Topography, hydrology and Spartina alterniflora growth range for restored salt marsh Elders Point East, Jamaica Bay, New York.

Transcription

1 Topography, hydrology and Spartina alterniflora growth range for restored salt marsh Elders Point East, Jamaica Bay, New York. Farshad Shafiei National Park Service, Gateway Faculty of Science 2012

2 Faculty of Science Department of Biology, Aquatic Ecology Lund University SE Lund FARSHAD SHAFIEI 1, PER CARLSSON 1, PATRICIA RAFFERTY 2 1 Department of Biology, Aquatic Ecology Lund University Sölvegatan Lund, Sweden 2 National Park Service, Northeast Region 120 Laurel Street Patchogue, NY November 2012 i

3 Contents Page Tables... Executive Summary... 1 Glossary... 2 Introduction... 3 Salt Marsh Ecology... 5 Marsh loss in Jamaica Bay... 7 Sea-level rise... 9 Possible causes of coastal marsh and islands Restoration, Elders Point East Objectives Marsh Topography Real Time Kinematic Global Positioning System (RTK-GPS) Hydrology Growth Range of Spartina alterniflora Methods Topographic and Vegetation Surveys, RTK_GPS Study Site map preparation Digital Elevation Model (DEM) Hydrologic Methods HOBO Water Level Specification Results Digital Elevation Model (DEM) Hydrology... 29

4 Tidal metrics (datums) Inundation analysis, Mapping MHHW and MLHW inundation Growth Range of S. alterniflora Relationship of the S. alterniflora to tidal metrics Discussion Bibliography... 41

5 Tables Table1.Total area of vegetated marsh island in Jamaica Bay (JBWPPAC, 2007; Christiano, 2010)... 7 Table 2. Average annual rates of vegetated marsh island loss in Jamaica Bay (JBWPPAC, 2007; Christiano, 2010)... 7 Table 3. Cross Validation result from ordinary Kriging from the training subset Table 4. Cross Validation result from ordinary Kriging from the training subset Table 5. Location of the tidal gauges in study area Table 6. Evaluation of the DEMs through Cross-Validation and logical test for each dataset are presented Table 7. The spring high tides happening during lunar cycle for each tidal gauge during the time frame of the project Table 8. The table shows how frequent and how long, the different elevation of the marsh gets inundated. For example, inundated elevation higher that NAVD 88 in first column indicated how frequent and long the marsh surface higher than NAVD 88 gets flooded Table 9. The statistic calculated for S. alterniflora points Page

6 Executive Summary Coastal salt marshes are shaped through a combination of physical (i.e., sediment accumulation/erosion) and biological (i.e., vegetation) processes. They are characterized by fine sediments and halophytic vegetation. The accretion rate and elevation change has been indicated as one of the most important factors in ecology of the marshes. The inundation regime and growth range of Spartina alterniflora also play major roles in formation of the marsh and sustaining it. Sea-level rise, sediment deficiency, hydrodynamic modifications of the bay and eutrophication have been hypothesized as major contributors to dramatic salt marsh loss in Jamaica Bay, New York. This study has been motivated by the issue of marsh loss and evaluation of Elders Point East restoration project. Salt marsh plants live within a narrow elevation range that is often less than 2 m. Topographic changes of less than 10 cm have been shown to significantly influence plant community in marshes. The Real Time Kinematic Global Positioning System (RTK-GPS) was used to survey the island surface to develop the topographic model and to compare with pervious study. The elevation data were used to create a Digital Elevation Model (DEM) for the marsh using ArcGIS 10.0 Geostatistical Analysis tool. The elevation model from this project indicates that using RTK-GPS would be the best method in comparison to Light Detection And Ranging (LiDAR) data for Jamaica Bay marshes. I could achieve the overall accuracy of ±8 cm for Elders Point East, however the accuracy of LiDAR data from previous work produced ±29 cm. The extent of inundation and the tidal range need to be evaluated in order to determine the sustainability of the marsh since the vegetation growth range is depended on inundation. In order to evaluate site specific hydrology, I deployed three tidal gauges (Non-Vented Titanium Water Level Loggers) to capture 2 months water level data. The reduction process was implied according to Tidal Datums Handbook from National Oceanic and Atmospheric Administration (NOAA) to compute site specific tidal datums. The comparison of tidal range with recent studies within the bay indicates 3 cm increase in mean tidal range between 2007 and This indicates that tidal range has been increasing within the bay at the same rate with sea-leave rise (3.9 mm yr -1) since At Elders Point East the S. alterniflora upper limit and lower limit of the growth range in relation to Mean High Water (MHW) are 0.45 m and m, respectively (Growth range = 0.77 m). The site specific growth range of S. alterniflora in this study, reported elevation change and accretion rate implies that the Elders Point East will be less vulnerable with respect to sea-level rise in comparison to marshes where the plants are located at lower elevations. 1

7 Glossary CO-OPS: Center for Operational Oceanographic Products and Services. DHQ: Diurnal High Water Inequality, the difference in elevation between MHHW and MLHW. DLQ: Diurnal Low Water Inequality, the difference in elevation between MHLW and MLLW. DTL: Diurnal Tide Level, the tidal datum midway between MHHW and MLLW. GMT: Greenwich Mean Time. RTK-GPS: Real Time Kinematic Global Positioning System. Gt: Great Diurnal Range, the difference in elevation between MHHW and MLLW. LiDAR: Light Detection And Ranging. MHHW: Mean Higher High Water, the arithmetic mean of the all higher high water heights. MHLW: Mean Higher Low Water, the arithmetic mean of all of the higher low water heights. MLHW: Mean Lower High Water, the arithmetic mean of all of the high water heights. MLLW: Mean Lower Low Water, the arithmetic mean of the lower low water heights. MTR or Mn: Mean Range of Tide, the difference in elevation between MLHW and MHLW. MSL: Mean Sea Level, the arithmetic mean of hourly heights observed over the National Tidal Datum Epoch (NTDE). MTL or HTL: Mean or Half Tide Level, the tidal datum equivalent to the average of MLHW and MHLW. NAVD 88: North American Vertical Datum of NGVD 29: National Geodetic Vertical Datum of NOAA: National Oceanic and Atmospheric Administration. NOS: National Ocean Service. NTDE: National Tidal Datum Epoch. STND: Station Datum. USACE: U.S. Army Corps of Engineers. UTC: Universal Time. 2

