Search

Blue carbon ecosystems such as mangroves are natural barriers to resisting and alleviating the impact of storm surges and extreme catastrophic weather. Accurate and efficient determination of the aboveground biomass of mangroves is of great importance for the protection and restoration of blue carbon ecosystems and their response to climate change. This study proposes a light gradient boosting model (LGBM) based on particle swarm optimization (PSO) algorithm for feature selection. We constructed and verified the proposed model using 227 quadrat datasets from a field survey and Sentinel-1 and Sentinel-2 data. The determination coefficient (R² ) and root-mean-square error (RMSE) were used to evaluate the performance of the model. Compared with random forest(RF), K-nearest neighbourhood regression(KNNR), extreme gradient boosting(XGBR), LGBM, and other machine learning algorithms, the LGBM-PSO model achieves better results (R² = 0.7807, RMSE = 24.6864 Mgha-1), The predicted range of mangrove biomass is 4.623–206.975 Mgha-1 . Therefore, the use of multisource remote sensing data combined with the LGBM-PSO model can provide better prediction results of aboveground biomass of mangroves, thereby providing a new method for estimating the aboveground biomass of large-scale mangroves. [ABSTRACT FROM AUTHOR]

Despite the fascinating biology of lichens, such as the symbiotic association of lichenforming fungi (mycobiont) with their photosynthetic partners and their ability to grow in harsh habitats, lack of genetic tools manipulating mycobiont has hindered studies on genetic mechanisms underpinning lichen biology. Thus, we established an Agrobacterium tumefaciens-mediated transformation (ATMT) system for genetic transformation of a mycobiont isolated from Cladonia macilenta. A set of combinations of ATMT conditions, such as input biomass of mycobiont, co-cultivation period with Agrobacterium cells, and incubation temperature, were tested to identify an optimized ATMT condition for the C. macilenta mycobiont. As a result, more than 10 days of co-cultivation period and at least 2 mg of input biomass of the mycobiont were recommended for an efficient ATMT, owing to extremely slow growth rate of mycobionts in general. Moreover, we examined T-DNA copy number variation in a total of 180 transformants and found that 88% of the transformants had a single copy T-DNA insertion. To identify precise T-DNA insertion sites that interrupt gene function in C. macilenta, we performed TAIL-PCR analyses for selected transformants. A hypothetical gene encoding ankyrin repeats at its C-terminus was interrupted by T-DNA insertion in a transformant producing dark-brown colored pigment. Although the identification of the pigment awaits further investigation, this proof-of-concept study demonstrated the feasibility of use of ATMT in construction of a random T-DNA insertion mutant library in mycobionts for studying genetic mechanisms behind the lichen symbiosis, stress tolerance, and secondary metabolite biosynthesis. [ABSTRACT FROM AUTHOR]