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Challenges and Opportunities for Integrating Lake Ecosystem Modelling Approaches

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Challenges and Opportunities for Integrating Lake Ecosystem Modelling Approaches Aquat Ecol (2010) 44:633–667 DOI 10.1007/s10452-010-9339-3 Challenges and opportunities for integrating lake ecosystem modelling approaches Wolf M. Mooij • Dennis Trolle • Erik Jeppesen • George Arhonditsis • Pavel V. Belolipetsky • Deonatus B. R. Chitamwebwa • Andrey G. Degermendzhy • Donald L. DeAngelis • Lisette N. De Senerpont Domis • Andrea S. Downing • J. Alex Elliott • Carlos Ruberto Fragoso Jr. • Ursula Gaedke • Svetlana N. Genova • Ramesh D. Gulati • Lars Ha˚kanson • David P. Hamilton • Matthew R. Hipsey • Jochem ‘t Hoen • Stephan Hu¨lsmann • F. Hans Los • Vardit Makler-Pick • Thomas Petzoldt • Igor G. Prokopkin • Karsten Rinke • Sebastiaan A. Schep • Koji Tominaga • Anne A. Van Dam • Egbert H. Van Nes • Scott A. Wells • Jan H. Janse Received: 8 July 2010 / Accepted: 9 August 2010 / Published online: 27 August 2010 Ó The Author(s) 2010. This article is published with open access at Springerlink.com Abstract A large number and wide variety of lake models. We also discuss a group of approaches that ecosystem models have been developed and published could all be classified as individual based: super- during the past four decades. We identify two challenges individual models (Piscator, Charisma), physiologically for making further progress in this field. One such structured models, stage-structured models and trait- challenge is to avoid developing more models largely based models. We briefly mention genetic algorithms, following the concept of others (‘reinventing the neural networks, Kalman filters and fuzzy logic. There- wheel’). The other challenge is to avoid focusing on after, we zoom in, as an in-depth example, on the only one type of model, while ignoring new and diverse multi-decadal development and application of the approaches that have become available (‘having tunnel lake ecosystem model PCLake and related models vision’). In this paper, we aim at improving the (PCLake Metamodel, Lake Shira Model, IPH- awareness of existing models and knowledge of TRIM3D-PCLake). In the discussion, we argue that concurrent approaches in lake ecosystem modelling, while the historical development of each approach and without covering all possible model tools and avenues. model is understandable given its ‘leading principle’, First, we present a broad variety of modelling there are many opportunities for combining approaches. approaches. To illustrate these approaches, we give We take the point of view that a single ‘right’ approach brief descriptions of rather arbitrarily selected sets of does not exist and should not be strived for. Instead, specific models. We deal with static models (steady state multiple modelling approaches, applied concurrently to and regression models), complex dynamic models a given problem, can help develop an integrative view (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, on the functioning of lake ecosystems. We end with a set LakeWeb, MyLake, PCLake, PROTECH, SALMO), of specific recommendations that may be of help in the structurally dynamic models and minimal dynamic further development of lake ecosystem models. Handling Editor: R. D. Gulati. W. M. Mooij (&) Á L. N. De Senerpont Domis Á D. Trolle Á E. Jeppesen A. S. Downing Á R. D. Gulati Á J. ‘t Hoen Aarhus University, National Environmental Research Netherlands Institute of Ecology (NIOO-KNAW), Institute, Department of Freshwater Ecology, Department of Aquatic Ecology, Rijksstraatweg 6, 8600 Silkeborg, Denmark 3631 AC Nieuwersluis, The Netherlands e-mail: [email protected] 123 634 Aquat Ecol (2010) 44:633–667 Keywords Aquatic Á Food web dynamics Á Plankton various types, overexploitation and invasive species, Á Nutrients Á Spatial Á Lake Á Freshwater Á Marine Á changes in land use and hydrology in the catchment Community Á Population Á Hydrology Á and climate change (e.g., Gulati and Van Donk 2002; Eutrophication Á Global change Á Climate warming Á MEA 2005; Mooij et al. 2005; Revenga et al. 2005; Fisheries Á Biodiversity Á Management Á Mitigation Á Jeppesen et al. 2009; MacKay et al. 2009). Adaptive processes Á Non-linear dynamics Á Analysis But there is also a downside to the large number Á Bifurcation Á Understanding Á Prediction Á Model and variety of models that have been published. We limitations Á Model integration identify two challenges: one related to the number of models and the other to the variety of models. With respect to the number of models, newly developed models often bear similarities to existing models Introduction (‘reinventing the wheel’) (e.g., Fitz et al. 1996). In such cases, it would most likely be more efficient to A large number and wide variety of lake ecosystem apply or adopt an existing model instead