3.16 4.45 4.45 4.45 89.10 105.27 105.27 105.27 (L.) Crantz Iva frutescens L. Jesuit’s Bark 1 0.3 0.49 0.49 0.49 0.49 7.12 7.12 7.09 7.09 60.67 60.67 67.36 67.36 Magnolia virginiana L. Sweetbay 1 0.3 0.43 0.43 0.43 0.43 3.16 3.16 3.16 3.16 89.10 89.10 89.10 89.10 Bare land 14 4.5 -0.47 0.57 0.13 0.25 2.00 9.10 5.41 6.00 0.09 105.27 34.87 14.22 Southeastern Naturalist A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 232 with increasing elevation (ρ = -0.45, P < 0.0001; Fig. 3d), increased with increasing salinity (ρ = 0.33, P = 0.0008; Fig. 3e), and declined with distance from shoreline (ρ = -0.20, P = 0.04; Fig. 3f). Swamp Sawgrass occupied the smallest elevation range (0.330–+0.586 m), with greater cover at higher elevations further inland (Table 1; Figs. 2, 3). Swamp Sawgrass percent cover increased with increasing elevation (ρ = 0.20, P =0.04; Fig. 3g), decreased with increasing salinity (ρ = -0.41, P < 0.0001; Fig. 3h), and increased with distance from shoreline (ρ = 0.76, P < 0.0001; Fig. 3i). Of the dominant species, Big Cordgrass and Swamp Sawgrass were spatially segregated, with Swamp Sawgrass cover increasing as Big Cordgrass cover decreased (ρ = -0.61, P < 0.0001; Table 2). Although Big Cordgrass and Black Needlerush occupied similar elevation and salinity ranges (Table 1), Black Needlerush cover tended to increase as Big Cordgrass cover decreased, although this relationship was not significant (ρ = -0.18, P = 0.75; Table 2). Similarly, Black Needlerush cover tended to increase as Swamp Sawgrass cover decreased; this relationship was not quite significant (ρ = -0.17, P = 0.08; Table 2). Figure 3. Scatterplots of environmental conditions (elevation, salinity, and distance from shoreline) by the percent cover of dominant plant species: (a–c) Big cordgrass, (d–f) Black Needlerush, and (g–i) Swamp Sawgrass. Spearman’s rho (ρ) values signify the nature (positive or negative) and strength of correlations. A positive/negative value indicates a positive/ negative correlation for a respective relationship between the plant species and environmental condition. P-value indicates significance at the α = 0.05 level. Significant relationships are indicated by an asterisk (*). Southeastern Naturalist 233 A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 Discussion Our findings suggest that wetland plant species zonation in Weeks Bay corresponded to changes in inundation and salinity that varied across the coastal transition. Although elevation ranges differed for the 3 dominant plant species, their ranges overlapped, especially between Black Needlerush and Big Cordgrass, and as such, zonation could not be defined by elevation (i.e., inundation) alone. When we also examined salinity, clear segregation between Swamp Sawgrass and the other 2 dominant species was apparent; there was a tendency for Black Needlerush to dominate when salinity was higher (>9 psu). Thus, salinity combined with elevation Table 2. Spearman’s rho correlation analysis between dominant plant species (Big Cordgrass, Black Needlerush, and Swamp Sawgrass). Spearman’s rho values signify the nature (positive or negative) and strength of correlations and P-value indicates significance at the α = 0.05 level. A positive value indicates cohabitation and a negative value indicate a lack of cohabitation. Significant values are indicated by an asterisk (*). Big Cordgrass Black Needlerush Swamp Sawgrass ρ P ρ P ρ P Big Cordgrass -0.18 0.75 -0.61 less than 0.0001* Black Needlerush -0.18 0.75 -0.17 0.08 Swamp Sawgrass -0.61 < 0.0001* -0.17 0.08 Figure 4. Spatial distribution of Big Cordgrass, Black Needlerush, and Swamp Sawgrass. Larger circles indicate higher percent cover at a sampling site and light-to-dark gradient indicates increasing porewater salinity based on field samples. Southeastern Naturalist A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 234 provides a possible explanation for relative spatial distributions of the dominant species along the elevation gradient in this Weeks Bay marsh. The observed influence of salinity as a driver of coastal-marsh plant zonation is consistent with the current paradigm in which salinity is viewed as a key indicator of vegetation and habitat classification (Adams 1963, Chapman 1974, Odum 1988, Pennings et al. 2005, Visser et al. 2002). In a study of temporal changes in vegetation in a tidal freshwater marsh, Perry