Final Report: Vegetative Indicators of Condition, Integrity, and Sustainability of Great Lakes Coastal Wetlands

EPA Grant Number: R828675C002
Subproject: this is subproject number 002 , established and managed by the Center Director under grant R828675
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).

Center: EAGLES - Great Lakes Environmental Indicators Project
Center Director: Niemi, Gerald J.
Title: Vegetative Indicators of Condition, Integrity, and Sustainability of Great Lakes Coastal Wetlands
Investigators: Johnston, Carol A. , Bedford, Barbara L. , Kelly, John T. , Zedler, Joy B.
Institution: University of Minnesota , Cornell University , U.S. Environmental Protection Agency , University of Wisconsin - Madison
EPA Project Officer: Packard, Benjamin H
Project Period: January 10, 2001 through January 9, 2005
RFA: Environmental Indicators in the Estuarine Environment Research Program (2000) RFA Text |  Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Water , Ecosystems

Objective:

The specific objectives of this research project were to: (1) identify vegetative indicators of condition of Great Lakes coastal wetlands that can be measured at a variety of scales; (2) develop relationships between environmental stressors and those vegetative indicators; and (3) make recommendations about the utility and reliability of vegetative indicators to guide managers toward long-term sustainable development.

Summary/Accomplishments (Outputs/Outcomes):

Methods

Wetland study sites were selected using an objective, stratified random statistical design spanning anthropogenic stressor gradients representing the entire geographic range of the U.S. Great Lakes coast. The 90 wetlands selected for study were distributed from the western end of Lake Superior to the eastern end of Lake Ontario. Sites were classified by hydrogeomorphic type as open-coast wetlands (n = 27), riverine wetlands (n = 35), or protected wetlands (n = 28). Sampling took place from 2001 to 2003 and was restricted to the months of July and August to ensure that most of the vegetation could be identified and peak annual growth was observed.

Sampling was done in 1 x 1-m2 plots distributed along randomly placed transects within areas of herbaceous wetland vegetation in the study sites selected. Transects were established with GIS prior to field campaigns, using a program called Sample (http://www.quantdec.com/sample Exit ) to randomize transect placement (Johnston, et al., in press). Transects were placed in areas mapped by national and state wetland inventories as emergent wetland vegetation. Each transect intersected a randomly selected point generated by the Sample program and was oriented to be perpendicular to the perceived water depth gradient, extending from open water to the upland boundary (or to a shrub-dominated wetland zone, if present). Transect length and target number of sample plots were determined in proportion to the size of the wetland to be sampled (20 plots/60 ha, minimum transect length = 40 m, minimum plots/site = 8). Transect coordinates were uploaded into a handheld GPS for use by field crews.

Plot locations were established in the field by dividing each transect into 20 m segments and randomly locating a plot in each segment using a random number table. Within each plot all vascular plant species were identified to the lowest taxonomic division possible. Large, identifiable nonvascular plants, such as Chara vulgaris L. and Sphagnum spp., also were given cover estimations. If a plant species could not be identified in the field, it was collected, pressed, and identified in the laboratory, but voucher specimens were not collected routinely. Percent cover was estimated visually for each taxon according to modified Braun-Blanquet cover class ranges: less than 1 percent; 1 to less than 5 percent; 5 to less than 25 percent; 25 to less than 50 percent; 50 to less than 75 percent; or 75 to 100 percent. Prior to data analyses, cover classes were converted to the midpoint percent cover of each class using the algebraic mid-points of the six cover class ranges (0.5, 3.0, 37.5, 62.5, 87.5). Field teams were jointly trained and tested to ensure consistency of visual observations (Kercher, et al., 2003).

Indicator Evaluation and Development

Research was conducted to evaluate existing indicators and develop new indicators. We identified indicators that were not useful as indicators.

Species Richness. We listed species richness (i.e., number of species per unit area) as a candidate indicator in our original proposal and expected that increased stress would decrease species richness. We found that species richness was suppressed by tall invasive plant species such as Typha x glauca and Phragmites australis (Figure 1), but that species richness was not in itself a good indicator of condition. Bourdaghs, et al. (in review) found species richness to be a much poorer indicator than either the floristic quality index (FQI) or mean coefficient of conservatism.

