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Analysis of macrophyte indicator variation as a function of sampling,temporal, and stressor effects
Affiliation:1. Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Cuyo, Padre Jorge Contreras 1300, 5500 Mendoza, Argentina;2. Museo de Historia Natural de San Rafael, Ballofet s/n, 5600 San Rafael, Mendoza, Argentina;3. Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP, CONICET-UNLPam), Universidad Nacional de La Pampa, Av. Uruguay 151, 6300 Santa Rosa, La Pampa, Argentina;4. GeoQuest Research Centre, School of Earth and Environmental Sciences, University of Wollongong NSW 2522, Australia;5. Department of Earth Sciences, University of Adelaide SA 5005, Australia;1. Department of Biology, Eastern Washington University, Cheney, WA 99004, USA;2. Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Function Ecology, 27570 Bremerhaven, Germany;3. Institute for Environmental Medicine, Department of Physiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA;4. Planeación Ambiental y Conservación, Centro de Investigaciones Biológicas del Noroeste, S.C., Instituto Politécnico Nacional 195, Playa Palo Santa Rita Sur, La Paz, Baja California Sur 23096, Mexico;1. Department of Earth and Atmospheric Sciences, University of Nebraska - Lincoln, Lincoln, NE, 68588, USA.;2. Department of Earth and Environmental Systems, Indiana State University, Terre Haute, IN 47809, USA
Abstract:Biological indicators that signal changes in lake condition are essential tools for guiding resource management decisions. Macrophyte-based indicators have traditionally been selected and evaluated in the context of nutrient-based stressors, although the need to evaluate indicators that are sensitive to climate stressors has been increasingly relevant. Moreover, indicators should ideally exhibit minimal sampling variation and have low natural temporal variation so there is high power to detect changes in the mean value over time. Eight macrophyte indicators were estimated in 23 Minnesota (USA) lakes using four years of repeated surveys to estimate sampling and temporal variation, response to development (phosphorus concentration) and climate stress (annual growing degree days), and power to detect significant change at various annual sampling intervals. Indicators included a macrophyte index of biotic integrity, floristic quality index, maximum depth of growth, total species richness, common species richness, mean richness, and frequency occurrence of rooted species and Chara sp. Overall, regression and smoothed additive models indicated significant relationships of indicators to total lake phosphorus and mean annual growing degree days. The macrophyte index of biotic integrity, floristic quality index, and the frequency rooted species had minimal sampling variation in this study, were responsive to development or climate stress, and had low annual variation (coefficients of variation 0.08, 0.10, and 0.19, respectively) resulting in high to moderate power (>50%) for detecting significant change over a 20 year period. Results from these analyses will facilitate the use of precise and powerful indicators that respond to stressors that are of concern for the management of freshwater glacial lakes.
Keywords:Climate  Development  Lake monitoring  Macrophytes  Power  Variation
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