Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 7, 1251-1269, 2014
http://www.geosci-model-dev.net/7/1251/2014/
doi:10.5194/gmd-7-1251-2014
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
Model description paper
03 Jul 2014
Analysing Amazonian forest productivity using a new individual and trait-based model (TFS v.1)
N. M. Fyllas1,*, E. Gloor1, L. M. Mercado2, S. Sitch2, C. A. Quesada3, T. F. Domingues4, D. R. Galbraith1, A. Torre-Lezama5, E. Vilanova5, H. Ramírez-Angulo5, N. Higuchi3, D. A. Neill6, M. Silveira7, L. Ferreira8, G. A. Aymard C.12, Y. Malhi9, O. L. Phillips1, and J. Lloyd10,11 1Ecology and Global Change, School of Geography, University of Leeds, UK
2School of Geography, University of Exeter, Exeter, UK
3Instituto Nacional de Pesquisas da Amazônia, Manaus, Brazil
4School of GeoSciences, University of Edinburgh, Edinburgh, Scotland, UK
5Instituto de Investigaciones para el Desarrollo, Forestal Facultad de Ciencias Forestales y Ambientales, Universidad de Los Andes, Merida, Venezuela
6Department of Wildlife Conservation and Management, Universidad Estatal Amazónica, Puyo, Pastaza, Ecuador
7Universidade Federal do Acre, Rio Branco, Brazil
8Museu Paraense Emílio Goeldi, Belém, Brazil
9Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, UK
10Centre for Tropical Environmental and Sustainability Science (TESS) and School of Marine and Tropical Biology, James Cook University, Cairns, Australia
11Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, UK
12UNELLEZ-Guanare, Programa de Ciencias del Agro y el Mar, Herbario Universitario (PORT), estado Portuguesa, Venezuela
*currently at: Department of Ecology & Systematics, Faculty of Biology, University of Athens, Athens, Greece
Abstract. Repeated long-term censuses have revealed large-scale spatial patterns in Amazon basin forest structure and dynamism, with some forests in the west of the basin having up to a twice as high rate of aboveground biomass production and tree recruitment as forests in the east. Possible causes for this variation could be the climatic and edaphic gradients across the basin and/or the spatial distribution of tree species composition. To help understand causes of this variation a new individual-based model of tropical forest growth, designed to take full advantage of the forest census data available from the Amazonian Forest Inventory Network (RAINFOR), has been developed. The model allows for within-stand variations in tree size distribution and key functional traits and between-stand differences in climate and soil physical and chemical properties. It runs at the stand level with four functional traits – leaf dry mass per area (Ma), leaf nitrogen (NL) and phosphorus (PL) content and wood density (DW) varying from tree to tree – in a way that replicates the observed continua found within each stand. We first applied the model to validate canopy-level water fluxes at three eddy covariance flux measurement sites. For all three sites the canopy-level water fluxes were adequately simulated. We then applied the model at seven plots, where intensive measurements of carbon allocation are available. Tree-by-tree multi-annual growth rates generally agreed well with observations for small trees, but with deviations identified for larger trees. At the stand level, simulations at 40 plots were used to explore the influence of climate and soil nutrient availability on the gross (ΠG) and net (ΠN) primary production rates as well as the carbon use efficiency (CU). Simulated ΠG, ΠN and CU were not associated with temperature. On the other hand, all three measures of stand level productivity were positively related to both mean annual precipitation and soil nutrient status. Sensitivity studies showed a clear importance of an accurate parameterisation of within- and between-stand trait variability on the fidelity of model predictions. For example, when functional tree diversity was not included in the model (i.e. with just a single plant functional type with mean basin-wide trait values) the predictive ability of the model was reduced. This was also the case when basin-wide (as opposed to site-specific) trait distributions were applied within each stand. We conclude that models of tropical forest carbon, energy and water cycling should strive to accurately represent observed variations in functionally important traits across the range of relevant scales.

Citation: Fyllas, N. M., Gloor, E., Mercado, L. M., Sitch, S., Quesada, C. A., Domingues, T. F., Galbraith, D. R., Torre-Lezama, A., Vilanova, E., Ramírez-Angulo, H., Higuchi, N., Neill, D. A., Silveira, M., Ferreira, L., Aymard C., G. A., Malhi, Y., Phillips, O. L., and Lloyd, J.: Analysing Amazonian forest productivity using a new individual and trait-based model (TFS v.1), Geosci. Model Dev., 7, 1251-1269, doi:10.5194/gmd-7-1251-2014, 2014.
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