ABSTRACT
Cinnamomumparthenoxylon (Jack) Meisn. is a tree in genus Cinnamomum that has been facing global threats due to forest degradation and habitat fragmentation. Many recent studies aim to describe habitats and assess population and species genetic diversity for species conservation by expanding afforestation models for this species. Understanding their current and future potential distribution plays a major role in guiding conservation efforts. Using five modern machine-learning algorithms available on Google Earth Engine helped us evaluate suitable habitats for the species. The results revealed that Random Forest (RF) had the highest accuracy for model comparison, outperforming Support Vector Machine (SVM), Classification and Regression Trees (CART), Gradient Boosting Decision Tree (GBDT) and Maximum Entropy (MaxEnt). The results also showed that the extremely suitable ecological areas for the species are mostly distributed in northern Vietnam, followed by the North Central Coast and the Central Highlands. Elevation, Temperature Annual Range and Mean Diurnal Range were the three most important parameters affecting the potential distribution of C.parthenoxylon. Evaluation of the impact of climate on its distribution under different climate scenarios in the past (Last Glacial Maximum and Mid-Holocene), in the present (Worldclim) and in the future (using four climate change scenarios: ACCESS, MIROC6, EC-Earth3-Veg and MRI-ESM2-0) revealed that of C.parthenoxylon would likely expand to the northeast, while a large area of central Vietnam will gradually lose its adaptive capacity by 2100.
ABSTRACT
MAIN CONCLUSION: Moderate levels of genetic diversity and differentiation of Anisoptera costata were determined. A population divergence occurred during Younger Dryas. The anthropogenic disturbance had significantly affected the genetic diversity of the species in low tropical forests. Anisoptera costata Korth, an endangered species, is mainly distributed in the lowland tropical forests of the Southeast region in Vietnam, which has not been explored for genetic diversity and demographic history. In this study, eight polymorphic microsatellite markers were used to analyze 232 wild trees of A. costata at nine different populations, representing the natural distribution range of the species in Vietnam. Genetic diversity within the populations was determined with mean values of 0.284 and 0.327 observed and expected heterozygosity, respectively, while genetic differentiation among populations was found with Weir and Cockerham index of 0.12 and Hedrick index of 1.38. These results indicated that habitat fragmentation by the anthropogenic disturbance may be the major factor for the low heterozygosity values and affected the number of alleles in all the targeted populations of A. costata in lowland tropical forests. Populations in the Central Southeast area had a higher level of genetic diversity than the populations in the Coastal and Western Southeast areas. The analysis of molecular variance showed that high genetic variation existed within populations (86.15%) compared to the variation among populations. A reduction in the population size of A. costata was determined by BOTTLENECK. Different clustering methods (Bayesian analysis, the neighbor-joining tree, and principal coordinate analysis) suggested optimal genetic clusters related to gene flow among different areas. Approximate Bayesian computation suggested that population divergence occurred during Younger Dryas. We also discussed the measures for species conservation based on these results.
