2004 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. , Gallegos, Charles L. , Hopkinson, Charles S , Porter, Dwayne , Jensen, John , Schalles, John , Oxborough, Kevin , Torres, Raymond , Geider, Richard
Current 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 , Ecosystem Management Research Institute
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, 2003 through February 28, 2004
RFA: Environmental Indicators in the Estuarine Environment Research Program (2000) RFA Text | Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Water , Ecosystems
The objective of this research project is to develop an indicator that is rapid, non-intrusive and has high temporal and spatial resolution. It also should be applicable to a range of stressors and species found in the coastal environment. The Atlantic Coast Environmental Indicators Consortium (ACE INC) Coastal Wetland Indicators (CWI) project has developed indicators at a range of temporal and spatial scales that are metrics of the status of coastal wetlands. These scales range spatially from the landscape scale to the level of an individual leaf and temporally from decades to hours. At the leaf-scale we have sought to develop indicators that are based upon plant pigment and that can be applied to a larger scale using remote sensor data. At the larger temporal and spatial scales, we have sought to develop indicators based on geomorphological patterns that can be remotely sensed. These geomorphological indicators are appropriate as metrics of long-term trends and vulnerability. For example, detection of wetland loss as the result of sea-level rise would be an appropriate application for the geomorphological indicators.
Background. All plants possess what is known as the xanthophyll cycle. This is a two-step de-epoxidation reaction that serves to protect photosystem II (PSII) during stress. The stress pigment zeaxanthin is an effective, non-photochemical quencher and protects PSII during light, water, temperature, and nutrient stress, as well as in response to chemical pollutants that impair PSII activity ( Marshall, et al., 2000).
Ecological Indicator . The indicator can be expressed as the epoxidation state, which is computed as a ratio of the concentrations of the different forms of the xanthin pigment: ES = ([zea]+0.5[anth])/([zea]+[anth]+[viol]). These pigments absorb energy within the visible wavelengths (520-580 nm) and are detectable. This change in the state of the xanthophyll cycle leads to a change in leaf reflectance between 520-580nm. The reflectance at this feature therefore may be used as an indicator of relative zeaxanthin levels and indirectly as an indicator of plant stress levels. This can be quantified as follows:
R is the reflectance at the specified wavelength. We have found that this stress index correlates well with the conversion to zeaxanthin in the xanthophyll cycle (quantified using HPLC analysis) for both species tested.
Ecological Effect/Impact. The epoxidation state can indicate water, temperature, light, pollutant, or nutrient stress. It does not necessarily indicate the specific cause of stress, but in combination with other measures, the causes can be determined. For example, nutrient stress (deficiency) causes de-epoxidation of the xanthophyll cycle, because of a decrease in the plant’s ability to repair normal levels of PSII damage. A nutrient stress also would be associated with a decline in chlorophyll concentration. The productivity of salt marsh vegetation is commonly limited by nitrogen availability, therefore the eutrophication of a marsh would manifest as an increase in epoxidation state.
Environmental Application. A change in epoxidation state of the xanthophyll cycle was detected in Spartina alterniflora and S. patens in different nutrient fertilized plots at Plum Island, Massachusetts (Figure 1). Nutrient additions lead to higher epoxidation states (i.e., lower stress levels). In both species, control plots showed the lowest epoxidation states indicating that both are limited by nutrients under normal in situ conditions. Xanthophyll cycling occurs in a matter of minutes such that the state of the cycle indicates stress conditions with high temporal resolution.
Figure 1. Epoxidation State in Spartina alterniflora and S. patens in Treatments Fertilized With Nitrogen and Phosphorus and Controls
Macro-Scale Indicators: 1. Land-Classification
Background. Because of variations in light scattering, reflectance, and absorption, different surfaces show distinctive reflectance signatures throughout the light spectrum. Leaf reflectance is dependant upon the physical structure of the leaf itself (and thus its scattering and reflecting properties) and the absorbance of light by pigments and bio-chemicals. Thus, plant communities often have different reflectance properties as they are composed of species that differ in the physical structure of their leaves and biochemical makeup. Furthermore, plant communities are distinctly different from other land-class types in their reflectance of light.
