@article{EhrlichGaedke2020,
  author    = {Ehrlich, Elias and Gaedke, Ursula},
  title     = {Coupled changes in traits and biomasses cascading through a tritrophic plankton food web},
  series = {Limnology and oceanography},
  volume    = {65},
  journal   = {Limnology and oceanography},
  number    = {10},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0024-3590},
  doi       = {10.1002/lno.11466},
  pages     = {2502 -- 2514},
  year      = {2020},
  abstract  = {Trait-based approaches have broadened our understanding of how the composition of ecological communities responds to environmental drivers. This research has mainly focussed on abiotic factors and competition determining the community trait distribution, while effects of trophic interactions on trait dynamics, if considered at all, have been studied for two trophic levels at maximum. However, natural food webs are typically at least tritrophic. This enables indirect interactions of traits and biomasses among multiple trophic levels leading to underexplored effects on food web dynamics. Here, we demonstrate the occurrence of mutual trait adjustment among three trophic levels in a natural plankton food web (Lake Constance) and in a corresponding mathematical model. We found highly recurrent seasonal biomass and trait dynamics, where herbivorous zooplankton increased its size, and thus its ability to counter phytoplankton defense, before phytoplankton defense actually increased. This is contrary to predictions from bitrophic systems where counter-defense of the consumer is a reaction to prey defense. In contrast, counter-defense of carnivores by size adjustment followed the defense of herbivores as expected. By combining observations and model simulations, we show how the reversed trait dynamics at the two lower trophic levels result from a "trophic biomass-trait cascade" driven by the carnivores. Trait adjustment between two trophic levels can therefore be altered by biomass or trait changes of adjacent trophic levels. Hence, analyses of only pairwise trait adjustment can be misleading in natural food webs, while multitrophic trait-based approaches capture indirect biomass-trait interactions among multiple trophic levels.},
  language  = {en}
}
@article{EhrlichKathGaedke2020,
  author    = {Ehrlich, Elias and Kath, Nadja Jeanette and Gaedke, Ursula},
  title     = {The shape of a defense-growth trade-off governs seasonal trait dynamics in natural phytoplankton},
  series = {The ISME journal},
  volume    = {14},
  journal   = {The ISME journal},
  number    = {6},
  publisher = {Nature Publishing Group},
  address   = {London},
  issn      = {1751-7362},
  doi       = {10.1038/s41396-020-0619-1},
  pages     = {1451 -- 1462},
  year      = {2020},
  abstract  = {Theory predicts that trade-offs, quantifying costs of functional trait adjustments, crucially affect community trait adaptation to altered environmental conditions, but empirical verification is scarce. We evaluated trait dynamics (antipredator defense, maximum growth rate, and phosphate affinity) of a lake phytoplankton community in a seasonally changing environment, using literature trait data and 21 years of species-resolved high-frequency biomass measurements. The trait data indicated a concave defense-growth trade-off, promoting fast-growing species with intermediate defense. With seasonally increasing grazing pressure, the community shifted toward higher defense levels at the cost of lower growth rates along the trade-off curve, while phosphate affinity explained some deviations from it. We discuss how low fitness differences of species, inferred from model simulations, in concert with stabilizing mechanisms, e.g., arising from further trait dimensions, may lead to the observed phytoplankton diversity. In conclusion, quantifying trade-offs is key for predictions of community trait adaptation and biodiversity under environmental change.},
  language  = {en}
}
@misc{EhrlichKathGaedke2020,
  author    = {Ehrlich, Elias and Kath, Nadja Jeanette and Gaedke, Ursula},
  title     = {The shape of a defense-growth trade-off governs seasonal trait dynamics in natural phytoplankton},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {6},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-51395},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-513956},
  pages     = {14},
  year      = {2020},
  abstract  = {Theory predicts that trade-offs, quantifying costs of functional trait adjustments, crucially affect community trait adaptation to altered environmental conditions, but empirical verification is scarce. We evaluated trait dynamics (antipredator defense, maximum growth rate, and phosphate affinity) of a lake phytoplankton community in a seasonally changing environment, using literature trait data and 21 years of species-resolved high-frequency biomass measurements. The trait data indicated a concave defense-growth trade-off, promoting fast-growing species with intermediate defense. With seasonally increasing grazing pressure, the community shifted toward higher defense levels at the cost of lower growth rates along the trade-off curve, while phosphate affinity explained some deviations from it. We discuss how low fitness differences of species, inferred from model simulations, in concert with stabilizing mechanisms, e.g., arising from further trait dimensions, may lead to the observed phytoplankton diversity. In conclusion, quantifying trade-offs is key for predictions of community trait adaptation and biodiversity under environmental change.},
  language  = {en}
}
@article{MooijTrolleJeppesenetal.2010,
  author    = {Mooij, Wolf M. and Trolle, Dennis and Jeppesen, Erik and Arhonditsis, George B. and Belolipetsky, Pavel V. and Chitamwebwa, Deonatus B. R. and Degermendzhy, Andrey G. and DeAngelis, Donald L. and Domis, Lisette Nicole de Senerpont and Downing, Andrea S. and Elliott, J. Alex and Fragoso Jr, Carlos Ruberto and Gaedke, Ursula and Genova, Svetlana N. and Gulati, Ramesh D. and H{\aa}kanson, Lars and Hamilton, David P. and Hipsey, Matthew R. and 't Hoen, Jochem and H{\"u}lsmann, Stephan and Los, F. Hans and Makler-Pick, Vardit and Petzoldt, Thomas and Prokopkin, Igor G. and Rinke, Karsten and Schep, Sebastiaan A. and Tominaga, Koji and Van Dam, Anne A. and Van Nes, Egbert H. and Wells, Scott A. and Janse, Jan H.},
  title     = {Challenges and opportunities for integrating lake ecosystem modelling approaches},
  series = {Aquatic ecology},
  volume    = {44},
  journal   = {Aquatic ecology},
  publisher = {Springer Science + Business Media B.V.},
  address   = {Dordrecht},
  issn      = {1573-5125},
  doi       = {10.1007/s10452-010-9339-3},
  pages     = {633 -- 667},
  year      = {2010},
  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 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.},
  language  = {en}
}
@misc{MooijTrolleJeppesenetal.2010,
  author    = {Mooij, Wolf M. and Trolle, Dennis and Jeppesen, Erik and Arhonditsis, George B. and Belolipetsky, Pavel V. and Chitamwebwa, Deonatus B. R. and Degermendzhy, Andrey G. and DeAngelis, Donald L. and Domis, Lisette Nicole de Senerpont and Downing, Andrea S. and Elliott, J. Alex and Fragoso Jr., Carlos Ruberto and Gaedke, Ursula and Genova, Svetlana N. and Gulati, Ramesh D. and H{\aa}kanson, Lars and Hamilton, David P. and Hipsey, Matthew R. and 't Hoen, Jochem and H{\"u}lsmann, Stephan and Los, F. Hans and Makler-Pick, Vardit and Petzoldt, Thomas and Prokopkin, Igor G. and Rinke, Karsten and Schep, Sebastiaan A. and Tominaga, Koji and Van Dam, Anne A. and Van Nes, Egbert H. and Wells, Scott A. and Janse, Jan H.},
  title     = {Challenges and opportunities for integrating lake ecosystem modelling approaches},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1326},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-42983},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-429839},
  pages     = {35},
  year      = {2010},
  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 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.},
  language  = {en}
}