Moss and vascular plant indices in Ohio wetlands have similar environmental predictors
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Abstract
Mosses and vascular plants have been shown to be reliable indicators of wetland habitat delineation and environmental quality. Knowledge of the best ecological predictors of the quality of wetland moss and vascular plant communities may determine if similar management practices would simultaneously enhance both populations. We used Akaike's Information Criterion to identify models predicting a moss quality assessment index (MQAI) and a vascular plant index of biological integrity based on floristic quality (VIBI-FQ) from 27 emergent and 13 forested wetlands in Ohio, USA. The set of predictors included the six metrics from a wetlands disturbance index (ORAM) and two landscape development intensity indices (LDIs). The best single predictor of MQAI and one of the predictors of VIBI-FQ was an ORAM metric that assesses habitat alteration and disturbance within the wetland, such as mowing, grazing, and agricultural practices. However, the best single predictor of VIBI-FQ was an ORAM metric that assessed wetland vascular plant communities, interspersion, and microtopography. LDIs better predicted MQAI than VIBI-FQ, suggesting that mosses may either respond more rapidly to, or recover more slowly from, anthropogenic disturbance in the surrounding landscape than vascular plants. These results supported previous predictive studies on amphibian indices and metrics and a separate vegetation index, indicating that similar wetland management practices may result in qualitatively the same ecological response for three vastly different wetland biological communities (amphibians, vascular plants, and mosses).
Study Area
Publication type | Article |
---|---|
Publication Subtype | Journal Article |
Title | Moss and vascular plant indices in Ohio wetlands have similar environmental predictors |
Series title | Ecological Indicators |
DOI | 10.1016/j.ecolind.2015.11.036 |
Volume | 62 |
Year Published | 2016 |
Language | English |
Publisher | Elsevier |
Publisher location | Amsterdam |
Contributing office(s) | Great Lakes Science Center |
Description | 9 p. |
First page | 138 |
Last page | 146 |
Country | United States |
State | Ohio |
Online Only (Y/N) | N |
Additional Online Files (Y/N) | N |
Google Analytic Metrics | Metrics page |