Assessing Natural and Anthropogenic Variability in Wetland Structure for Two Hydrogeomorphic Riverine Wetland Subclasses

Abstract

The hydrogeomorphic approach (HGM) to wetland classification and functional assessment has been applied regionally throughout the United States, but the ability of HGM functional assessment models to reflect wetland condition has limited verification. Our objective was to determine how variability derived from anthropogenic effects and natural variability impacted site assessment variables within regional wetland subclasses in central Oklahoma. We collected data for nine potential assessment variables including vegetation physiognomy (e.g., tree basal area, herbaceous cover, canopy cover, etc.) and soil organic matter at wetlands of two HGM riverine subclasses (oxbow and riparian) in May and June, 2010. Using Akaike Information Criteria, we identified limited relationships between landscape disturbance metrics and assessment variables within subclasses. The high degree of natural variability from climatic and hydrologic factors within both subclasses may be masking the impact of landscape disturbance on the other measured assessment variables. Precipitation had significant effects on assessment variables within each of the subclasses. To reduce natural climatic variability, the reference domain may need to be further subdivided. The approach used in this study provides fairly rapid and quantitative methods for evaluating the effectiveness of using HGM assessment variables in assessing wetland condition regionally.

Rapid Buffer Assessment Fails to Predict and Classify Wetland Floristic Quality in Oklahoma

“…Regional HGM subclasses offer better ecological resolution but were not used due to sample size limitations and the difficulty in characterizing and ascribing wetlands to subclasses in Oklahoma (Dvorett et al 2012). High climatic variability may also pose a challenge for wetland assessments in this region (Dvorett et al 2013), and we did not account (explicitly) for the wide range of precipitation across Oklahoma (Hoagland 2000). We did, however, split the Central Great Plains in western Oklahoma from ecoregions farther east, and we separated a drought/transitional period (2012-2013 surveys) from above-normal precipitation (2014-2015 surveys) across the region.…”

“…Crane (2014) similarly concluded that buffer metrics in the USA-RAM did not reliably predict vegetation diversity for Oklahoma depressional wetlands, and Bried et al (2014) showed mismatches between the USA-RAM buffer assessment and vegetation-based wetland quality classes in Oklahoma. Wetland assessment and classification in general appears to be challenging across Oklahoma due to a high degree of environmental and climatic variability (Hoagland 2000;Dvorett et al 2012Dvorett et al , 2013.…”

Species residency status affects model selection and hypothesis testing in freshwater community ecology

“…Following Dvorett et al (2013), we assigned a weighting coefficient (range: 0-1) to each of the 15 major land-use/land-cover (LULC) classes in the 2011 National Land Cover Dataset (NLCD) based on potential impacts to wetlands. We also calculated the combined percentage of altered land-use types (those with weighting coefficients <1; see Table 1 and Dvorett et al, 2013) at each buffer scale as a measure of anthropogenic disturbance. We also calculated the combined percentage of altered land-use types (those with weighting coefficients <1; see Table 1 and Dvorett et al, 2013) at each buffer scale as a measure of anthropogenic disturbance.…”

Assessment of temporal and spatial landscape and avifauna changes in the Yellow River wetland natural reserves in 1990–2013, China

“…The loss of natural habitats due to the reclamation of land for urban and industrial development, agriculture and aquaculture has been substantial and continues to grow (Zhou et al, 2010;Prabhadevi and Reddy, 2012;Ottinger et al, 2013;Yuan et al, 2014). Like many other types of environment, riverine environments are affected by natural environmental changes, anthropogenic activities and synergistic interactions between the two (Smith et al, 2008;Euliss and Mushet, 2011;Dvorett et al, 2013).…”