Final Report: Development of an Optical Indicator of Habitat Suitability for Submersed Aquatic Vegetation

EPA Grant Number: R828684C002
Subproject: this is subproject number 002 , established and managed by the Center Director under grant R828684
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).

Center: EAGLES - Atlantic Slope Consortium
Center Director: Brooks, Robert P.
Title: Development of an Optical Indicator of Habitat Suitability for Submersed Aquatic Vegetation
Investigators: Wardrop, Denice Heller , Havens, Kirk , Hershner, Carl , Thornton, Kent
Institution: Pennsylvania State University - Main Campus , FTN Associates Ltd. , Virginia Institute of Marine Science
EPA Project Officer: Hiscock, Michael
Project Period: March 1, 2001 through February 28, 2005 (Extended to February 28, 2006)
RFA: Environmental Indicators in the Estuarine Environment Research Program (2000) RFA Text |  Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Water , Ecosystems

Objective:

This was one of four projects under the Atlantic Slope Consortium (ASC) Center. It was related closely to Project R828684C001. The objective of this research project was to develop a regionally extensive diagnostic indicator of habitat suitability for submerged aquatic vegetation (SAV) based on optical properties. For this purpose, field studies were conducted to understand the regional variation in optical properties of suspended particulate material in the Chesapeake Bay region.

A healthy aquatic ecosystem is one that can sustain its intended uses. This simple statement defines the approach our research team has taken in the search for useful indicators of aquatic system conditions in the mid-Atlantic region. This has been a useful strategy based on our desire that indicators meet tests of both technical merit and practicality.

Developing indicators of aquatic ecosystem health that are practical tools for resource management means the concept of health must be defined so that it is possible to measure and that the indicators link health directly with management needs and practices. This objective helped us focus on ecosystem services rather than the fuzzy concept of sustainability. This objective also incorporates the selection of reference conditions and provides a direct connection to the water quality management goal of attaining designated aquatic uses. Focusing on ecosystem services reduced the number of options for indicator development.

Indicators intended to inform management must be practical. The underlying metric must be something that has a reasonable cost:information ratio. Metrics that require unique analytical capabilities are likely to find only limited application, whereas metrics using commonly available analytical capabilities and technologies will have comparatively greater utility.

A final challenge in the development of indicators of aquatic ecosystem health is identifying those metrics that show a response over the entire gradient of stress from no or minimal stress to severely stressed. An underlying construct in many indicator development efforts has been the presumption that health of aquatic ecosystems can be described along a gradient of stress. Increasing levels of stress are assumed to result in a corresponding reduction in health. This dose-response model suggests that indicators are inadequate if they cannot detect changes over the gradient in stressors.

Summary/Accomplishments (Outputs/Outcomes):

This is a summary report for the NCER Web Site. A more detailed report entitled “Integration of Ecological and Socioeconomic Indicators for Estuaries and Watersheds of the Atlantic Slope,” which includes additional figures, is available on the Web at http://www.asc.psu.edu/public/pubs/_Final Report_AtlanticSlopeConsortium.pdf (PDF, 96pp., 2.88MB, about PDF) Exit .

We recognized that if the indicators developed during the ASC project are to be integrated into environmental decisionmaking, it is imperative to provide a framework for indicator selection and use. Management efforts generally are directed at answering the following basic questions:

  • How big is the problem (e.g., where is the resource, and what is its condition)?
  • Is it getting better or worse?
  • What is causing it?
  • What can be done to fix the problem (e.g., how can we improve the health of the impaired system, and what level of health can be maintained)? Once action is taken, is management making a difference? How can any of the above be communicated to the public?