8 Introduction Coastal salt marshes are shaped through a combination of physical (i.e., sediment accumulation/erosion) and biological (i.e., vegetation) processes. They are characterized by fine sediments and halophytic vegetation. Coastal marshes provide habitat for migratory birds, transient fisheries species and native flora and fauna, as well as storm flow protection (Reed, 1990). Less than 10% of the United States land mass is coastal land; however more than half of the nation population lives and works on the coastal lands (Reed, 2002). That population density has contributed to deterioration of coastal marshes in several ways. Jamaica Bay is a coastal ecosystem in which rich biological habitats have been altered dramatically by human developments. The Bay is located within the Boroughs of Brooklyn and Queens, New York City, and Nassau County, NY. The Bay encompasses 67.3 square kilometers and opens into the Atlantic Ocean via Rockaway Inlet. The bay includes tidal salt marsh islands, fringing marsh, upland habitat, mud flats, and tidal creeks. In term of development and infrastructures, the bay includes navigational channels, recreational area, landfills, urban communities, business and retail services, and J. F. Kennedy International Airport. In the early 19th century, Jamaica Bay was characterized with large areas of tidal salt marsh (Messaros et al., 2012). Jamaica Bay has been distinguished for its plentiful and diverse shellfish and ecological function as a nursery and feeding source for several bird species (JBERRT, 2002) and various fish species rely on the bay for habitat (USFWS, 1997). Jamaica Bay plays an important role during seasonal migration of for various bird species (NYCDEP, 2006). Most of the Jamaica Bay ecosystem is within Gateway National Recreation Area, a unit of the National Park Service, and is connected to the lower bay of New York Harbor by the Rockaway Inlet (Figure 1.). The Jamaica Bay Federal navigation channel extends from offshore of Rockaway Point, Queens, through Rockaway Inlet and intersects at the southern edge of Floyd Bennett Field (Barren Island), Brooklyn (Figure 2.). The main longshore drift is to the west along the south shore of Long Island on the Atlantic Ocean (Kana, 1995) and has increased the length of the Rockaway peninsula since the early 19 th century (Englebright, 1975). Historically the westward Rockaway peninsula has stretched out which subsequently jetties were constructed in order to stabilize it. This stabilization may have reduced sediments supply into the bay. In addition, the widespread twentieth century urbanization of Long Island may have eliminated upland sediment sources, as well as overwash deposits from storms (Hartig et al., 2002). Renfro, et al., 2010 states that sediment deficient supply to the marsh surface is less likely to be the cause of marsh loss in Jamaica Bay. They suggest that other factors may be responsible for the failure of marshes to increase their elevation parallel to sea level rise. Other reasons include eutrophication of the water and H 2 S build-up in the marsh peat pore water. Tidal range has increased followed by an increase in water depth, such as that caused by dredging of navigation channels and modification of the hydrodynamics (Swanson et al., 2008). This may further increase tidal currents and worsen erosion. As a result, the marsh hydro-period could be influenced and plants get inundated for a longer than prior to dredging of the channels in Jamaica Bay. 3

9 Figure 1. Gateway National Recreational Units. Map produced using Gateway GIS data sources. Figure 2. Jamaica Bay Unit, New York. Map produced using Gateway GIS data sources and satellite imagery taken by Bing Maps. 4

10 Salt Marsh Ecology Separate zones of salt marsh vegetation forms in response to several of biophysical factors (Hartig et al., 2002). Species composition at lower elevations is mainly governed by physical and chemical factors. However, at higher elevations, interspecific competition affects the plant community (Bertness, 1991). Along the Atlantic Coast, the main plant species of the low marsh intertidal zone Spartina alterniflora (salt marsh cordgrass) play a significant role providing food and habitats for wildlife and physical formation (for peat accretion) to the marsh (Hartig et al., 2002). The high marsh species Spartina patens (salt hay) take over at MHW (Bertness, 1991). High marsh portion of the intertidal zone gets inundated less frequently and S. patens rarely occurs in the low marsh, where oxygen flow to its rhizomes becomes limited by regular flooding (Hartig et al., 2002). In contrast, S. patens competition restricts S. alterniflora from the high marsh. Salicornia virginica (glasswort) can also be present in the low marsh (Bertness et al., 1987). Although all of these plants plant species are adapted to saline environments, in terms of botany, the high marsh is much more diverse than the low marsh (Hartig et al., 2002). Species such as Juncus gerardii and Distichlis spicata grow in less inundated high marsh zone. Species location is governed mainly by frequency of tidal inundation (Bertness, 1991). Changes in salt marsh plant zonation are significantly correlated with inundation time and zonation which can be used as an indicator for sea-level rise (Hartig et al., 2001b). Salt marsh vegetation respond to sea-level rise by shifting to low marsh, to coastal shoals, and finally to mudflats, and also by migrating inland (Hartig et al., 2001b). The accretion rate and elevation change has been indicated as one of the most important factors in ecology of the marshes. The definition of accretion can vary a bit. The accretion is a measure of deposition on the marsh due to mainly surface processes (deposition /erosion) (Cahoon et al., 2012). The material accumulated on top of the marker horizons (feldspar layer) is primarily due to the processes going on at the surface (Figure 3.). The elevation change is measured by the Surface Elevation Table (SET) as the net elevation change of the marsh surface to all the processes occurring down to the bottom of the SET benchmark (Figure 4.). This would include accretion (surface processes) and belowground processes like decomposition, compaction, dewatering, root growth, etc (Cahoon et al., 2012). The SET rate is a slightly different number from marker horizon but is more relevant since it incorporates all the processes occurring in the soil profile. 5

11 Figure 3. from right, sampling marker horizons using Cryogenic Coring by James Lynch in JoCo during the monitoring salt marsh development processes at Jamaica Bay and me measuring the SET height (May, 2012). Figure 4.from right, feldspar marker horizon from Elders Point East during the monitoring salt marsh development processes at Jamaica Bay (May, 2012). Measuring a "cryo core" (Cahoon, et al., 2012). 6

12 Marsh loss in Jamaica Bay Historically Jamaica Bay was less water than land, but the area of vegetated emergent marsh islands in the bay has decreased dramatically (JBWPPAC, 2007). In 1907, Jamaica Bay comprised 9979 ha in total in which 3430 ha was covered by water and 6549 ha marsh islands (Englebright, 1975). Human modification such as dredging or filling can be the cause for most of the fringing marsh degradation in Jamaica Bay prior to early 1970 th (Black, 1981). Excluding areas affected directly by dredging and filling, only ha remained by 2008 from the 950 ha of vegetated marsh island in the bay in 1951 which indicate there have been other factors contributing to the marsh loss after 1970 th (Table 1). During that 57 year period, 66.5% of the salt marsh islands within the bay were changed from emergent vegetated habitat to submerged and intertidal habitat (JBWPPAC, 2007; Christiano, 2010). The calculated average rate of marsh loss increased during that time period from 6.9 ha y -1 ( ) to 13.4 ha y -1 ( ) (Table 2) (JBWPPAC, 2007). Recent analysis ( , Figure 5.) indicates that the rate of loss may be decreasing to 7.7 ha y -1 (Christiano, 2010). By analysis of aerial photographs, the New York State Department of Conservation (NYSDEC, 2001) estimated that nearly 567 ha of tidal salt marsh island within Jamaica Bay have been gone since 1924, with the rate of loss dramatically increasing in recent years. Table1.Total area of vegetated marsh island in Jamaica Bay (JBWPPAC, 2007; Christiano, 2010) Time Period 1951* Vegetated Marsh (ha) *From 1951 to 1974, 23 ha of marsh island were estimated as lost because of the building of West Pond and 115 ha vanished as a result of the Broad Creek and Goose Pond marsh impoundments. The loss of the remaining 161 ha has been due to other contributing factors. Table 2. Average annual rates of vegetated marsh island loss in Jamaica Bay (JBWPPAC, 2007; Christiano, 2010) Time Period Average rate of loss (ha year -1 )

