caa a22 4500 445383976 CHVBK 20180317143026.0 cr unu---uuuuu 170323e20111201xx s 000 0 eng 10.1007/s10021-011-9479-x doi (NATIONALLICENCE)springer-10.1007/s10021-011-9479-x Acid Sensitivity of Lakes in Nova Scotia, Canada: Assessment of Lakes at Risk [Elektronische Daten] [Marta Wolniewicz, Julian Aherne, Peter Dillon] The sensitivity of surface waters to acidic deposition is governed by the interaction of catchment geology, soils, topography, land use, climate and atmospheric deposition. Accordingly at the landscape scale, catchment attributes may be used to predict lake chemistry (for example, acid neutralising capacity (ANC), pH, calcium (Ca2+) and dissolved organic carbon (DOC)). Empirical (multiple linear regression) models based on average measured chemistry (2000-2006) for 204 lakes in Nova Scotia (NS) Canada, and their catchment attributes, were used to predict chemistry for all lakes in NS (n=6104). Damage to aquatic biota, such as loss of species and/or reduced biodiversity has been widely evaluated using critical chemical thresholds commonly based on pH, ANC and Ca2+. The proportion of sensitive lakes in NS (that is, the stock at risk) was estimated as lakes with ANC less than 20μeql−1, pH below 6, and Ca2+ less than 75 μeql−1 (13, 73 and 74%, respectively). Many lakes in NS are characterized by high DOC (>7mgl−1); in these lakes organic acids contribute to total acidity, making anthropogenic influences difficult to discern. To account for the potential contribution of organic acidity, all lakes with pH below 6 (and DOC<7mgl−1) and lakes below a threshold for ANC adjusted for organic acids were quantified; 63% of the lakes fell below either of these thresholds. Despite substantial reductions in sulphur emissions in North America since the 1980s, many lakes in NS remain at risk to acidic deposition. Springer Science+Business Media, LLC, 2011 acid neutralising capacity nationallicence calcium nationallicence pH nationallicence dissolved organic carbon nationallicence catchment attributes nationallicence empirical models nationallicence multiple linear regression nationallicence Wolniewicz Marta Environmental and Resource Studies, Trent University, 1600 West Bank Drive, K9J 7B8, Peterborough, ON, Canada aut Aherne Julian Environmental and Resource Studies, Trent University, 1600 West Bank Drive, K9J 7B8, Peterborough, ON, Canada aut Dillon Peter Environmental and Resource Studies, Trent University, 1600 West Bank Drive, K9J 7B8, Peterborough, ON, Canada aut Ecosystems Springer-Verlag 14/8(2011-12-01), 1249-1263 1432-9840 14:8<1249 2011 14 10021 https://doi.org/10.1007/s10021-011-9479-x text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10021-011-9479-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wolniewicz Marta Environmental and Resource Studies, Trent University, 1600 West Bank Drive, K9J 7B8, Peterborough, ON, Canada aut NATIONALLICENCE 700 1- Aherne Julian Environmental and Resource Studies, Trent University, 1600 West Bank Drive, K9J 7B8, Peterborough, ON, Canada aut NATIONALLICENCE 700 1- Dillon Peter Environmental and Resource Studies, Trent University, 1600 West Bank Drive, K9J 7B8, Peterborough, ON, Canada aut NATIONALLICENCE 773 0- Ecosystems Springer-Verlag 14/8(2011-12-01), 1249-1263 1432-9840 14:8<1249 2011 14 10021 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer