Abstract: Key message: The natural durability of Dicorynia guianensis Amsh’s Heartwood is conferred by the high content of antioxidant phenolic compounds, especially tannins and flavonoids combined with the presence of fungistatic alkaloids. The content of phenolic compounds increases according to the natural durability classes, from durable wood (class 2) to moderately durable wood (class 3) and correlated to the antioxidant capacity.
Context: The heartwood of Dicorynia guianensis Amsh is resistant to white rot fungi decay, but the mechanism of this natural durability is not fully elucidated.
Aims: Biochemical studies were carried out in order to better understand the role of extractives in natural durability of D. guianensis.
Methods: The powders from durable and moderately durable heartwood were extracted with methanol, ethanol, and hot water. The quantity of total phenols, tannins, and flavonoids as well as antioxidant activity, evaluated by 2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid) were determined using colorimetric methods. Antifungal activity was assessed by using two white rot fungi. The bioactive fractions and compounds were obtained using bio-guided fractionation, HPLC isolation, MS and RMN spectroscopic analyses.
Results: Durable woods contain higher amounts of heartwood extract and antioxidant activity. Antioxidant activity was highly correlated with the content of phenolics. The purification of the most antioxidant fraction FII affords the characterization of (+)-catechin (−)-epicatechin, neoastilbin, astilbin, and isoastilbin. Alkaloid fraction FIII exhibits dose-dependent fungistatic activity against Pycnoporus sanguineus Linnaeus and Trametes versicolor Quelet.
Conclusion: Phenolic antioxidants and fungistatic alkaloids positively impact the natural durability of D. guianensis.

Abstract: Tree mortality in tropical forests is a complex ecological process for which modelling approaches need to be improved to better understand, and then predict, the evolution of tree mortality in response to global change. The mortality model introduced here computes an individual probability of dying for each tree in a community. The mortality model uses the ontogenetic stage of the tree because youngest and oldest trees are more likely to die. Functional traits are integrated as proxies of the ecological strategies of the trees to permit generalization among all species in the community. Data used to parametrize the model were collected at Paracou study site, a tropical rain forest in French Guiana, where 20,408 trees have been censused for 18 years. A Bayesian framework was used to select useful covariates and to estimate the model parameters. This framework was developed to deal with sources of uncertainty, including the complexity of the mortality process itself and the field data, especially historical data for which taxonomic determinations were uncertain. Uncertainty about the functional traits was also considered, to maximize the information they contain. Four functional traits were strong predictors of tree mortality: wood density, maximum height, laminar toughness and stem and branch orientation, which together distinguished the light-demanding, fast-growing trees from slow-growing trees with lower mortality rates. Our modelling approach formalizes a complex ecological problem and offers a relevant mathematical framework for tropical ecologists to process similar uncertain data at the community level. © 2013 Aubry-Kientz et al.

Abstract: Increasing evidence shows that the functioning of the tropical forest biome is intimately related to the climate variability with some variables such as annual precipitation, temperature or seasonal water stress identified as key drivers of ecosystem dynamics. How tropical tree communities will respond to the future climate change is hard to predict primarily because several demographic processes act together to shape the forest ecosystem general behavior. To overcome this limitation, we used a joint individual-based model to simulate, over the next century, a tropical forest community experiencing the climate change expected in the Guiana Shield. The model is climate dependent: temperature, precipitation and water stress are used as predictors of the joint growth and mortality rates. We ran simulations for the next century using predictions of the IPCC 5AR, building three different climate scenarios (optimistic RCP2.6, intermediate, pessimistic RCP8.5) and a control (current climate). The basal area, above-ground fresh biomass, quadratic diameter, tree growth and mortality rates were then computed as summary statistics to characterize the resulting forest ecosystem. Whatever the scenario, all ecosystem process and structure variables exhibited decreasing values as compared to the control. A sensitivity analysis identified the temperature as the strongest climate driver of this behavior, highlighting a possible temperature-driven drop of 40% in average forest growth. This conclusion is alarming, as temperature rises have been consensually predicted by all climate scenarios of the IPCC 5AR. Our study highlights the potential slow-down danger that tropical forests will face in the Guiana Shield during the next century. © 2019, The Author(s).

Abstract: Automatic tree crown segmentation from remote sensing data is especially challenging in dense, diverse, and multilayered tropical forest canopies, and tracking mortality by this approach is even more difficult. Here, we examine the potential for combining airborne laser scanning (ALS) with multispectral and hyperspectral data to improve the accuracy of tree crown segmentation at a study site in French Guiana. We combined an ALS point cloud clustering method with a spectral deep learning model to achieve 83% accuracy at recognizing manually segmented reference crowns (with congruence >0.5). This method outperformed a two-step process that involved clustering the ALS point cloud and then using the logistic regression of hyperspectral distances to correct oversegmentation. We used this approach to map tree mortality from repeat surveys and show that the number of crowns identified in the first that intersected with height loss clusters was a good estimator of the number of dead trees in these areas. Our results demonstrate that multisensor data fusion improves the automatic segmentation of individual tree crowns and presents a promising avenue to study forest demography with repeated remote sensing acquisitions.

Abstract: Background: Tropical trees undergo severe stress through seasonal drought and flooding, and the ability of these species to respond may be a major factor in their survival in tropical ecosystems, particularly in relation to global climate change. Aquaporins are involved in the regulation of water flow and have been shown to be involved in drought response; they may therefore play a major adaptive role in these species. We describe genetic diversity in the PIP sub-family of the widespread gene family of Aquaporins in five Neotropical tree species covering four botanical families. Results: PIP Aquaporin subfamily genes were isolated, and their DNA sequence polymorphisms characterised in natural populations. Sequence data were analysed with statistical tests of standard neutral equilibrium and demographic scenarios simulated to compare with the observed results. Chloroplast SSRs were also used to test demographic transitions. Most gene fragments are highly polymorphic and display signatures of balancing selection or bottlenecks; chloroplast SSR markers have significant statistics that do not conform to expectations for population bottlenecks. Although not incompatible with a purely demographic scenario, the combination of all tests tends to favour a selective interpretation of extant gene diversity. Conclusions: Tropical tree PIP genes may generally undergo balancing selection, which may maintain high levels of genetic diversity at these loci. Genetic variation at PIP genes may represent a response to variable environmental conditions.