TY - JOUR A1 - van Rees, Charles B. A1 - Waylen, Kerry A. A1 - Schmidt-Kloiber, Astrid A1 - Thackeray, Stephen J. A1 - Kalinkat, Gregor A1 - Martens, Koen A1 - Domisch, Sami A1 - Lillebo, Ana A1 - Hermoso, Virgilio A1 - Grossart, Hans-Peter A1 - Schinegger, Rafaela A1 - Decleer, Kris A1 - Adriaens, Tim A1 - Denys, Luc A1 - Jaric, Ivan A1 - Janse, Jan H. A1 - Monaghan, Michael T. A1 - De Wever, Aaike A1 - Geijzendorffer, Ilse A1 - Adamescu, Mihai C. A1 - Jähnig, Sonja C. T1 - Safeguarding freshwater life beyond 2020 BT - recommendations for the new global biodiversity framework from the European experience JF - Conservation letters N2 - Plans are currently being drafted for the next decade of action on biodiversity-both the post-2020 Global Biodiversity Framework of the Convention on Biological Diversity (CBD) and Biodiversity Strategy of the European Union (EU). Freshwater biodiversity is disproportionately threatened and underprioritized relative to the marine and terrestrial biota, despite supporting a richness of species and ecosystems with their own intrinsic value and providing multiple essential ecosystem services. Future policies and strategies must have a greater focus on the unique ecology of freshwater life and its multiple threats, and now is a critical time to reflect on how this may be achieved. We identify priority topics including environmental flows, water quality, invasive species, integrated water resources management, strategic conservation planning, and emerging technologies for freshwater ecosystem monitoring. We synthesize these topics with decades of first-hand experience and recent literature into 14 special recommendations for global freshwater biodiversity conservation based on the successes and setbacks of European policy, management, and research. Applying and following these recommendations will inform and enhance the ability of global and European post-2020 biodiversity agreements to halt and reverse the rapid global decline of freshwater biodiversity. KW - climate change KW - conservation KW - ecosystem services KW - rivers KW - sustainable KW - development goals KW - water resources KW - wetlands Y1 - 2020 U6 - https://doi.org/10.1111/conl.12771 SN - 1755-263X VL - 14 IS - 1 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Mooij, Wolf M. A1 - Brederveld, Robert J. A1 - de Klein, Jeroen J. M. A1 - DeAngelis, Don L. A1 - Downing, Andrea S. A1 - Faber, Michiel A1 - Gerla, Daan J. A1 - Hipsey, Matthew R. A1 - Janse, Jan H. A1 - Janssen, Annette B. G. A1 - Jeuken, Michel A1 - Kooi, Bob W. A1 - Lischke, Betty A1 - Petzoldt, Thomas A1 - Postma, Leo A1 - Schep, Sebastiaan A. A1 - Scholten, Huub A1 - Teurlincx, Sven A1 - Thiange, Christophe A1 - Trolle, Dennis A1 - van Dam, Anne A. A1 - van Gerven, Luuk P. A. A1 - van Nes, Egbert H. A1 - Kuiper, Jan J. T1 - Serving many at once: How a database approach can create unity in dynamical ecosystem modelling JF - Environmental modelling & software with environment data news N2 - 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/). KW - Modelling framework KW - Programming language KW - Differential equation KW - Community-based modelling KW - Database approach to modelling KW - DATM Y1 - 2014 U6 - https://doi.org/10.1016/j.envsoft.2014.04.004 SN - 1364-8152 SN - 1873-6726 VL - 61 SP - 266 EP - 273 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Sachse, Rene A1 - Petzoldt, Thomas A1 - Blumstock, Maria A1 - Moreira, Santiago A1 - Paetzig, Marlene A1 - Ruecker, Jacqueline A1 - Janse, Jan H. A1 - Mooij, Wolf M. A1 - Hilt, Sabine T1 - Extending one-dimensional models for deep lakes to simulate the impact of submerged macrophytes on water quality JF - Environmental modelling & software with environment data news N2 - 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. (C) 2014 Elsevier Ltd. All rights reserved. KW - Lake model KW - Macrophytes KW - Water quality Y1 - 2014 U6 - https://doi.org/10.1016/j.envsoft.2014.05.023 SN - 1364-8152 SN - 1873-6726 VL - 61 SP - 410 EP - 423 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Lischke, Betty A1 - Hilt, Sabine A1 - Janse, Jan H. A1 - Kuiper, Jan J. A1 - Mehner, Thomas A1 - Mooij, Wolf M. A1 - Gaedke, Ursula T1 - Enhanced input of terrestrial particulate organic matter reduces the resilience of the clear-water state of shallow lakes: A model study JF - Ecosystems N2 - The amount of terrestrial particulate organic matter (t-POM) entering lakes is predicted to increase as a result of climate change. This may especially alter the structure and functioning of