and Hershner (1999) documented an increase in the abundance of Big Cordgrass with increasing saltwater influence. Black Needlerush, which can occupy zones with dissimilar environmental conditions (Touchette et al. 2009), has a more ubiquitous presence throughout Weeks Bay. It is also common in marshes along the south Atlantic and northern Gulf of Mexico coasts where it dominates 20.7% and 7.3% of marshes, respectively (Eleuterius 1976). Further, interactions of plant community dominance between Big Cordgrass and Black Needlerush in response to salinity are well documented (Higinbotham et al. 2004, Pennings et al. 2005, Touchette et al. 2009, White and Alber 2009). Hackney et al. (1996) found that Black Needlerush occupied higher-salinity areas than Big Cordgrass (average salinities 17 psu and 13 psu, respectively), a pattern that we observed in the Weeks Bay marsh as well. While we found the 2 species to occupy similar salinity ranges in general, Black Needlerush was found more at the sites with the very highest salinity values. Given that zonation was linked to salinity, the effects of projected SLR on the Weeks Bay marsh and other similar ecosystems may be more tied to its effects on salinity than inundation. Under projected conditions of global climate change, changes in precipitation patterns in the Weeks Bay watershed could alter freshwater delivery and salinity in these marshes (Wong et al. 2014). Higher salinities would likely favor Black Needlerush and may result in a sharper salinity gradient along the coastal transition, while lower salinities could favor Swamp Sawgrass. Based on the spatial salinity profile in the survey area, sea-level rise could reduce salinity, rather than increase it, by flushing out salts that have accumulated behind the berm. The area of highest observed salinity (and highest Black Needlerush dominance) was on the landward side of this berm. Field observations indicated that this situation may be a result of evaporation and subsequent salt accumulation, resulting in higher salinity than that of the Bay water (Schroeder et al. 1992). In the event of higher sea levels, tidal flushing could lower salinities in this area by flushing these salts, thus, favoring Big Cordgrass. The already marginal coastal marshes in Weeks Bay may also be under threat of coastal squeeze (Borchert et al. 2017). As the dominant species in the upland marsh zone, Swamp Sawgrass is limited by salinity and forested wetland habitat on its seaward and landward extents, respectively. The salinity tolerances of Black Needlerush and Big Cordgrass are much higher than that of Swamp Sawgrass; thus, the possibility of elevated salinity from SLR may restrict its habitable zone as Black Needlerush and Big Cordgrass migrate inland. On the landward extreme, the forested wetlands that border the Swamp Sawgrass zone have been expanding into coastal marsh habitat (Constantin 2015), which further reduces Southeastern Naturalist 235 A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 the inhabitable coastal transition and may limit the capacity of marsh transgression upland. In the presence of these barriers, upriver migration may be necessary for these intertidal, saline ecosystems to persist in the face of rising seas. In Alabama, landward migration of tidal marshes on protected land is estimated to be possible on 45% of the area, and thus, the Weeks Bay NERR represents an important conservation target and potential migration corridor (Enwright et al. 2016). Consequently, it is critical that environmental management strategies integrate landward migration corridors to facilitate natural mechanisms of ecosystem resilience by increasing ecosystem connectivity. Prescribed burning of marshes may be one mechanism by which upland forest barriers to marsh migration are reduced. Fire can promote a more natural forest-towetland ecotone (Knickerbocker et al. 2009, Poulter et al. 2009), in which marsh– forest transitions are facilitated in response to changing environmental conditions. Ecosystems exposed to fire events have been shown to be more spatially fluid in response to changing environmental conditions and display more distinct ecotone boundaries than those in which fire is absent (Boughton et al. 2006, Smith et al. 2013). The first prescribed burn on record for the Weeks Bay marsh was not until 2008 (S. Phipps, Weeks Bay NERR, AL, pers. comm.), and