No abstract

The BAHD acyltransferase family is a unique class of plant proteins that acylates plant metabolites and participates in plant secondary metabolic processes. However, the BAHD members in Lithospermum erythrorhizon remain unknown and uncharacterized. Although the heterologously expressed L. erythrorhizon BAHD family member LeSAT1 in Escherichia coli has been shown to catalyze the conversion of shikonin to acetylshikonin in vitro, its in vivo role remains unknown. In this study, the characterization, evolution, expression patterns, and gene function of LeBAHDs in L. erythrorhizon were explored by bioinformatics and transgenic analysis. We totally identified 73 LeBAHDs in the reference genome of L. erythrorhizon. All LeBAHDs were phylogenetically classified into five clades likely to perform different functions, and were mainly expanded by dispersed and WGD/segmental duplication. The in vivo functional investigation of the key member LeBAHD1/LeSAT1 revealed that overexpression of LeBAHD1 in hairy roots significantly increased the content of acetylshikonin as well as the conversion rate of shikonin to acetylshikonin, whereas the CRISPR/Cas9-based knockout of LeBAHD1 in hairy roots displayed the opposite trend. Our results not only confirm the in vivo function of LeBAHD1/LeSAT1 in the biosynthesis of acetylshikonin, but also provide new insights for the biosynthetic pathway of shikonin and its derivatives.

No abstract

Forest dynamics is critical to forested ecosystems, and considerable efforts have been devoted to monitoring long-term forest dynamics with the goals of sustainable management and conservation of forests. However, little attention has been given to mountain forests, which are more challenging to monitor due to complex topography, weather, and their distribution. We developed a 30-m resolution tree-canopy cover (TCC) and forest change dataset for the Eastern Himalayas from 1986 to 2021. The tree-canopy cover estimation was validated against estimates from the space-borne Global Ecosystem Dynamics Investigation (GEDI), demonstrating strong consistency (R-square greater than 0.81). A comprehensive assessment for the forest change dataset was performed using 448 visually interpreted points and reported high accuracy of the dataset, i.e., 97.7% and 95.9% for forest loss and gain, respectively. Higher producer and user accuracies were reported for forest loss (PA = 78.0%, UA = 60.9%) than these for forest gain (PA = 61.7%, UA = 56.7%). The results indicated that (1) the mean tree-canopy cover in the region increased by 2.76% over the past three decades, from 40.67% in 1990 to 43.43% in 2020, suggesting the forests have improved during the period; (2) forest loss was identified for a total area of 6990 km2 across the study area, which is less than the 10,700 km2 identified as forest gain; (3) stronger forest gains were found at elevations greater than 3000 m asl, indicating faster forest growth in high elevations likely influenced by the warming temperatures in the Eastern Himalayas.

Forest dynamics, including forest loss and gain, are long-term complex ecological processes affected by nature and human activities. It is particularly important to understand the long-term forest dynamics of protected areas to evaluate their conservation efforts. This study adopted the Landsat tree-canopy cover (TCC) method to derive annual TCC data for the period 1984–2020 for the protected areas of northeast China, where protection policies have been carried out since the end of the 20th century, e.g., the Natural Forest Conversion Program (NFCP). A strong correlation was found between the TCC estimates derived from Landsat and LiDAR observations, suggesting the high accuracy of TCC. Forest loss and gain events were also identified from the time series of TCC estimates. High correlations were reported for both forest loss (Producer’s accuracy = 85.21%; User’s accuracy = 84.26%) and gain (Producer’s accuracy = 87.74%; User’s accuracy = 88.31%), suggesting that the approach can be used for monitoring and evaluating the effectiveness of the NFCP and other forest conservation efforts. The results revealed a fluctuating upward trend of the TCC of the protected area from 1986 to 2018. The increased area of TCC was much larger than the decreased area, accounting for 59.68% and 40.34%, respectively, suggesting the effectiveness of protection policies. Since the NFCP was officially implemented in 1998, deforestation was effectively curbed, the area of forest loss was significantly reduced (slope: −14.24%/year), and the area of forest gain significantly increased (slope: 4.13%/year). We found that regional forest changes were mainly manifested in “forest gain after loss (forest recovery)” and “forest gain with no loss (forest newborn)”, accounting for 40.29% and 37.28% of the total area of forest change, respectively. Moreover, the forest gain area far exceeds the forest loss area, reaching 11.24 million hectares, suggesting a successful forest recovery due to forest protection.