Analysing Amazonian forest productivity using a new individual and trait-based model (TFS v.1)

Abstract

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.

Predicting species dominance shifts across elevation gradients in mountain forests in Greece under a warmer and drier climate

“…Currently, there is great effort to include functional trait variation into vegetation dynamics models, in order to account for the potential plasticity in the ecosystems' response to climate change (Scheiter et al 2013;Fyllas et al 2014; van Bodegom et al Triangles indicate P. nigra and diamonds F. sylvatica basal area field measurements at different elevations. The graph summarises simulations made using the plastic model set-up 2014).…”

“…In addition to the above, the role of inter-and intra-specific functional trait variation has been recently highlighted as an important component that needs to be incorporated into vegetation dynamics model (Scheiter et al 2013;Fyllas et al 2014;van Bodegom et al 2014;Sakschewski et al 2015). Traditionally, parameterisation of species and/or plant functional types (PFTs) is based on the use of some ''average'' or ''appropriate'' mean trait value, for characteristics that have a direct effect on the regeneration, the growth and the mortality of the simulated species.…”

Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests

“…Some leaves hang up in the vegetation and decompose above the ground. When Frangi and Lugo (1985) suspended old leaves from palms in a Puerto Rican forest, they found that roughly half the leaf mass was lost through decomposition in 4 months. A second issue is the leaf mass removed by herbivores (Table 7).…”

“…Demographic models such as the Ecosystem Demography model (Moorcroft et al, 2001;Medvigy et al, 2009;Fisher et al, 2015) are designed in part to capture the variation between recently disturbed and old-growth forests. Similarly, individual-based models such as TFS and LPJ-GUESS (Fyllas et al, 2014;Pappas et al, 2015) explicitly represent the within-landscape spatial heterogeneity. With those models the smaller-scale observations, such as those from individual hectares, can be usefully compared directly to the model output.…”

The big data revolution and paleoecology

“…At a fundamental level, this research seeks to explain aspects of the function of plants and ecosystems (Ali et al 2015). trait-based analyses are also being used to explore the controls on within-and between-site diversity (Ackerly and Cornwell 2007) and to develop vegetation models based on fundamental principles rather than empirical relationships (Fyllas et al 2014). Ecologists are also exploring how species and ecosystems respond to climate change, on shorter (acclimation) and longer (adaptation, migration) timescales.…”