## Assessment of Wetland Ecosystem Condition across Landscape Regions: A Multi-metric Approach > [!Cite]- > Faber-Langendoen, Don, Joe Rocchio, Steve Thomas, Mike Kost, Cloyce Hedge, Bill Nichols, Kathleen Strakosch Walz, et al. “Assessment of Wetland Ecosystem Condition across Landscape Regions: A Multi-Metric Approach,” n.d. ## Notes %% begin notes %% %% end notes %% %% begin annotations %% ## Annotations | evernote 2016.04.27 EPA's Environmental Monitoring and Assessment Program (EMAP) is a research program to develop the tools necessary to monitor and assess the status and trends of national ecological resources over broad spatial and temporal scales. We tested and applied the method using a multi-level framework (remote, rapid, intensive) and multiple metrics that cover hydrology, soils, vegetation, size, buffer, and landscape. Ecological integrity can be defined as “an assessment of the structure, composition, and function of an ecosystem as compared to reference ecosystems operating within the bounds of natural or historic disturbance regimes.” This broad definition can serve as a guide to developing ecological integrity assessment methods that are distinct from related assessment methods for ecological functions or ecosystem services. Critical to our effort was the use of conceptual models that highlight ecological factors and attributes for which metrics (or specific indicators) of integrity are most needed. We defined metrics as values derived from specific measures (e.g., basal area, stand structural class, species diversity) that inform us about the status of an ecological factor or attribute of integrity. For our model, the primary rank factors and major ecological factors were landscape context (landscape, buffer), size, and condition (vegetation, soils, and hydrology). We then selected key metrics that are most responsive, practical, cost-effective and well-tested in measuring the condition of the ecosystem. The conceptual model also provided a structure in which to identify known stressors, or agents of change, that affect these major ecological factors. Together they can help guide management decisions to maintain or restore ecological integrity. Data on the ecological condition of ecosystems can be used for ambient monitoring of status and trends, to prioritize sites for conservation or restoration, guide mitigation applications at site and watershed or landscape scales and contribute to land use planning (Fennessy et al. 2007, Faber-Langendoen et al. 2008). For example, as part of the National Wetland Condition Assessment in 2011, the Environmental Protection Agency (EPA) carefully designed a comprehensive field survey methodology to assess wetland condition, relying on a reference site approach to establish the criteria for wetland condition (USEPA 2011). They were able to draw on a growing body of assessment methods that provide standardized field sampling and reporting methods for assessing ecological condition (e.g., Mack 2001, 2004, Herrick et al. 2005, Pellant et al. 2005, Collins et al. 2006, Fennessy et al. 2007). There are a number of ways to approach condition assessments, and it is important to clarify the conceptual bases for doing so, in order to ensure that the methods address their intended goals. One important basis on which to assess condition is that of ecological integrity (Andreasen et al. 2001). Building on the related concepts of biological integrity and ecological health, ecological integrity is a broad and useful endpoint for ecological assessment and reporting (Harwell et al. 1999). Building upon this foundation, others suggested interpreting the integrity of ecosystems by developing suites of indicators or metrics comprising key biological aspects of ecosystems, such as Vegetation IBIs (Mack and Kentula 2010), or more broadly to included, biological, physical and functional attributes of those ecosystems (Harwell et al. 1999, Andreasen et al. 2001, Parrish et al. 2003). Critical to this endeavor is the use of conceptual models that highlight ecological attributes for which indicators of integrity are most needed. A conceptual ecological model delineates linkages between key ecosystem attributes and known stressors, or agents of change. It helps identify the ecological attributes we most need to understand regarding the ecological dynamics of the ecosystem, and which we must address when making management decisions to maintain ecological integrity (Noon 2003).  The goal of an ecological integrity assessment is to provide a succinct assessment of the current status of the composition, structure and processes of a particular occurrence of an ecosystem type. Objectives of an ecological integrity assessment can include \[summarized\]: - Prioritize interventions - Track status over time - Contribute to information on conservation status - Prioritize field survey work - Assess restoration/mitigation efforts - Inform species populations viability ranks (based on the integrity of ecological systems they depend upon) Assessments of ecosystem condition can be based on observations defined as points, polygons, or patches \[e.g., rasters\]. The natural variation in both space and time is thus essential to shaping ecosystems. Consequently, the natural range of variability depends on specifying the time frame. For purposes of assessment projects, where the horizon is usually 30 to 100 years, we normally treat the natural variability in each key attribute of a system as occurring within stable limits. However, there may be situations in which this is not appropriate. Resource managers often use the concept of a range of natural variability (RNV) (e.g. Landres et al. 1999, Oliver et al. 2007). Given these challenges, it is important to emphasize what can and cannot be achieved by using RNV as a component of ecological integrity (Higgs and Hobbs 2010). To suggest that we can simply take over the management of natural ecosystems without understanding RNV is to invite failures in these complex systems (restraint and respect). Because it can be difficult to define what is natural, alternative terms have been suggested, including “acceptable range of variation” (Parrish et al. 2003). Our method is based on the following set of key steps: 1. determine the purpose of the assessment 2. develop a general conceptual model for wetlands, adapted, as needed, for various ecosystem types 3. rely on indicators of ecological attributes that span the major structural, compositional and ecological processes of the system 4. select indicators across three levels of assessment – (i) remote sensing, (ii) rapid ground-based, and (iii) intensive ground-based metrics5. scale the thresholds or assessment points of the indicators based, in part on ranges of natural and historic variability, ecological models, benchmark or reference sites6. summarize indicators using ratings and integrate into an overall index of ecological integrity The result \[of a conceptual model\] is a set of hypotheses about how the system functions, its defining characteristics and dynamics, and critical environmental conditions and disturbance regimes that may act as drivers of these characteristics and dynamics. These hypotheses both guide management and monitoring, and highlight gaps in knowledge that require additional investigations (Unnasch et al. 2009). Metrics are sometime referred to as indicators, and here we use the term in the sense of a fine-grained indicator. For clarity, we distinguish “metrics” from both “measures” and “general indicators.” Measures are those values that are collected directly in the field (e.g., diameter of tree at breast height, species percent cover) and metrics are values derived from specific measures (e.g., basal area, stand structural class, species diversity) that inform us about the status of an ecological attribute of integrity. Metrics are selected to meet ecological, technical and management needs (Tierney et al. 2009, Unnasch et al. 2009, Fancy 2009).  Metric Evaluation Critieria: - Specific (redundancy) - Sensitive (descriminatory) - Comprehensive (range) - Measurable - Technically feasible - Timely - Cost-effective - Partner-based: compatible with the practices of key partners, or based on measures they already collect - Legal mandates A variety of statistical methods are available to help assess the statistical rigor of metrics, applicable to both rapid and intensive metrics. The most readily assessed criteria include comprehensive range, discriminatory power or responsiveness, and redundancy (Blocksum et al. 2002, Klemm et al. 2003, Jacobs et al. 2010). %% end annotations %% %% Import Date: 2024-08-15T08:00:01.962-06:00 %%