2003 Progress Report: Assessing an HGM-based Wetland Classification and Assessment Scheme Along a 1000 km Gradient of the Appalachian Mountains: Hydrology, Soils and Wetland FunctionEPA Grant Number: R829497
Title: Assessing an HGM-based Wetland Classification and Assessment Scheme Along a 1000 km Gradient of the Appalachian Mountains: Hydrology, Soils and Wetland Function
Investigators: Cole, Charles Andrew , Brooks, Robert P. , Cirmo, Christopher P. , Wardrop, Denice Heller
Institution: Pennsylvania State University , The State University of New York at Cortland
EPA Project Officer: Packard, Benjamin H
Project Period: January 15, 2002 through January 14, 2005 (Extended to August 31, 2006)
Project Period Covered by this Report: January 15, 2003 through January 14, 2004
Project Amount: $973,301
RFA: Development of National Aquatic Ecosystem Classifications and Reference Conditions (2001) RFA Text | Recipients Lists
Research Category: Ecosystems , Water , Aquatic Ecosystems
Attributing functions to various wetland types is difficult without an organizing classification scheme. In recent years, there has been increasing focus on the development of theory and models based on the hydrogeomorphic (HGM) approach to wetland classification and assessment (Brinson, 1993; Brinson, 1995; Brinson, 1996). This approach classifies wetlands and assesses function primarily based on the location of the wetland in the landscape, the source of water for that wetland, and the dynamics of the water onsite. According to the HGM classification hierarchy, wetlands are grouped into national-level classes (Smith, et al., 1995) under which regional subclasses are defined (e.g., Cole, et al., 1997), and an analogous structure is followed for the development of functional assessment models. HGM has proven useful in organizing and understanding a variety of wetland data (e.g., Cole and Brooks, 2000a).
In Pennsylvania, a regional HGM classification and assessment protocol has been available for some time (see HGM key in Cole, et al., 1997). The primary focus to date in Pennsylvania has been on the development of data (water, soils, plants, macroinvertebrates) and functional assessment models for four HGM subclasses (riparian depression, slope, headwater floodplain, mainstem floodplain). Specifically, a long-term hydrologic data set (> 8 years for some sites) has allowed for a deeper understanding of function in each of these subclasses.
Although a wealth of data have been collected relative to these subclasses in Pennsylvania, these data have primarily been restricted to wetland sites in central Pennsylvania. These four HGM subclasses have only been described from the Ridge and Valley province of the Appalachian Mountains of central Pennsylvania. It is of great interest to ecologists and the regulatory community to determine if similar HGM subclasses occur further to the north and south of Pennsylvania also in the Appalachian Mountains. In other words, can we find similarly classified wetlands outside of the geographic range of the original data set for which the key and functional models were developed? More to the point, do these additional wetlands function in a comparable manner to their Pennsylvania counterparts? If so, this would allow for quick application of available functional assessment models and data rather than spend considerable additional effort in their development in other areas. This project would provide valuable information on the ability to transfer developed models across geographic boundaries.
Our goal is to determine the latitudinal extent of the HGM classification and functional assessment process developed in Pennsylvania. A broad-based wetland classification and functional assessment approach would be of great utility in the development of defensible biocriteria in the Appalachian Mountain region.
Specifically, this project addresses the following objectives:
- Determine the applicability of the HGM classification key (Cole, et al., 1997) and the functional assessment models (Wardrop, et al., 1998) to regions outside of Pennsylvania.
- Develop a set of reference wetlands in New York and Virginia, using the HGM key in Cole, et al. (1997). Additional sites will thus extend the current Appalachian wetland reference data set along a much larger latitudinal gradient (1000 km) than currently exists only in Pennsylvania.
- Apply standard assessment protocols (Brooks, et al., 1996; Wardrop, et al., 1998) and models of function (Wardrop, et al., 1998) to all wetland sites to determine if both physical structure (e.g., hydrology, soils, plant communities) and inferred function are similar (within each HGM subclass) along this gradient.
In April 2003, five headwater floodplain sites, five riparian depressions, and seven slope sites were chosen in the George Washington National Forest in Virginia and West Virginia. In May 2003, five headwater floodplain sites, five riparian depression, and six slope sites were instrumented with wells and data loggers to measure shallow ground water and inundation levels at the sites.
In July 2003, the entire field protocol was completed on nine sites in the Virginia area. The entire field protocol includes grid setup, grid survey, survey of wells on site, survey microtopography, debris census, vegetation protocol, soil pits, site map, GPS wells and baseline points, habitat similarity index (HSI), stressor checklist, photos, and voucher specimens. Three slope sites, two riparian depressions, and four headwater floodplain sites were completed. Denice Wardrop joined the team for the first 2 days of work, and Andrew Cole for 1 day the following week to provide guidance and quality control. In October 2003, a trip was made down to Virginia to download data from the wells and check the batteries for the coming winter.
