• Title of article

    Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity

  • Author/Authors

    Stapanian، نويسنده , , Martin A. and Mack، نويسنده , , John and Adams، نويسنده , , Jean V. and Gara، نويسنده , , Brian and Micacchion، نويسنده , , Mick، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    7
  • From page
    120
  • To page
    126
  • Abstract
    Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.
  • Keywords
    disturbance , Substrate , Lasso , Wetland vegetation , VIBI , Shrinkage
  • Journal title
    Ecological Indicators
  • Serial Year
    2013
  • Journal title
    Ecological Indicators
  • Record number

    2092590