2002 Progress Report: Coastal Wetland IndicatorsEPA Grant Number: R828677C003
Subproject: this is subproject number 003 , established and managed by the Center Director under grant R828677
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
Center: EAGLES - Atlantic Coast Environmental Indicators Consortium
Center Director: Paerl, Hans
Title: Coastal Wetland Indicators
Investigators: Morris, James T. , Novakowski, Karyn I. , Gallegos, Charles L. , Montane, Juana M. , Hopkinson, Charles S , Rodriguez, Diana , Herrick, Gabe , Marshall, Helen , Torres, Raymond , Valentine, Vinton
Institution: University of South Carolina at Columbia , Texas A & M University , University of North Carolina at Chapel Hill
Current Institution: Marine Biological Laboratory
EPA Project Officer: Packard, Benjamin H
Project Period: March 1, 2001 through February 28, 2005
Project Period Covered by this Report: March 1, 2001 through February 28, 2002
RFA: Environmental Indicators in the Estuarine Environment Research Program (2000) RFA Text | Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Water , Ecosystems
The main objectives of this research project are to: (1) develop a suite of indicators of the condition of coastal wetlands that are based on physical and biological criteria, with an emphasis on higher plant-based pigment indicators; and (2) link these indicators to remote-sensing capabilities.
The Atlantic Coast Environmental Indicators Consortium (ACE INC), Coastal Wetland Indicators component has been active since August 2001. During the initial months of the project, most of the activity was organizational. Two postdoctoral fellows have been hired, Helen Marshall, an expert on plant pigments and biooptical modeling, with a Ph.D. from the University of Wales, and Vinton Valentine, with a Ph.D. from the University of Delaware. Dr. Marshall is working on a major objective of our project, which is to develop a suite of indicators of the condition of coastal wetlands that is based on biophysical criteria. One set of indicators that we are developing is based on measurements of plant pigments. These will be correlated with the optical properties of single leaves and with whole canopies to develop algorithms that will be used to interpret remotely sensed data and to derive indices of wetland plant productivity, stress, and change at the landscape scale. Dr. Valentine brings expertise in image analysis and geographic information systems (GIS) to the project. With the addition of Dr. Valentine, our efforts in classification of marsh drainage networks will commence. Hypotheses that address the responses of leaf pigments and their optical properties to nutrients and salt stress will be tested using samples collected from experimentally manipulated test plots in the field. A second indicator of coastal wetlands that can be derived from remotely sensed data relies on interpreting the geomorphic pattern and fractal signature of coastal wetland drainage networks. The pattern of existing channel networks is a consequence of the existing geomorphic equilibrium and conveys information about the stability of coastal wetlands. Proposed field work in 2001 was deferred until 2002, because of the late arrival of funds to initiate the project.
The structure of the program, its elements, and principal scientists are diagrammed in Figure 1.
Figure 1. Schematic of the Structure, Elements, and Principal Scientists of Coastal Wetland Indicators
We have taken advantage of a long-term, N-P factorial fertilization experiment in our South Carolina salt marsh study site to test for the sensitivity of plant pigments and the spectrum of reflected light from plant leaves to nutrient condition. These are variables that make attractive indicators as they clearly have application to remote sensing. Our data show that Spartina biomass and productivity respond to N, but not to singular additions of P. However, results of scanning with a spectroradiometer (see Figure 2) showed that P-treated plants had significantly higher reflectance in the near-infrared reflectance (NIR), irrespective of N treatment, in a spectral region that is largely determined by cell structure. Microscopic analysis showed that the bundle cells of P-treated plants were more lignified and also differed in the dimensions of their bundle sheaths. The observed differences in spectral reflectance should be great enough to be detectable by remote sensors and could provide a means of monitoring nutritional status.
Figure 2. The Spectrum of Light Reflected From the Leaves of Spartina alterniflora. Plants treated with phosphorus had higher reflectance in the near infrared.
