Abstract: Background: Managed forests are a major component of tropical landscapes. Production forests as designated by national forest services cover up to 400 million ha, i.e. half of the forested area in the humid tropics. Forest management thus plays a major role in the global carbon budget, but with a lack of unified method to estimate carbon fluxes from tropical managed forests. In this study we propose a new time- and spatially-explicit methodology to estimate the above-ground carbon budget of selective logging at regional scale. Results: The yearly balance of a logging unit, i.e. the elementary management unit of a forest estate, is modelled by aggregating three sub-models encompassing (i) emissions from extracted wood, (ii) emissions from logging damage and deforested areas and (iii) carbon storage from post-logging recovery. Models are parametrised and uncertainties are propagated through a MCMC algorithm. As a case study, we used 38 years of National Forest Inventories in French Guiana, northeastern Amazonia, to estimate the above-ground carbon balance (i.e. the net carbon exchange with the atmosphere) of selectively logged forests. Over this period, the net carbon balance of selective logging in the French Guianan Permanent Forest Estate is estimated to be comprised between 0.12 and 1.33 Tg C, with a median value of 0.64 Tg C. Uncertainties over the model could be diminished by improving the accuracy of both logging damage and large woody necromass decay submodels. Conclusions: We propose an innovating carbon accounting framework relying upon basic logging statistics. This flexible tool allows carbon budget of tropical managed forests to be estimated in a wide range of tropical regions. © 2016 The Author(s).

Abstract: Despite the lowtree diversity and scarcity of the understory vegetation, the high morphological plasticity of mangrove trees induces, at the stand level, a very large variability of forest structures that need to be mapped for assessing the functioning of such complex ecosystems. Fully constrained linear spectral unmixing (FCLSU) of very high spatial resolution (VHSR) multispectral images was tested to fine-scale map mangrove zonations in terms of horizontal variation of forest structure. The study was carried out on three Pleiades-1A satellite images covering French island territories located in the Atlantic, Indian, and Pacific Oceans, namely Guadeloupe, Mayotte, and New Caledonia archipelagos. In each image, FCLSU was trained from the delineation of areas exclusively related to four components including either pure vegetation, soil (ferns included), water, or shadows. It was then applied to the whole mangrove cover imaged for each island and yielded the respective contributions of those four components for each image pixel. On the forest stand scale, the results interestingly indicated a close correlation between FCLSU-derived vegetation fractions and canopy closure estimated from hemispherical photographs R 2 = 0.95) and a weak relation with the Normalized Difference Vegetation Index (R 2 = 0.29). Classification of these fractions also offered the opportunity to detect and map horizontal patterns of mangrove structure in a given site. K-means classifications of fraction indeed showed a global view of mangrove structure organization in the three sites, complementary to the outputs obtained from spectral data analysis. Our findings suggest that the pixel intensity decomposition applied to VHSR multispectral satellite images can be a simple but valuable approach for (i) mangrove canopy monitoring and (ii) mangrove forest structure analysis in the perspective of assessing mangrove dynamics and productivity. As with Lidar-based surveys, these potential new mapping capabilities deserve further physically based interpretation of sunlight scattering mechanisms within forest canopy. © 2019 by the authors.

Abstract: We developed nuclear and plastid single nucleotide polymorphism (SNP) and insertion/deletion (INDEL) markers for Dipteryx species using a combination of restriction associated DNA sequencing (RADSeq) and low coverage MiSeq genome sequencing. Of the total 315 loci genotyped using a MassARRAY platform, 292 loci were variable and polymorphic among the 73 sampled individuals from French Guiana, Brasil, Peru, and Bolivia. A final set of 56 nuclear SNPs, 26 chloroplast SNPs, 2 chloroplast INDELs, and 32 mitochondrial SNPs identifying significant population structure was developed. This set of loci will be useful for studies on population genetics of Dipteryx species in Amazonia.

Abstract: We developed nuclear and chloroplastic single nucleotide polymorphism (SNP) and INDEL (insertion/deletion) markers using restriction associated DNA sequencing (RADSeq) and low coverage MiSeq genome sequencing to set up a genetic tracking method of the geographical origin of Hymenaea sp. From two initial sets of 358 and 32 loci used to genotype at least 94 individuals, a final set of 75 nSNPs, 50 cpSNPs and 6 INDELs identifying significant population structure was developed. © 2018, Springer Nature B.V.