Ecological Indicator. The indicator detects physical/structural land surface properties using four wavelength bands (ADAR data) and uses a neural network to classify vegetated areas and land surface types and to differentiate major coastal wetland plant communities. A neural network was trained to distinguish six land surface types from four wavelength bands in images taken from fixed wing aircraft (Figure 2). Work is continuing with hyperspectral data, which we expect will allow the land classes to be refined even further, possibly even providing enough information to compute a stress index of the vegetation (see above).
Ecological Effect/Impact. Land use classification and change analysis are fundamental management tools that provide information about a wide variety of environmentally important topics that range from the calculation of impervious surface area to changes in forest cover. Canned GIS packages (e.g., ArchInfo) incorporate algorithms that allow various kinds of classifications to be performed. Our use of neural networks for classification is novel. Although not a first, the manner in which we have combined neural net classification with elevation data from a LIDAR sensor provides a means of analyzing an important geomorphological metric that has not been possible before (Morris, et al., 2005).
Figure 2. Left: An ADAR Image of North Inlet estuary, SC. Right: Land classification of the ADAR image produced by a neural network trained to discriminate among the reflectance patterns of different land surface types.
Environmental Application. Land-use classification has many applications. In the context of coastal wetlands, a time-series of classified images is used for change detection. For example, over time is there a change in the area of salt marsh and/or has it moved? Land-classification can provide geostatistical data of the type described below and, when combined with elevations, can provide details about the vulnerability of a coastal wetland to sea-level rise. The ability to forecast vulnerability can provide an early warning that would prompt a management response to mitigate the threat. A decision could be made to divert sediment-laden water from a river into the adjacent marshes, for example, as is being done now in coastal Louisiana.
Macro-Scale Indicators: 2. Geomorphological Pattern
Background. The geomorphic configuration of tidal marshes reflects the complex interaction of a variety of factors over time. Sea-level change, sediment supply, sedimentation and accretion, plant growth, and organic matter preservation interact to create particular landscape configurations within tidal wetland systems. Tidal channels serve as conduits for sediments, nutrients, detritus, and organisms. Other hydrographic features, such as ponds and pannes, reveal clues about the state of marsh development, condition of the vegetated marsh surface, and habitat space for fish and birds. These configurations change as the underlying factors change. When viewing the tidal marsh landscape, there is a range in conditions from maximum marsh development in equilibrium with sea level to highly degraded marshes with extensive ponds and large areas of open-water habitat. Our work explores the use of geomorphometric measures of the channel and ditch networks and other hydrographic features of tidal marshes as indicators of condition.
Ecological Indicator. Using features mapped from aerial imagery, a variety of metrics can be calculated that describe the physical configuration or form and condition of the marsh channel and ditch network and other hydrographic features. The metrics examined for this reporting period include:
- Drainage Density: total channel length, total ditch length, or total watercourse length per unit area. This is an indicator of landscape dissection and acts as a surrogate for habitat edge.
- Sinuosity Mean and Range: mean of actual channel or ditch section lengths divided by straight-line lengths between section ends. This is an indicator of departure from natural channel characteristic, variable water velocity, potential for erosion and deposition, and varied edge habitat; a larger number indicates more a convoluted channel.
- External Link Mean Length:mean length of all external or terminal links in basin. A larger number indicates network extension through headward erosion.
- External Link Frequency: number of external or terminal links per unit area. This is an indicator of the hydrological capacity of a marsh network; a larger number indicates an expansive network.
- Marsh:Network Area Ratio: total marsh area in basin to total network area in basin. This is a measure of marsh area to network area; a larger number indicates a more developed tidal wetland.
- Multi-Fractal Dimensions: negative slope of plot of log of box counts to log of box lengths for each curve segment. The channel segment fractal dimension provides a measure of sinuosity and gives a composite measure of the drainage density and spatial distribution of channels. The branching structure fractal dimension gives a measure of channel bifurcation.
- Marsh:Water Area Ratio: total marsh area to total water area. This is a measure of marsh area to network area; a larger number indicates a more developed tidal wetland.
- Pond Density: number of ponds per unit area extent of ponds within the marsh area; a larger number indicates more individual ponds within the landscape and, therefore, greater habitat complexity.
- Pond Surface Area Ratio: total ponded area per unit area. This is a measure of the proportion of marsh area that is ponded and, therefore, not vegetated.