Percent of all Taxa That Are Obligate Wetland Plants. We expected that the proportion of obligate wetland species would decrease with increasing anthropogenic stress. The relationship was weak, however, because the vast majority of the plants we encountered were obligate wetland species, regardless of the environmental condition of the wetlands sampled. This metric was poorly related (r2 = 0.057) to the overall stress index developed by Danz (see overall report for R828675).

Presence of Endangered or Threatened Species. We encountered state-listed species in several wetlands in Michigan, Ohio, Pennsylvania, and New York, but our sampling methodology was not designed to seek out endangered or threatened species, so we could not test its utility as an indicator of environmental condition.

he Three Tallest Plant Species, Invasive Cattails, and <em>Phragmites</em>, Shade Out Other Plant Species in Their Plots

Figure 1. The Three Tallest Plant Species, Invasive Cattails, and Phragmites, Shade Out Other Plant Species in Their Plots

Existing Indicators That Were Effective Indicators

FQI and Mean Coefficient of Conservatism. These existing indices are both based on the coefficient of conservatism (C), which is a numerical score from 0 to 10 assigned to each plant species in a local flora that reflects the likelihood that a species is found in remnant natural habitats. Such lists are compiled by state and currently exist for four of the states in which we sampled coastal wetlands: Wisconsin, Michigan, Ohio, and Illinois. FQI is computed by multiplying the mean coefficient of conservatism by the square root of species richness for an observational unit. FQI and mean C were better at discriminating differences between sites, independent of a condition gradient, than species richness alone, but neither index type outperformed the other. Both types of indices also were found to be acceptable ecological indicators of condition, although floristic quality indices consistently outperformed coefficient of conservatism indices in this capacity. FQI had an r2 = 0.56 with the stress index developed by Danz.

Percent of all Taxa That Are Native Plants. This indicator was significantly related (r2 = 0.326) to the stress index developed by Danz, and it was particularly sensitive to the proportion of row crop area in watersheds draining to coastal wetlands.

New Indicators of Environmental Condition

We developed several new indicators using the wetland vegetation data. Each is briefly described below.

Multitaxa Wetland Vegetation Indices. Two indices based on either a 10-taxa index or a 4-taxa index were developed. Each uses mean percent cover estimated in a series of 1 m x 1 m transects spanning a moisture gradient within emergent wetland stands. The indices both were shown to be highly correlated with the stress index that represented a variety of stressors affecting these wetland systems. The indices are relevant to the entire Great Lakes coastal system because the taxa used are all widespread throughout the region.

Maximum Canopy Height. This index is a relatively simple metric of plant biomass within a wetland. Maximum canopy height of wetland plants as measured during the maximum growth stage in July or August was highly correlated with the stress index. This measurement is related to several factors associated with disturbance in wetland systems including: (1) fertilization by nutrients contributed by non-point source pollution, (2) invasive plant species that tend to be taller than non-invasive species, and (3) tall plants shade out other plants which results in reductions of plant biological diversity within the wetland. This indicator is relevant to all Great Lakes coastal wetlands and may have applications to many other wetland systems.

Species Dominance Index (SDI). This index indicates ecological integrity of wetland ecosystems by identifying dominant plant species and categorizing their behavior as one of seven forms of dominance. The index combines three related attributes of dominance in a similar fashion that is commonly used by plant ecologists for the calculation of importance values. Dominance uses three attributes: mean plant cover (abundance of the dominant species), mean species suppression (number of species associated with the dominant species), and tendency toward high cover (the likelihood that a species is abundant when it occurs). SDI is calculated like an importance value in which each value is standardized from 0 to 1, summed, and divided by 3. Cut-off values can be assigned for the various forms of dominance in a wetland.

The index is useful because a dominant plant species may control its habitat and the presence and performance of other species in the wetland community. The concept is transferable to any wetland. It has been examined for use in restoration efforts at the University of Wisconsin (UW), in microcosms, and in both natural and restored salt marshes in southern California.

Zedler has initiated a new series of “Arboretum Leaflets” that are posted at a link from the UW Arboretum Web Site (http://www.botany.wisc.edu/zedler/leaflets.html Exit ). These documents summarize the SDI as well as other relevant material on wetland ecosystems.


