Evaluating the effectiveness of Floristic Quality Assessment as a tool for determining the condition of depressional wetlands across ecoregions. (July 2019)

• Record Type: Journal Article
• Authors: Gallaway, Sarah; Davis, Craig; Dvorett, Daniel; Tramell, Brooks
• Is Part Of: Ecological indicators. Volume 102(2019)
• Page Start: 488
• Page End: 496
• Publication Date: 2019-07
• Subjects: Depressional wetlands -- Environmental gradients -- Floristic quality assessment -- Floristic quality index -- Reference condition; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2019.02.021
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Floristic Quality Index can evaluate depressional wetland condition in Oklahoma. Regional environmental differences can influence Floristic Quality Index results. Reference criteria should be established based on ecoregions. Abstract: Floristic Quality Assessment (FQA) has been recognized as a useful tool for evaluating wetland condition and guiding conservation and management efforts. However, FQA validation to confirm that results represent actual wetland condition is limited. Moreover, FQA has been applied across large regions without consideration for the high environmental variability (e.g., temperature, precipitation, and topography) within application areas, which may limit the effectiveness of FQA as an assessment tool. Because Oklahoma contains diverse ecoregions and extreme environmental gradients, this provides an opportunity to examine the influence of spatial and environmental variability on FQA results. We sampled 68 depressional wetlands dispersed across the state to (1) validate an FQA metric, Floristic Quality Index (FQI), with two established condition assessment methods (i.e., Landscape Development Intensity Index [LDI] and Oklahoma Rapid Assessment Method [OKRAM]) and (2) evaluate the influence of environmental variation (e.g., high and low precipitation) on FQI scores. In our validation analysis, we found a strong positive relationship between FQI and OKRAM, indicating the FQI was able to detect changes in wetland condition in depressional wetlands along a disturbance gradient. Additionally, strong negative relationships between FQI and LDI suggest that FQI is responsive to stressors within the surrounding landscape. When evaluating environmental influence on FQI scores, we found substantial variation between reference wetlands based on location, with higher scores occurring in eastern sites (high precipitation) and lower scores occurring in western sites (low precipitation). We used Canonical Correspondence Analysis (CCA) to assess the relationship between plant communities and environmental variables, and found that precipitation was more indicative of plant species distribution than wetland condition (i.e., disturbed or reference condition). Thus, C -values of plant species (i.e., predetermined values assigned to individual plant species) and corresponding FQI scores differed significantly across ecoregions based on high and low precipitation, regardless of wetland condition. This phenomenon highlights the importance of considering regional environmental differences when developing FQI thresholds for wetland assessments, especially across diverse states or ecoregions. To reduce the influence of regional differences on FQIs, as well as other vegetation-based methods, condition class thresholds and reference criteria should be established based on ecoregions to more accurately capture wetland condition using FQI.