How do we know which indicator to use to answer any or all of the above questions? There are many existing frameworks for indicator selection. Many of these frameworks, however, are concerned with the use of ecological indicators only for describing system condition, status, and trends, degree of stressor impact, or system sustainability. Therefore, each represents only a narrow range of questions posed to managers. A more general framework is required, one that is broad enough to address the range of decisions that an environmental manager must make (e.g., assessment through restoration), as well as other issues affecting the general public. The framework, however, also must be detailed enough to cover the technical concerns that developers of indicators consider essential to their proper use (e.g., the spatial/temporal extent over which the indicator is valid). Finally, because the framework is meant to support decisionmaking, it also must address the existing social and environmental constraints of the management unit (i.e., what is the predominant land use). We propose a taxonomy based upon three elements: the type of question being asked, the spatial and temporal scale of interest, and the context or land use (social choices). The proposed taxonomy is depicted in Figure 1; each element is described in detail below.

Figure 1. Taxonomy of Ecological Indicators

Type of Question

Given the basic questions listed previously, we propose the following categories in our taxonomy:

  1. Condition assessment/state: snapshot of the current state of the ecosystem. With condition indicators, measurements are compared to a threshold or value(s) to indicate whether the system is in good or poor condition. Examples are Indices of Biotic Integrity (IBIs) that have been developed for a number of organisms, including fish and birds. Trends in ecological health can be assessed by monitoring condition indicators over time.
  2. Performance evaluation: evaluating the effectiveness of management actions. Evaluation indicators must embody two criteria: responsiveness to management actions and relevance at the management spatial and temporal scale. An example might be increased fish IBI scores because best management practices to reduce stream bank erosion were implemented in a watershed.
  3. Stressor diagnosis: identification of factors causing a change in condition and demonstration of clear relationship between cause and condition. Examples include stream bank erosion (stressor) and decreased diversity in fishes (condition) or increased nutrient loading (stressor) and estuarine harmful algae blooms (condition). Identification of factors at a multitude of spatial and temporal scales is desirable. For many management decisions, particularly at larger spatial scales, associations or correlations among condition and stressor indicators, rather than cause-effect relationships, can be sufficient.
  4. Communication to the public: encouraging comprehension of condition in a clear and understandable form. These indicators must be both useful and relevant. Examples include both the Sneaker Index (i.e., being able to see your sneakers in waist-deep water) and blue crab abundance in the Chesapeake Bay (http://www.chesapeakebay.net/indicators.htm Exit ).
  5. Futures assessment: estimating the probable trend in condition or assessing the vulnerability of a system to a particular event or activity. These indicators are utilized most often at large spatial and temporal scales. Examples include regional responses to climate change, such as impacts to agricultural and forestry production, fresh water quality and quantity, and biodiversity.

Spatial and Temporal Scale

Ecological indicators document the state of ecological structure, such as biotic diversity, rate of ecological function, or production. Indicators may measure processes directly (such as primary productivity of seagrass beds) or infer structure from pattern (such as utilizing IBIs as descriptors of community structure). Ecological patterns emerge, and processes operate, at a range of spatial and temporal scales. This leads us to the inevitable conclusion that the relevant scales must be specified when selecting indicators. Most resource management decisions occur at local levels (i.e., county, community, land zones). Therefore, we thought that a relevant scale for monitoring coastal indicators would be a small watershed (i.e., U.S. Geological Survey [USGS]) 14-digit hydrologic category, which typically is tens to hundreds of km2 and encompasses several stream or river reaches, with adjacent riparian corridors, associated wetlands and waterbodies, and the contributing drainage basin), or an estuarine segment (composed of deepwater areas, vegetated and unvegetated shallows, tidal wetlands and creeks, and the adjacent terrestrial habitats). Thus, indicators developed during this ASC project can be validated at the scale at which most management decisions are made and implemented. The categories of spatial and temporal scale designated in the taxonomy are a first attempt to recognize applicable scales for coastal indicators, and include scales both larger/longer and smaller/shorter than the small watershed or estuarine segment. It is expected that users of the taxonomy will decide what categories of scale are relevant to them.

