Abstract: We investigate chloroplast DNA variation in a hyperdiverse community of tropical rainforest trees in French Guiana, focusing on patterns of intraspecific and interspecific variation. We test whether a species genetic diversity is higher when it has congeners in the community with which it can exchange genes and if shared haplotypes are more frequent in genetically diverse species, as expected in the presence of introgression. We sampled a total of 1,681 individual trees from 472 species corresponding to 198 genera and sequenced them at a noncoding chloroplast DNA fragment. Polymorphism was more frequent in species that have congeneric species in the study site than in those without congeners (30% vs. 12%). Moreover, more chloroplast haplotypes were shared with congeners in polymorphic species than in monomorphic ones (44% vs. 28%). Despite large heterogeneities caused by genus-specific behaviors in patterns of hybridization, these results suggest that the higher polymorphism in the presence of congeners is caused by local introgression rather than by incomplete lineage sorting. Our findings suggest that introgression has the potential to drive intraspecific genetic diversity in species-rich tropical forests.

Abstract: Satellite telemetry is an increasingly utilized technology in wildlife research, and current devices can track individual animal movements at unprecedented spatial and temporal resolutions. However, as we enter the golden age of satellite telemetry, we need an in-depth understanding of the main technological, species-specific and environmental factors that determine the success and failure of satellite tracking devices across species and habitats. Here, we assess the relative influence of such factors on the ability of satellite telemetry units to provide the expected amount and quality of data by analyzing data from over 3,000 devices deployed on 62 terrestrial species in 167 projects worldwide. We evaluate the success rate in obtaining GPS fixes as well as in transferring these fixes to the user and we evaluate failure rates. Average fix success and data transfer rates were high and were generally better predicted by species and unit characteristics, while environmental characteristics influenced the variability of performance. However, 48% of the unit deployments ended prematurely, half of them due to technical failure. Nonetheless, this study shows that the performance of satellite telemetry applications has shown improvements over time, and based on our findings, we provide further recommendations for both users and manufacturers.

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: Around 30 Mm3 of sawlogs are extracted annually by selective logging of natural production forests in Amazonia, Earth’s most extensive tropical forest. Decisions concerning the management of these production forests will be of major importance for Amazonian forests’ fate. To date, no regional assessment of selective logging sustainability supports decision-making. Based on data from 3500 ha of forest inventory plots, our modelling results show that the average periodic harvests of 20 m3 ha−1 will not recover by the end of a standard 30 year cutting cycle. Timber recovery within a cutting cycle is enhanced by commercial acceptance of more species and with the adoption of longer cutting cycles and lower logging intensities. Recovery rates are faster in Western Amazonia than on the Guiana Shield. Our simulations suggest that regardless of cutting cycle duration and logging intensities, selectively logged forests are unlikely to meet timber demands over the long term as timber stocks are predicted to steadily decline. There is thus an urgent need to develop an integrated forest resource management policy that combines active management of production forests with the restoration of degraded and secondary forests for timber production. Without better management, reduced timber harvests and continued timber production declines are unavoidable.

Abstract: Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.