Use of Maryland Biological Stream Survey Data to Determine Effects of Agricultural Riparian Buffers on Measures of Biological Stream Health |
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Authors: | Linda S Barker Gary K Felton Estelle Russek-Cohen |
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Institution: | (1) Md. Department of Natural Resources, Fisheries Service, Tawes Office Building, Annapolis, MD 21401, USA;(2) Department of Biological Resources Engineering, University of Maryland, College Park, MD 20742–2315, USA;(3) Department of Animal and Avian Sciences, University of Maryland, College Park, 20742, USA |
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Abstract: | 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. |
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Keywords: | agriculture Benthic macroinvertebrate best management practice biocriteria buffer Chesapeake Bay IBI land use Maryland Non-point-source pollution rapid bioassessment regression tree modeling Riparian Stream Water quality |
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