Implementation of ecological modeling as an effective management and investigation tool: Lake Kinneret as a case study |
| |
| Authors: | G Gal MR Hipsey A Parparov U Wagner V Makler T Zohary |
| |
| Institution: | 1. Yigal Alon Kinneret Limnological Laboratory, Israel Oceanographic and Limnological Research, PO Box 447, Migdal 14950, Israel;2. Centre for Water Research, University of Western Australia, 35 Stirling Hwy, Nedlands, Western Australia 6009, Australia;3. Faculty of Civil and Environmental Engineering, The Technion, Haifa 32000, Israel;1. WHERD, Water Science and Technology Directorate, Environment Canada, 867 Lakeshore Road, Burlington, ON L7R 4A6, Canada;2. Department of Physical & Environmental Sciences, University of Toronto, 1265 Military Trail, Toronto, ON M1C 1A4, Canada;3. Algal Taxonomy and Ecology Inc., 31 Laval Drive, Winnipeg, MB R3T 2X8, Canada;1. Aarhus University, Department of Bioscience, Vejlsøvej 25, DK-8600 Silkeborg, Denmark;2. Sino-Danish Centre for Education and Research, Beijing, China;3. Centre for Ecology and Hydrology, Algal Modelling Unit, Lake Ecosystem Group, Bailrigg, Lancaster, LA1 4AP England, UK;4. Department of Aquatic Ecology, Netherlands Institute of Ecology (NIOO-KNAW), P.O. Box 50, 6700 AB Wageningen, The Netherlands;5. Department of Aquatic Ecology and Water Quality Management, Wageningen University, P.O. Box 47, 6700 AA Wageningen, The Netherlands;6. PBL Netherlands Environmental Assessment Agency, P.O. Box 303, NL-3720 AH Bilthoven, The Netherlands;7. Bolding and Burchard ApS, Strandgyden 25, 5466 Asperup, Denmark;8. Environmental Research Institute, University of Waikato, Private Bag 3105, Hamilton 3240, New Zealand;9. Greenland Climate Research Centre (GCRC), Greenland Institute of Natural Resources, Kivioq 2, P.O. Box 570, 3900 Nuuk, Greenland;1. Aquatic EcoDynamics Group, UWA School of Agriculture and Environment, The University of Western Australia, Australia;2. Department of Lake Research, Helmholtz Centre for Environmental Research (UFZ), Germany;3. Limnological Institute, University of Konstanz, Germany;4. Department of Physical and Environmental Sciences, University of Toronto, Canada;5. Kinneret Limnological Laboratory, Israel Oceanographic & Limnological Research, Israel;6. Environmental Research Institute, The University of Waikato, New Zealand;7. Center for Limnology, University of Wisconsin–Madison, USA;8. Department of Biological Science, Virginia Tech, USA;9. Department of Natural Resources, Cornell University, USA;10. Bren School of Environmental Science and Management, University of California, Santa Barbara, USA;11. Center for Integrated Data Analytics, U.S. Geological Survey, USA;12. Water Research Centre, The Environment Institute, School of Biological Sciences, The University of Adelaide, Australia;13. Department of Bioscience, Århus University, Denmark;14. Department of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY 12180, USA;15. Department of Ecosystem Research, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Germany;p. Department of Civil Engineering, University of Granada, Spain;q. Department of Geography, Ludwig-Maximilians-University of Munich, Germany;r. National Research Council, Water Research Institute (IRSA-CNR), Italy;s. Marine Science Institute, University of California Santa Barbara, USA;t. Marine Institute, Ireland;u. Centre for Ecology and Hydrology, Lancaster, United Kingdom;v. Group of Aquatic Physics, Department F.-A. Forel for Environmental and Aquatic Sciences, Institute for Environmental Sciences, University of Geneva, Switzerland;w. Faculty of Civil and Environmental Engineering, Technion - Israel Institute of Technology, Israel;x. National Research Council, Water Research Institute (IRSA-CNR), Rome, Italy;y. Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences (CAS), China;z. INRA, UMR CARRTEL, Université de Savoie Mont Blanc, Thonon les Bains, France;11. Institute of Coastal Research, Helmholtz-Zentrum Geesthacht (HZG), Geesthacht, Germany;12. Department of Ecology, Evolution and Marine Biology, University of California Santa Barbara, USA;13. Oranim College, Israel;14. Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, France;15. Science and Strategy, Waikato Regional Council, New Zealand;16. DICATAM Department, Università degli Studi di Brescia, Italy;17. Water Research Institute, University of Granada, Spain;18. Dorset Environmental Science Centre, Ontario Ministry of Environment and Cimate Change, Canada;19. Earth Science Research Center, Institute for the Study of Earth, Oceans and Space, University of New Hampshire, Durham, USA;110. Surface Waters – Research and Management, Eawag: Swiss Federal Institute of Aquatic Science and Technology, Switzerland;111. Department of Ecohydrology, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Germany;112. LEESU Ecole des Ponts ParisTech - Université Paris-Est, France;113. Australian Water Quality Centre, South Australian Water Corporation, Australia;114. Faculty of Information Management and Media, Karlsruhe University of Applied Sciences, Germany;115. Department of Meteorology, University of Reading, United Kingdom;1. Department of Environmental Engineering, Chungbuk National University, 52 Naesudong-ro, Hengduk-gu, Cheongju city, Chungbuk, Republic of Korea;2. Centre for Water Research, The University of Western Australia, Crawley, Western Australia, Australia;3. School of Earth and Environment, The University of Western Australia, Crawley, Western Australia, Australia;4. Gyeonggi-do Environmental Preservation Association, Republic of Korea |
| |
| Abstract: | The need for scientifically based management of lakes, as key water resources, requires the establishment of quantitative relationships between in-lake processes responsible for water quality (WQ) and the intensity of major management measures (MM, e.g. nutrient loading). In this paper, we estimate the impact of potential changes in nutrient loading on the Lake Kinneret ecosystem. Following validation of the model against a comprehensive dataset, we applied an approach that goes beyond scenario testing by linking the lake ecosystem model DYRESM–CAEDYM with a set of ecosystem variables included in a pre-assessed system of water quality indices. The emergent properties of the ecosystem predicted from the model simulations were also compared with lake data as a form of indirect validation of the model. Model output, in good agreement with lake data, indicated differential effects of nitrogen and phosphorus nutrient loading on concentrations, and major in-lake fluxes, of TN and TP, and dynamics and algal community structure. Both model output and lake data indicated a strong relationship between nitrogen loading and in-lake TN values. This relationship is not apparent for phosphorus and only a weak relationship exists between phosphorus loading and in-lake TP. The modeling results, expressed in terms of water quality, allowed establishment of critical/threshold values for the nutrient loads. Implementation of the ecological modeling supplemented with the quantified set of WQ indices allowed us to take a step towards establishment of the association between permissible ranges for water quality and major management measures, i.e. towards sustainable management. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
