Here, through single‐molecule real‐time sequencing, we present a high‐quality genome sequence of the Japanese larch (Larix kaempferi), a conifer species with great value for wood production and ecological afforestation. The assembled genome is 10.97 Gb in size, harboring 45,828 protein‐coding genes. Of the genome, 66.8% consists of repeat sequences, of which long terminal repeat retrotransposons are dominant and make up 69.86%. We find that tandem duplications have been responsible for the expansion of genes involved in transcriptional regulation and stress responses, unveiling their crucial roles in adaptive evolution. Population transcriptome analysis reveals that lignin content in L. kaempferi is mainly determined by the process of monolignol polymerization. The expression values of six genes (LkCOMT7, LkCOMT8, LkLAC23, LkLAC102, LkPRX148, and LkPRX166) have significantly positive correlations with lignin content. These results indicated that the increased expression of these six genes might be responsible for the high lignin content of the larches' wood. Overall, this study provides new genome resources for investigating the evolution and biological function of conifer trees, and also offers new insights into wood properties of larches.

The stem height–diameter allometric relationship is fundamental in determining forest and ecosystem structures as well as in estimating tree volume, biomass, and carbon stocks. Understanding the effects of silvicultural practices on tree height–diameter allometry is necessary for sustainable forest management, though the impact of measures such as thinning on the allometric relationship remain understudied. In the present study, the effects of thinning on tree height–diameter allometry were evaluated using Masson pine height and diameter growth data from a plantation experiment that included unthinned and thinned treatments with different intensities. To determine whether thinning altered the height–diameter allometry rhythm, the optimal height–diameter model was identified and dummy variable methods were used to investigate the differences among model parameters for different thinning treatments. Periodic (annual) allometric coefficients were calculated based on height and diameter increment data and were modeled using the generalized additive mixed model (GAMM) to further illustrate the response of tree height–diameter allometry to different thinning treatments over time. Significant differences were detected among the parameters of the optimal height–diameter model (power function) for different thinning treatments, which indicated that the pattern of the height–diameter allometry relationship of Masson pine was indeed altered by thinning treatments. Results also indicated a nonlinear trend in the allometric relationship through time which was significantly affected by thinning. The height–diameter allometric coefficient exhibited a unimodal convex bell curve with time in unthinned plots, and thinning significantly interfered with the original trend of the height–diameter allometric coefficient. Thinning caused trees to increase diameter growth at the expense of height growth, resulting in a decrease of the ratio of tree height to diameter, and this trend was more obvious as the thinning intensity increased.

There is growing concern that public benefits from forests are underprovided in current forest management regimes and need to be increased through policy and economic measures that promote conservation. Ecological compensation is a type of institutional arrangement for the sustainable use of ecosystem services achieved by adjusting the distribution of costs and benefits among different stakeholders using economic measures. However, how to accurately and reasonably determine the compensation standard for ecological services has not been guided by scientific methods and theories. This study provides an estimation of the compensation standard for forest ecological services based on the forest multifunction evaluation and financial net present value analysis, and a case study was performed in Southwest China. The results showed that most forest types brought some economic loss to the managers but contributed great ecological benefits to the public when they were managed as ecological forests. It is crucial to incentivize forest managers to participate in voluntary conservation programs through ecological compensation. The results of this analysis can potentially guide sustainable forest management by both accurate quantification of the value of forest ecosystem services and an improved understanding of the costs of voluntary forest conservation schemes currently in use in many countries.

Forest biomass is an important indicator of forest ecosystem productivity, and it plays vital roles in the global carbon cycling, global climate change mitigating, and ecosystem researches. Multiscale, rapid, and accurate extraction of forest biomass information is always a research topic. In this study, comprehensive investigation of a larch (Larix olgensis) plantation was performed using remote sensing and field-based monitoring methods, in combination with LiDAR-based multisource data and machine learning methods. On this basis, a universal, multiscale (single tree, stand, management unit, and region), and unit-high-precision continuous monitoring method was proposed for forest biomass components. The results revealed the following. (1) Airborne LiDAR point cloud variables exhibited significant correlation with the aboveground components (except leaves) and the whole-plant biomass ($R_{adj}^2$ > 0.91), suitable for extraction or estimation of forest parameters such as biomass and stock volume. (2) In terms of biomass monitoring at forest stand and management unit scale, a random forest model performed well in fitting accuracy and generalization ability, whereas a multiple linear regression model produced clearer explanation regarding the biomass of each forest component. (3) Using seasonal phenological characteristics in the study area, larch distribution information was extracted effectively. The overall accuracy reached 90.0%, and the kappa coefficient reached 0.88. (4) A regional-scale forest biomass component estimation model was constructed using a long short-term memory model, which effectively reduced the probability of biomass underestimation while ensuring good estimation accuracy, with R² exceeding 0.6 for the biomass of the aboveground and whole-plant components. This research provides theoretical support for rapid and accurate acquisition of large-scale forest biomass information.