Context of the Question

Identification of context requires us to ask ourselves the following: To whom do we want to be compared? What is a useful comparison? In many cases, the health of the system is compared to how far that system has departed from an ideal condition. In environmental management, the ideal traditionally has been a system devoid of human impact. Although this comparison has utility in a general assessment of condition, it has little relevance in environmental decisionmaking for a variety of reasons. First, there are few, if any, systems or landscapes devoid of human impact. Second, a pristine condition often is unattainable, so a more realistic benchmark needs to be identified. For example, in an urbanized watershed, restoration to a pristine condition is neither possible nor sustainable. What is needed is a relevant benchmark for an urban watershed: what are realistic expectations for the best urban watershed? The problem is one of identifying system condition benchmarks for watersheds having different human use contexts. The conditions one would expect to find in a forested wilderness are vastly different than those expected in an urban watershed.

The research mandate of the ASC project was to identify relevant benchmarks for small watersheds and estuarine segments within the context of various “social choices.” The term “social choice” is used to mean the predominant land use in a watershed because these land-use patterns are the cumulative result of individual social choices. When land-use patterns in small watersheds across the mid-Atlantic are examined, four major categories can be identified: forested, agriculture, urban, and mixed (i.e., no one land-use type is predominant) (Figure 2). For each context or social choices category, we can ask three questions: (1) How “good” can the environment be, given those social choices? (2) What are the causes of its current condition? (3) What can be done to improve condition?

Figure 2. Predominant Land-Use Categories or “Social Choices” Evaluated in ASC Watersheds

The framework indicates there are both multiple ecological states and multiple reference conditions that satisfy various social choice and spatial/temporal scale categories. All of the ASC indicators were characterized within this taxonomy. A Fish Community Index (FCI) developed for the ASC will provide an example of how the framework can be used to select an indicator, as well as determining the usefulness of the indicator.

Case Study

As part of the ASC project, an FCI was developed and tested as an indicator of ecosystem health in the unique environment of nearshore, shallow water estuarine systems. The resulting FCI is presented as a case study to demonstrate the utility of the taxonomy.

Biotic and habitat variables often are developed together, because they generally represent the response and stressor axes, respectively, of the cause-effect (stressor-condition) curve. We linked response to probable stressors by evaluating the FCI in relation to habitat condition metrics that were assessed at multiple spatial scales (subtidal habitat, shoreline condition, and watershed land use). Within the study area (Chesapeake Bay), habitat conditions were characterized in estuarine segments that represented the variability in dominant land use types of surrounding watersheds. The FCI fits into the taxonomy as follows. The FCI is a straightforward indicator of condition.

At each estuarine segment in the study, the following were measured: shoreline land use, shoreline structures (piers, riprap, etc.), subtidal habitat, and macrobenthic and fish communities. The segments were part of an experimental design that was stratified according to dominant watershed land use. Biotic responses were correlated with habitat condition in the nearshore area and along the shoreline (Figure 3). Because correlations between habitat and biota were noted, if clear stressor-condition relationships can be determined and thresholds of response established, then shoreline surveys can become an essential diagnostic management tool.

Links among habitat metrics were evidenced between subtidal habitat and shoreline condition, as well as riparian and watershed land use. For example, as shoreline condition improved, the amount of subtidal habitat increased (e.g., woody debris, amount of submerged aquatic vegetation). These relationships provide opportunities for the development of restoration measures. If thresholds of shoreline alteration can be established that impact fish communities, then the shoreline condition assessment (currently underway) will provide a spatially flexible tool to predict and test for expected biotic responses. These indicators then could be utilized to predict future biotic responses to a given shoreline condition scenario.

Figure 3. Chart of Indicators, Spatial/Temporal Scales of Interest, and Societal Choices

Spatial and Temporal Scale

The spatial scale of the FCI ranges from site to watershed level, depending on the associated habitat feature. For instance, when assessing subtidal habitat, the indicator addresses site-level impacts, and when assessing watershed land use, the FCI addresses watershed-level impacts. Temporally, the FCI currently operates over a short timescale. The use of long-term monitoring data, however, allows for the expansion of the timescale to multiple years.

