Challenges and opportunities for integrating lake ecosystem modelling approaches

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

Research output: Contribution to journalArticle

147 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)633-667
Number of pages35
JournalAquatic Ecology
Volume44
Issue number3
DOIs
StatePublished - Sep 2 2010

Fingerprint

ecosystem modeling
lake ecosystem
lakes
ecosystems
dynamic models

Keywords

  • Adaptive processes
  • Analysis
  • Aquatic
  • Bifurcation
  • Biodiversity
  • Climate warming
  • Community
  • Eutrophication
  • Fisheries
  • Food web dynamics
  • Freshwater
  • Global change
  • Hydrology
  • Lake
  • Management
  • Marine
  • Mitigation
  • Model integration
  • Model limitations
  • Non-linear dynamics
  • Nutrients
  • Plankton
  • Population
  • Prediction
  • Spatial
  • Understanding

ASJC Scopus subject areas

  • Aquatic Science
  • Ecology, Evolution, Behavior and Systematics

Cite this

Mooij, W. M., Trolle, D., Jeppesen, E., Arhonditsis, G., Belolipetsky, P. V., Chitamwebwa, D. B. R., ... Janse, J. H. (2010). Challenges and opportunities for integrating lake ecosystem modelling approaches. Aquatic Ecology, 44(3), 633-667. https://doi.org/10.1007/s10452-010-9339-3

Challenges and opportunities for integrating lake ecosystem modelling approaches. / Mooij, Wolf M.; Trolle, Dennis; Jeppesen, Erik; Arhonditsis, George; Belolipetsky, Pavel V.; Chitamwebwa, Deonatus B R; Degermendzhy, Andrey G.; DeAngelis, Donald L.; De Senerpont Domis, Lisette N.; Downing, Andrea S.; Elliott, J. Alex; Fragoso, Carlos Ruberto; Gaedke, Ursula; Genova, Svetlana N.; Gulati, Ramesh D.; Håkanson, Lars; Hamilton, David P.; Hipsey, Matthew R.; 't Hoen, Jochem; Hülsmann, 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, Jan H.

In: Aquatic Ecology, Vol. 44, No. 3, 02.09.2010, p. 633-667.

Research output: Contribution to journalArticle

Mooij, WM, Trolle, D, Jeppesen, E, Arhonditsis, G, Belolipetsky, PV, Chitamwebwa, DBR, Degermendzhy, AG, DeAngelis, DL, De Senerpont Domis, LN, Downing, AS, Elliott, JA, Fragoso, CR, Gaedke, U, Genova, SN, Gulati, RD, Håkanson, L, Hamilton, DP, Hipsey, MR, 't Hoen, J, Hülsmann, S, Los, FH, Makler-Pick, V, Petzoldt, T, Prokopkin, IG, Rinke, K, Schep, SA, Tominaga, K, van Dam, AA, van Nes, EH, Wells, SA & Janse, JH 2010, 'Challenges and opportunities for integrating lake ecosystem modelling approaches', Aquatic Ecology, vol. 44, no. 3, pp. 633-667. https://doi.org/10.1007/s10452-010-9339-3
Mooij WM, Trolle D, Jeppesen E, Arhonditsis G, Belolipetsky PV, Chitamwebwa DBR et al. Challenges and opportunities for integrating lake ecosystem modelling approaches. Aquatic Ecology. 2010 Sep 2;44(3):633-667. https://doi.org/10.1007/s10452-010-9339-3
Mooij, Wolf M. ; Trolle, Dennis ; Jeppesen, Erik ; Arhonditsis, George ; Belolipetsky, Pavel V. ; Chitamwebwa, Deonatus B R ; Degermendzhy, Andrey G. ; DeAngelis, Donald L. ; De Senerpont Domis, Lisette N. ; Downing, Andrea S. ; Elliott, J. Alex ; Fragoso, Carlos Ruberto ; Gaedke, Ursula ; Genova, Svetlana N. ; Gulati, Ramesh D. ; Håkanson, Lars ; Hamilton, David P. ; Hipsey, Matthew R. ; 't Hoen, Jochem ; Hülsmann, 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, Jan H. / Challenges and opportunities for integrating lake ecosystem modelling approaches. In: Aquatic Ecology. 2010 ; Vol. 44, No. 3. pp. 633-667.
@article{50c03761cc6d450fafc81f45eb817223,
title = "Challenges and opportunities for integrating lake ecosystem modelling approaches",
abstract = "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.",
keywords = "Adaptive processes, Analysis, Aquatic, Bifurcation, Biodiversity, Climate warming, Community, Eutrophication, Fisheries, Food web dynamics, Freshwater, Global change, Hydrology, Lake, Management, Marine, Mitigation, Model integration, Model limitations, Non-linear dynamics, Nutrients, Plankton, Population, Prediction, Spatial, Understanding",
author = "Mooij, {Wolf M.} and Dennis Trolle and Erik Jeppesen and George Arhonditsis and Belolipetsky, {Pavel V.} and Chitamwebwa, {Deonatus B R} and Degermendzhy, {Andrey G.} and DeAngelis, {Donald L.} and {De Senerpont Domis}, {Lisette N.} and Downing, {Andrea S.} and Elliott, {J. Alex} and Fragoso, {Carlos Ruberto} and Ursula Gaedke and Genova, {Svetlana N.} and Gulati, {Ramesh D.} and Lars H{\aa}kanson and Hamilton, {David P.} and Hipsey, {Matthew R.} and {'t Hoen}, Jochem and Stephan H{\"u}lsmann and Los, {F. Hans} and Vardit Makler-Pick and Thomas Petzoldt and Prokopkin, {Igor G.} and Karsten Rinke and Schep, {Sebastiaan A.} and Koji Tominaga and {van Dam}, {Anne A.} and {van Nes}, {Egbert H.} and Wells, {Scott A.} and Janse, {Jan H.}",
year = "2010",
month = "9",
day = "2",
doi = "10.1007/s10452-010-9339-3",
language = "English",
volume = "44",
pages = "633--667",
journal = "Netherlands Journal of Aquatic Ecology",
issn = "1380-8427",
publisher = "Springer Netherlands",
number = "3",