13 Figure 5. Salt marsh change analysis in Jamaica Bay. The yellow area shows the restored salt marsh Elders Point East (Study location of current study. The analysis and map produced by Christiano, 2010 (GIS specilist in Gateway). 8

14 Sea-level rise The mean sea level or the average level of tidal waters is known as the term sea level, usually calculated during about a 19 year period. These metrics generally show the water level relative to the land, and thus integrate changes in the elevation of the land (i.e., subsidence or uplift) as well as absolute changes in sea level (i.e., rise in sea level caused by increasing its volume or adding water) (CCSP, 2009). Two different terms are used by scientists for clearness (CCSP, 2009): - Global sea-level rise refers to the average increase in the level of the world s oceans as a result of several factors, the most important being thermal expansion of the oceans and the addition of water by melting of ice sheets, ice caps, and glaciers. - Relative sea-level rise refers to the change in sea level relative to the altitude of the contiguous land, which can also sink or rise due to natural and human-induced factors. Relative sea-level changes comprise both global sea-level rise and changes in the vertical elevation of the land surface. In U.S. Climate Change Science Program report (CCSP, 2009) an evaluation was made from implication of three relative sea-level rise predictions over the next century developed from a combination of the twentieth century relative sea-level rise pace and either a 2 or 7 mm yr -1 increase in global sea level: Scenario 1: the 20 th century rate, which is generally 3 to 4 mm yr -1 in the mid-atlantic region (30 to 40 cm total by the year 2100); Scenario 2: the 20 th century rate in addition 2 mm yr -1 increase of rate (50 to 60 cm total by 2100); Scenario 3: the 20 th century rate in addition 7 mm yr -1 increase of rate (100 to 110 cm total by 2100). The twentieth century rate of sea-level rise is the regional long term pace of relative sea-level rise that has been measured at NOAA tide gauges in the mid-atlantic study area. First scenario evaluates the impact if sea-level rise in future happens at the same pace as was measured during the twentieth century at a specific region. First and second scenarios are inside the range of those reported in the recent IPCC Report Climate Change 2007: The Physical Science Basis, particularly in the chapter Observations: Oceanic Climate Change and Sea Level. Third scenario is in agreement with higher approximations suggested by latest studies. Tide-gauge observations from New York to North Carolina show that relative sea-level rise (the combination of global sea-level rise and land subsidence) rates were higher than the global average and generally varied between 2.4 and 4.4 mm yr -1 (CCSP, 2009). The majority of the Atlantic Coast experience higher rates of sea-level rise (2 to 4 mm yr -1 ) than the current global average (1.7 mm yr -1 ). To a degree due to the latest global warming and to regional subsidence resulting from crustal readjustments to the removal of ice following the last glaciation Regional SLR rate exceed the mean 20 th century global SLR of 1.7 mm yr -1 (Gornitz et al., 2001). Recently, the IPCC Fourth Assessment Report (IPCC, 2007) estimated that global sea-level is likely to rise 18 to 59 cm over the next century; however, possible increased melt-water contributions from Greenland and Antarctica were not considered (IPCC, 2007). 9

15 Possible causes of coastal marsh and islands There has been assumption regarding the causes of the wetland losses in Jamaica Bay. For instance, Hartig et al., 2002 indicated the sea-level rise and sediment deficient essential for marsh accretion, and physical modification (both natural and those due to dredging and filling). However, a pollution impact was suggested by other study (Kolker, 2005). With regard to the physical alteration, the New York City Department of Environmental Protection (NYCDEP, 2006) indicate that the volume of the bay has increased 350% while the surface area of the bay has been reduced from 101 km 2 in the mid-nineteenth century to 53 km 2. Inundation, including sea-level rise, is assumed result in expansion of interior marsh island tidal pools, reduction in vegetation density, demolition of the peat root system, erosion and collapsing the marsh platform (Hartig et al., 2002). Considerable amount of sewage effluent ( L/d) have been discharged into the bay (NYCDEP, 2006) which contribute to eutrophic conditions in deeper parts at times during the summer. Kolker (2005) hypothesizes that the released hydrogen sulfide in such condition will diminish the marsh vegetation. Diminished root production can also lead to a loss in marsh elevation (Mendelssohn et al., 2002). Lower subsidence has been found in a vegetated marsh compared to nearby pools without vegetation (Erwin et al., 2006). Marsh degradation follows the weakening and collapse of peat along the perimeter of marsh islands, broadening of tidal creeks, and the expansion of intertidal pools within the marsh (JBWPPAC, 2007; Hartig et al., 2002). Browne (2011) studied the factors that influence the collapse of the edge of Spartina alterniflora salt marshes, focusing on Hempstead Bay, the westernmost bay of Long Island's South Shore Estuary reserve. He indicated that the modified edges by dredging continued to lose marsh at a high rate long after the primary modification (Figure 6.). In addition, there was a significant correlation between the distance of the marsh to borrow pits and marsh loss (Browne, 2011). He indicates that urbanization and increased boat traffic after 1966 are significantly correlated to marsh loss in Hempstead Bay. A number of natural factors were also associated with marsh loss, including having a large fetch and storm impacts and tidal flow rate (Browne, 2011). However, he found no correlation between increased nutrient load and marsh loss or gain. Probably, several of the above, if not all, have played significant role to the marsh losses in the bay (Swanson et al., 2008). Sea-level rise has been indicated as possible contributor; however, marsh losses on Long Island are not happening at anywhere about the same rate in contiguous and nearby bays for example Moriches Bay, Hempstead Bay and Great South Bay (Swanson et al., 2008). There has been a gradient of marsh loss west to east, with the greatest losses in the south shore of Long Island in the west where the Jamaica Bay is located (Kolker, 2005). He suggests that the less marsh loss in east could be partially due to decreased development. In long run, relative sea-level rise in all of these bays are experiencing about the same rate (2.77 mm yr -1 ) as measured at the Battery in New York City (NOAA, 2012 Sandy Hook). Another aspect of sea-level rise is the increase in tidal range within the bay due to physical modifications such as dredging and filling for navigational improvements and other development projects (Swanson, 2002). At some locations in Jamaica bay, Swanson, et al (2008) suggest that the actual water level over the marshes at high tide resulting from modifications in tidal hydrodynamics is as severe as that due to the increase in sea-level rise that occurred during last 100 years, mainly so during spring tides. 10