We also have made progress in relating the density of chl-a in the plant canopy to the reflectance data in remote imagery, and we have successfully trained a neural network to classify remote imagery. The neural network was able to map chl-a density as well as plant community distributions and major landscape features with stunning success. This is an important step, because chl-a concentration provides information about a plant's condition. The concentration of chl-a in plant tissues varies with phenology and with nutrition. Moreover, because photosynthetic rate and chl-a concentration are directly related, chl-a is actually a more sensitive indicator of the condition of higher plants than biomass and should be investigated as an index of stress. Accessory pigments, measured by high-performance liquid chromatography (HPLC), provide even more information about the condition of plants. Furthermore, because chl-a is highly absorbent of radiation in the range of Landsat Thematic Mapper spectral band 3 (630-690 nm) and reflective in spectral band 4 (760-900 nm), it should be feasible to use remote sensing techniques to monitor the condition of vegetation (see Figure 2) and the density of pigments in the plant canopy (see Figures 3 and 4).
Figure 3. An Airborne Data Acquisition and Registration (ADAR) Image, Classified to Show Chl-a Density in a Salt Marsh at North Inlet
At North Inlet, previous attempts to remotely sense pigments have met with some success (see Figures 2 and 3) using spatially precise ADAR data, but our experience has shown that hyperspectral data will be needed to make significant advances in the remote sensing of plant pigments. However, we have had great success in training neural networks to interpret remote data, and we expect that significant progress will be made using neural networks to interpret hyperspectral data.
Figure 4. A Neural Network was Trained to Interpret the Four ADAR Bands (Blue, Green, Red, and NIR). The output of the neural network is the Chl-a density in the plant canopy. The fit using the neural network is significantly better than can be obtained using regression analysis and traditional models.
Our group also is looking specifically at xanthophyll pigments. These pigments react rapidly to a variety of environmental stressors in both micro-algae and higher plants. The xanthophyll pigments perform a cyclic interconversion (epoxidation and de-epoxidation) during light and nutrient stress, which directly affects the rate of carbon fixation and of primary production, by competing with the photosystem 2 light harvesting antenna. This cycle causes changes in the proportion of different wavelengths of light reflected by the photosynthetic apparatus and as such can be used as a remote-sensing indicator to assess nutrient availability and the rate of primary production in a variety of ecosystems. Experiments have been performed at the Plum Island Estuary in Massachusetts and North Inlet in South Carolina. These experiments used a series of fertilized plots to assess how changes in nutrient stress affect xanthophyll cycling and concurrent changes in leaf reflectance both at single-leaf and community levels. Reflectance was analyzed around 530 nm wavelength and the change from a "no feature" was calculated and named "delta reflectance." Delta reflectance correlated linearly with the epoxidation state of the xanthophyll cycle at both single-leaf (see Figure 5) and plant-canopy levels (see Figure 6). Changes in the overall size of the xanthophyll pool affected the magnitude of values of delta reflectance, and they can be used to predict actual concentrations of each of the xanthophyll pigments. In this way, the environmental stress that salt marsh plants are under can be remotely sensed using the reflectance as an indicator. The work is currently being developed to consider larger scale community work such that the reflectance data may be collected by airborne sensors. Common coastal pollutants and their affects on xanthophyll cycling also are being examined. Xanthophyll cycling occurs rapidly (10 minutes) and can provide an environmental indicator with high spatial and temporal resolution.
Figure 5. Relationship Between the State of the Xanthophyll Cycle and Delta Reflectance in S. alterniflora
Figure 6. Relationship Between the Epoxidation State of the Xanthophyll Cycle and the Delta Reflectance in S. patens
Primary Production Indicators
Long-term research at North Inlet has documented a trend of increasing primary production in the salt marsh (Morris, et al. 2002). Interannual variation that exists around a trend of increasing production is related to anomalies in mean sea level. Several lines of information lead us to believe that the long-term trend is an indication that the elevation of the salt marsh surface has not kept pace with sea-level rise during the last decade. If this trend continues, and if our interpretations are correct, then marsh productivity will begin to decline as marsh elevation falls to a level that is suboptimal. If the trend continued, the marsh would be replaced by intertidal mud flat and then open water.
