@article{JanssenArhonditsisBeusenetal.2015,
  author    = {Janssen, Annette B. G. and Arhonditsis, George B. and Beusen, Arthur and Bolding, Karsten and Bruce, Louise and Bruggeman, Jorn and Couture, Raoul-Marie and Downing, Andrea S. and Elliott, J. Alex and Frassl, Marieke A. and Gal, Gideon and Gerla, Daan J. and Hipsey, Matthew R. and Hu, Fenjuan and Ives, Stephen C. and Janse, Jan H. and Jeppesen, Erik and Joehnk, Klaus D. and Kneis, David and Kong, Xiangzhen and Kuiper, Jan J. and Lehmann, Moritz K. and Lemmen, Carsten and Oezkundakci, Deniz and Petzoldt, Thomas and Rinke, Karsten and Robson, Barbara J. and Sachse, Rene and Schep, Sebastiaan A. and Schmid, Martin and Scholten, Huub and Teurlincx, Sven and Trolle, Dennis and Troost, Tineke A. and Van Dam, Anne A. and Van Gerven, Luuk P. A. and Weijerman, Mariska and Wells, Scott A. and Mooij, Wolf M.},
  title     = {Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective},
  series = {Aquatic ecology : the international forum covering research in freshwater and marine environments},
  volume    = {49},
  journal   = {Aquatic ecology : the international forum covering research in freshwater and marine environments},
  number    = {4},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {1386-2588},
  doi       = {10.1007/s10452-015-9544-1},
  pages     = {513 -- 548},
  year      = {2015},
  abstract  = {Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5-10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary.},
  language  = {en}
}
@article{MooijBredervelddeKleinetal.2014,
  author    = {Mooij, Wolf M. and Brederveld, Robert J. and de Klein, Jeroen J. M. and DeAngelis, Don L. and Downing, Andrea S. and Faber, Michiel and Gerla, Daan J. and Hipsey, Matthew R. and Janse, Jan H. and Janssen, Annette B. G. and Jeuken, Michel and Kooi, Bob W. and Lischke, Betty and Petzoldt, Thomas and Postma, Leo and Schep, Sebastiaan A. and Scholten, Huub and Teurlincx, Sven and Thiange, Christophe and Trolle, Dennis and van Dam, Anne A. and van Gerven, Luuk P. A. and van Nes, Egbert H. and Kuiper, Jan J.},
  title     = {Serving many at once: How a database approach can create unity in dynamical ecosystem modelling},
  series = {Environmental modelling \& software with environment data news},
  volume    = {61},
  journal   = {Environmental modelling \& software with environment data news},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {1364-8152},
  doi       = {10.1016/j.envsoft.2014.04.004},
  pages     = {266 -- 273},
  year      = {2014},
  abstract  = {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. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-SA license (http://creativecommons.org/licenses/by-nc-sa/3.0/).},
  language  = {en}
}