Error propagation through a bayesian network for biomass estimation in neotropical forests

The above-ground biomass (AGB) of tropical forests is a crucial variable for the global ecological problems. It concerns both scientists and decision makers, especially through the recently set carbon market. Estimations of AGB from tree inventories are also a crucial point for the development of new methods of estimation, especially from above (plane, satellite). Tree inventories are the actual material for assessing carbon stocks. They produce a large range of datasets. Some cover small area and give hi-quality information: diameter at breast height (DBH), species Latin names, heights, ... Some datasets cover very large areas but give low-quality information: range of DBH instead of precise measure, family name or even no floristic specification, no heights, ... In addition, some other databases are required, like wood density data and weighted trees. For this study located in French Guiana, we use all of those kinds of datasets. To make correct inferences about biomass stocks and their evolution, it is essential to quantify the uncertainty associated with AGB estimates. It is also essential to answer those two questions: 1- Where does the uncertainty come from, and 2- How does it change with the data quality. To answer those questions, we calculate the AGB with a full hierarchical Bayesian model. It allows us to propagate errors through the model until the final AGB distribution. We can then perform a sensibility analysis, changing the error laws. The error laws are describing the uncertainty associated with every field measure. Both width and shapes may vary. Finally, we discuss the changes in AGB posterior distribution with the changes in error laws and data type. We also give some implication for both previous work and future experiments. (Résumé d'auteur

GUYAFOR: a network of research permanent plots of tropical forests in French Guiana

GUYAFOR, a network of forest research permanent plots, is dedicated to long term studies in forest dynamics and biodiversity. Forest plots have been established in French Guyana from the late 60's to recent years by Cirad, ONF and CNRS. From 2000, they are progressively integrated in the GUYAFOR network with standardized protocols for both tree inventories and environmental characterization. The network includes 45 plots distributed on 10 sites mainly in the coastal area.157 800 trees above 10 cm dbh are monitored within 235 ha at regular intervals (2 to 4 years). Undisturbed forests are monitored on all sites. Forests subjected to different logging treatments are also monitored on four sites (Paracou, Organabo, Risquetout and Montagne Tortue), providing a unique feature to this network. Recent works carried out on the Guyafor network include studies to understand patterns of tree biological diversity at specific, functional and evolutionary levels and studies on the effects of logging practices on the carbon cycle. (Résumé d'auteur

Assessment of forest degradation in the Amazon using multi-sensors techniques: the case of Paragominas (Brazil). O-2215-01

The Amazonian pioneer front region is a mosaic of different forests types and agricultural landscapes resulting from the colonization of the region through forest conversion into pasture and agricultural lands. Fearnside and Guimaraes (1996) showed that 47% of the deforested area is rapidly abandoned. It also appears that logged forests surface is equivalent to deforested areas (Asner et al., 2005). Consequently a degradation gradient exists from low impacted logged forests (depending of the logging intensity) to young secondary (regrowth) forests. To obtain more accurate estimation of carbon stocks, it is important today to take into account the degraded forest gradient including all degraded forest stages between mature intact forests and non-forest areas. The first main challenge is to identify and to characterize the various stages. The identification of forest degradation is still a complex and expansive problem even if it has been focused until now only on logged tropical rainforest (Asner, 2009; Gond and Guitet, 2009; Desclées et al., 2006; Asner et al., 2005; Souza et al., 2003). In parallel estimation of biomass loss in the degraded forest is little-studied. Within temperate and boreal forests some estimation are made by Solberg et al., (2013). The combination of optical remotely sensed data (Landsat-8), radar (Terra-Sar-X) and Lidar (IceSat) have to be studied to analyze the potential of the multisensors techniques to characterize the tropical rainforest degradation (Betbeder et al., 2014). The study presents the first results obtained during the field work at Paragominas (Pará, Brazil) on different forest degradation intensities (Bérenguer et al., 2014). This field database is then compared with multi-sensors remote sensing to better understand multiple interactions and to establish a forest degradation typology. (Texte intégral

LiDAR shows that higher forests have more slender trees

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. (Résumé d'auteur

Current knowledge of general patterns of biomass dynamics after logging in Amazonian forests

Sustainable management of tropical forests for timber production has been proposed as a potential tool for the conservation of large areas of tropical forest. The key is to identify practices that promote repeated extraction of forest goods (timber and non timber forests products) without compromising important forest services (e.g., biodiversity and carbon). Currently, 350 million hectares of tropical moist forests worldwide are designated as production forests, about a quarter of which is managed by rural communities and indigenous people. Yet general management guidelines remain elusive, in large part because not only harvesting practices but also forest types vary broadly both within and among regions. For example, the Amazon region shows a strong east-west gradient in both floristic composition and forest dynamics. This paper presents a literature review of our present knowledge of the biomass dynamics of tropical forests in the Amazon after logging. The objectives are (i) to disentangle the mechanisms behind different types of responses in different forests; and (ii) to propose research priorities to improve forest management guidelines so that they better reflect the gradient of forest types across the region. (Résumé d'auteur