16 Within the bay the low marsh has accreted at 8 mm yr -1 and high marsh at 5 mm yr -1 (Zeppie, 1977). New York coastal salt marsh accretion generally can keep up with present rates of sealevel rise (Hartig et al., 2001a), however they suggest that the accretion rates specifically for Jamaica bay from Zeppie, 1977 have gone through changes as a result of significant difference in the degree of development projects in bay between 70 th and recent years. So, this rate may not reflect the current actual rate of accretion in Jamaica Bay marshes. The reported elevation change and accretion rate for Elders Point East measured with Surface Elevation Table (SET) and marker horizons have been 4.4 mm yr -1 and 5.5 mm yr -1,respectively (Lynch, 2012). The rate of local sea-level rise in Jamaica Bay has been around 3.9 mm yr -1 as determined by tide-gauge data ( ) from Sandy Hook station (NOAA, 2012 Sandy Hook) in comparison to current global average (1.7 mm yr -1 ). Sea-level rise may cause marsh loss in the future (Hartig et al., 2002); but, marsh loss over the past century is not correlated to sea-level rise (Kolker, 2005). Analysis by Hartig et al., (2002) shows that over the next 80 years, present rates of accretion would only be sufficient to sustain Jamaica Bay marsh islands under the most conservative predictions for future sea-level rise. Figure 6. The erosion is shown along the marsh edge, exposing underlying peat layers. This illustrates a transitional stage in the transformation of low marsh to mud flat. (a. JoCo marsh, May 2012), (b. tidal channel at Yellow Bar Hassock, photo from Hartig, et al., 2002). 11

17 Restoration, Elders Point East Marsh restoration, by increasing elevation through the addition of sediment to the marsh surface, is one tool that the National Park Service has employed to understand and manage marsh loss in Jamaica Bay. The focus of this study will be the Elders Point East marsh located within Jamaica Bay, New York (Figure 7.). The geographic coordinate of the marsh is (40 38'13"N, 73 50'50"W). Elders Point is currently comprised of two discrete islands, Elders Point East and Elders Point West that together total about 4.9 ha prior to the restoration project led by the U.S. Army Corps of Engineers, NY District in 2005 (Messaros et al., 2012). Elders Point was historically one island with an area of roughly 53.4 ha but over the last more than 80 years, marsh loss in the middle of the island split the connection creating two discrete islands separated by mud flat (Messaros et al., 2012). Restoration construction of 15.7 ha of salt marsh island at Elders Point East was initiated in June 2006 with the placement of 190,066 m 3 of clean sediment (95% or greater sand).the restoration design provided for the placement of dredge material to establish an elevation appropriate for the growth of salt marsh vegetation. 9.7 ha was filled, graded, and planted in In addition, waterfowl barrier was erected in 2006 to protect the newly planted vegetation. Fill was placed in the remaining 6 ha in 2006; however final grading, planting and the erection of waterfowl barrier on that portion of the project were not completed until the spring of Plugs of S. alterniflora were planted at 0.3 m spacing at design elevations of 0.46 to 0.76 m above mean sea level. Along the perimeter of the project, vegetation was planted on 0.3 or 0.46 m centers with quart pots of S. alterniflora. Quart pots were used to provide greater initial biomass and to facilitate root development and subsequent sediment stabilization along the perimeter of the project where wave energy and winter storm damage was anticipated to be greatest. All vegetation planted in 2006 was fertilized with 18:6:11 Osmocote slow release fertilizer at a rate of 15 g per plug and 30 g per quart pot. The site was also designed to include approximately 0.6 ha of high marsh. At design elevations of 0.76 m above mean sea level and higher, plugs of S. alterniflora and D. spicata were planted with bare root S. patens. All three species were planted in a single hole on 0.46 m centers. Since the D. spicata plugs were field collected (S. alterniflora plugs were grown from seed), the plugs often contained other high marsh species (Symphyotrichumt enuifolium and Salicornia europea). Only S. alterniflora plugs and quart pots (around the perimeter) were planted in In addition, with the exception of a 0.6 ha experimental treatment on the southeast side of the island, vegetation planted in 2007 was not fertilized. In addition to the planted components of the restoration design, approximately 2 ha of existing S. alternifora hummocks were selectively filled. Sediment fill was placed between the existing hummocks to increase the sediment elevation between the hummocks to approximately the level of the hummocks. Design elevations of the surrounding fill areas were graded into the select fill areas. During construction, some existing vegetation had to be excavated and relocated. These hummocks were removed with intact root system and benthic communities by a bobcat and immediately placed, at design elevation, in areas that had been filled to the design specifications. The relocated hummocks were spaced on approximately 10 m centers over 2 areas totaling approximately 0.4 ha. Furthermore, the volume of sediment available for restoration construction was not adequate to meet the project design. As a result, the area of the project that was planted in 2007 was not built to the full design elevations. In addition, much of that area was designed to be select fill; however, no sediment was placed within most of that select fill area. 12

18 A comprehensive monitoring and adaptive management program has been implemented at Elders Point East to determine factors contributing to the success or failure of the restoration, test various Spartina planting techniques, justify adaptive management actions, and better understand factors contributing to marsh loss throughout Jamaica Bay. Monitoring was initiated prior to restoration (2005) has continued annually through Monitoring metrics include vegetation, nekton and benthic species composition and abundance, marsh surface elevation and sediment accretion, marsh surface topography, and habitat change. Additional vegetation metrics include stem density, stem height, belowground production, and total above- and belowground biomass. 13