ecosystems in small, shallow lakes which can rapidly shift from a clear-water, macrophyte-dominated into a turbid, phytoplankton-dominated state. We used the integrative ecosystem model PCLake to predict how rising t-POM inputs affect the resilience of the clear-water state. PCLake links a pelagic and benthic food chain with abiotic components by a number of direct and indirect effects. We focused on three pathways (zoobenthos, zooplankton, light availability) by which elevated t-POM inputs (with and without additional nutrients) may modify the critical nutrient loading thresholds at which a clear-water lake becomes turbid and vice versa. Our model results show that (1) increased zoobenthos biomass due to the enhanced food availability results in more benthivorous fish which reduce light availability due to bioturbation, (2) zooplankton biomass does not change, but suspended t-POM reduces the consumption of autochthonous particulate organic matter which increases the turbidity, and (3) the suspended t-POM reduces the light availability for submerged macrophytes. Therefore, light availability is the key process that is indirectly or directly changed by t-POM input. This strikingly resembles the deteriorating effect of terrestrial dissolved organic matter on the light climate of lakes. In all scenarios, the resilience of the clear-water state is reduced thus making the turbid state more likely at a given nutrient loading. Therefore, our study suggests that rising t-POM input can add to the effects of climate warming making reductions in nutrient loadings even more urgent. KW - climate change KW - PCLake KW - bistability KW - alternative stable states KW - critical nutrient loading KW - ecosystem modeling KW - allochthony KW - t-POM Y1 - 2014 U6 - https://doi.org/10.1007/s10021-014-9747-7 SN - 1432-9840 SN - 1435-0629 VL - 17 IS - 4 SP - 616 EP - 626 PB - Springer CY - New York ER - 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 - JOUR A1 - van Gerven, Luuk P. A. A1 - Brederveld, Robert J. A1 - de Klein, Jeroen J. M. A1 - DeAngelis, Don L. A1 - Downing, Andrea S. A1 - Faber, Michiel A1 - Gerla, Daan J. A1 - Janse, Jan H. A1 - Janssen, Annette B. G. A1 - Jeuken, Michel A1 - Kooi, Bob W. A1 - Kuiper, Jan J. A1 - Lischke, Betty A1 - Liu, Sien A1 - Petzoldt, Thomas A1 - Schep, Sebastiaan A. A1 - Teurlincx, Sven A1 - Thiange, Christophe A1 - Trolle, Dennis A1 - van Nes, Egbert H. A1 - Mooij, Wolf M. T1 - Advantages of concurrent use of multiple software frameworks in water quality modelling using a database approach JF - Fundamental and applied limnology : official journal of the International Association of Theoretical and Applied Limnology N2 - Water quality modelling deals with multidisciplinary questions ranging from fundamental to applied. Addressing this broad range of questions requires multiple analysis techniques and therefore multiple frameworks. Through the recently developed database approach to modelling (DATM), it has become possible to run a model in multiple software frameworks without much overhead. Here we apply DATM to the ecosystem model for ditches PCDitch and its twin model for shallow lakes PCLake. Using DATM, we run these models in six frameworks (ACSL, DELWAQ, DUFLOW, GRIND for MATLAB, OSIRIS and R), and report on the possible model analyses with tools provided by each framework. We conclude that the dynamic link between frameworks and models resulting from DATM has the following main advantages: it allows one to use the framework one is familiar with for most model analyses and eases switching between frameworks for complementary model analyses, including the switch between a 0-D and 1-D to 3-D setting. Moreover, the strength of each framework - including runtime performance - can now be easily exploited. We envision that a community-based further development of the concept can contribute to the future development of water quality modelling, not only by addressing multidisciplinary questions but also by facilitating the exchange of models and process formulations within the community of water quality modellers. KW - Database Approach To Modelling KW - DATM KW - PCLake KW - PCDitch KW - OSIRIS KW - ACSL KW - R KW - GRIND KW - DUFLOW KW - DELWAQ KW - Modelling Framework KW - Model Implementation KW - Model Analysis KW - Differential Equations KW - Community-based Modelling Y1 - 2015 U6 - https://doi.org/10.1127/fal/2015/0631 SN - 1863-9135 VL - 186 IS - 1-2 SP - 5 EP - 20 PB - Schweizerbart CY - Stuttgart 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 -