it is possible that future fire management strategies will reduce recent forest encroachment (Constantin 2015) and promote marsh migration in response to rising sea level. The continued practice of prescribed burns, along with monitoring of changes in salinity and the location of the marsh–forest ecotone, are vital to gain insight to the future distribution of species along this coastal transition. In addition to SLR and forest expansion, human activities that alter coastal habitat could affect coastal wetland resilience. For instance, the vulnerability of unvegetated and human-altered shorelines to erosional loss is a well-documented occurrence worldwide (Gedan et al. 2010). Hard shoreline structures, such as bulkheads that are intended to stabilize shoreline, can exacerbate erosion by focusing tidal action on a small area of land resulting in “vertical erosion”. They can also act as a physical barrier preventing landward migration of plant species in response to changing environmental conditions. These bulkhead shorelines are common in areas of urban and residential development to protect property from wave damage. In Weeks Bay, the majority of shoreline erosion is concentrated in areas with bulkhead structures or unvegetated sediment (Constantin 2015, Douglass and Pickel 1999, Jones et al. 2009), making the narrow zone of intertidal marsh an important resource for the area. Although the findings of this study support the prevailing paradigm that intertidal marsh species’ distributions arise in response to changes in both elevation and salinity (Battaglia et al. 2012, Pennings et al. 2005)—factors that will likely change with SLR—they also demonstrate high levels of overlap among plant species along an elevation gradient. Models of SLR impacts that are based on general, coarsely grouped categories of vegetation do not capture this finer-scale heterogeneity, and thus, may miss important species-specific, biological feedbacks to elevation. Further, upslope barriers to species migration, coupled with seaward stresses associated with Southeastern Naturalist A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 236 hardened shorelines and erosion, may reduce the ability of Weeks Bay marshes to respond to SLR in the future. To facilitate sustainable coastal development practices and minimize coastal squeeze, it may be necessary to utilize prescribed burns to manage upland barriers, limit the presence of bulkheads or other hardened structures, and promote natural mechanisms of ecosystem resilience to SLR. In so doing, environmental managers may be able to enhance marsh transgression and reduce erosional land loss, thereby promoting a more resilient coastal landscape in Weeks Bay, AL, and similar marshes along the northern Gulf of Mexico. Acknowledgments We thank Jonathan Benstead and Just Cebrian for feedback during the development of the project. A special thanks to Dale Steve Nevitt and Sara Martin for help in the field. We are grateful to Larry Allain for aid in plant identification, Michael Kendrick for assistance with data analysis, and Scott Phipps and Eric Brunden at the Weeks Bay NERR for support during the duration of these projects. Comments from two anonymous reviewers greatly improved the quality of this manuscript. Funding for this and related projects was provided by The University of Alabama and Grant NA09NOS4190153 from the NOAA NERRS Science Collaborative. Literature Cited Adams, D.A. 1963. Factors influencing vascular plant zonation in North Carolina salt marshes. Ecology 44:445–456. Alizad, K., S.C. Hagen, J.T. Morris, P. Bacopoulos, M.V. Bilskie, J.F. Weishampel, and S.C. Medeiros. 2016. A coupled, two-dimensional hydrodynamic-marsh model with biological feedback. Ecological Modeling 327:29–43. Battaglia, L.L., M.S. Woodrey, M.S. Peterson, K.S. Dillon, and J.M. Visser. 2012. Wetlands of the Northern Gulf Coast. Pp. 75–88, In D.P. Batzer, and A.H. Baldwin (Eds.). Wetland Habitats of North America: Ecology and Conservation Concerns. University of California Press, Berkeley, CA. 408 pp. Borchert, S.M., M.J. Osland, N.M. Enwright, and K.T. Griffith. 2017. Coastal wetland adaptation to sea level rise: Quantifying potential for landward migration and coastal squeeze. Journal of Applied Ecology 55:2876–2887. Boughton, E.A., P.F. Quintana-Ascencio, E.S. Menges, and R.K. Boughton. 