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 - GEN A1 - Wurzbacher, Christian A1 - Fuchs, Andrea A1 - Attermeyer, Katrin A1 - Frindte, Katharina A1 - Grossart, Hans-Peter A1 - Hupfer, Michael A1 - Casper, Peter A1 - Monaghan, Michael T. T1 - Shifts among Eukaryota, Bacteria, and Archaea define the vertical organization of a lake sediment T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Background Lake sediments harbor diverse microbial communities that cycle carbon and nutrients while being constantly colonized and potentially buried by organic matter sinking from the water column. The interaction of activity and burial remained largely unexplored in aquatic sediments. We aimed to relate taxonomic composition to sediment biogeochemical parameters, test whether community turnover with depth resulted from taxonomic replacement or from richness effects, and to provide a basic model for the vertical community structure in sediments. Methods We analyzed four replicate sediment cores taken from 30-m depth in oligo-mesotrophic Lake Stechlin in northern Germany. Each 30-cm core spanned ca. 170 years of sediment accumulation according to 137Cs dating and was sectioned into layers 1–4 cm thick. We examined a full suite of biogeochemical parameters and used DNA metabarcoding to examine community composition of microbial Archaea, Bacteria, and Eukaryota. Results Community β-diversity indicated nearly complete turnover within the uppermost 30 cm. We observed a pronounced shift from Eukaryota- and Bacteria-dominated upper layers (<5 cm) to Bacteria-dominated intermediate layers (5–14 cm) and to deep layers (>14 cm) dominated by enigmatic Archaea that typically occur in deep-sea sediments. Taxonomic replacement was the prevalent mechanism in structuring the community composition and was linked to parameters indicative of microbial activity (e.g., CO2 and CH4 concentration, bacterial protein production). Richness loss played a lesser role but was linked to conservative parameters (e.g., C, N, P) indicative of past conditions. Conclusions By including all three domains, we were able to directly link the exponential decay of eukaryotes with the active sediment microbial community. The dominance of Archaea in deeper layers confirms earlier findings from marine systems and establishes freshwater sediments as a potential low-energy environment, similar to deep sea sediments. We propose a general model of sediment structure and function based on microbial characteristics and burial processes. An upper “replacement horizon” is dominated by rapid taxonomic turnover with depth, high microbial activity, and biotic interactions. A lower “depauperate horizon” is characterized by low taxonomic richness, more stable “low-energy” conditions, and a dominance of enigmatic Archaea. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1111 KW - Archaea KW - Eukaryota KW - Bacteria KW - community KW - freshwater KW - lake KW - DNA metabarcoding KW - beta-diversity KW - sediment KW - turnover Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-431965 SN - 1866-8372 IS - 1111 ER -