Abstract: A major challenge for forest managers is to define the optimal cutting cycle to ensure that the resource is sustained in the long term. Matrix models of forest dynamics allow time-projection of diameter-class distributions and thus assessment of the time needed, after logging, to recover a given part of the exploitable stock. They are easy to build and they only require, as input variables, the diameter structure of the population(s) under scope. However, such models are based on a coarse description of tree population dynamics and must be used with caution. In particular, as trees are only described from a diameter threshold (usually 10 cm dbh), recruitment of a new tree cannot be linked with the preceding generation since too much time elapsed between seed dispersal and the installation of a 10-cm recruit. This causes predictions of matrix models to be highly questionable in the long term when ingrowth to larger dbh classes greatly depends on the way recruitment has been modelled. We used a case study from French Guiana to test whether or not a simple matrix model is reliable enough to help forest managers choose between management alternatives. We focused on the major timber species Dicorynia guianensis Amshoff (Caesalpiniaceae) harvested under a selective cutting regime. We compared predictions of D. guianensis stock recovery in the short and long term provided by two models: StoMat, a non-regulated matrix model, and SELVA, a single-tree distance dependent model explicitly simulating the entire species life cycle. Both models were independently calibrated on data from Paracou permanent sample plots. We showed that: (i) the short-term recovery of the exploitable stock predicted by StoMat is reliable for a large range of disturbance conditions; (ii) recruitment implementation in StoMat does not influence projections until the third felling cycle; (iii) for shared initial stand conditions SELVA and StoMat give consistent mid- and long-term predictions: the simple recruitment model used into StoMat could efficiently summarise the regeneration processes of the species under low felling intensity. Our results indicate that the current felling regime used in French Guiana may not be sustainable on a long-term basis. In any case, no more than 60% of the initial stock would be recovered after logging. We conclude that simple models can provide as reliable predictions as more complicated ones. They may be sufficient to assess the recovery of a species' exploitable stock even in the long term, or at least assess the (un)sustainability of particular harvesting regimes. (c) 2005 Elsevier B.V. All rights reserved.

Abstract: Reliable above-ground biomass (AGB) estimates are required for studies of carbon fluxes and stocks. However, there is a huge lack of knowledge concerning the precision of AGB estimates and the sources of this uncertainty. At the tree level, the tree height is predicted using the tree diameter at breast height (DBH) and a height sub-model. The wood-specific gravity (WSG) is predicted with taxonomic information and a WSG sub-model. The tree mass is predicted using the predicted height, the predicted WSG and the biomass sub-model. Our models were inferred with Bayesian methods and the uncertainty propagated with a Monte Carlo scheme. The uncertainties in the predictions of tree height, tree WSG and tree mass were neglected sequentially to quantify their contributions to the uncertainty in AGB. The study was conducted in French Guiana where long-term research on forest ecosystems provided an outstanding data collection on tree height, tree dynamics, tree mass and species WSG. We found that the uncertainty in the AGB estimates was found to derive primarily from the biomass sub-model. The models used to predict the tree heights and WSG contributed negligible uncertainty to the final estimate. Considering our results, a poor knowledge of WSG and the height-diameter relationship does not increase the uncertainty in AGB estimates. However, it could lead to bias. Therefore, models and databases should be used with care. This study provides a methodological framework that can be broadly used by foresters and plant ecologist. It provides the accurate confidence intervals associated with forest AGB estimates made from inventory data. When estimating region-scale AGB values (through spatial interpolation, spatial modelling or satellite signal treatment), the uncertainty of the forest AGB value in the reference forest plots has to be taken in account. We believe that in the light of the Reducing Emissions from Deforestation and Degradation debate, our method is a crucial step in monitoring carbon stocks and their spatio-temporal evolution. © 2012 The Authors. Methods in Ecology and Evolution © 2012 British Ecological Society.

Abstract: The dynamic model of plant growth GreenLab describes plant architecture and functional growth at the level of individual organs. Structural development is controlled by formal grammars and empirical equations compute the amount of biomass produced by the plant, and its partitioning among the growing organs, such as leaves, stems and fruits. The number of organs initiated at each time step depends on the trophic state of the plant, which is evaluated by the ratio of biomass available in plant to the demand of all the organs. The control of the plant organogenesis by this variable induces oscillations in the simulated plant behaviour. The mathematical framework of the GreenLab model allows to compute the conditions for the generation of oscillations and the value of the period according to the set of parameters. Two case-studies are presented, corresponding to emergence of oscillations associated to fructification and branching. Similar alternating patterns are commonly reported by botanists. In this article, two examples were selected: alternate patterns of fruits in cucumber plants and alternate appearances of branches in Cecropia trees. The model was calibrated from experimental data collected on these plants. It shows that a simple feedback hypothesis of trophic control on plant structure allows the emergence of cyclic patterns corresponding to the observed ones. © EDP Sciences, 2012.

Abstract: Aridity has increased in recent decades in the Mediterranean Basin and is projected to continue to increase in the coming decades. We studied the consequences of drought on the concentrations, stoichiometries and stocks of carbon (C), nitrogen (N), phosphorus (P) and potassium (K) in leaves, foliar litter of a three dominant woody species and soil of a Mediterranean montane holm oak forest where soil-water content was experimentally reduced (15 % lower than the control plots) for 15 years. Nitrogen stocks were lower in the drought plots than in the control plots (8.81 ± 1.01 kg ha−1 in the forest canopy and 856 ± 120 kg ha−1 in the 0−15 cm soil layer), thus representing 7 and 18 % lower N stocks in the canopy and soil respectively. δ15N was consistently higher under drought conditions in all samples, indicating a general loss of N. Foliar C and K stocks were also lower but to a lesser extent than N. Decreases in biomass and C and N stocks due to drought were smallest for the most dominant tall shrub, Phillyrea latifolia, so our results suggest a lower capacity of this forest to store C and nutrients but also substantial resulting changes in forest structure with increasing drought. © 2020 Elsevier B.V.

Abstract: High-density Airborne Laser Scanning was used to derive the Canopy Height Model (CHM) of an experimental forest site in the neotropics (Paracou, French Guiana). Individual tree heights were computed by manually segmenting tree crowns on the CHM and then extracting the local maximum canopy height. Three hundred and ninety-six (396) height estimates were matched from dominant or emergent trees with the corresponding ground records of stem diameters sampled in two plots with different mean canopy heights (28.1 m vs. 31.3 m). Tree slenderness was found to be positively and very significantly correlated with mean canopy height at the plot level. The same correlation was observed at the species population level for the three species adequately sampled. It can therefore be concluded that stratification by canopy height is to be recommended when deriving allometric relationships in order to avoid bias in Above Ground Biomass estimations.