Salt marshes provide important habitats for many species in the estuaries along the east and Gulf coasts of North America. With many species dependent on these coastal marshlands and extensive documentation that these marshlands are disappearing, a clear understanding of the mechanisms causing loss is critical. Much of the salt marsh was lost to reclamation and construction before these activities were curtailed circa 1970; however, losses due to other causes have continued and multiple hypothesized causes have been proposed, not all mutually exclusive. Yet it remains unclear whether there are legacy effects from the reclamation projects. When the edges of salt marshes are cut into, and gentle vegetated slopes are replaced by sharp edges adjoining deep water of 2 m or more, erosion could accelerate and could continue for many years. One method that may help shed light on the relative importance of the various causes of salt marsh erosion would be to compare the erosion rates of specific edges within a marshland that are exposed to particular conditions. We therefore used several sets of aerial photography spanning 84 years to track the changes at specific edge locations along marsh edges and then make comparisons between anthropogenically created edges and naturally created edges, including comparisons within use and width categories of navigational channels. Erosion rates were found to remain significantly higher on channelized edges than along otherwise similar wetland edges even several decades after modification. Likely reasons include the continued exposure of underlying layers that lack reinforcing plant root systems, vertical edges that are more vulnerable to undermining from wave action, and increased erosion related to altered tidal flows.
Wetlands serve as a valuable natural resource supplying may ecosystem services (Keddy et al. 2009), including roles as nurseries for thousands of species, as barriers protecting human infrastructure from storm surges, in the dissipation of wave energy, in denitrification, and as water filtration systems (Möller et al. 1999; Shriver et al. 2004; Cooper 2005; Zedler and Kercher 2005; Costanza et al. 2008; Feagin et al. 2010; Barbier et al. 2011, Fagherazzi 2014). Globally, wetlands have lost about half their area worldwide since the 1900 (Spiers 2001; Larsen et al. 2009; Keddy et al. 2009). Many mechanisms have proposed to explain the losses of salt marshes (Mendelssohn and McKee 1988; McKee et al. 2004; Edwards et al. 2005; Silliman et al. 2005; Mendelssohn et al. 2006; Alber et al. 2008; Ogburn and Alber 2006; Gedan et al. 2011; Deegan et al. 2007; Deegan et al. 2012), and it is unlikely that any single factor is the major cause of marsh loss throughout their geographic range. Even within a single bay, different marshes may respond differently (Wigand et al. 2014).
Boat traffic is sometimes implicated in edge erosion (Zabawa and Ostrom 1980; Dorava and Moore 1997; Davis et al. 2009). However, many natural forces are also erosive, including waves formed by winds over long stretches of water (Pye 1995; Schwimmer 2001; Leonardi et al. 2016), but these waves can be larger when water becomes deepened by sea-level rise, excessive dredging, or other reasons. Tidal currents can induce meander patterns of erosion and redeposition (Biggs 1982; Kearney et al. 1988; Kleinhans et al. 2009) and wind-driven wave action can also have strong effects (Fagherazzi and Wiberg 2008; Leonardi and Fagherazzi 2014; Priestas et al. 2015). The interaction of sea-level rise and sediment deposition rates can also cause the widening of creeks (Fagherazzi et al. 2012). However, little attention has been payed to potential enhancement of erosion due to the creation of engineered edges along channels directly cut through marshlands or into wetlands.
In this study, it was expected that the cut edges in salt marshes would be less stable and more prone to slumping and other erosional forces than natural edges under otherwise similar conditions. Secondly, it was expected that the edges would become more stable over time. This study attempts to address these questions using the test case of Hempstead Bay, Long Island, New York.
Maps, aerial photographs, bathymetry, and historical records from various sources were used to locate edges that were the result of engineering projects implemented between 1879 and 2012, as detailed below.
The Hempstead Bay study site is on the Atlantic Coast of North America currently includes approximately 7900 ha of wetlands and close to 2500 ha of salt marsh, mostly covered with Spartina alterniflora (Fig. 1). These wetlands are typically grouped into the West Bay, Middle Bay, and East Bay. These bays lack distinct river deltas, but have meander streams with point bars and the sediments range from fine-grained sands to silts and clays. The study location is at the high end of micotidal, with a range of approximately 1.8 m and two cycles per day. Tidal exchange with the Atlantic Ocean flows through the East Rockaway Inlet and Jones Inlet, where both ebb-tidal and flood-tidal bars are found as is typical of tidal inlets (Biggs 1982).