Context of the Question

To develop and test the FCI and habitat measures, 25 watersheds (14-digit, hydrologic unit code [HUC]) were selected throughout low-to-moderate salinity regions of the Chesapeake Bay. Each watershed was placed into one of three broad land-use categories based on principal land use percentages, forested, agricultural, or developed, and the FCI was mapped onto these broad land-use categories. Developed and agricultural watersheds had significantly lower FCI scores than did forested ones.

Conclusions:

Primary elements of the taxonomy are intended to address explicitly three major obstacles to effective identification of impaired areas and their restoration: the type of question being asked, the spatial and temporal scale of interest, and identification of appropriate benchmark reference domains. Indicators are categorized as to which fundamental question they are useful in answering. They also are categorized so managers can select those that are useful for their spatial (stream reach, watershed, ecoregion, state) and temporal (day, season, year) management frame of reference and interest. Finally, the taxonomy identifies major classes of landscape patterns that emerge from individual social choices to provide the necessary context for the questions being asked. The taxonomy indicates there are both multiple ecological states and multiple reference conditions that satisfy various social choice and spatial/temporal scale categories.

We believe the three primary elements of question, scale, and context are the most compelling basis of the taxonomy. We envision the taxonomy providing the following assistance:

  • Guiding indicator selection.
  • Evaluating existing ecosystem indicator programs to identify conditions or stressors that currently are lacking indicators.
  • Designing and developing new ecosystem indicator programs.

Journal Articles:

No journal articles submitted with this report: View all 5 publications for this subproject

Supplemental Keywords:

indicators, integrated assessment, wetland, stream, estuary, watershed, biological integrity, decisionmaking, ecosystem, environmental exposure and risk, geographic area, ecology, exposure indicators, bioindicators, land use, mid-Atlantic, hydrology, estuarine ecosystems,, RFA, Scientific Discipline, Air, ENVIRONMENTAL MANAGEMENT, Geographic Area, Water, ECOSYSTEMS, Ecosystem Protection/Environmental Exposure & Risk, Hydrology, Nutrients, Ecosystem/Assessment/Indicators, Ecosystem Protection, climate change, Air Pollution Effects, Ecological Effects - Environmental Exposure & Risk, Terrestrial Ecosystems, Ecological Monitoring, Mid-Atlantic, Ecological Risk Assessment, Biology, Atmosphere, Ecological Indicators, Risk Assessment, environmental monitoring, remote sensing, coastal ecosystem, aquatic ecosystem, bioindicator, degradation, ecological exposure, ecosystem assessment, watersheds, aquatic biota , optical indicators, socioeconomics, aquatic habitat, biomonitoring, ecological assessment, estuarine ecosystems, integrated assessment, nutrient stress, ecosystem indicators, Atlantic Slope Consortium, submerged aquatic vegetation, aquatic ecosystems, environmental stress, integrative indicators, bioindicators, Chesapeake Bay trophic network, ecosystem stress, Chesapeake Bay

Relevant Websites:

http://www.asc.psu.edu/ Exit
http://www.chesapeakebay.net/indicators.htm Exit
http://www.asc.psu.edu/public/pubs/_Final Report_AtlanticSlopeConsortium.pdf (PDF, 96pp., 2.88MB, about PDF) Exit

Progress and Final Reports:

Original Abstract
  • 2001
  • 2002 Progress Report
  • 2003 Progress Report
  • 2004 Progress Report

  • Main Center Abstract and Reports:

    R828684    EAGLES - Atlantic Slope Consortium

    Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
    R828684C001 Integrated Assessment of Estuarine Ecosystems
    R828684C002 Development of an Optical Indicator of Habitat Suitability for Submersed Aquatic Vegetation
    R828684C003 Integrated Assessment of Watersheds
    R828684C004 Socioeconomic and Institutional Research