2006. Association of ecotones with relative elevation and fire in an upland Florida landscape. Journal of Vegetation Science 17:361–368. Brewer, J.S., and J.B Grace. 1990. Plant community structure in an oligohaline tidal marsh. Vegetatio 962:93–107. Brower, J.E., H. Zar, and C.N. von Ende. 1990. Field and Laboratory Methods for General Ecology. McGraw-Hill, Boston, MA. 288 pp. Chapman, V.J. 1974. Salt marshes and salt deserts of the world. Pp. 3–19, In R.J. Reimold and W.H. Queen (Eds.). Ecology of Halophytes. Academic Press, New York, NY. 620 pp. Constantin, A.J. 2015. Land-cover change and wetland plant zonation in Weeks Bay, Alabama. M.Sc. Thesis. The University of Alabama, Tuscaloosa, AL. 68 pp. Cooper, A. 1982. The effects of salinity and waterlogging on the growth and cation uptake of salt marsh plants. New Phytologist 90:263–275. Southeastern Naturalist 237 A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 Dahl, T.E. 1990. Wetlands losses in the United States, 1780s to1980s. US Department of the Interior, Fish and Wildlife Service, Washington, DC. 112 pp. Dahl, T.E. 2011. Status and trends of wetlands in the conterminous United States, 2004 to 2009. US Department of the Interior, Fish and Wildlife Service, Washington, DC. 108 pp. Dı́az, S., and M. Cabido. 2001. Vive la difference: Plant functional diversity matters to ecosystem processes. Trends in Ecology and Evolution 16:646–655. Douglass, S.L., and B.H. Pickel. 1999. The tide doesn't go out anymore: The effect of bulkheads on urban bay shorelines. Shore and Beach 67:19–25. Earle, J.C., and K.A. Kershaw. 1989. Vegetation patterns in James Bay coastal marshes. III. Salinity and elevation as factors influencing plant zonations. Canadian Journal of Botany 67:2967–2974. Eleuterius, L.N. 1976. The distribution of Juncus roemerianus in the salt marshes of North America. Chesapeake Science 17:289. Elmqvist, T., C. Folke, M. Nyström, G. Peterson, J. Bengtsson, B. Walker, and J. Norberg. 2003. Response diversity, ecosystem change, and resilience. Frontiers in Ecology and the Environment 9:488–494. English Nature. 1992. Coastal Zone Conservation: English Nature’s Rationale, Objectives and Practical Recommendations. English Nature, Peterborough, UK. Enwright, N.M., K.T. Griffith, and M.J. Osland. 2016. Barriers to and opportunities for landward migration of coastal wetlands with sea-level rise. Frontiers in Ecology and Environment14:307–316. Gedan, K.B., and M.D. Bertness. 2010. How will warming affect the salt marsh foundation species Spartina patens and its ecological role? Oecologia 164:479–487. Godfrey, R.K., and J.W. Wooten. 1979. Aquatic and Wetland Plants of the Southeastern United States: Monocotyledons. University of Georgia Press, Athens, GA. 728 pp. Godfrey, R.K., and J.W. Wooten. 1981. Aquatic Plants of the Southeastern United States: Dicotyledons. University of Georgia Press, Athens, GA. 944 pp. Grime, J.P. 1977. Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory. American Naturalist 111:1169–1194. Grime, J.P. 1979. Competition and the struggle for existence. Pp. 123–139, In R.M. Anderson, B.D. Turner, and L.R. Taylor (Eds.). Population dynamics. Blackwell Scientific, Oxford, UK. 434 pp. Hackney, C.T., S. Brady, L. Stemmy, M. Boris, C. Dennis, T. Hancock, and E. Barbee. 1996. Does intertidal vegetation indicate specific soil and hydrologic conditions? Wetlands 16:89–94. Higinbotham, C.B., M. Alber, and A.G. Chalmers. 2004. Analysis of tidal marsh vegetation patterns in two Georgia estuaries using aerial photography and GIS. Estuaries27: 670–683. Jones, S.C., D.K. Tidwell, and S.B. Darby. 2009. Comprehensive shoreline mapping, Baldwin and Mobile counties, Alabama: Phase I. Open File Report 0921. Alabama Geological Survey, Tuscaloosa, AL. 38 pp. Kirwan, M.L., and G.R. Guntenspergen. 2009. Accelerated sea-level rise: A response to Craft et al. Frontiers in Ecology and the Environment 7:126–127. Kirwan, M.L., and J.P. Megonigal. 2013. Tidal wetland stability in the face of human impacts and sea-level rise. Nature 504:53–60. Kirwan, M.L., G.R. Guntenspergen, A. D’Alpaos, J.T. Morris, S.M. Mudd, and S. Temmerman 2010. Limits on the adaptability of coastal marshes to rising sea level. Geophysical Research Letters 37:L23401. Southeastern Naturalist A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 238 Knickerbocker, C.M., S. Leitholf, E.L. Stephens, D.J. Keellings, H. Laird, C.J.R. Anderson, and P.F. Quintana-Ascencio. 