Starting with colonization in the seventeenth century and continuing into the 1950s, the Hempstead Bays and their watersheds have been altered in many ways, deepened with borrow pits, crossed by navigational channels, and often removed when dredging supplied fill. The fill was frequently used to cover sections of salt marsh for use as roadways, housing, and industrial areas (Browne 2011).
Photographic Data Sets Used in This Study
A series of 13 sets of aerial photographs covering 86 years were used, including the years 1926, 1950, 1956, 1966, 1973, 1978, 1983 1989, 1994, 2000, 2004, 2007, and 2012. Ortho-referenced photographs were obtained from the New York State Office of Technology (NYS Department of Technology) for the years 1994–2007. NOAA Hurricane Sandy assessment images from November 2012 were also used in this study (http://storms.ngs.noaa.gov/storms/sandy/). Images of survey maps from 1879 and 1880 (US Coast and Geodetic Survey Reg. No. T-1471 and T-1538) were downloaded from the Stony Book University Library online map collection (http://digital.library.stonybrook.edu/cdm/landingpage/collection/limaps). Data traced from these survey documents were also made available by the New York State Department of Technology. Older photography (1926–1989) were from photographic prints from the archives of the Town of Hempstead Department of Conservation and Waterways that were scanned at high resolution and then referenced to match the 2000 and 2004 ortho-photographs using Blue Marble Geographic Geographic Transformer® Version 6.0 (Blue Marble Geographics Incorporated). Aerial photography from 1956 to 1989 were prints from individual photographs from aerial surveys and referenced well to submeter accuracy. Available photography for 1926 and 1950 were re-photographed composites that had therefore lost some detail and exhibited the spherical aberrations of the component prints. Accurate referencing for the 1926 and 1950 sets required digital subsetting for the retrieval of individual images before referencing.
A reference outline of the marshland’s outer edges was created from the 1994 images and 500 points were then randomly chosen along edges using a Python script (Fig.2). Measurements of change were made between the year of a photograph and the 1994 reference line and changes between various combinations of years were calculated from those measurements (Browne 2009, 2011).
The response variable for statistical tests was the change in the location of the marsh edges between specific years, with changes between1966 and 2007 used for most comparisons. A second response variable is the annualized change in a channelized edge over the intervals between each pair of photographic sets to be regressed against the age of the edge, estimated as the time interval from the middle of each interval to the date of the oldest photo containing a particular channelized edge. Code written in R (R Development Core Team 2009) estimated the age of subsequent measurements for each sample point along channelized marsh edges, producing an approximate ages for each location the hypothesis of stabilization through time could be explored.
Boat traffic was ranked by relative levels of activity and potential wake impact on wetlands from high (A) to low (E) and none (X), although this report does not focus on boat traffic per se (Table 1; see Electronic Supplemental Information for categorization detail). Categories of channelized edges (DT for dredged through) and natural edges were made independently.
Identification of channelized edges was primarily through historical data, derived by comparing pre- and post-construction spatial data. Channelized edges on the remaining marshes are of direct anthropogenic origin, intentionally created as part of some major construction project prior to legal protection for these wetlands. These edges were usually straight and deeply cut, marking the sharp boundary where the damage to the marsh occurred. For example, the marshlands were surveyed by the US Coast and Geodetic Survey in 1879 and 1880 provided a comparison with the photography from 1926 and later, aiding in the identification of channelized edges and the locations of older inlets.
Statistical analysis and graphical representations of trends were done in the R environment (R Development Core Team 2009). The response variable was in meters of marsh loss and independent variable in number of years, with these units retained to aid in interpretation of loss rates. Because the retained untransformed response variable was non-normal, non-parametric Mann-Whitney tests (aka unpaired Wilcoxon) with continuity correction for paired comparisons were performed using the wilcox.test() function in R. When multiple tests are performed that are not independent, type I error becomes more likely and false discovery rate control is required (Benjamini and Hochberg 1995). The recommendations of Benjamini and Hochberg (1995) were employed to adjust down the critical P value for significance when interpreting Mann-Whitney tests. Box plots show the median as a bold horizontal line with the first and third quartiles defining the box. The “whiskers” of the box plots are defined as 1.5 times the inter-quartile range or the maximum or minimum if 1.5 range is not exceeded. Points exceeding 1.5 the inter-quartile range are plotted individually. Notches in box plots are calculated as plus and minus 1.58 times the inter-quartile range divided by the square root of the number of samples and were developed by Tukey to visualize approximate significance when notches do not overlap (Crowley 2007, pp.154–157). Violin plots are box plots marking the median, upper and lower quartile of data, and Tukey notches, but also illustrate the range and the distribution of data points. Additionally, the channelized edges were mapped against 2011 bathymetry (R. Flood, Stony Brook University) to illustrate additional patterns that may explain causality. Methods used for additional supportive information, including sediment analysis and modeled tidal flows, can be found in the Electronic Supplementary Material.
