title: Water chemistry in 179 randomly selected Swedish headwater streams related to forest production, clear-felling and climate.
abstract: From a policy perspective, it is important to understand forestry effects on surface waters from a landscape perspective. The EU Water Framework Directive demands remedial actions if not achieving good ecological status. In Sweden, 44 % of the surface water bodies have moderate ecological status or worse. Many of these drain catchments with a mosaic of managed forests. It is important for the forestry sector and water authorities to be able to identify where, in the forested landscape, special precautions are necessary. The aim of this study was to quantify the relations between forestry parameters and headwater stream concentrations of nutrients, organic matter and acid-base chemistry. The results are put into the context of regional climate, sulphur and nitrogen deposition, as well as marine influences. Water chemistry was measured in 179 randomly selected headwater streams from two regions in southwest and central Sweden, corresponding to 10 % of the Swedish land area. Forest status was determined from satellite images and Swedish National Forest Inventory data using the probabilistic classifier method, which was used to model stream water chemistry with Bayesian model averaging. The results indicate that concentrations of e.g. nitrogen, phosphorus and organic matter are related to factors associated with forest production but that it is not forestry per se that causes the excess losses. Instead, factors simultaneously affecting forest production and stream water chemistry, such as climate, extensive soil pools and nitrogen deposition, are the most likely candidates The relationships with clear-felled and wetland areas are likely to be direct effects.
authors.affiliation: Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Box 7050, SE-750 07, Uppsala, Sweden, Stefan.Lofgren@slu.se.
authors.forename: Stefan
authors.initials: S
authors.lastname: Löfgren
authors.forename: Mats
authors.initials: M
authors.lastname: Fröberg
authors.forename: Jun
authors.initials: J
authors.lastname: Yu
authors.forename: Jakob
authors.initials: J
authors.lastname: Nisell
authors.forename: Bo
authors.initials: B
authors.lastname: Ranneby
mesh_terms: D001499:Bayes Theorem; D002980:Climate; D004777:Environment; D004784:Environmental Monitoring; D016468:Forestry; D065928:Forests; D009584:Nitrogen / Q000032:analysis; D010758:Phosphorus / Q000032:analysis; D045483:Rivers / Q000737:chemistry*; D012987:Soil; D013548:Sweden; D014873:Water Pollutants / Q000032:analysis*; D014876:Water Pollution / Q000706:statistics & numerical data
chemical_list: D012987:Soil; D014873:Water Pollutants; D010758:Phosphorus; D009584:Nitrogen