- Mean Pond Size: a larger size indicates larger ponds in marsh area on average and, therefore, less vegetated marsh and possibly more habitat space.
- Hypsometry: describes the frequency distribution of elevations or area below a given elevation. Hypsometric analyses have been used to characterize landscape features and to assess landscape response to external forcing.
Ecological Effect/Impact. Tidal wetlands are threatened by a variety of factors, some of which are natural and some anthropogenic. The summary by Boesch, et al. (1994) of factors responsible for marsh loss in the Mississippi delta could apply anywhere and range from construction of dikes that prevent flooding (and sediment supply) and dams that trap sediment to sea-level rise. There is also evidence in some estuaries of a legacy effect from colonial deforestation that may now, after reforestation of watersheds, be resulting in marsh loss as a result of a decline in sediment supply. Our modeling work suggests that marshes are quickly lost when they cross a threshold. We have hypothesized that, as this threshold is approached, there are changes in the geomorphological patterns that can signal when a change is occurring.
Much of our work has been exploratory. For example, we have examined the relationship between creek length and watershed (or flowshed) area to determine if these properties vary by a constant ratio as they are known to do in terrestrial watersheds. We found a power function relationship between area and length, as in terrestrial watersheds, which indicates scale invariance between these landscape parameters. Likewise, length-area analyses show that there exists an upper limit to the degree to which watersheds greater than approximately 2000 m 2 are dissected by intertidal creek networks. Data that plot above this limit may indicate that the landscape is in a dynamic state. In our study area, there are 24 such creek networks that are among the smaller watersheds in the system. These observations indicate that the smallest watersheds are likely to be most responsive to estuarine change and all or part of these 24 networks should be target sites for more refined studies of ecosystem stability.
Environmental Application. Tidal creek structure is an indicator of coastal wetland stability. Our preliminary findings indicate that tidal creek suspended sediment concentration is inversely related to tidal creek length. This observation indicates that less extensive and shorter creek networks are the dominant sources of inorganic and nutrient rich organic particulate matter (allocthonous and autochthonous) to the salt marsh platform area. Creek length and total creek length per unit area are therefore likely indicators of tidal wetland stability.
Training and Development
In cooperation with Thomas Millette of Mount Holyoke College, we involved a number of summer interns and work study students in mapping marsh features of the Plum Island Estuary from orthophotograph images. We conducted a field check session with these students during the summer to prepare them for the mapping ponds and pannes and to evaluate previous results on the ground.
We hosted Lauren Fety, an extern from Brown University, during the January 2004 inter-session break. Ms. Fety georectified a historical topographic survey sheet for use in our marsh ponding study.
We graduated two M.S. students from the University of South Carolina. One has moved on to a Ph.D. program, and the other is working in the consulting area.
We participated in the Workshop on Revisiting the Regional Protocol for Monitoring Tidal Wetland Restoration in the Gulf of Maine on September 29-30, 2004, at the Wells National Estuarine Research Reserve, Wells, Maine. Our participation focused on examining and revising protocol variables and methods as part of the hydrology and soils/sediments functional group. We offered information regarding base mapping, elevation data collection, and pond metabolism. The workshop gave us an opportunity to discuss our research with personnel from a variety of federal, regional, state, and non-profit organizations active in the Gulf of Maine.
We co-organized (with ACE INC co-investigator Raymond Torres, Danika van Proosdij, and Sergio Fagherazzi) a Chapman Conference on Salt Marsh Geomorphology: Physical and Ecological Effects on Landform in Halifax, Nova Scotia, Canada on October 9-13, 2004. The conference brought together international experts on marsh geomorphology and ecology with a goal of understanding the effects of human activities, climate changes, and sea-level rise on intertidal marshes.
We attended the New England Estuarine Research Society Fall 2004 Meeting on October 21-23, 2004. We met with a number of people from U.S. Environmental Protection Agency (EPA) National Health and Environmental Effects Research Laboratory (NHEERL), Atlantic Ecology Division (AED). We discussed the geomorphometric indicators investigated to date, development of reference conditions, and possible applications of and enhancements to our indicators in support of regional projects.
