TY  - JOUR
A1  - Janssen, Annette B. G.
A1  - Arhonditsis, George B.
A1  - Beusen, Arthur
A1  - Bolding, Karsten
A1  - Bruce, Louise
A1  - Bruggeman, Jorn
A1  - Couture, Raoul-Marie
A1  - Downing, Andrea S.
A1  - Elliott, J. Alex
A1  - Frassl, Marieke A.
A1  - Gal, Gideon
A1  - Gerla, Daan J.
A1  - Hipsey, Matthew R.
A1  - Hu, Fenjuan
A1  - Ives, Stephen C.
A1  - Janse, Jan H.
A1  - Jeppesen, Erik
A1  - Joehnk, Klaus D.
A1  - Kneis, David
A1  - Kong, Xiangzhen
A1  - Kuiper, Jan J.
A1  - Lehmann, Moritz K.
A1  - Lemmen, Carsten
A1  - Oezkundakci, Deniz
A1  - Petzoldt, Thomas
A1  - Rinke, Karsten
A1  - Robson, Barbara J.
A1  - Sachse, Rene
A1  - Schep, Sebastiaan A.
A1  - Schmid, Martin
A1  - Scholten, Huub
A1  - Teurlincx, Sven
A1  - Trolle, Dennis
A1  - Troost, Tineke A.
A1  - Van Dam, Anne A.
A1  - Van Gerven, Luuk P. A.
A1  - Weijerman, Mariska
A1  - Wells, Scott A.
A1  - Mooij, Wolf M.
T1  - Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective
JF  - Aquatic ecology : the international forum covering research in freshwater and marine environments
N2  - 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.
KW  - Water quality
KW  - Ecology
KW  - Geochemistry
KW  - Hydrology
KW  - Hydraulics
KW  - Hydrodynamics
KW  - Physical environment
KW  - Socio-economics
KW  - Model availability
KW  - Standardization
KW  - Linking
Y1  - 2015
U6  - https://doi.org/10.1007/s10452-015-9544-1
SN  - 1386-2588
SN  - 1573-5125
VL  - 49
IS  - 4
SP  - 513
EP  - 548
PB  - Springer
CY  - Dordrecht
ER  - 
TY  - GEN
A1  - Mooij, Wolf M.
A1  - Trolle, Dennis
A1  - Jeppesen, Erik
A1  - Arhonditsis, George B.
A1  - Belolipetsky, Pavel V.
A1  - Chitamwebwa, Deonatus B. R.
A1  - Degermendzhy, Andrey G.
A1  - DeAngelis, Donald L.
A1  - Domis, Lisette Nicole de Senerpont
A1  - Downing, Andrea S.
A1  - Elliott, J. Alex
A1  - Fragoso Jr., Carlos Ruberto
A1  - Gaedke, Ursula
A1  - Genova, Svetlana N.
A1  - Gulati, Ramesh D.
A1  - Håkanson, Lars
A1  - Hamilton, David P.
A1  - Hipsey, Matthew R.
A1  - ‘t Hoen, Jochem
A1  - Hülsmann, Stephan
A1  - Los, F. Hans
A1  - Makler-Pick, Vardit
A1  - Petzoldt, Thomas
A1  - Prokopkin, Igor G.
A1  - Rinke, Karsten
A1  - Schep, Sebastiaan A.
A1  - Tominaga, Koji
A1  - Van Dam, Anne A.
A1  - Van Nes, Egbert H.
A1  - Wells, Scott A.
A1  - Janse, Jan H.
T1  - Challenges and opportunities for integrating lake ecosystem modelling approaches
T2  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2  - 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.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1326 
KW  - aquatic
KW  - food web dynamics
KW  - plankton
KW  - nutrients
KW  - spatial
KW  - lake
KW  - freshwater
KW  - marine
KW  - community
KW  - population
KW  - hydrology
KW  - eutrophication
KW  - global change
KW  - climate warming
KW  - fisheries
KW  - biodiversity
KW  - management
KW  - mitigation
KW  - adaptive processes
KW  - non-linear dynamics
KW  - analysis
KW  - bifurcation
KW  - understanding
KW  - prediction
KW  - model limitations
KW  - model integration
Y1  - 2010
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-429839
SN  - 1866-8372
IS  - 1326
ER  - 
TY  - JOUR
A1  - Mooij, Wolf M.
A1  - Trolle, Dennis
A1  - Jeppesen, Erik
A1  - Arhonditsis, George B.
A1  - Belolipetsky, Pavel V.
A1  - Chitamwebwa, Deonatus B. R.
A1  - Degermendzhy, Andrey G.
A1  - DeAngelis, Donald L.
A1  - Domis, Lisette Nicole de Senerpont
A1  - Downing, Andrea S.
A1  - Elliott, J. Alex
A1  - Fragoso Jr, Carlos Ruberto
A1  - Gaedke, Ursula
A1  - Genova, Svetlana N.
A1  - Gulati, Ramesh D.
A1  - Håkanson, Lars
A1  - Hamilton, David P.
A1  - Hipsey, Matthew R.
A1  - ‘t Hoen, Jochem
A1  - Hülsmann, Stephan
A1  - Los, F. Hans
A1  - Makler-Pick, Vardit
A1  - Petzoldt, Thomas
A1  - Prokopkin, Igor G.
A1  - Rinke, Karsten
A1  - Schep, Sebastiaan A.
A1  - Tominaga, Koji
A1  - Van Dam, Anne A.
A1  - Van Nes, Egbert H.
A1  - Wells, Scott A.
A1  - Janse, Jan H.
T1  - Challenges and opportunities for integrating lake ecosystem modelling approaches
JF  - Aquatic ecology
N2  - 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.
KW  - aquatic
KW  - food web dynamics
KW  - plankton
KW  - nutrients
KW  - spatial
KW  - lake
KW  - freshwater
KW  - marine
KW  - community
KW  - population
KW  - hydrology
KW  - eutrophication
KW  - global change
KW  - climate warming
KW  - fisheries
KW  - biodiversity
KW  - management
KW  - mitigation
KW  - adaptive processes
KW  - non-linear dynamics
KW  - analysis
KW  - bifurcation
KW  - understanding
KW  - prediction
KW  - model limitations
KW  - model integration
Y1  - 2010
U6  - https://doi.org/10.1007/s10452-010-9339-3
SN  - 1573-5125
SN  - 1386-2588
VL  - 44
SP  - 633
EP  - 667
PB  - Springer Science + Business Media B.V.
CY  - Dordrecht
ER  -