TY - JOUR A1 - Jeltsch, Florian A1 - Blaum, Niels A1 - Brose, Ulrich A1 - Chipperfield, Joseph D. A1 - Clough, Yann A1 - Farwig, Nina A1 - Geissler, Katja A1 - Graham, Catherine H. A1 - Grimm, Volker A1 - Hickler, Thomas A1 - Huth, Andreas A1 - May, Felix A1 - Meyer, Katrin M. A1 - Pagel, Jörn A1 - Reineking, Björn A1 - Rillig, Matthias C. A1 - Shea, Katriona A1 - Schurr, Frank Martin A1 - Schroeder, Boris A1 - Tielbörger, Katja A1 - Weiss, Lina A1 - Wiegand, Kerstin A1 - Wiegand, Thorsten A1 - Wirth, Christian A1 - Zurell, Damaris T1 - How can we bring together empiricists and modellers in functional biodiversity research? JF - Basic and applied ecology : Journal of the Gesellschaft für Ökologie N2 - 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. KW - Biodiversity theory KW - Biodiversity experiments KW - Conservation management KW - Decision-making KW - Ecosystem functions and services KW - Forecasting KW - Functional traits KW - Global change KW - Monitoring programmes KW - Interdisciplinarity Y1 - 2013 U6 - https://doi.org/10.1016/j.baae.2013.01.001 SN - 1439-1791 VL - 14 IS - 2 SP - 93 EP - 101 PB - Elsevier CY - Jena ER - TY - JOUR A1 - Jeltsch, Florian A1 - Bonte, Dries A1 - Peer, Guy A1 - Reineking, Björn A1 - Leimgruber, Peter A1 - Balkenhol, Niko A1 - Schröder-Esselbach, Boris A1 - Buchmann, Carsten M. A1 - Müller, Thomas A1 - Blaum, Niels A1 - Zurell, Damaris A1 - Böhning-Gaese, Katrin A1 - Wiegand, Thorsten A1 - Eccard, Jana A1 - Hofer, Heribert A1 - Reeg, Jette A1 - Eggers, Ute A1 - Bauer, Silke T1 - Integrating movement ecology with biodiversity research - exploring new avenues to address spatiotemporal biodiversity dynamics Y1 - 2013 UR - http://download.springer.com/static/pdf/827/art%253A10.1186%252F2051-3933-1- 6.pdf?auth66=1394891271_f1a4cb74d6be42ee3f8872ef2ca22c24&ext=.pdf U6 - https://doi.org/10.1186/2051-3933-1-6 ER - TY - JOUR A1 - Reineking, Björn A1 - Schröder-Esselbach, Boris T1 - Constrain to perform : regularization of habitat models N2 - Predictive habitat models are an important tool for ecological research and conservation. A major cause of unreliable models is excessive model complexity, and regularization methods aim to improve the predictive performance by adequately constraining model complexity. We compare three regularization methods for logistic regression: variable selection, lasso, and ridge. They differ in the way model complexity is measured: variable selection uses the number of estimated parameters, the lasso uses the sum of the absolute values of the parameter estimates, and the ridge uses the sum of the squared values of the parameter estimates. We performed a simulation study with environmental data of a real landscape and artificial species occupancy data. We investigated the effect of three factors on relative model performance: (1) the number of parameters (16, 10, 6, 2) in the 'true' model that determined the distribution of the artificial species, (2) the prevalence, i.e. the proportion of sites occupied by the species, and (3) the sample size (measured in events per variable, EPV). Regularization improved model discrimination and calibration. However, no regularization method performed best under all circumstances: the ridge generally performed best in the 16-parameter scenario. The lasso generally performed best in the 10-parameter scenario. Variable selection with AIC was best at large sample sizes (EPV >= 10) when less than half of the variables influenced the species distribution. However, at low sample sizes (EPV < 10), ridge and lasso always performed best, regardless of the parameter scenario or prevalence. Overall, calibration was best in ridge models. Other methods showed overconfidence, particularly at low sample sizes. The percentage of correctly identified models was low for both lasso and variable selection. Variable selection should be used with caution. Although it can produce the best performing models under certain conditions, these situations are difficult to infer from the data. Ridge and lasso are risk-averse model strategies that can be expected to perform well under a wide range of underlying species-habitat relationships, particularly at small sample sizes. Y1 - 2006 UR - http://www.sciencedirect.com/science/journal/03043800 U6 - https://doi.org/10.1016/j.ecolmodel.2005.10.003 SN - 0304-3800 ER - TY - JOUR A1 - Schröder-Esselbach, Boris A1 - Reineking, Björn T1 - Validierung von Habitatmodellen Y1 - 2004 UR - http://brandenburg.geoecology.uni-potsdam.de/users/schroeder/download/publications/ schroeder_reineking_ufzbericht9_2004b.pdf ER - TY - JOUR A1 - Reineking, Björn A1 - Schröder-Esselbach, Boris T1 - Variablenselektion : Strategien der Modellbildung in der Habitatmodellierung Y1 - 2004 UR - http://brandenburg.geoecology.uni-potsdam.de/users/schroeder/download/publications/ reineking_schroeder_ufzbericht9_2004b.pdf ER - TY - JOUR A1 - Reineking, Björn A1 - Schröder-Esselbach, Boris T1 - Gütemaße für Habitatmodelle Y1 - 2004 UR - http://brandenburg.geoecology.uni-potsdam.de/users/schroeder/download/publications/ reineking_schroeder_ufzbericht9_2004a.pdf ER - TY - JOUR A1 - Reineking, Björn A1 - Schröder-Esselbach, Boris T1 - Computer-intensive methods in the analysis of species-habitat relationships Y1 - 2003 UR - http://brandenburg.geoecology.uni-potsdam.de/users/schroeder/download/publications/ reineking_schroeder_aktheorie2003.pdf ER -