[Text] / W.M. Mooij [et al.] // Aquat. Ecol. - 2010. -
Vol. 44,
Is. 3. - pp. 633-667,
DOI 10.1007/s10452-010-9339-3. - Cited References: 260. - WM, RG, IP, SG, PV and AD were supported by grant 047.017.012 of the Netherlands Organization for Scientific Research (NWO) and the Russian Foundation for Basic Research (RFBR). LDSD was supported by NWO grant 817.01.007. DT and EJ were supported by EU-REFRESH, EU-WISER, CLEAR (a Villum Kann Rasmussen Centre of Excellence Project on lake restoration) and CRES. We thank Prof. Andre De Roos for his insightful comments and Dr. Tom Andersen for his contribution to the text. JJ wishes to thank Drs. T. Aldenberg, Dr. L. Van Liere, Mr. M.J. 't Hart, Ir. M.H.J.L Jeuken, Ing. S. van Tol, Ir. J.S. Sloot and many others including the many people who provided lake data, for their contributions to PCLake. This is publication 4838 of the Netherlands Institute of Ecology (NIOO-KNAW).
. - ISSN 1386-2588
РУБ Ecology + Limnology + Marine & Freshwater Biology
Аннотация: A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the
functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
Доп.точки доступа: Mooij, W.M.; Trolle, D.; Jeppesen, E.; Arhonditsis, G.; Belolipetsky, P.V.; Белолипецкий, Павел Викторович; Chitamwebwa, D.B.R.; Degermendzhy, A.G.; DeAngelis, D.L.; Domis, L.N.D.; Downing, A.S.; Elliott, J.A.; Fragoso, C.R.; Gaedke, U.; Genova, S.N.; Генова, Светлана Николаевна; Gulati, R.D.; Hakanson, L.; Hamilton, D.P.; Hipsey, M.R.; 't Hoen, J.; Hulsmann, S.; Los, F.H.; Makler-Pick, V.; Petzoldt, T.; Prokopkin, I.G.; Rinke, K.; Schep, S.A.; Tominaga, K.; Van Dam, A.A.; Van Nes, E.H.; Wells, S.A.; Janse, J.H.