Soil samples were sent to the Agricultural Analytical Lab at Penn State University (PSU), and the analysis has been received. Voucher plant specimens have been checked by Sarah Miller at the PSU Cooperative Wetlands Center (CWC) for correct identification. Field data sheets were photocopied and the copies are stored at different locations.
For the nine sites completed in 2003, unknown plant samples were identified and reconciled with the data sheets. Updated data sheets were photocopied and stored in a second location. Field and soil analysis data has been entered electronically, and data have been double checked and backed up on the Web site and CD.
In June of 2003, grid setup, vegetation protocol, soil pits, site map, GPS of wells and baseline, HSI, stressor checklist, and voucher specimens were done on eight sites (four slopes, two headwater floodplains, and two riparian depression). In August of 2003, grid survey, survey of wells, microtopography survey, debris census, and photos were completed on three slope sites. The remaining five sites were completed in the fall of 2003. In October 2003, all wells were downloaded and batteries checked for the winter. Unknown plant specimens were identified and reconciled with the data sheets. Data sheets have been photocopied and stored in a second location. Soil samples were sent to the Agricultural Analytical Lab at PSU, and results have been received. Voucher plant specimens have been checked by Sarah Miller from the CWC.
These field and soil data have been entered electronically and double checked and backed up on the Web site and by CD.
Also in 2003, an additional six slope sites were instrumented with wells, bringing the total number of slope sites instrumented up to eight. One additional riparian depression was instrumented, bringing the total to five, and three additional headwater floodplain sites were instrumented, bringing the total up to five sites.
In 2002, the entire field protocol was completed on five sites in Pennsylvania, three riparian depressions, one slope, and one headwater floodplain. Field and soil analysis data have been entered electronically and checked, as wells as data sheets archived electronically for these five sites. Hard copies of data have been stored in a second location and data backed up on the Web site and CD.
Over the summer of 2003, the entire field protocol was run on 11 sites in the Catskills. Grid setup, vegetation protocol, soil pits, site maps, HSI, stressor checklist, photos, and vouchers were completed at all sites. Four of these 11 sites in the Catskills group need to be surveyed in the spring of 2004. This will lead to 11 sites completed in the Catskills area of New York. Soil samples and voucher specimens were picked up in Cortland, New York, on September 11, 2003. The soil samples were sent to the Agricultural Analytical Lab at PSU, and the plant voucher specimens sent to the CWC at PSU for identification. All 11 sites have been instrumented with wells.
Jessica Peterson made two separate visits in June to the Catskills in New York to run the vegetation protocol with the New York team. During these trips she checked for consistency in the application of the protocol and consistency in plant identification between the New York and PSU teams. Well data from Catskill sites were downloaded in January 2004 and the Adirondacks in October of 2004, with batteries replaced.
All hydrology data from the three states has been placed into Excel files and converted to measurements of water level relative to ground surface. These data have been compared over the time period of June 2003 to October 2003, which is a common time period for all sites. Statistical measures (median, maximum, minimum, percentage of time in the root zone, inundated, and saturated) have been determined for each site and compared across sites. Cluster analyses were used to assess the validity of the classification scheme using selected hydrologic parameters: the median and the percent time in the root zone. Preliminary assessment of these clusters does not indicate clear separation of wetland subclasses with all states combined . Previous work in the Ridge and Valley Province of Pennsylvania suggests that an extended time series of hydrological data (> 1 year) is needed to capture interannual variability. As such, we may extend hydrological sampling through 2005. Descriptive statistics (mean, standard error) have been determined for soil variables over sites in all three states. Discriminant analysis, backwards method, was conducted on soil data to find variables most predictive of classification and state. To meet the assumptions of homogeneity of variance and normality for the discriminant analysis, the following variables were log transformed with the equation log10(x+1): total nitrogen, pH, phosphorus, organic matter, ammonium, potassium, and calcium. Percent clay was square root transformed. Assumptions could not be met for magnesium and nitrate, and therefore, these values were left out of the analysis. Percentage of silt was included in the discriminant analysis and required no transformation. Percent sand was excluded from the model because it was related to percent clay and silt, which could potentially cause an ill-converted matrix, violating assumptions of the analysis. For all variables found to be significant in the discriminant analysis, an analysis of variance (ANOVA) was run and least squared mean differences between state and class interactions were compared. Overview and detailed maps of site location were created with the TIGER mapping program of the U.S. Census Bureau, published at http://tiger.census.gov/cgi-bin/mapbrowse-tbl Exit .
Graduate Student Research
Stacey Hoeltje (C.A. Cole - Major Advisor). I am using the construction of a major highway in central Pennsylvania as a framework to compare ecological functions (as measured by the HGM models used for the overall project). Wetlands impacted by this construction project are undisturbed, forested, groundwater-fed slope wetlands. The created wetlands are all in a floodplain setting on the valley floor. Two comparisons are being used in this study. The first is to determine if the created floodplain sites are replacing the ecological functions lost from the impacted slope wetlands. The second will be to determine if the created mainstem floodplain wetlands perform similar ecological functions (and to the same degree) as natural reference mainstem floodplain wetlands. This comparison will determine if the created wetlands are similar to something that might be found in that landscape setting, even if they do not resemble to impacted slope wetlands.