We also participated in the Northeastern Ecosystem Research Cooperative on November 17-18, 2004. As an invited plenary speaker, we discussed the effects of activities in watersheds on coastal ecosystems, including tidal marshes. The meeting was attended by New England scientists as well as representatives from federal, regional, state, and non-profit organizations active in New England.
We continued our direct collaboration with state and federal organizations that manage wetland resources in the Gulf of Maine region. We have regular contact with personnel from the Massachusetts Office of Coastal Zone Management regarding data and information sharing, as well as indicator use for assessing salt marsh responses to human and natural stressors. They are interested in how they can incorporate our research into their work on rapid assessment of salt marshes. We also have solicited MACZM input as we pursue plans to collect LIDAR and digital aerial photography for the Plum Island Estuary study area. We are in frequent contact with personnel from EPA NHEERL AED to share information and to obtain feedback on the indicators that we are investigating. We have shared information about marsh ponding with personnel from the Parker River National Wildlife Refuge and the U.S. Fisheries and Wildlife Service Region 5.
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. All the indicators being developed, however, have a significant potential for being developed as applications that can be calibrated using remotely sensed data. To date, progress has been made using pigments and reflected light as indicators of the condition of vegetation, neural networks have proven to be effective tools for classifying remote sensor data, significant trends in the productivity of coastal wetlands have been observed, and we have documented that we are able to discern interannual changes in the relative elevation of the marsh surface.
Future geomorphometric indicators work for Plum Island Estuary will explore additional metrics, such as pond shape and perimeter:area ratio. In some cases, the metric values need to be refined through more precise mapping classification. For example, a number of external links are a result of reducing connected ponds to a centerline channel. We will continue to refine measures that have promise or are intuitively appealing, such as sinuosity. Accounting for these features may result in different interpretations. With the completion of the hydrographic features mapping of the Plum Island tidal marshes by Thomas Millette, Christopher Hayward, and their students at Mount Holyoke College, we will calculate metrics on a larger number of areas to determine variability and robustness. We also plan to map features in selected locations from 1938 aerial photography and run metrics for those locations to confirm our notions revealed by the change trajectories. In collaboration with National Science Foundation-supported National Center for Airborne Laser Mapping (NCALM), we plan to collect LIDAR data and digital aerial imagery for the Plum Island Estuary in late winter/early spring 2005. We will use the resulting elevation data products to help identify tidal creeksheds and to investigate geomorphometric indicators that rely on topography, such as local relief and hypsometric interval. Using creeksheds, we can revisit the more classical watershed metrics similar to the work undertaken by Ray Torres and others in the North Inlet marshes. The elevation data should also provide the ability to examine indicators such as the distribution of vegetation species and biomass relative to elevation and water level. For example, examining the location of S. patens relative to tidal water level and range will give us information about the condition and vulnerability of large portions of the Plum Island tidal marshes.
Boesch DF, Josselyn MN, Mehta AJ, Morris JT, et.al. Scientific assessment of coastal wetland loss, restoration and management in Louisiana. Journal of Coastal Research 1994;20(Special Issue):1-89.
Journal Articles on this Report : 6 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|
||Montane JM, Torres R. Accuracy of LiDAR in a Salt Marsh Environment. Remote Sensing of the Environment (in review, 2005).||
||Morris JT, Porter D, Neet M, Noble PA, Schmidt L, Lapine LA, Jensen JR. Integrating LIDAR elevation data, multi-spectral imagery and neural network modelling for marsh characterization. International Journal of Remote Sensing 2005;26(23):5221-5234.||
||Morris JT. Scale-dependent responses of coastal wetlands to rising sea level. Estuarine and Coastal Marine Science (submitted, 2005).||
||Novakowski KI, Torres R, Gardner LR. Geomorphic analysis of tidal creek networks. Water Resources Research 2004;40(5):W05401.||
||Torres R, Styles R. Effects of Salt Marsh topography on tidal asymmetry. Estuarine Coastal and Shelf Science (in review, 2005).||
||Valentine V, Hopkinson Jr. CS, Millette TL, Hayward CD, et al. Formation of ponds in marshes of the Plum Island Sound estuary. Estuarine, Coastal and Shelf Science (submitted, 2005).||
Supplemental Keywords:coastal wetlands, marsh habitat, higher aquatic plants, photopigments, geomorphology, tidal ecosystems, regional indicators, 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