Journal Articles on this Report : 5 Displayed | Download in RIS Format

Other subproject views: All 37 publications 9 publications in selected types All 7 journal articles
Other center views: All 268 publications 54 publications in selected types All 45 journal articles
Type Citation Sub Project Document Sources
Journal Article Bourdaghs M, Johnston CA, Regal RR. Properties and performance of the Floristic Quality Index in Great Lakes coastal wetlands. Wetlands 2006;26(3):718-735. R828675C002 (Final)
  • Abstract: SpringerLink-Abstract
    Exit
  • Journal Article Frieswyk CB, Zedler JB. Vegetation change in Great Lakes coastal wetlands: deviation from the historical cycle. Journal of Great Lakes Research 2007;33(2):366-380. R828675 (Final)
    R828675C002 (Final)
  • Full-text: Science Direct PDF
    Exit
  • Abstract: BioOne Abstract
    Exit
  • Journal Article Johnston CA, Meysembourg P. Comparison of the Wisconsin and National Wetlands Inventories. Wetlands 2002;22(2):386-405. R828675 (Final)
    R828675C002 (2002)
    R828675C002 (2003)
    R828675C002 (Final)
  • Full-text: University of Minnesota PDF
    Exit
  • Abstract: BioOne
    Exit
  • Journal Article Johnston CA, Bedford BL, Bourdaghs M, Brown T, Frieswyk C, Tulbure M, Vaccaro L, Zedler JB. Plant species indicators of physical environment in Great Lakes coastal wetlands. Journal of Great Lakes Research 2007;33(Suppl 3):106-124. R828675C002 (Final)
  • Full-text: Science Direct PDF
    Exit
  • Abstract: BioOne-Abstract
    Exit
  • Journal Article Kercher SM, Frieswyk CB, Zedler JB. Effects of sampling teams and estimation methods on the assessment of plant cover. Journal of Vegetation Science 2003;14(6):899-906. R828675 (Final)
    R828675C002 (2002)
    R828675C002 (2003)
    R828675C002 (2004)
    R828675C002 (Final)
    R828010 (Final)
  • Full-text: University of Wisconsin - Full Text PDF
    Exit
  • Abstract: Wiley Online-Abstract
    Exit
  • Supplemental Keywords:

    Great Lakes, monitoring, indicators, risk assessment, stressor, ecological effects, animal, plant, diatoms, toxics, aquatic ecosystem, aquatic ecosystems, atmospheric pollutant loads, climate variability, coastal ecosystem, coastal environments, diatoms, ecological assessment, ecological condition, ecological response, ecosystem assessment, ecosystem impacts, ecosystem indicators, ecosystem stress, environmental consequences, environmental stressor, environmental stressors, estuarine ecosystems, hierarchically structured indicators, human activities, hydrologic models, hydrological, hydrological stability, nutrient stress, nutrient supply, nutrient transport, toxic environmental contaminants,, RFA, Scientific Discipline, ENVIRONMENTAL MANAGEMENT, Geographic Area, Water, ECOSYSTEMS, Ecosystem Protection/Environmental Exposure & Risk, Nutrients, Ecosystem/Assessment/Indicators, Ecosystem Protection, Ecological Effects - Environmental Exposure & Risk, Environmental Monitoring, Ecological Monitoring, Ecological Risk Assessment, Ecology and Ecosystems, Great Lakes, Ecological Indicators, Risk Assessment, ecological condition, nutrient supply, coastal ecosystem, nutrient transport, aquatic ecosystem, diatoms, hydrological stability, ecosystem assessment, hierarchically structured indicators, wetland vegetation, vegetative indicators, environmental stressor, hydrological, coastal environments, environmental consequences, ecological assessment, estuarine ecosystems, nutrient stress, ecosystem indicators, aquatic ecosystems, toxic environmental contaminants, water quality, ecosystem stress

    Relevant Websites:

    http://glei.nrri.umn.edu Exit
    http://www.botany.wisc.edu/zedler/leaflets.html Exit

    Progress and Final Reports:

    Original Abstract
  • 2001
  • 2002 Progress Report
  • 2003 Progress Report

  • Main Center Abstract and Reports:

    R828675    EAGLES - Great Lakes Environmental Indicators Project

    Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
    R828675C001 Great Lakes Diatom and Water Quality Indicators
    R828675C002 Vegetative Indicators of Condition, Integrity, and Sustainability of Great Lakes Coastal Wetlands
    R828675C003 Testing Indicators of Coastal Ecosystem Integrity Using Fish and Macroinvertebrates
    R828675C004 Development and Assessment of Environmental Indicators Based on Birds and Amphibians in the Great Lakes Basin
    R828675C005 Development and Evaluation of Chemical Indicators for Monitoring Ecological Risk