Articles | Volume 11, issue 4
https://doi.org/10.5194/bg-11-1261-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-11-1261-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model
F. Hartig
UFZ – Helmholtz Centre for Environmental Research, Department of Ecological Modelling, Permoserstr. 15, 04318 Leipzig, Germany
University of Freiburg, Department of Biometry and Environmental System Analysis, Tennenbacher Str. 4, 79085 Freiburg, Germany
C. Dislich
UFZ – Helmholtz Centre for Environmental Research, Department of Ecological Modelling, Permoserstr. 15, 04318 Leipzig, Germany
University of Göttingen, Department of Ecosystem Modelling, Büsgenweg 4, 37077 Göttingen, Germany
T. Wiegand
UFZ – Helmholtz Centre for Environmental Research, Department of Ecological Modelling, Permoserstr. 15, 04318 Leipzig, Germany
A. Huth
UFZ – Helmholtz Centre for Environmental Research, Department of Ecological Modelling, Permoserstr. 15, 04318 Leipzig, Germany
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26 citations as recorded by crossref.
- Forest community response to invasive pathogens: the case of ash dieback in a British woodland J. Needham et al. 10.1111/1365-2745.12545
- A spatial simulation model to explore the long-term dynamics of podocarp-tawa forest fragments, northern New Zealand N. Morales & G. Perry 10.1016/j.ecolmodel.2017.04.007
- An individual‐based forest model to jointly simulate carbon and tree diversity in Amazonia: description and applications I. Maréchaux & J. Chave 10.1002/ecm.1271
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- Predicting the abundance of forest types across the eastern United States through inverse modelling of tree demography M. Vanderwel et al. 10.1002/eap.1596
- Bayesian Synthetic Likelihood L. Price et al. 10.1080/10618600.2017.1302882
- Community dynamics under environmental change: How can next generation mechanistic models improve projections of species distributions? A. Singer et al. 10.1016/j.ecolmodel.2015.11.007
- Quo vadis, agent-based modelling tools? A. Daly et al. 10.1016/j.envsoft.2022.105514
- Towards Process-based Range Modeling of Many Species M. Evans et al. 10.1016/j.tree.2016.08.005
- The Latitudinal Diversity Gradient: Novel Understanding through Mechanistic Eco-evolutionary Models M. Pontarp et al. 10.1016/j.tree.2018.11.009
- Simulating Carbon Stocks and Fluxes of an African Tropical Montane Forest with an Individual-Based Forest Model R. Fischer et al. 10.1371/journal.pone.0123300
- From theory to practice in pattern‐oriented modelling: identifying and using empirical patterns in predictive models C. Gallagher et al. 10.1111/brv.12729
- Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion V. Trotsiuk et al. 10.1111/gcb.15011
- Bayesian calibration of a growth‐dependent tree mortality model to simulate the dynamics of European temperate forests M. Cailleret et al. 10.1002/eap.2021
- Integration of tree hydraulic processes and functional impairment to capture the drought resilience of a semiarid pine forest D. Nadal-Sala et al. 10.5194/bg-21-2973-2024
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- An extended empirical saddlepoint approximation for intractable likelihoods M. Fasiolo et al. 10.1214/18-EJS1433
- A simulation method to infer tree allometry and forest structure from airborne laser scanning and forest inventories F. Fischer et al. 10.1016/j.rse.2020.112056
- Which demographic processes control competitive equilibria? Bayesian calibration of a size‐structured forest population model L. Heiland et al. 10.1002/ece3.10232
- Productivity of Fagus sylvatica under climate change – A Bayesian analysis of risk and uncertainty using the model 3-PG A. Augustynczik et al. 10.1016/j.foreco.2017.06.061
- Tackling unresolved questions in forest ecology: The past and future role of simulation models I. Maréchaux et al. 10.1002/ece3.7391
- Predicting how many animals will be where: How to build, calibrate and evaluate individual-based models E. van der Vaart et al. 10.1016/j.ecolmodel.2015.08.012
- Approximate Bayesian computation to recalibrate individual-based models with population data: Illustration with a forest simulation model G. Lagarrigues et al. 10.1016/j.ecolmodel.2014.09.023
- Global warming likely to enhance black locust (Robinia pseudoacacia L.) growth in a Mediterranean riparian forest D. Nadal-Sala et al. 10.1016/j.foreco.2019.117448
- Bayesian parameter inference for individual-based models using a Particle Markov Chain Monte Carlo method M. Kattwinkel & P. Reichert 10.1016/j.envsoft.2016.11.001
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