Extending one-dimensional models for deep lakes to simulate the impact of submerged macrophytes on water quality
Sachse, R. ; Petzoldt, T. ; Blumstock, M. ; Moreira, S. ; Pätzig, M. ; Rücker, J. ; Janse, J.H. ; Mooij, W.M. ; Hilt, S. - \ 2014
Environmental Modelling & Software 61 (2014). - ISSN 1364-8152 - p. 410 - 423.
shallow eutrophic lakes - phytoplankton biomass - nutrient dynamics - phosphorus - ecosystem - growth - state - fish - zooplankton - vegetation
Submerged macrophytes can stabilise clear water conditions in shallow lakes. However, many existing models for deep lakes neglect their impact. Here, we tested the hypothesis that submerged macrophytes can affect the water clarity in deep lakes. A one-dimensional, vertically resolved macrophyte model was developed based on PCLake and coupled to SALMO-1D and GOTM hydrophysics and validated against field data. Validation showed good coherence in dynamic growth patterns and colonisation depths. In our simulations the presence of submerged macrophytes resulted in up to 50% less phytoplankton biomass in the shallowest simulated lake (11 m) and still 15% less phytoplankton was predicted in 100 m deep oligotrophic lakes. Nutrient loading, lake depth, and lake shape had a strong influence on macrophyte effects. Nutrient competition was found to be the strongest biological interaction. Despite a number of limitations, the derived dynamic lake model suggests significant effects of submerged macrophytes on deep lake water quality.
Serving many at once: How a database approach can create unity in dynamical ecosystem modelling
Mooij, W.M. ; Brederveld, R.J. ; Klein, J.J.M. de; DeAngelis, D.L. ; Downing, A.S. ; Faber, M. ; Gerla, D.J. ; Hipsey, M.R. ; Hoen, J. 't; Janse, J.H. ; Janssen, A.B.G. ; Jeuken, M. ; Kooi, B.W. ; Lischke, B. ; Petzoldt, T. ; Postma, L. ; Schep, S.A. ; Scholten, H. ; Teurlincx, S. ; Thiange, C. ; Trolle, D. ; Dam, A.A. van; Gerven, L.P.A. van; Nes, E.H. van; Kuiper, J.J. - \ 2014
Environmental Modelling & Software 61 (2014). - ISSN 1364-8152 - p. 266 - 273.
shallow lakes - simulation - eutrophication - management - package - pclake
Simulation modelling in ecology is a field that is becoming increasingly compartmentalized. Here we propose a Database Approach To Modelling (DATM) to create unity in dynamical ecosystem modelling with differential equations. In this approach the storage of ecological knowledge is independent of the language and platform in which the model will be run. To create an instance of the model, the information in the database is translated and augmented with the language and platform specifics. This process is automated so that a new instance can be created each time the database is updated. We describe the approach using the simple Lotka-Volterra model and the complex ecosystem model for shallow lakes PCLake, which we automatically implement in the frameworks OSIRIS, GRIND for MATLAB, ACSL, R, DUFLOW and DELWAQ. A clear advantage of working in a database is the overview it provides. The simplicity of the approach only adds to its elegance. © 2014 The Authors.
A community-based framework for aquatic ecosystem models
Trolle, D. ; Hamilton, D.P. ; Hipsey, M.R. ; Bolding, K. ; Bruggeman, J. ; Mooij, W.M. ; Janse, J.H. ; Nielsen, A. ; Jeppesen, E. ; Elliott, J.A. ; Makler-Pick, V. ; Petzoldt, T. ; Rinke, K. ; Flindt, M.R. ; Arhonditsis, G.B. ; Gal, G. ; Bjerring, R. ; Tominaga, K. ; Hoen, J. 't; Downing, A.S. ; Marques, D.M. ; Fragoso, C.R. ; Sondergaard, M. ; Hanson, P.C. - \ 2012
Hydrobiologia 683 (2012)1. - ISSN 0018-8158 - p. 25 - 34.
climate-change - lake kinneret - phytoplankton - management - fish
Here, we communicate a point of departure in the development of aquatic ecosystem models, namely a new community-based framework, which supports an enhanced and transparent union between the collective expertise that exists in the communities of traditional ecologists and model developers. Through a literature survey, we document the growing importance of numerical aquatic ecosystem models while also noting the difficulties, up until now, of the aquatic scientific community to make significant advances in these models during the past two decades. Through a common forum for aquatic ecosystem modellers we aim to (i) advance collaboration within the aquatic ecosystem modelling community, (ii) enable increased use of models for research, policy and ecosystem-based management, (iii) facilitate a collective framework using common (standardised) code to ensure that model development is incremental, (iv) increase the transparency of model structure, assumptions and techniques, (v) achieve a greater understanding of aquatic ecosystem functioning, (vi) increase the reliability of predictions by aquatic ecosystem models, (vii) stimulate model inter-comparisons including differing model approaches, and (viii) avoid 're-inventing the wheel', thus accelerating improvements to aquatic ecosystem models. We intend to achieve this as a community that fosters interactions amongst ecologists and model developers. Further, we outline scientific topics recently articulated by the scientific community, which lend themselves well to being addressed by integrative modelling approaches and serve to motivate the progress and implementation of an open source model framework.
Challenges and opportunities for integrating lake ecosystem modelling approaches
Mooij, W.M. ; Trolle, D. ; Jeppesen, E. ; Arhonditsis, G. ; Belolipetsky, P.V. ; 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. ; Gulati, R.D. ; Hakanson, L. ; Hamilton, D.P. ; Hipsey, M.R. ; Hoen, J. 't; Hulsmann, S. ; Los, F.H. ; Makler-Pick, V. ; Petzoldt, T. ; Prokopkin, I.G. ; Rinke, K. ; Schep, S.A. ; Tominaga, K. ; Dam, A.A. van; Nes, E.H. van; Wells, S.A. ; Janse, J.H. - \ 2010
Aquatic Ecology 44 (2010)3. - ISSN 1386-2588 - p. 633 - 667.
fresh-water ecosystems - of-the-art - daphnia population-dynamics - trophic state indicators - predator-prey system - causes regime shifts - library salmo-oo - shallow lakes - climate-change - submerged macrophytes
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.