Use of Maryland Biological Stream Survey Data to Determine Effects of Agricultural Riparian Buffers on Measures of Biological Stream Health

Publication Year: 
Linda S. Barker, Gary K. Felton, and Estelle Russek-Cohen
  • Study performed in Maryland (USA) to explore importance of riparian buffers for stream ecology, specifically in agricultural areas
  • Forest buffers placement and width found to affect benthic index of biotic integrity (BIBI) and physical habitat index (PHI)
  • Fish index of biotic integrity (FIBI) is not a good measure of buffer effectiveness; practitioners should choose measures of buffer effectiveness carefully

This study was undertaken to determine the importance of riparian buffers to stream ecology in agricultural areas. The original Maryland Biological Stream Survey (MBSS) data set was partitioned to represent agricultural sites in Maryland's Coastal Plain and Piedmont regions. ANOVA, multiple linear regression (MLR), and CART regression tree models were developed using riparian and site catchment landscape characteristics. MBSS data were both stratified by physiographic region and analyzed as a combined data set. All models indicated that land management at the site was not the controlling factor for fish IBIs (FIBI) at that site and, hence, using FIBI to evaluate site-scale factors would not be a prudent procedure. Measures of instream habitat and location in the stream network were the dominant explanatory factors for FIBI models. Both CART and MLR models indicated that forest buffers were influential on benthic IBIs (BIBI). Explanatory variables reflected instream conditions, adjacent landscape influence, and chemistry in the Coastal Plains sites, all of which are relatively site specific. However, for Piedmont sites, hydrologic factors were important, in addition to adjacent landscape influence, and chemistry. Both Coastal Plain and Piedmont CART models identified several hydrologic factors, emphasizing the dominant control of hydrology on the physical habitat index (PHI). Riparian buffers were a secondary influence on PHI in the Coastal Plain, but not in the Piedmont. Between 40% and 70% of the variation in FIBI, BIBI, and PHI was explained by the “easily obtainable” variables available from the MBSS data set. While these are empirical results specific to Maryland, the general findings are of use to other locations where the establishment of forest buffers is considered as an aquatic ecosystem restoration measure.