Research on marsh stability in northern marshes continues on several fronts: (1) establishment of sites for monitoring sedimentation and erosion, (2) marsh elevation surveys, and (3) geomorphic descriptions of marsh condition.
Monitoring Sedimentation and Erosion. Sedimentation-erosion tables (SET) platforms now have been established at six primary locations (see Figures 7 and 8) that stretch across multiple gradients: (1) land-sea or riverine versus oceanic sediment source, (2) vegetation communities (S. alterniflora, S. patens, and T. augustifolia), and (3) distance from creek waters (creekside versus inland marshes). SET platforms and marker horizons have been established along 300-m transects extending away from creekbanks. Five transects have been established along the Rowley River, which is one of the rivers discharging into Plum Island Sound. Three additional SET sites have been established at experimental sites, where marshes are fertilized with N and P. Initial elevation was measured at each SET platform in the fall of 2002. Sites will be monitored with a 6-month frequency.
Additional SET platforms will be established once we have mapped and classified the estuarine drainage creek network. Our hypothesis is that drainage network configuration will give an indication of whether a marsh is keeping up with sea level rise or not. We will establish SET platforms in each major network type to test this hypothesis.
Marsh Elevation Surveys. High-precision global positioning system (GPS) surveys of marsh elevation have been conducted throughout the Plum Island Sound marshes, from the salt water marshes surrounding Plum Island Sound to the tidal freshwater marshes along the upper Parker River. Kinematic surveys were conducted following the establishment of a series of high-precision benchmarks throughout the Plum Island Sound region. This benchmark network was tied into the geoid by surveying up to the primary elevation benchmark at Salisbury Beach in New Hampshire. The precision and accuracy of our benchmark network is 2-3 mm and that of the kinematic elevations is better than 1 cm. Our next objectives are to attempt to extrapolate spot measurements across the marsh platform. We will determine if we can do this by coupling aerial imagery and elevation measures with a neural net analysis. Ultimately, we need much better elevation data for our study marshes and the coast as a whole. High-precision lidar imagery is our first choice of elevation data. This is expensive data to obtain and we seek assistance from the U.S. Environmental Protection Agency (EPA) in this regard.
Figure 7. Installation of SET Platforms in Plum Island Marshes During Winter to Minimize Disturbance to Vegetation
Figure 8. Locations of SET Platforms (Triangles) and Elevation Measurements (Red Circles) in the Plum Island Estuary
Geomorphic Characterization. Our efforts in this area began in earnest with the addition of Dr. Valentine to the project. Thomas Millette from Mt. Holyoke College also is teaming up with us in our effort to classify marsh drainage networks. Our first priority is to catalog the available maps and imagery of our study region. We are contacting numerous state, federal, and local research groups for information on these items. Our catalog will indicate product type, scale, area of coverage, date, quality, and price. Once we have cataloged the sources of information, we will attempt to obtain those that should be most useful in: (1) mapping drainage networks, (2) mapping plant community composition and distribution, and (3) illustrating change over time.
Figure 9. An Example of One of the 1 sq km Grids Analyzed for Geomorphic Characteristics Along the Plum Island Sound Marshes
An undergraduate student in the Marine Biological Laboratory (MBL) Semester in Environmental Science, Jennifer Franklin, conducted her semester research project on geomorphic characteristics of the Plum Island marshes (Franklin, 2002). She analyzed the distribution of creeks and ponds in marshes along the entire salinity gradient of the estuary. In each of three regions (fresh, brackish, and marine), she documented the length and drainage density of 1st-, 2nd-, 3rd-, and 4th-order streams as well as mosquito ditches (see Figure 9). She also quantified total edge and the relative extent of marsh, water, and ponds along this gradient. Franklin observed some very striking gradients along the length of the estuary, which may correlate with marsh success in keeping up with sea level rise. The low salinity, upper estuary marshes had the greatest extent of marsh (85 percent), the greatest drainage density (see Figure 10), the greatest length of mosquito ditches (347 m ha-1), and the least areal extent of ponding (0.02 percent). In contrast, the saline marshes, closest to the ocean, had the least extent of marsh (11 percent), the lowest drainage density, the least length of mosquito ditches (105 m ha-1) and the greatest extent of ponding (6 percent). Although drainage creek divides were marked by high marsh in the low salinity marshes, they were frequently marked with broad expanses of marsh depressions and ponds in the saline marshes. We would conclude from this preliminary survey of geomorphic characteristics that the upper estuary marshes, which are close to their sediment supply (the Parker River), are maintaining their elevation relative to sea level, while the high salinity marshes, which are the most removed from sediment supply, are not keeping up with sea level rise.
