Return to search

Performance of Floristic Quality Assessment in Massachusetts Forested Wetlands

In order to combat the loss of valuable wetland functions and services, federal, state and tribal governments must have the tools to accurately assess and monitor the condition of wetland ecosystems. One particular method of wetland assessment is Floristic Quality Assessment (FQA), which has been growing in popularity throughout the United States since its creation in the 1970s. FQA relies on vegetative indicators of human disturbance to assess the integrity of an ecosystem. FQA calculations are based on Coefficients of Conservatism (C-scores), professionally-assigned scores ranging from 0-10 that denote a local species' tolerance to anthropogenic disturbance. Despite increasing interest in the use of FQA, few studies have thoroughly tested the performance of FQA, especially in New England. We used the Conservation Assessment and Prioritization System (CAPS), a landscape-based, coarse-scale assessment method, as a basis for evaluating FQA's performance in Massachusetts's forested wetlands. Our objective was to use CAPS Index of Ecological Integrity (IEI) scores (a form of generalized stressor gradient) to evaluate the performance of a variety of FQA indices (biological condition gradients), using C-scores from 7 states in the Northeast, and 2 ecoregions in Massachusetts. Based on our calculations of r-squared, and Spearman's rank analysis, we determined that FQA and C-scores have a moderate to weak relationship with the CAPS index of ecological integrity. Of the 12 indices and metrics we tested, the index with the strongest relationship to the IEI stressor gradient was mean Coefficient of Conservatism. Based on this research a number of suggestions are proposed for improving FQA as it applies to wetland assessment.

Identiferoai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:masters_theses_2-1688
Date09 July 2018
CreatorsGorss, Carolyn
PublisherScholarWorks@UMass Amherst
Source SetsUniversity of Massachusetts, Amherst
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceMasters Theses

Page generated in 0.0021 seconds