19 Objectives This study expands upon the monitoring that has been conducted at the Elders Point East marsh restoration project. Specifically, for the Elders Point East marsh, this study seeks to develop a Digital Elevation Model for the marsh surface, to determine the growth range of S. alterniflora, and to evaluate the hydrology of the restored marsh, Elders Point East. Marsh Topography Information on marsh elevation is important to coastal managers, particularly for flood inundation mapping, coastal hazard assessments and modeling sea-level rise. Development of a Digital Elevation Model (DEM) requires accurate elevation data. Salt marsh plants live within a narrow elevation range that is often less than 2 m (Hladik et al., 2012).Topographic changes of less than 10 cm have been shown to significantly influence plant community in marshes (Silvestri et al., 2005). Over the recent years, many investigators have used Light Detection and Ranging (LiDAR) to obtain information about ground elevation and vegetation pattern. LiDARderived DEMs can be effective at representing surface elevations in some environments, creating a high-resolution topographic data set of the marsh; however, studies examining LiDAR- derived DEM accuracies in S. alterniflora marshes have reported errors. DEMs have been found to overestimate marsh ground elevations with a mean error of 0.07 to 0.17 m, and these errors have been found to increase with both increasing vegetation density and plant height (Morris et al., 2005). Previously, National Park Service attempted to obtain marsh elevations from existing LiDAR data; however, that data set provided no penetration within shallow water habitats (marsh pools and intertidal mudflats) and lacked multiple returns (necessary for determination of bare earth elevation) in the dense unstratified salt marsh vegetation (August et al., 2009). The LiDAR data set also lacked coverage in many areas of the Bay due to Federal Aviation Administration constraints on overflight in proximity to J.F.K. International Airport (August et al., 2009). In addition, the accuracy of LiDAR data (± 29 cm) is not sufficient (Cahoon and Gutenspergen, 2010; August et al., 2009). Validation of LiDAR vertical accuracies in salt marshes was conducted by using a network of Real Time Kinematic Global Positioning System control points. The technology was evaluated for cost-effectiveness versus detailed ground survey, and usefulness in salt marsh restoration projects (Hladik et al., 2012).The result from their study (Hladik et al., 2012) conclude that these forms of corrections can significantly improve the accuracy of LiDAR- derived DEMs in salt marshes and more highlight the importance of accuracy assessments before DEM data are used, especially in environments such as salt marshes where small differences in elevation can have major effects on inundation patterns and vegetation community. 14

20 Real Time Kinematic Global Positioning System (RTK-GPS) RTK-GPS makes use of carrier phase measurement of the GPS signal. Basically, it represents real-time implementation of differential correction (Gao, 2007). RTK-GPS heights result in the accuracy of around ±10 cm, but can be more accurate in open area (Schmidt et al., 2003), such as the reported ±5.3 cm at the 95% confidence level (Featherstone et al., 2001). This level of accuracy has provided applications in offshore and land environments demanding real-time measurements. The RTK system derives the coordinates of a remote point by reducing carrier phase data over a GPS baseline between the reference (base) station and the remote point. The RTK base/reference point doesn t need necessary to be visible and may be 1.5 km distant from the project site. Advantages of the RTK-GPS system are that it is mobile, collects data quickly, and measures elevation with reasonable accuracy. Since the overall objective of the previous work with LiDAR data (August et al., 2009) in Jamaica Bay couldn t meet the required accuracy, the current study was implemented using RTK-GPS surveys for collecting site specific elevation data at Elders Point East. The idea is to test how accurate the elevation model could be by this method and if it is a good method for Jamaica Bay considering constraints with LiDAR data. 15

21 Hydrology Understanding of interaction between site specific hydrology, topography and vegetation is crucial for coastal marsh sustainability. Previously, there wasn t any site specific hydrology data for Elders Point East. In this project, I used three tidal gauges to record the water level data, so later I could use to develop site specific hydrology and inundation analysis. The tidal modulation for the study area, Elders Point East follows the semidiurnal tidal pattern which is composed of tidal metrics Mean Higher High Water (MHHW), Mean Lower High Water (MLHW), Mean Higher Low Water (MHLW) and Mean Lower Low Water (MLLW). Duration of rise from low water to high water, and duration of fall together, on an average will be a period of hours for a semidiurnal tide. In a normal semidiurnal tide, duration of rise and duration of fall each will be approximately equal to 6.21 hours (CO-OPS, 2001). The highest tides and spring tides are produced at new and full moon. The smallest tides, neap tides, occur during the first and third quarters of the moon. Therefore, the relationship between growth range and tidal metrics was investigated. A comparison is made with similar studies to evaluate the current condition of the Elders Point East. All the tidal metrics explained below calculated based on water heights of the tide observed over a specific 19-year Metonic cycle. However, for stations with shorter series, a comparison of simultaneous observations is made with a primary control tide station in order to derive the equivalent of a 19-year value (CO-OPS2, 2003). Since the timeframe of the project was less than 3 months, so the tide data collection for Elders Point East is considered as tertiary station. The present National Tidal Datum Epoch ( ) from Sandy Hook station will be used as control for the reduction of our relatively short series through the method of comparison of simultaneous observations and for monitoring long-period sea level trends and variations (CO- OPS, 2001). 16

22 Growth Range of Spartina alterniflora Growth range is defined by the lowest and highest elevations at which salt marsh plants can survive. The plant species inhabiting in the intertidal zone are adapted to inundation and their tolerance for the frequency, period, and depth of flooding, salinity and soil oxidative state determine their position within the intertidal landscape (Cahoon et al., 2010). In other words, their vertical relationship to local sea-level is related to their position within the coast. Therefore, tidal range is an important dynamic factor establishing the vertical growth range of salt marsh plants in relative to local sea-level. There is a positive relationship between tidal range and growth range of the plant species (Cahoon et al., 2010; Reed, 2002). Marshes with a small tidal range will have a small growth range, and consequently a less possibility to build up elevation capital, compared to marshes with a great tidal and growth range. Natural capital is defined as a reserve of natural resources that contribute to the stability and flexibility of a system (Cahoon et al., 2010). Regarding coastal marsh, elevation capital is one form of natural capital which means the buildup of material supplies that have formed the elevation of the marsh within the tidal area, and may secure these ecosystems from sea-level rise (Cahoon et al., 2010). Within Jamaica Bay, S. alterniflora is the dominant plant species in low marsh habitats. High marsh vegetation within Jamaica Bay is comprised of a mix of S. patens and D. spicata with S. alterniflora, Limonium carolinianum and Syphohotrichium tenufolim. The dominance of S. alterniflora in low marsh habitats has been attributed to its ability to oxygenate the rhizosphere in anoxic soils (McKee et al., 1988). S. alterniflora occurs in distinct bands of tall and short form plants on the seaward and terrestrial borders of the low marsh, respectively and vegetation species follow a general zonation pattern across the topographical gradient from low to high marsh (Hladik et al., 2012). The variation in the vertical distribution of this species reported among marsh studies was attributed primarily to differences in mean tidal range (MTR) (McKee et al., 1988). A positive correlation between MTR and elevational growth range demonstrated that the S. alterniflora zone expands with increasing tidal amplitude (McKee et al., 1988). 17