Edge change data from 1966 to 2007 were collected for 30 points that fell on channelized marsh edges and 408 points that fell on natural marsh edges. The change in location of the marsh edge between 1966 and 2007 for measurement points located along channels created by dredging was compared to the change observed for those points along natural marsh edge is described in Table 1. On average, the edges of marshes that were channelized retreated horizontally by 27.52 (±3.82) m while those points on natural edges of marsh retreated on average 8.38 (±0.76) m, and these differences were highly significant using a Mann-Whitney U test (P < 0.001, n1 = 408, n2 = 30; Table 2). A box plot with Tukey notches illustrates the large difference between channelized and natural edges (Fig. 3).
To take into account the potential influence of wind-driven waves due to waterway width, a subset of measurement points for both categories with widths within the range typical for the channelized edges (76 to 400 m) was required (Fig. 4). Along these similarly sized waterways, channelized marsh edges retreated horizontally by an average of 29.41 (±4.19) m while natural edges retreated on average 10.62 (±1.18) m (Table 3), and these differences were highly significant using a Mann-Whitney U test (P < 0.001, n1 = 177, n2 = 26).
This analysis was repeated and was further restricted to a subset of measurement points on channelized marsh edges that were also along navigational channels so as to better control for vessel traffic. In this case, the channelized marsh edges retreated horizontally by an average of 30.05 (±4.21) m while those points on natural edges of marsh facing similarly sized navigational channels retreated a mean distance of 13.59 (±1.21) m (Table 4, Fig. 5). Again, there was a significant difference between these two groups using a Mann-Whitney U test (P < 0.001, n1 = 100, n2 = 25).
To control for differing vessel use, channelized and natural edges of similar width (75–400 m across) were further subdivided by vessel use categories (Table 5) and are illustrated in a violin plot (Fig. 6). The results of Wilcox tests are in Table 6. Given the small number of measurement points for some categories, this test had relatively low power, yet significant difference were still found between the highest use channelized edges (A and B) and the lower use natural edges (B through E). Marsh edges channelized between 1890 and 1966 (Fig. 2) showed higher loss rates than all categories of natural marsh edges during the same period (Fig. 7), and the loss of marsh edge over 81 years, relative to the 1994 reference edge, shows little indication that the loss of marsh from channelized edges had slowed through time (Fig. 8). Loss along channelized edges was consistently greater than natural edges of marsh along all classes of channels.
When comparing changes in marsh surface with 2011 bathymetry, it was discovered that some artificially created channels that had provided shorter routes to and from inlets for tidal flows had expanded in width beyond their original size, i.e., the Reynolds Channel (Fig. 9), State Boat Channel, and Swift Creek. Hydraulic radii for a channelized section of the Reynolds Channel had also increased and were estimated to be 1.50, 4.38, and 6.10 m for 1926, 1950, and 2012, respectively (see Electronic Supplemental Material). Sediment samples were obtained from the Reynolds Channel (Fig. 9), and grain size results were used to calculate the critical depth-averaged flows for initiation of sediment movement. When these results were compared with modeled depth-averaged peak tidal flows for each sampling location, sediment movement during peak tidal flows was found to be likely (see Electronic Supplemental Material). Other created channels that were orthogonal to tidal flow were filling (i.e., Sea Dog Creek), consistent with an interaction between the channelizing of marsh edges and the relative direction and strengths of tidal flows.
Little evidence of stabilization through time was found. The linear model regressing the annualized losses for each location against the estimated age at the time of measurement was not statistically significant and explained virtually none of the variance (Fig. 10). The relative lack of stabilization through time is also demonstrated by comparing the median annualized rates for edges with less than 40 years of recovery since channelization (−0.384 m year−1) to those with more than 40 years of recovery (−0.359 m year−1), results that are virtually identical.
This study confirmed that channelized edges of marshes can have significantly more erosion than channels retaining natural edges, even after accounting for boat traffic. Within the study site, 16.5 ha of marsh were lost along these channelized areas between 1983 and 2004. This represented a total of 15.2% of the 108.6 ha of marsh lost in the Hempstead Bay during this period, even though marsh islands possessing at least one channelized edge comprise less than 7% of the total marshland edge. Edges that were channelized retreated an average of 27.5 m over the 51-year period from 1966 and 2007, compared to a mean retreat of 8.4 m for other marsh edges. Channelized edges, therefore, lost marsh area at a rate 3.25 times faster than that seen along other types of edges. Channelized areas in the study estuary were not typically created primarily as navigation channels; however, channels created specifically for navigation in other estuaries may sustain similar or even additional impacts. Prior studies of navigational channels have focused on the effects of vessel traffic rather than the origin of the channel (e.g., Price 2006; Davis et al. 2009); thus, it is difficult to determine to what degree the rate of marsh loss documented in other studies were primarily from boat traffic or due to other influences, including lasting effects from deliberate cuts through the marsh.
