Dokument-ID Dokumenttyp Verfasser/Autoren Herausgeber Haupttitel Abstract Auflage Verlagsort Verlag Erscheinungsjahr Seitenzahl Schriftenreihe Titel Schriftenreihe Bandzahl ISBN Quelle der Hochschulschrift Konferenzname Quelle:Titel Quelle:Jahrgang Quelle:Heftnummer Quelle:Erste Seite Quelle:Letzte Seite URN DOI Abteilungen OPUS4-46022 Wissenschaftlicher Artikel Tietjen, Britta; Huth, Andreas Modelling dynamics of managed tropical rainforests - An aggregated approach The overuse of rainforests in the last century and its consequences necessitate a rethinking of logging policies. To this end models have been developed to simulate rainforest dynamics and to allow optional management strategies to be evaluated. Parameterisation of presently existing models for a certain site needs a lot of work, thus the parameterisation effort is too high to apply the models to a wide range of rainforests. Hence, in this paper we introduce the simplified model FORREG using the knowledge we have gained from a more complex model, FORMIX3-Q. The FORREG model uses differential equations to determine the volume growth of three successional species groups. Parameterisation is simplified by a genetic algorithm, which determines the required internal model parameters from characteristics of the forest dynamics. The new model is employed to assess the sustainability of various logging policies in terms of yield and damage. Results for three forests are discussed: (1) the tropical lowland rain forest in the Deramakot Forest Reserve, (2) the Lambir National Park in Malaysia and (3) a subtropical forest in Paraguay. Our model reproduces both undisturbed forest dynamics and dynamics of logged forests simulated with FORMIX3-Q very well. However, the resultant volumes of yield and damage differ slightly from those gained by FORMIX3-Q if short logging cycles are simulated. Choosing longer logging cycles leads to a good correspondence of both models. For the Deramakot Forest Reserve different logging cycles are compared and discussed. (c) 2006 Elsevier B.V. All rights reserved. Amsterdam Elsevier 2006 12 Ecological modelling : international journal on ecological modelling and engineering and systems ecolog 199 4 421 432 10.1016/j.ecolmodel.2005.11.045 Institut für Umweltwissenschaften und Geographie OPUS4-35166 Wissenschaftlicher Artikel Jeltsch, Florian; Blaum, Niels; Brose, Ulrich; Chipperfield, Joseph D.; Clough, Yann; Farwig, Nina; Geissler, Katja; Graham, Catherine H.; Grimm, Volker; Hickler, Thomas; Huth, Andreas; May, Felix; Meyer, Katrin M.; Pagel, Jörn; Reineking, Björn; Rillig, Matthias C.; Shea, Katriona; Schurr, Frank Martin; Schroeder, Boris; Tielbörger, Katja; Weiss, Lina; Wiegand, Kerstin; Wiegand, Thorsten; Wirth, Christian; Zurell, Damaris How can we bring together empiricists and modellers in functional biodiversity research? Improving our understanding of biodiversity and ecosystem functioning and our capacity to inform ecosystem management requires an integrated framework for functional biodiversity research (FBR). However, adequate integration among empirical approaches (monitoring and experimental) and modelling has rarely been achieved in FBR. We offer an appraisal of the issues involved and chart a course towards enhanced integration. A major element of this path is the joint orientation towards the continuous refinement of a theoretical framework for FBR that links theory testing and generalization with applied research oriented towards the conservation of biodiversity and ecosystem functioning. We further emphasize existing decision-making frameworks as suitable instruments to practically merge these different aims of FBR and bring them into application. This integrated framework requires joint research planning, and should improve communication and stimulate collaboration between modellers and empiricists, thereby overcoming existing reservations and prejudices. The implementation of this integrative research agenda for FBR requires an adaptation in most national and international funding schemes in order to accommodate such joint teams and their more complex structures and data needs. Jena Elsevier 2013 9 Basic and applied ecology : Journal of the Gesellschaft für Ökologie 14 2 93 101 10.1016/j.baae.2013.01.001 Institut für Geowissenschaften OPUS4-46997 Wissenschaftlicher Artikel Grimm, Volker; Berger, Uta; Bastiansen, Finn; Eliassen, Sigrunn; Ginot, Vincent; Giske, Jarl; Goss-Custard, John; Grand, Tamara; Heinz, Simone K.; Huse, Geir; Huth, Andreas; Jepsen, Jane U.; Jorgensen, Christian; Mooij, Wolf M.; Mueller, Birgit; Piou, Cyril; Railsback, Steven Floyd; Robbins, Andrew M.; Robbins, Martha M.; Rossmanith, Eva; Rueger, Nadja; Strand, Espen; Souissi, Sami; Stillman, Richard A.; Vabo, Rune; Visser, Ute; DeAngelis, Donald L. A standard protocol for describing individual-based and agent-based models Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers. (c) 2006 Elsevier B.V. All rights reserved. Amsterdam Elsevier 2006 12 Ecological modelling : international journal on ecological modelling and engineering and systems ecolog 198 115 126 10.1016/j.ecolmodel.2006.04.023 Institut für Biochemie und Biologie