23 Methods Topographic and Vegetation Surveys, RTK_GPS Elevation surveys were conducted in late May and early June, Each survey was completed when the marsh was not flooded (i.e. no more than 4 hours before or after low tide). A Trimble G R8-RTK base and rover system with internal radio was used for all surveys. Trimble Business Center was used to export the elevation points from RTK-GPS unit and process the elevation data. Vertical and horizontal controls were established using existing monuments and NOAA Online Positioning User Service (OPUS) static processing. Later, processed elevation data were exported to Microsoft Office Excel and eventually in ArcGIS desktop. Elevation data was collected along 33 transects spaced at 20 m intervals (Figure7.). The location of each transect was determined using satellite imagery of the area and uploaded to the RTK controller prior to initiation of the field surveys. Elevation points were collected at approximately 10 m intervals along each transect. Additional points (<10m interval) were collected to capture elevation changes that occurred within a short distance such as berms and creeks. Fewer points (>10m interval) were collected on the beach where the intertidal shoreline exhibited a gradual slope without depressions or significant topographic changes. Elevations were all positioned in the NAD 83 reference frame and projected into UTM coordinate zone 18N. RTK elevations were collected in NAVD 88 orthometric heights (in meters) computed using the National Geodetic Survey GEOID 09 (Conus). All data collection and analysis have been done in metric system (SI) and coordinate order as Northing, Easting and Elevation. RTK & Infill was used for survey style. The total area the elevation survey was 22 ha. Since the survey happened during the nesting season of birds the upland area of the island was occupied by plenty of birds and their nests. Eventually, I decided not to survey the upland (0.97 ha) in order to prevent disturbance to birds and their nests (Figure 7.). Since S. alterniflora doesn t occurs in upland, the lack of vegetation data from upland wouldn t be detrimental to S. alterniflora growth range analysis. In order to see if the lack of elevation data from upland could influence the DEM and topographic analysis, I used the upland elevation data from Topographic and Bathymetric Survey for Elder s Point East and West Island (debruin, 2005). Later, I created DEM with and without upland elevation points. The accuracy of the DEMs was similar either to include the upland elevation points or not. Cover type was identified and recorded at each elevation point. Cover type categories were: bare (absence of emergent vegetation); water (bare areas which were either in creeks, creek banks or internal pools); S. alterniflora (vegetative cover included S. alterniflora); and, other vegetation (vegetative cover other than S. alterniflora). A cover category was assigned by evaluating the dominant cover type for approximately 1m 2 areas in front of the surveyor and inclusive of the elevation point (Figure 9.). A total of 1501 elevation points and cover type attributes were recorded within the 22 ha surveyed area which were used for final DEM analysis (Figure 8). 18

24 Figure 7. Project study area; Elders Point East marsh restoration, Jamaica Bay, NY. Zone 18 North UTM coordinates are provided on each axis. The location of elevation transects are depicted by purple lines. The location of water level data loggers are indicated by red stars. The area covered in yellow indicates the portion of this study for which only unvegetated elevation data has been analyzed. The area covered in blue indicates the upland area that was not surveyed during this study. The salt marsh extent in 1951 in black line shows how the Elders Point East and West were used to connected. 19

25 Figure 8.This photo depicts the northeast shoreline of the study area and the transition (right to left in the photo) from S. alterniflora dominated cover type, across a berm to the unvegetated intertidal shoreline (bare cover type). The author is collecting data at a point with the designation of bare since the 1m 2 areas in front of the surveyor lacks vegetation. Study Site map preparation S. alterniflora points collected from Excluded area in the southern half of the island were excluded from growth range analysis of S. alterniflora; however the other types bare, water and other vegetation collected from that area were used for analysis (Figure 7.). During restoration the volume of sediment available for restoration construction was not adequate to meet the project design at this area. As a result, the area of the project that was planted in 2007 was not built to the full design elevations. In addition, much of that area was designed to be select fill; however, no sediment was placed within most of that select fill area. The shoreline border based on NAVD 88 which was representative of pre-restoration area was used to separate this part. We decided not to consider the elevation of vegetation in that specific area since it doesn t reflect vegetation response and growth range after restoration. The vegetation in that part dominantly occurs in sparse hummocks which have a significant elevation difference from the ground. Finally, a set of elevation points including 699 points (Only S. alterniflora points) was used as the base for vegetation analysis and growth range of S. alterniflora. 20

26 Digital Elevation Model (DEM) The elevation data were used to create a DEM for the marsh by applying the Ordinary Kriging method in the ArcGIS 10.0 Geostatistical Analysis tool according to Topographic mapping RTK-GPS standard operating procedures (USGS, 2012) with the following modifications. The data set was subdivided to allow for cross validation. The training subset consists of 1126 ground control points (75% of the total data set). The validation subset consists of 375 points (25% of the total data set) which was reserved for cross validation. Eventually, two DEMs were created, one from 1126 training points and the other from all 1501 ground control points. Parameters such as lag number, size and maximum neighbors were changed until to reach a lower Root Mean Square Error (RMSE) for the model. According to ArcGIS 10 help, determining the suitable lag size and lag number depends on several factors: For data points are positioned on a sampling grid, the grid spacing is typically a good indicator for lag size; however, if the data is collected using an uneven or random sampling system, the selection of a right lag size is not so clear-cut (ArcGIS10 Help, 2012). In this study, transects were evenly spaced at 20 m but points along transects weren t evenly spaced. A rule of thumb is to multiply the lag size by the number of lags, which should be about half the largest distance among all points. Also, if the range of the fitted semivariogram model is very small relative to the extent of the empirical semivariogram, you can reduce the lag size. On the other hand, if the range of the fixed semivariogram model is large relative to the extent of the observed semivariogram, you can increase the lag size (ArcGIS10 Help, 2012). By trying different lag sizes, numbers, maximum neighbors, final RMSEs and considering the data structure, I decided to set 30, 10 and 13 for lag number, lag size and maximum neighbors, respectively. These parameters were applied to the training dataset to develop a geostatitical layer that was clipped later and exported as a raster layer with the default value and 2.2 meter cell size. External Cross-Validation Cross-validation gives an idea of how well the model predicts the anonymous values in the creation of surface. In cross-validation the model exclude a point sequentially, predicts its value using the rest of the data, then compares the predicted and observed values. In a best model, the mean error should be close to zero; the RMS and average standard error should be as small as possible. The absolute value of the difference between predicted heights from the model and the observed heights (validation subset) is averaged, providing a metric of model accuracy (Equation 1.). Then, I calculated the RMSE for the validation subset. Finally, I went through a logical test for those validated points to find out the percentage of the points with prediction error calculated RMSE. This helps to understand how good the model predicts the elevation of the marsh and if the resulted error is due to the most or least portion of elevation points. The kriging model made with the 75% of points (training subset) was converted to a raster and then extracted to the validation subset (25% of total point) using Extract to Points tool which resulted in prediction values for the validation subset. First, I applied the kriging for the training points and finally with all points as input dataset. The Cross Validation results from ordinary Kriging are shown in tables 3 and 4. 21

