Using dual classifications in the development of avian wetland indices of biological integrity for wetlands in West Virginia, USA

Abstract

Considerable resources are being used to develop and implement bioassessment methods for wetlands to ensure that "biological integrity" is maintained under the United States Clean Water Act. Previous research has demonstrated that avian composition is susceptible to human impairments at multiple spatial scales. Using a site-specific disturbance gradient, we built avian wetland indices of biological integrity (AW-IBI) specific to two wetland classification schemes, one based on vegetative structure and the other based on the wetland's position in the landscape and sources of water. The resulting class-specific AW-IBI was comprised of one to four metrics that varied in their sensitivity to the disturbance gradient. Some of these metrics were specific to only one of the classification schemes, whereas others could discriminate varying levels of disturbance regardless of classification scheme. Overall, all of the derived biological indices specific to the vegetative structure-based classes of wetlands had a significant relation with the disturbance gradient; however, the biological index derived for floodplain wetlands exhibited a more consistent response to a local disturbance gradient. We suspect that the consistency of this response is due to the inherent nature of the connectivity of available habitat in floodplain wetlands.

Influence of environmental parameters on litter decomposition in wetlands in West Virginia, USA

“…In September and October of 2007, we collected four litter types (broadleaf cattail Typha latifolia L., common rush Juncus effusus L., brookside alder Alnus serrulata (Ait.) Willd., and reed canary grass Phalaris arundinacea L.) which were chosen because they are common, dominant wetland plant species in West Virginia (Balcombe et al 2005;Veselka IV 2008). Litter mixes can have non-additive decomposition rates compared to single species (Gartner & Cardon 2004), so a fifth litter type was created with a mixture (3:2:1) of reed canary grass, common rush, and brookside alder to approximate ratios of plant species present in the wetlands (Balcombe et al 2005).…”

Using two classification schemes to develop vegetation indices of biological integrity for wetlands in West Virginia, USA

“…However, due to the number of sites used in this study (151), we are confident we adequately sampled the major HGM classes found in West Virginia ( Fig. 1; Veselka et al 2009). We categorized wetlands by both the Cowardin and regional HGM subclass (Cole et al 1997) type (Table 1).…”

“…We stratified sampling across both wetland Cowardin classes and the major US Environmental Protection Agency's Level 3 aquatic ecoregions within West Virginia, USA: the Central Appalachians, the Ridge and Valley, and the Western Allegheny Plateau (Omernik 1987;Woods et al 1999) by targeting previously studied wetlands (Balcombe et al 2005) and selecting random 7.5-min quadrangles using a Geographic Information System database (Veselka et al 2009). We conducted "reconnaissance" on the random quadrangles, selecting accessible sites that did not require extensive property ownership investigations or permissions due to project constraints.…”

“…These partitions decreased sample size substantially. As a result, appropriate subclass designations were combined into designated HGM management classes to promote Veg-IBIs as intuitive tools targeted for use by natural resource agencies, the private sector, and (Omernik 1987;Woods et al 1999) trained volunteer groups to enable the tracking of wetland biological integrity trends over time and ensure compliance of antidegradation standards Veselka et al 2009). These classes differ in name and definition, providing more details about a wetland's function than the original HGM classifications (Brinson 1993;e.g.…”

“…Because of the regulatory mandate promoting the maintenance of wetland function and biological integrity in the landscape, this study uses both the Cowardin classifications and HGM-based classes. Moreover, we found that augmenting one approach with the alternative has been shown to increase avian IBI sensitivity to human impairment (Veselka et al 2009). …”