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Найдено документов в текущей БД: 2

    Challenges and opportunities for integrating lake ecosystem modelling approaches
[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.

    Long-term dynamics of chlorophyll concentration in the ocean surface layer (by space data)
/ A. Shevyrnogov, G. Vysotskaya // Advances in Space Research. - 2007. - Vol. 39, Is. 1. - P. 197-202, DOI 10.1016/j.asr.2006.10.015 . - ISSN 0273-1177

Кл.слова (ненормированные):
Dynamics -- Ocean -- Phytopigment -- Climatology -- Concentration (process) -- Hydrology -- Marine biology -- Ocean currents -- Plants (botany) -- Biosphere -- Ocean -- Phytopigments -- Chlorophyll

Аннотация: To preserve the biosphere and to use it efficiently, it is necessary to gain a deep insight into the dynamics of the primary production process on our planet. Variability of chlorophyll concentration in the ocean is one of the most important components of this process. These investigations are, however, very labor-consuming, because of the difficulties related to the accessibility of the water surface and its large size. In this work long-term changes in chlorophyll concentration in the surface layer of the ocean have been analyzed on the basis of the CZCS data for 7.5 years from 1979 to 1986 and the SeaWiFS data from 1997 to 2004. It has been shown that the average chlorophyll concentration calculated in all investigated areas varies moderately. However, when analyzing spatially local trends, the areas have been detected that have significant rise and fall of chlorophyll concentrations. Some interesting features of the long-term dynamics of chlorophyll concentration have been found. The opposite directions of long-term trends (essential increase or decrease) cannot be explained only by large-scale hydrological phenomena in the ocean (currents, upwellings, etc.). The measured chlorophyll concentration results from the balance between production and destruction processes. Which process dominates is determined by various hydrophysical, hydrobiological, and climatic processes, leading to sharp rises or falls of the concentration. It is important to estimate the scale of the areas in which this or that process dominates. Therefore, the study addresses not only the dynamics of the mean value but also the dynamics of the areas in which the dominance of certain factors has led to a sharp fall or rise in chlorophyll concentration. Thus, the obtained results can be used to estimate long-term changes in the ocean biota. В© 2006 COSPAR.

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Доп.точки доступа:
Shevyrnogov, A.; Vysotskaya, G.; Высоцкая, Галина Степановна