Can we model forest demography globally? Benchmarking of state-of-the-art Demographic DGVMs
- 1Lund University, Department of Physical Geography and Ecosystem Science, Lund, Sweden (annemarie.eckes-shephard@nateko.lu.se)
- 2Met Office Hadley Centre, FitzRoy Road, Exeter, Devon, EX1 3PB, United Kingdom
- 3Department of Silviculture, Institute of Forest Sciences, Warsaw University of Life Sciences – SGGW, Nowoursynowska 159/34, 02-776 Warsaw, Poland
- 4Mathematics and Statistics, University of Exeter, Streatham Campus, North Park Road, Exeter EX4 4QF, United Kingdom
- 5School of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol BS8 1TQ UK
- 6University of Birmingham, School of Geography, Earth and Environmental Sciences B15 2TT Birmingham, UK
- 7CICERO Center for International Climate Research, Gaustadalléen 21, 0349 Oslo, Norway
- 8Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW 2751, Australia
- 9Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- 10Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland
- 11Amsterdam Institute for Life and Environment, Vrije Universiteit Amsterdam, Amsterdam, 1081, the Netherlands
- 12Institute of Geography, University of Bern, Hallerstrasse 12, 3012 Bern, Switzerland
- 13Oeschger Centre for Climate Change Research, University of Bern, Falkenplatz 16, 3012 Bern, Switzerland
- 14Center for Geography and Environmental Sciences, Univertsity of Exeter, Laver Building, North Park Road, Exeter EX4 4QE, United Kingdom
- 15Center for Climate Systems Research, Columbia University, 2880 Broadway, New York, NY 10025, USA
- 16Forest Global Earth Observatory, Smithsonian Tropical Research Institute, Washington, DC, USA
Forests in Dynamic Global Vegetation Models (DGVMs) have historically been simulated as area-averaged plant functional types in each gridcell instead of representing communities of trees of different sizes and ages (demography). Just as the behaviour of a tree differs according to its ontogeny, so the behaviour of forests is known to differ depending on their demography. Accurately simulating demography is therefore key in order to address questions on afforestation and management strategies, as well as assessments of resilience of forests to disturbances such as drought and fire or diversity changes after a disturbance. Ultimately, demography determines the overall forest biomass in natural forests and is a key arbiter of growth and mortality rates. DGVMs are now able to simulate size and age structure of the trees in forests.
However, these models have so far not been benchmarked alongside each other.
We evaluate 6 DGVMs (BiomeE, CABLE-POP, FATES, LPJ-GUESS, JULES-RED, ORCHIDEE) against observations on regrowth dynamics as well as natural forests at boreal, temperate and tropical sites. We examine whether the models capture observed regrowth dynamics after disturbance, well-known stand size structure and well-established processes such as self-thinning. We outline the planned route forward towards a standardised international benchmarking framework for demographic DGVMs.
How to cite: Eckes-Shephard, A., Argles, A., Brzeziecki, B., Cox, P., De Kauwe, M. G., Esquivel Muelbert, A., Fisher, R. A., Knauer, J., Koven, C. D., Lehtonen, A., Longo, M., Luyssaert, S., Marqués, L., Moore, J., Needham, J. F., Olin, S., Peltoniemi, M., Sitch, S., Stocker, B., Weng, E., Zuleta, D., and Pugh, T.: Can we model forest demography globally? Benchmarking of state-of-the-art Demographic DGVMs, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14120, https://doi.org/10.5194/egusphere-egu23-14120, 2023.