of creating a models have been developed and published during new one. With respect to the variety of models, we the past four decades, indicating the strong interest in identify the risk that the approach taken in any capturing in a model the essential processes in lake specific model is too narrow and ignores other ecosystems (e.g., Jørgensen 2010). The scientific approaches that could be useful or even essential interest in understanding fundamental processes in for gaining understanding and making predictions lake ecosystems can be traced back to the seminal (‘having tunnel vision’) (e.g., Scheffer 1998, p308). paper by Forbes (1887) on the lake as a microcosm. Before starting a lake ecosystem modelling pro- Another major purpose has been to develop predic- ject, it is essential to be aware of existing models and tive tools supporting inter-disciplinary ecosystem concurrent approaches and to properly conceptualize management (Carpenter et al. 1999), acknowledging the issues, the variables, the time and space scales the great importance of lake ecosystems for society and the desired outcomes for the model simulations (MEA 2005). The ecological quality of lakes is (Robson et al. 2008). We observe that publications threatened by a large number of anthropogenic stress that deal with a wide range of concurrent approaches factors, in particular eutrophication, pollution of in lake ecosystem modelling are scarce, although E. Jeppesen A. S. Downing Á J. ‘t Hoen Á E. H. Van Nes Greenland Climate Research Centre (GCRC), Greenland Wageningen University, Department of Aquatic Ecology Institute of Natural Resources, Kivioq 2, P.O. Box 570, and Water Quality, P.O. Box 47, 6700 AA Wageningen, 3900 Nuuk, Greenland The Netherlands G. Arhonditsis J. A. Elliott University of Toronto, Department of Physical & Centre for Ecology and Hydrology, Lancaster Environmental Sciences, Toronto, ON M1C 1A4, Canada Environment Centre, Lake Ecosystem Group, Algal Modelling Unit, Bailrigg, Lancaster LA1 4AP, England, P. V. Belolipetsky Á S. N. Genova UK Institute of Computational Modelling (SB-RAS), Siberian Federal University, 660036 Krasnoyarsk, Russia C. R. Fragoso Jr. Federal University of Alagoas, Centre for Technology, D. B. R. Chitamwebwa Campus A.C. Simo˜es, 57072-970 Maceio´-AL, Brazil Tanzania Fisheries Research Institute (TAFIRI), Mwanza Centre, P.O. Box 475, Mwanza, Tanzania U. Gaedke Institute of Biochemistry and Biology, Department of A. G. Degermendzhy Á I. G. Prokopkin Ecology and Ecosystem Modelling, University of Institute of Biophysics (SB-RAS), Akademgorodok, Potsdam, Am Neuen Palais 10, 14469 Potsdam, Germany 660036 Krasnoyarsk, Russia L. Ha˚kanson D. L. DeAngelis Swedish University of Agricultural Sciences, Department University of Miami, Florida Integrated Science Centre, of Aquatic Sciences and Assessment, P.O. Box 7050, USGS, Coral Gables, FL 33124, USA 75007 Uppsala, Sweden 123 Aquat Ecol (2010) 44:633–667 635 some attempts have been made (Van Nes and by rather arbitrarily selected existing models. The Scheffer 2005; Mooij et al. 2009; Jørgensen 2010), purpose of this first section is to provide the reader and several overviews concerning complex dynamic with ideas for potential approaches in lake ecosys- lake ecosystem models have been provided (e.g., tem modelling, some of which, we believe, might Schauser and Strube 2007; Reichert and Mieleitner otherwise be overlooked. In the second part of this 2008). In this paper, we wish to proceed further in the paper, we focus on the multi-decadal development direction of integrating lake ecosystem modelling and application of a specific lake ecosystem model, approaches, without claiming to be comprehensive. PCLake. The aim of this section is to show the The ideas published here were stimulated by a potential for expanding and redirecting the approach collaborative research effort by Dutch and Russian taken in an existing model. In the final section, the scientists funded by a stimulus programme of the challenges and opportunities for integrating lake Netherlands Organization for Scientific Research and ecosystem modelling approaches are discussed. We the Russian Foundation for Basic Research. The aim of end this section with a set of specific recommenda- this research programme was to combine the extensive tions that may be of help in the further development knowledge of modelling temperate shallow lake of lake ecosystem models. ecosystems of the Dutch team (e.g., Janse 2005; Janse et al. 2008) with the skilled mathematical knowledge of modelling hydro-dynamic processes of the Russian Lake ecosystem modelling approaches team (e.g., Belolipetsky et al. 2010; Genova et al. 2010). The integrated model that resulted from this The modelling of lake eutrophication started with collaborative research project is documented else- empirical models relating total phosphorus (TP) and where (Prokopkin
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