27 Equation 1. Root Mean Square Error calculation: z Predicted: predicted heights from the model, z Observed: Observed heights from validation subset, n: the number of compared heights. RMSE = [Σ (z Predicted - z Observed ) 2 / n] Table 3. Cross Validation result from ordinary Kriging from the training subset. Training subset Regression function * x Samples 1126 of 1126 Mean Root-Mean-Square Mean Standardized Root-Mean-Square Standardized Average Standard Error Table 3. Cross Validation result from ordinary Kriging from the training subset. All points Regression function * x Samples 1501 of 1501 Mean Root-Mean-Square Mean Standardized Root-Mean-Square Standardized Average Standard Error

28 Hydrologic Methods In order to determine the site specific tidal regime for Elders East we used four Non-Vented Loggers (HOBO U Water Level) manufactured by Onset Computer Corporation. Three loggers were deployed underwater in PVC stilling wells to record water pressure above sensor and one logger was deployed above ground, away from water just to capture the atmospheric pressure. The water level loggers record the raw water pressure above the sensor which later by having simultaneous atmospheric pressure from barometric logger could be converted to barometrically compensated water level. The HOBO Water Level Titanium is recommended for saltwater deployment for recording water levels and temperatures in wetlands and tidal areas. This data logger features high accuracy at a reasonable price and HOBO ease-of-use, with no cumbersome vent tubes or desiccants to maintain (Onset, 2012) HOBO Water Level Specification Operation Range: 0 to 207 kpa (0 to 30 psia); approximately 0 to 9 m (0 to 30 ft) of water depth at sea level, or 0 to 12 m (0 to 40 ft) of water at 3,000 m (10,000 ft) of altitude Water Level Accuracy: Typical error: ±0.05% FS, 0.5 cm (0.015 ft) water, Maximum error: ±0.1% FS, 1.0 cm (0.03 ft) water Resolution: < 0.02 kpa (0.003 psi), 0.21 cm (0.007 ft) water Pressure Response Time (90%): < 1 second Thermal Response Time (90%): Approximately 10 minutes in water to achieve full temperature compensation of the pressure sensor Temperature Measurements: Operation Range: -20 to 50 C (-4 to 122 F) Accuracy: ±0.44 C from 0 to 50 C (±0.79 F from 32 to 122 F) Resolution: 0.10 C at 25 C (0.18 F at 77 F) Response Time (90%): 3.5 minutes in water (typical) Stability (Drift): 0.1 C (0.18 F) per year The loggers were deployed May 18 th, 2012 to collect water level data through July 19 th, 2012 (Figure 10.). The loggers were launched at the office prior to deployment and were set to collect the water levels in 15 min interval. I used 1.04 m PVC wells for the loggers. I used several metal pole around each well and tightened the well and poles together with metal clamps in order to stabilize the position of the wells after deployment. I recorded the deployment time and other required measurements such as elevation of the logger relative to NAVD88. Those measurements are necessary for the processing of the raw data and corrections. Table 5 presents the location of the loggers in our study area. 23

29 Table 4. Location of the tidal gauges in study area. Location Northing Easting Elevation of the well cap relative to NAVD88 (m) Southern creak, in Elders Point East Canarsie, in bay Northeast of the Elders Point East, in bay Figure 9. Deployment of the loggers in PVC well. 24

30 As it was explained, the raw data from water level loggers must be processed before the correct tidal metrics could be interpreted. The process comprised of two major steps: Barometric Compensation Process: Primarily the collected data of loggers is the only water pressure plus atmosphere pressure above the sensor, not the water height above it. So, this pressure must be converted to water height. The Barometric Compensation Assistant (BCA) in HOBOware (Onset Computer Corporation) was used to determine the water depth from pressure readings by considering water density and temperature in to computation (Onset, 2012). Later, the water heights resulted from the Barometric Compensation Process could be corrected and calculated relative to NAVD88. Compute equivalent NTDE tidal datums for short term stations using the method of comparison of simultaneous observations: The output data from first step went through the second step after removing the noises. The noises in data are inevitable due to the disturbance in the time I deployed and pulled out the loggers. So, only the data which were logged after stabilizing the ambient of the loggers must be used. The loggers; Southern creek in island, Northeast of the island in bay, Canarsie in bay produced 5945, 5933 and 5936 water heights data with 15 min interval. Later, using a search function in excel the maximum (for High Water) and minimum (Low Water) value were identified, while also excluding duplicate max or min values from each 24 row array in sequence. The function returned the maximum reading (High Water) and minimum reading (Low Water) for that 20 row array. When the logger is set to log every 15 min, this is searching at 6 hour intervals, enough to capture the max and min water levels. Then, I went through all the maximum and minimum water levels manually and sorted all to MHHW, MLHW, MHLW and MLLW. From here, the reduction process was done according to COMPUTATIONAL TECHNIQUES FOR TIDAL DATUMS HANDBOOK (CO-OPS2, 2003). There are two different methods in order to compute equivalent NTDE tidal datums, Monthly Mean Comparison and Tide By Tide comparison (TBYT). The TBYT was used since Datums Team in User Services Center for NOAA recommended and confirmed the suitability of the method for my data. Actually, monthly mean datum computation requires the data to be on a calendar month time frame. Since the data didn t cover two full calendar months, it was more reliable that I use the TBYT method of datum computation. With TBYT the time difference is not an issue. The importance is to have properly matched tide picks. So, following the procedures for TBYT datum computation which is explained with examples in COMPUTATIONAL TECHNIQUES FOR TIDAL DATUMS HANDBOOK (CO-OPS2, 2003), the equivalent NTDE tidal datums for all three loggers were computed. 25

31 Inundation analysis Sea-level rise and tidal range change have a significant impact on how high water levels rise and how often. The inundation analysis is beneficial in determining the frequency (or the occurrence of high waters for different elevations above a specified threshold) and duration (or the amount of time that the specified location is inundated by water) of observed high waters (tides). Statistical output from these analyses can be useful in planning marsh restoration activities. Additionally, the analyses have broader applications for the coastal engineering and mapping community, such as, ecosystem management and regional climate change. Since the water heights were calculated relative to NAVD88 and there are 15 min water heights for the study area, I could calculate the frequency and duration of the water level relative to different metrics. Mapping MHHW and MLHW inundation In order to determine the extent of inundation for high waters, the mapping process was implied in ArcGIS In order to incorporate tidal variability within an area when mapping inundation a modeled tidal surface (or raster) is needed that represents this variability. In addition, this surface must be represented in the same vertical datum as the elevation data, which is the orthometric datum of NAVD88. A tidal surface was created by using tide gauges and their associated vertical datum conversions. A point shapefile of the selected tide gauges was created in ArcCataloge 10.0 using their latitude and longitude information, MHHW and MLHW. A raster was created by Geostatistical Analyst Tool in ArcGIS 10.0 (Inverse Distance Weighting interpolation) for the area using the point shapefile. Then, DEM values subtracted from water surface (Raster Calculator) to derive initial inundation depth grid. 26

