4 results for Jeppesen, Erik

  • Exploring, exploiting and evolving diversity of aquatic ecosystem models: A community perspective

    Janssen, Annette B.G.; Arhonditsis, George B.; Beusen, Arthur; Bolding, Karsten; Bruce, Louise; Bruggeman, Jorn; Couture, Raoul-Marie; Downing, Andrea S.; Alex Elliott, J.; Frassl, Marieke A.; Gal, Gideon; Gerla, Daan J.; Hipsey, Matthew R.; Hu, Fenjuan; Ives, Stephen C.; Janse, Jan H.; Jeppesen, Erik; Jöhnk, Klaus D.; Kneis, David; Kong, Xiangzhen; Kuiper, Jan J.; Lehmann, Moritz K.; Lemmen, Carsten; Özkundakci, Deniz; Petzoldt, Thomas; Rinke, Karsten; Robson, Barbara J.; Sachse, René; Schep, Sebastiaan A.; Schmid, Martin; Scholten, Huub; Teurlincx, Sven; Trolle, Dennis; Troost, Tineke A.; Van Dam, Anne A.; Van Gerven, Luuk P. A.; Weijerman, Mariska; Wells, Scott A.; Mooij, Wolf M. (2015)

    Journal article
    University of Waikato

    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.

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  • Predicting the effects of climate change on trophic status of three morphologically varying lakes: Implications for lake restoration and management

    Trolle, Dennis; Hamilton, David P.; Pilditch, Conrad A.; Duggan, Ian C.; Jeppesen, Erik (2010)

    Journal article
    University of Waikato

    To quantify the effects of a future climate on three morphologically different lakes that varied in trophic status from oligo-mesotrophic to highly eutrophic, we applied the one-dimensional lake ecosystem model DYRESM-CAEDYM to oligo-mesotrophic Lake Okareka, eutrophic Lake Rotoehu, both in the temperate Bay of Plenty region, and highly eutrophic Lake Ellesmere, in the temperate Canterbury region, New Zealand. All three models were calibrated for a three-year period and validated for a separate two-year period. The model simulations generally showed good agreement with observed data for water column temperature, dissolved oxygen (DO), total phosphorus (TP), total nitrogen (TN) and chlorophyll a (Chl a) concentrations. To represent a possible future climate at the end of this century, mean annual changes in air temperature by 2100, derived from the IPCC A2 scenario downscaled for these lake regions, were added to the daily baseline temperatures for years 2002–2007. Lake model simulations using this future climate scenario indicate differential increases in eutrophication in all three lakes, especially during summer months. The predicted effects on annual mean surface water concentrations of TP, TN and Chl a will be equivalent to the effects of increasing external TN and TP loading by 25–50%. Simulations for the polymictic, eutrophic Lake Rotoehu further indicate that cyanophytes will be more abundant in the future climate, increasing by >15% in their contribution to annual mean Chl a. Therefore, future climate effects should be taken into account in the long-term planning and implementation of lake management as strategies may need to be refined and adapted to preserve or improve the present-day lake water quality.

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  • Challenges and opportunities for integrating lake ecosystem modelling approaches

    Mooij, Wolf M.; Trolle, Dennis; Jeppesen, Erik; Arhonditsis, George B.; Belolipetsky, Pavel V.; Chitamwebwa, Deonatus B.R.; Degermendzhy, Andrey G.; DeAngelis, Donald L.; Domis, Lisette N. De Senerpont; Downing, Andrea S.; Elliott, J. Alex; Fragoso, Carlos Ruberto, Jr.; Geadke, Ursula; Genova, Svetlana; Gulati, Ramesh D.; Hakanson, Lars; Hamilton, David P.; Hipsey, Matthew R.; Hoen, Jochem't; Hulsmann, Stephan; Los, F. Hans; Makler-Pick, Vardit; Petzoldt, Thomas; Prokopkin, Igor G.; Rinke, Karsten; Schep, Sebastiaan A.; Tominaga, Koji; Van Dam, Anne A.; Van Nes, Egbert H.; Wells, Scott A.; Janse, Jane H. (2010)

    Journal article
    University of Waikato

    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 trait-based 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.

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  • A community-based framework for aquatic ecosystem models

    Trolle, Dennis; Hamilton, David P.; Hipsey, Matthew R.; Bolding, Karsten; Bruggeman, Jorn; Mooij, Wolf M.; Janse, Jan H.; Nielsen, Anders; Jeppesen, Erik; Elliott, J. Alex; Makler-Pick, Vardit; Petzoldt, Thomas; Rinke, Karsten; Flindt, Mogens R.; Arhonditsis, George B.; Gal, Gideon; Bjerring, Rikke; Tominaga, Koji; Hoen, Jochem't; Downing, Andrea S.; Marques, David M.; Fragoso, Carlos R.; Søndergaard, Martin; Hanson, Paul C. (2011)

    Journal article
    University of Waikato

    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.

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