Development of volunteer-driven indices of biological integrity for wetlands in West Virginia

Wetland indices of biological integrity (IBIs) are used to satisfy the water resources monitoring requirements of the Clean Water Act (CWA). However, debate still exists on what classification systems and taxa to base these IBIs upon. Our cumulative research, representing indices of biological integrity designed for regional HGM subclasses, designated HGM management classes and Cowardin et al. (1979) classes for West Virginia. The indices were derived from metrics calculated from anuran, avian, macroinvertebrate, and vegetation communities; each representing increasing levels of resources associated with gathering the necessary data. For example, avian and anuran data used to derive floodplain wetland IBI metrics can be collected by volunteers, but the disturbance scores only account for 46% and 18% of the variation in IBI scores, respectively. Alternatively, the disturbance scores account for 56% and 47% of the variation in vegetation and invertebrate IBI scores, respectively. However, if the floodplain wetland was also a scrub-shrub wetland, by adding the avian and anuran metrics of both floodplain and scrub-shrub IBIs, the resulting hybrid-class, multi-taxa IBI disturbance scores accounts for 89% of the variation in IBI scores. We evaluate each of these taxa groups alone and in combination, in single and hybrid classification schemes, to examine changes in sensitivities to the disturbance gradient. The result is a decision making tool that can assist resource managers by providing them with the opportunity to stretch finite resources; while still ensuring the monitoring captures changes in wetland communities due to human disturbance.;Keywords. Indices of biological integrity, IBIs, wetlands, disturbance, anuran communities, avian communities, macroinvertebrate communities, vegetation communities, West Virginia

Using multiple taxa and wetland classification schemes for enhanced detection of biological response signatures to human impairment

Wetland indices of biological integrity (IBIs) are a common component in monitoring the wetland water resources as required by the United States’ Clean Water Act (CWA). The effectiveness of an IBI to monitor disturbance is dependent on the metrics being consistently responsive to measures of human disturbance within a described classification category. We present IBIs designed for two types of commonly used wetland classification systems – the hydrogeomorphic (HGM) and the National Wetlands Inventory (NWI). The metrics making up the IBIs were derived from anuran, avian, macroinvertebrate, and vegetation communities; each representing increasing levels of resources associated with gathering the necessary data. Knowing which communities’ data best corresponds to impairment can maximize limited wetland monitoring resources, especially if the response differs based on the wetland vegetation type NWI or HGM position on the landscape. By combining these two classification schemes together, to better define a wetland’s form and context on the landscape, more of the variability in community metrics are explained by human impairment. Moreover, when multiple taxa are used within a single wetland classification scheme, the response of the multi-taxa community IBI to the human disturbance gradient is often more sensitive than one-taxa group alone. This approach, a combination of taxa, in hybrid 2-system classification schemes, creates additional utility in measuring the effectiveness of wetland assessments and, or restoration success

Obligations of Researchers and Managers to Respect Wetlands: Practical Solutions to Minimizing Field Monitoring Impacts

Research and field monitoring can disturb wetland integrity. Adoption of ethical field practices is needed to limit monitoring induced stressors such as trampling, non-native seed and invertebrate dispersal, and disease and fungal spread. We identify a linear pathway of deterioration highlighting stressors that can progress to cumulative impacts, consequences, and losses at the site scale. The first step to minimize disturbance is to assess and classify the current ecosystem quality. We present a tiered framework for wetland classification and link preventative measures to the wetland tier. Preventative measures are recommended at various intensities respective to the wetland tier, with higher tiered wetlands requiring more intense preventative measures. In addition, preventative measures vary by time of implementation (before, during, and after the wetland visit) to mitigate impacts at various temporal scales. The framework is designed to increase transparency of field monitoring impacts and to promote the adoption of preventative measures. Implementing preventative measures can build accountability and foster a greater appreciation for our roles as researchers and managers in protecting wetlands