2009. Tree encroachment of a Sawgrass (Cladium jamaicense) marsh within an increasingly urbanized ecosystem. Natural Areas Journal 29:15–26. La Peyre, M.K.G., J.B. Grace, E. Hahn, and I.A. Mendelssohn. 2001. The importance of competition in regulating plant species abundance along a salinity gradient. Ecology 82:62–69. McLeod, E., B. Poulter, J. Hinkel, E. Reyes, and R. Salm. 2010. Sea-level–rise impact models and environmental conservation: A review of models and their applications. Ocean and Coastal Management 53:507–517. McLeod, E., G.L. Chmura, S. Bouillon, R. Salm, M. Björk, C.M. Duarte, C.E. Lovelock, W.H. Schlesinger, and B.R. Silliman. 2011. A blueprint for blue carbon: Toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2. Frontiers in Ecology and the Environment 9:552–560. Mitsch, W. J., and J.G. Gosselink. 2015. Wetlands. John Wiley and Sons, Inc., Hoboken, NJ. 736 pp. National Estuarine Research Reserve System (NERRS). 2008. Weeks Bay, AL. Available online at Accessed 1 February 2014. Nixon, S.W. 1982. The ecology of New England high salt marshes: A community profile. Number FWS/OBS–81/55. National Coastal Ecosystems Team, Washington, DC. Graduate School of Oceanography, Rhode Island University, Kingston, RI. Odum, W.E. 1988. Comparative ecology of tidal freshwater and salt marshes. Annual Review of Ecology and Systematics 19:147–176. Pennings, S.C., M.B. Grant, and M.D. Bertness. 2005. Plant zonation in low-latitude salt marshes: Disentangling the roles of flooding, salinity, and competition. Journal of Ecology 93:159–167. Perry, J.E., and C.H. Hershner. 1999. Temporal changes in the vegetation pattern in a tidal freshwater marsh. Wetlands 19:90–99. Peterson, G., C.R. Allen, and C.S. Holling. 1998. Ecological resilience, biodiversity, and scale. Ecosystems 1:6–18. Pethick, J. 1993. Shoreline adjustments and coastal management: Physical and biological processes under accelerated sea-level rise. Geographical Journal 159:162–168. Poulter, B., S.S. Qian, and N.L. Christensen. 2009. Determinants of coastal treeline and the role of abiotic and biotic interactions. Plant Ecology 202:55–66. Schroeder, W.W., S.P. Dinnel, and W.J. Wiseman. 1992. Salinity structure of a shallow, tributary estuary. Pp. 155–171, In D. Prandle (Ed.). Dynamics and Exchanges in Estuaries and the Coastal Zone. American Geophysical Union, Washington, DC. 650 pp. Smith, T.J., III, A.M. Foster, G. Tiling-Range, and J.W. Jones. 2013. Dynamics of mangrove– marsh ecotones in subtropical coastal wetlands: Fire, sea-level rise, and water levels. Fire Ecology 9:66–77. Stagg, C.L., and I.A. Mendelssohn. 2011. Controls on resilience and stability in a sedimentsubsidized salt marsh. Ecological Applications 21:1731–1744. Takekawa, J.Y., K.M. Thorne, K.J. Buffington, K.A. Spragens, K.M. Drexler, J.Z. Schoellhamer, C.T. Overton, and M.L. Casazza. 2013. Final report for sea-level response modeling for San Francisco Bay estuary tidal marshes. US Geological Survey Open File Report 2012–1081. Sacramento, CA. 161 pp. Touchette, B.W., G.A. Smith, K.L. Rhodes, and M. Poole. 2009. Tolerance and avoidance: Two contrasting physiological responses to salt stress in mature marsh halophytes Juncus roemerianus Scheele and Spartina alterniflora Loisel. Journal of Experimental Marine Biology and Ecology 380:106–112. Southeastern Naturalist 239 A.J. Constantin, W.P. Broussard III, and J.A. Cherry 2019 Vol. 18, No. 2 Visser, J.M., C.E. Sasser, R.H. Chabreck, and R.G. Linscombe. 2002. The impact of a severe drought on the vegetation of a subtropical estuary. Estuaries 25:1184–1195. Vitousek, P.M., H.A. Mooney, J. Lubchenco, and J.M. Melillo. 1997. Human domination of Earth’s ecosystems. Science 277:494–499. White, S.N., and M. Alber. 2009. Drought-associated shifts in Spartina alterniflora and S. cynosuroides in the Altamaha River estuary.Wetlands 29:215–224. Wong, P.P., I.J. Losada, J.-P. Gattuso, J. Hinkel, A. Khattabi, K.L. McInnes, Y. Saito, and A. Sallenger. 2014. Coastal systems and low-lying areas. Pp. 361–409, In C.B. Field, V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L.White (Eds.). Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Cambridge University Press, Cambridge, UK and New York, NY. 1140 pp. Zedler, J.B. 1977. Salt marsh community structure in the Tijuana Estuary, California. Estuarine and Coastal Marine Science 5:39–53.