A statistical methodology for exploring elevational differences in precipitation chemistry |
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| Institution: | 1. Department of Forest Management, Oregon State University and EPA-CERL, 200 SW 35th Street, Corvallis, OR 97333, U.S.A.;2. NSI Technology Services Corporation, Western Conifers Research Cooperative, U.S. EPA Environmental Research Laboratory, 200 SW 35th Street, Corvallis, OR 97333, U.S.A.;3. U.S. Environmental Protection Agency, Region VIII, 999 18th Street, Suite 500, Denver, CO 80202-2405, U.S.A.;1. Department of Food Science, Faculty of Science, University of Copenhagen, Frederiksberg, Denmark;2. Department of Marketing, Copenhagen Business School, Frederiksberg, Denmark;1. Department of Computer Science, KU Leuven, Celestijnenlaan 200A, 3001 Heverlee, Belgium;2. Department of Computer Science and Technology, Tsinghua University, 100084 Beijing, China;1. MARUM – Center for Marine Environmental Sciences, University of Bremen, Leobener Straße 2, D-28359 Bremen, Germany;2. Alfred-Wegener-Institut Helmholtz Zentrum für Polar- und Meeresforschung, Am Handelshafen 12, D-27570 Bremerhaven, Germany;3. University of Applied Sciences, An der Karlstadt 8, D-27568 Bremerhaven, Germany;4. Leibniz-Institute for Freshwater Ecology and Inland Fisheries, Department of Chemical Analytics and Biogeochemistry, Mueggelseedamm 301, 12587 Berlin, Germany;5. Bruker Daltonik GmbH, Fahrenheitstraße 4, 28359 Bremen, Germany;6. Department of Oceanography, National Sun Yat-Sen University, 80424 Kaohsiung, Taiwan;1. Research Group of Analytical Chemistry and Life Sciences, Department of Analytical Chemistry, Campus of Fuentenueva, University of Granada, E-18071 Granada, Spain;2. Department of Chemistry, University of Tirana, St. Bulevardi \"Zogu I\", 1001 Tirana, Albania;3. Research Group on Nutrition, Diet and Risk Assessment, Department of Nutrition and Food Science, University of Granada, Campus of Cartuja s/n, 18071 Granada, Spain |
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| Abstract: | A statistical methodology for exploring the relationships between elevation and precipitation chemistry is outlined and illustrated. The methodology is only applicable to situations where the precipitation at two (or more) matched sites is correlated. Maximum likelihood tests are utilized, with contour ellipses of assumed bivariate log-normal distributions to assist in the interpretation. Data from 12 sites located in the southern Rocky Mountains of the U.S. were used for illustration. The results indicate differences in sulphate concentrations between airsheds, between snow and rain, and between higher and lower elevations in the Rocky Mountains. There are other approaches for investigating these issues, however, the likelihood ratio with contour ellipses is easy to apply and interpret, and we feel that it provides a greater insight than some of the more common analyses of variance or regression techniques. However, it is important to note that the superiority of one method over others depends on the criterion used. |
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