Contrasting with expectation, the erosion after channelization did not seem to slow after the initial removal of marsh, but continued with higher rates for at least 50 to 80 years after the initial damage (Fig. 7). Strong tidal currents alone will drive patterns of erosion and redeposition (meanders) in tidal wetlands (Biggs 1982; Kearney et al. 1988; Kleinhans et al. 2009), resuspending and removing sediment from the marsh (Wang 2002; Larsen et al. 2009). Altered hydrology induces continuing shifts in tidal flows end river courses, and therefore neighboring wetlands, by altering sediment transport (Teal 2001; Renfro et al. 2010), and even the local tidal range may also be affected (Swanson and Wilson 2008). This study demonstrated that, at least in some cases, rerouted tidal flows may lead to accelerated sediment removal, meanders, and the growth of a created channel far beyond its original constructed cross section, leading to large continued wetland losses. Additional studies with more sample points, different tidal regimes, and longer time intervals may be needed before patterns in the deceleration of erosion rates can be fully documented along altered tidal channels.
To our knowledge, this is the first study that contrasted navigational channels that retained natural edges with those constructed with channelized edges. The degree to which the results of this study may be applied to other locations may depend on the construction of vessels and local hydrological conditions. Large cargo ships in narrow channels will create strong local displacement currents as water from ahead of the ship moves around the ship (Davis et al. 2009); back-flow effects are only noticeable if the displacement of the ship is large relative to the volume of the channel and not found with small surface planing boats. While some studies have concluded that vessel passage can cause erosion by creating short period waves and their own currents that resuspend sediment in lakes and rivers (Dorava and Moore 1997; Hofmann et al. 2008; Hofmann et al. 2011), other studies that have considered confounding factors have concluded that in those cases, boat use was a comparatively minor factor in the loss of marshlands (Zabawa and Ostrom 1980; Houser 2010). Management efforts focused only at reducing wakes from boats in channels may therefore fail when high water flow rates, natural meander dynamics, wind-driven waves, channelized edges, or other factors are the dominant causes of erosion.
The practice of dredging channels directly through marshlands, or into the edges of marshland, is no longer allowed in most parts of the USA; thus, new damage of this type is not expected to be widespread in future years. We suggest that wetland management programs in other locations should also take steps to prevent this type of damage to valuable marshes. However, the results of this study indicated that simple legal protection from additional new damage to marsh edges was insufficient for stemming marsh loss from channels that were cut decades ago. Efforts to slow or stop the continued loss of marsh areas that have been channelized in the past will likely require new stabilization or restoration methods wherever the cutting of channels through wetlands has occurred.
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I particularly want to thank Dianna Padilla for her help and support through this work and Ronald Masters for his support when applying for grants and implementing the data collection. People who have contributed their effort and skills directly to this project by assisting with referencing photographs and mapping the edges include Jonathan Ciappetta, Richard Chlystun, Rory Eblen, Karen Eichelburger, Elizabeth Gonzales, Margaret Gotsch, Ryan Mayer, Kevin Medrano, Alexander Mintz, Kerry Muldoon, Stephen Naham, Tina Scharf, Sharon Sclafani, and Kenneth Ullrich. Thanks to Jeffery Herter of the New York Department of State Division of Coastal Resources for the use of traced outlines from the Coast and Geodetic survey maps 1471b, 1538a, and 1538b. Thanks to Dr. Roger Flood, Stony Brook University School of Marine and Atmospheric Science (SoMAS), for the use of his 2011 bathymetry, Charles Flagg and Robert Wilson, also from Stony Brook University SoMAS, for the use of results from their Great South Bay hydrological modeling project. Partial funding was provided by the New York Department of State Division of Coastal Resources for matching grant no. T006429 for a trends analysis of the salt marshes within Hempstead Bay awarded to and matched by the Town of Hempstead Department of Conservation and Waterways. We would also like to thank the anonymous reviewers for their helpful suggestions.
Communicated by Carles Ibanez Marti
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Browne, J.P. Long-Term Erosional Trends Along Channelized Salt Marsh Edges. Estuaries and Coasts 40, 1566–1575 (2017). https://doi.org/10.1007/s12237-017-0245-y