32 Results Digital Elevation Model (DEM) DEMs, the one form training subset and the one with all points were evaluated (Table 6). The training subset was validated by the validation subset to see how the model works, but later the model from all the points will be our final result since it was created from all points and resulted in a lower RMSE. The RMSE for the validation subset was Later, I went through a logical test for those validated points to find out the percentage of the points with prediction error The result was quite satisfactory with 75% of the points having prediction errors smaller than (RMSE). The prediction values from cross validation for training subset and all points were tested logically as the result is presented (Table 6). Thus, the final interpolated surface (Figure 7.) from all points resulted in 88% of points having error less than RMSE of 0.08 m. I also tried to test the accuracy and reliability of the topographic model in a different way. I already had the elevation of the well cap (above marsh surface) relative to NAVD88 and the height from marsh surface to the RTK point (top of the cap) through field measurement. I wanted to see how accurate could be predicted the well cap height by using the interpolated marsh surface and adding it to the marsh surface height to the RTK point. The result was satisfactory since the predicted elevation for the logger Elders Point East-Southern creek was only m lower than the exact RTK measurement for that point. Even for the logger Elders Point East- Northeast which wasn t located within the extent of the survey, the predicted elevation was only m higher than the exact RTK measurement for that point. Table 5. Evaluation of the DEMs through Cross-Validation and logical test for each dataset are presented. Interpolated Surfaces Number of points RMSE (m) Logical Test RMSE x% Training set (From Cross-Validation) Validation (Extracted validation points from Training) All points (From Cross-Validation)

33 Figure 10. Prediction map of all elevation point dataset (1501 points) for Elders Point East created by ordinary kriging (shown in hillshade and filled contours) and elevation contours (0.5 m interval). 28

34 Hydrology Tidal metrics (datums) The spring high tides happening during lunar cycle were acquired from the data individually for each tidal gauge (Table 7.). All required tidal metrics were computed as it is illustrated in figure 8. As you see the logger Southern creek-in island recorded significantly different values in comparison to other loggers (Northeast of the island in bay and Canarsie in bay). The lower values in MHLW and MLLW water are explainable since this tidal gauge was deployed in marsh to capture more marsh specific hydrology data, so, deployment location wasn t low enough to record the actual low water level and lower low water. But, the higher values for MHHW and MLLW in comparison to other tidal gauges couldn t be explained and understood. Table 6. The spring high tides happening during lunar cycle for each tidal gauge during the time frame of the project. Southern creek in island Moon Phase-Date Moon Phase-Time Spring Tide (m) Spring Tide-Date Spring Tide-Time New Moon - 5/20/ : /20/ :45 Full Moon - 6/4/2012 7: /4/ :15 New Moon - 6/19/ : /19/ :45 Full Moon - 7/3/ : /4/ :45 New Moon - 7/19/2012 0: /18/ :00 Canarsie in bay Moon Phase-Date Moon Phase-Time Spring Tide (m) Spring Tide -Date Spring Tide -Time New Moon - 5/20/ : /20/ :51 Full Moon - 6/4/2012 7: /4/ :15 New Moon - 6/19/ : /19/ :39 Full Moon - 7/3/ : /4/ :48 New Moon - 7/19/2012 0: /17/ :24 Northeast of the island in bay Moon Phase- Date Moon Phase-Time Spring Tide (m) Spring Tide-Date Spring Tide-Time New Moon - 5/20/ : /22/ :30 Full Moon - 6/4/2012 7: /4/ :06 New Moon - 6/19/ : /19/ :44 Full Moon - 7/3/ : /3/ :52 New Moon - 7/19/2012 0: /18/ :01 29

35 Water level relative to NAVD88(m) Tidal Metrics -1.5 MHHW MLHW MHLW MLLW DTL MTL MSL GT MN (MTR) DHQ DLQ Southern creek in island Canarsie in bay Northeast of the island in bay Accepted datums NATDE Figure 11. Tidal metrics computed for each tidal gauge. The accepted metrics NATDE from Sandy Hook reference station were used for computation. 30

36 Inundation analysis, Mapping MHHW and MLHW inundation The frequency and duration of the water level relative to different metrics were calculated for each tide gauge (Table 8). The area where gets flooded in MHHW and MLHW are shown in figures 13 and 14. The marsh doesn t get flooded in MHLW, so the inundation is not required to be analyzed. Table 7. The table shows how frequent and how long, the different elevation of the marsh gets inundated. For example, inundated elevation higher that NAVD 88 in first column indicated how frequent and long the marsh surface higher than NAVD 88 gets flooded. Southern creek in island Inundated elevation Frequency Percentage Time (min) Time (h) Higher than NAVD Higher than MTL (0.138) Higher than MLHW (0.716) Higher than MHHW (0.821) Higher than Growth Range/Lower (0.334) Higher than Growth Range/Upper (1.105) Within Growth Range ( ) Total Canarsie in bay Inundated elevation Frequency Percentage Time (min) Time (h) Higher than NAVD Higher than MTL (-0.157) Higher than MLHW (0.679) Higher than MHHW (0.785) Higher than Growth Range/Lower (0.334) Higher than Growth Range/Upper (1.105) Within Growth Range ( ) Total Northeast of the island in bay Inundated elevation Frequency Percentage Time (min) Time (h) Higher than NAVD Higher than MTL (-0.208) Higher than MLHW (0.624) Higher than MHHW (0.730) Higher than Growth Range/Lower (0.334) Higher than Growth Range/Upper (1.105) Within Growth Range ( ) Total

37 Figure 12. Inundated area at MHHW is illustrated in blue. 32

38 Figure 13. Inundated area at MLHW is illustrated in blue. 33

39 Growth Range of S. alterniflora After checking and sorting the points attributed with S. alterniflora in ArcMap and Microsoft Office Excel, the highest, the lowest, mean and median were calculated as are shown (Table 9). Since the survey was implemented on the evenly spaced transects, the points at the start and end of each transect with S. alterniflora attribute were representative of the elevations which S. alterniflora either started to grow or stopped to grow. In this way, the upper limit and lower limit of the S. alterniflora growth are respectively m and m above NAVD88. As a result, the growth range will be within the m. Table 8. The statistic calculated for S. alterniflora points. Occurrence of S. alterniflora point Highest Lowest Mean Range Median Elevation relative to NAVD88 (m) The frequency distribution of the different cover types was investigated to see the relationship of different cover type to elevation as it is illustrated figure 15. Relationship of the S. alterniflora to tidal metrics In order to understand the response of vegetation to tidal range, I calculated upper and lower limit of growth range relative to different tidal metrics which are important and are considered as critical boundaries for vegetation. Since there was a study by (McKee, et al., 1988) in which they specifically looked at this relationship between different salt marshes at the east coast of the U.S., I decided to combine their data in order to have a comparison for different location in within United States (Figure 16.). 34

40 Figure surveyed elevation points with attributed cover type from Elders Point East. 35