Figure 10. Drainage Density (m per Hectare) Along the Plum Island Sound Marshes
Geomorphic indicator research at the North Inlet, SC, estuarine marsh is focused on assessment and trend analyses of 1-dimensional, 2-dimensional, and 3-dimensional topographic data from the intertidal zone, and intertidal channel network pattern. Karyn Novakowski (a graduate student with R. Torres) digitized approximately 7,000 intertidal channel networks and quantified their main channel length (L) and contributing area (A). Her analyses show that L and A are related by a power function, and that most intertidal channel L-A data plot within the range of terrestrial channel network values (see Figure 11). Hence, tidal channel networks with bidirectional flow and cohesive sediment are similar to terrestrial channel networks with unidirectional flow and noncohesive sediment. These observations indicate that channel evolution and channel optimization theories developed for terrestrial systems may apply to intertidal systems. We currently are exploring this inference.
Figure 11.Log-Log Plot of Main Channel Length and Watershed Area for Creek Networks in North Inlet, SC. The trendline through the marsh data gives a value of L = 2.53 ± 1.11A0.733 ± 0.02 with an R2 value of 0.75. The 95 percent confidence intervals are shown as dashed black lines.
Although intertidal marsh landscapes seem flat and featureless, they have very subtle topographic variations that dictate the spatial variability of hydroperiod, and direction and magnitude of sheetflow during tidal inundation. The status and stability of this subtle topography may be used as an indicator of estuarine health and stability. Juana Montane (a graduate student with R. Torres) is creating the first ever, high-density, high-resolution, high-accuracy digital elevation model (DEM) for an entire, pristine intertidal marsh island using real-time kinematics (RTK) GPS. The South Carolina Geodetic Survey is a collaborative partner in this effort. Together, we installed two class-A (National Geodetic Survey standards) bench marks on Merry Island. Their lateral positions are known to within 5 mm, and their vertical positions are known to with 10 mm of the geoid. To date, we have 9,000 of an estimated 13,000 xyz coordinates needed to fully characterize the island surface; density of points is approximately 5 m2 on the marsh island platform and approximately 1 m in and around the channels (see Figure 12). These data will serve as ground truth for a LiDAR mission planned through the newly formed, National Science Foundation (NSF)-sponsored National Center for Airborne LiDAR Mapping (NCALM). Our DEM shows that marsh platform has approximately 80 cm of vertical relief and channels have 200 cm (see Figure Y). When the DEM is completed, we will perform spatial analyses of hydroperiod and hypsometric integrals. We hypothesize that these topographic indices, combined with tidal prism estimates, can be used as indicators of estuarine stability.
Figure 12. Post Map Showing Position and Track of RTK GPS Topographic Survey. Each dot represents a single x,y,z coordinate for the marsh surface. S-N elevation transect location indicated on post map.
Training and Development
Jennifer Franklin conducted her semester research project on geomorphic characteristics of the Plum Island marshes (Franklin, 2002). The project currently supports two graduate students. The North Inlet project supports two female Ph.D. candidates, one Hispanic and one Caucasian. A workshop is planned for the Spring 2003 ACE INC meeting to be held in Charleston, SC.