To make these comparisons, all of the sites will be sampled using the HGM approach and the protocol used for the Appalachian wetland project. The vegetation, soils, and microtopography data will be transformed into variables, which will be applied to a suite of 12 HGM functional models. Each model will result in a number from zero to one, zero meaning that function is not supported at the site, one meaning the function is occurring at a reference standard for that site. The functional behavior of the created wetlands will be compared to that of the reference floodplains and slopes. It is important to note that these models were not developed with the intentions of applying them to created wetlands. However, if the created wetlands are truly replacing the natural wetlands, both types of wetlands should be able to be compared using this method.
Zaneta Hough (C.A. Cole - Major Advisor). This study aims to elucidate the functional differences between two wetland subclasses (riparian depression, slope-sites used from a larger U.S. Environmental Protection Agency project) by examining decomposition. This will be accomplished by employing a litter bag experiment in which the decomposition and nitrogen dynamics of a standard substrate (Phalaris arundinacea) are tracked seasonally for a 1-year period at 14 sites in central Pennsylvania (slopes n = 7, riparian depressions n = 7). Additionally, decomposition will be related to hydrologic variables to assess their influence on decomposition. Initial results from one sampling period indicate that riparian depressions have a greater mass loss (p = 0.0545) using a two-way ANOVA with subclass and plot as factors. Subsequent analysis will be done with Repeated Measures MANOVA to incorporate time as a factor.
Patrick Ryan (D.H. Wardrop - Major Advisor). Temperature, moisture, nutrient quality, and microbial activity are driving forces in controlling decomposition rates. In headwater floodplain systems, cyclic patterns of flooding and water table fluctuations correspond to alternating periods of anaerobic and aerobic states. These alternating conditions in turn affect organic matter accumulation and decomposition. It has been hypothesized that human disturbance in and around wetland systems may impact the hydrologic pattern, altering the nutrient cycling and thus the functioning of wetland systems. The question I am addressing is: Does decomposition, nutrient content, and microbial activity differ with differing degrees of human disturbance? To answer this question I conducted a litterbag study on 18 headwater floodplain sites in the Ridge and Valley physiographic province of Pennsylvania. Vegetation was collected in the late summer 2003. Control litter, from one site, was placed at all sites along with in situ litter at its perspective site. To answer my question, samples were retrieved at six intervals and analyzed for mass loss, carbon, nitrogen, lignin, cellulose, and microbial activity through substrate-induced respiration. Temperature and water levels at sites were also collected on a 2-hour and 6-hour basis, respectively.
Control and in situ litter samples were deposited at field sites in the beginning of September 2003. Collection times are at 0.5, 1, 2, 4, 8, and 12 months from the date samples were placed in the field. Mass loss numbers from the first four collections have been completed. Initial and 0.5 month samples have been processed for carbon, nitrogen, lignin, and cellulose contents. Results from the 1-month collection are currently being analyzed. Samples from the 2- and 4-month collections are dried and are being prepared for analysis. Water level data are being collected on a 6-hour basis with ecotone monitoring wells and temperature data on a 2-hour basis is being collected with HOBO® temperature loggers currently at all sites.
Work is scheduled to begin in New York in late April (depending upon snow levels). We expect to work in Virginia, Pennsylvania, and New York from May through August 2004, at which time data collection should be complete (with the probable exception of hydrology). Data entry will commence during summer and will continue through fall 2004. Because of the complexity of this project and the time likely needed for additional hydrology data during 2005, extensive data analysis, and the preparation of reports and manuscripts, we expect to ask for a 16-month no-cost extension, leaving us with a final end date of June 2006.
Six instrumented sites (one headwater floodplain, three riparian depressions, and three slopes) and one uninstrumented sites (one slope) lack the field protocol, a total of seven sites. Well data will be downloaded in May and October of 2004.
Five sites will need protocol work completed—two slopes and three headwater floodplains. Well data will be downloaded from all sites in May 2004 and again in October 2004.
Data sheets are being archived, with triplicate copies being kept in separate locations; the originals remain with Dr. Cirmo at Cortland. Soil data have already been entered electronically and double checked at PSU. Field data are currently being electronically entered by Lauren McChesney in Cortland, New York. Lauren met with Jessica Peterson at PSU the last week of February to synchronize data entry and data analysis efforts between the PSU and Cortland teams. Unknown plant specimens from New York were identified by Sarah Miller at the CWC, and she is currently checking voucher specimens.
Surveying will be completed at the last four sites in the Catskills in April by Lauren McChesney and Jessica Peterson.
Eleven sites in the Adirondack Region have been identified and instrumented with wells in the summer and fall of 2003. In the summer of 2004, protocol will be completed at these 11 sites. Jessica Peterson will make a trip up for a week to assist the New York team and act as quality control.