}

TY - JOUR

T1 - Challenges and opportunities for integrating lake ecosystem modelling approaches

AU - Mooij, Wolf M.

AU - Trolle, Dennis

AU - Jeppesen, Erik

AU - Arhonditsis, George

AU - Belolipetsky, Pavel V.

AU - Chitamwebwa, Deonatus B R

AU - Degermendzhy, Andrey G.

AU - DeAngelis, Donald L.

AU - De Senerpont Domis, Lisette N.

AU - Downing, Andrea S.

AU - Elliott, J. Alex

AU - Fragoso, Carlos Ruberto

AU - Gaedke, Ursula

AU - Genova, Svetlana N.

AU - Gulati, Ramesh D.

AU - Håkanson, Lars

AU - Hamilton, David P.

AU - Hipsey, Matthew R.

AU - 't Hoen, Jochem

AU - Hülsmann, Stephan

AU - Los, F. Hans

AU - Makler-Pick, Vardit

AU - Petzoldt, Thomas

AU - Prokopkin, Igor G.

AU - Rinke, Karsten

AU - Schep, Sebastiaan A.

AU - Tominaga, Koji

AU - van Dam, Anne A.

AU - van Nes, Egbert H.

AU - Wells, Scott A.

AU - Janse, Jan H.

PY - 2010/9/2

Y1 - 2010/9/2

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 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.

AB - 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.

KW - Adaptive processes

KW - Analysis

KW - Aquatic

KW - Bifurcation

KW - Biodiversity

KW - Climate warming

KW - Community

KW - Eutrophication

KW - Fisheries

KW - Food web dynamics

KW - Freshwater

KW - Global change

KW - Hydrology

KW - Lake

KW - Management

KW - Marine

KW - Mitigation

KW - Model integration

KW - Model limitations

KW - Non-linear dynamics

KW - Nutrients

KW - Plankton

KW - Population

KW - Prediction

KW - Spatial

KW - Understanding

UR - http://www.scopus.com/inward/record.url?scp=77956268654&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77956268654&partnerID=8YFLogxK

U2 - 10.1007/s10452-010-9339-3

DO - 10.1007/s10452-010-9339-3

M3 - Article

AN - SCOPUS:77956268654

VL - 44

SP - 633

EP - 667

JO - Netherlands Journal of Aquatic Ecology

JF - Netherlands Journal of Aquatic Ecology

SN - 1380-8427

IS - 3

ER -