Contributions to State of Knowledge
The indicators that we are developing will provide new tools for evaluating the condition of coastal wetlands. The actual products will be indicators that are based on measurements made in the field. However, all of the indicators being developed have significant potential for being developed as applications that can be calibrated using remotely sensed data. To date: (1) progress has been made using pigments and reflected light as indicators of the condition of vegetation; (2) neural networks have proven to be effective tools for classifying remote sensor data; (3) significant trends in the productivity of coastal wetlands have been observed; and (4) we have documented that we are able to discern interannual changes in the relative elevation of the marsh surface. There is a paucity of detailed topographic information from intertidal marshes. This results from a lack of studies designed to investigate interactions between process and form in intertidal environment. Our efforts will help fill the gap in our understanding of the evolution and stability of intertidal landscapes.
Morris JT, Sundareshwar PV, Nietch CT, Kjerfve B, Cahoon DR. Responses of coastal wetlands to rising sea level. Ecology 2002;83(10):2869-2877.
Franklin J. Salt marshes and sealevel rise: sediment dispersal in the Plum Island Sound marsh ecosystem. Final Semester Research Project Report, 2002, 41 pp.
We will continue to explore the use of pigment and geomorphic indicators to a broader suite of conditions and systems. Collaborations are underway with personnel from the Estuarine and Great Lakes Program (EaGLe), Research for the Gulf of Mexico-Consortium for Estuarine Ecoindicator Research (GOM-CEER), and ASC scientists to compare and expand indicators being evaluated in this project. Future activities will emphasize these collaborations in the context of the EaGLe and other (e.g., National Science Foundation-Long-Term Ecosystem Research [LTER]) research efforts aimed at long-term, cross-ecosystem indices of coastal wetland condition and change. Our future activities are focused on investigating the development of optimal channel patterns and form that facilitate water and nutrient exchange between subtidal and intertidal environments.
Journal Articles on this Report : 3 Displayed | Download in RIS Format
|Other subproject views:||All 89 publications||19 publications in selected types||All 17 journal articles|
|Other center views:||All 383 publications||99 publications in selected types||All 88 journal articles|
||Jensen JR, Olsen G, Schill SR, Porter DE, Morris J. Remote sensing of biomass, leaf-area-index and chlorophyll a and b content in the ACE Basin and National Estuarine Research Reserve using sub-meter digital camera imagery. Geocarto International 2002;17(3):27-36.||
||Mwamba MJ, Torres R. Rainfall effects on marsh sediment redistribution, North Inlet, SC. Marine Geology 2002;189(3-4):267-287.||
||Torres R, Mwamba MJ, Goni MA. Properties of marsh sediment mobilized by low tide rainfall. Limnology and Oceanography 2003;48(3):1245-1253.||
Supplemental Keywords:coastal wetlands, marsh habitat, higher aquatic plants, photopigments, geomorphology, tidal ecosystems, regional indicators, light detection and ranging, LIDAR, nutrient status, physiology, sea level rise, neural network analysis, wetland management., RFA, Scientific Discipline, Air, Water, ECOSYSTEMS, Ecosystem Protection/Environmental Exposure & Risk, RESEARCH, estuarine research, Hydrology, Ecosystem/Assessment/Indicators, climate change, Air Pollution Effects, Aquatic Ecosystems, Monitoring, Ecological Monitoring, Atmosphere, Ecological Indicators, environmental monitoring, remote sensing, coastal ecosystem, bioindicator, plant indicator, coastal watershed, estuaries, coastal environments, diagnostic indicators, ecosystem indicators, environmental indicators, coastal ecosystems
Progress and Final Reports:Original Abstract
Main Center Abstract and Reports:R828677 EAGLES - Atlantic Coast Environmental Indicators Consortium
Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R828677C001 Phytoplankton Community Structure as an Indicator of Coastal Ecosystem Health
R828677C002 Trophic Indicators of Ecosystem Health in Chesapeake Bay
R828677C003 Coastal Wetland Indicators
R828677C004 Environmental Indicators in the Estuarine Environment: Seagrass Photosynthetic Efficiency as an Indicator of Coastal Ecosystem Health