RESUMEN

Based on the continuous inventory data of forest resources in Zhejiang Province in 2019 and 2021, we used statistical methods such as polynomial regression to analyze the impacts of topography and forest spatial structure on average annual diameter at breast height (DBH) growth of main pioneer tree species in natural broad-leaved mixed forests. The results showed that DBH of Schima superba, Quercus glauca, Quercus fabri, Lithocarpus glaber, Castanopsis eyrei, and Castanopsis sclerophylla were between 5-50.8, 5-41.5, 5-50.8, 5-43.9, 5-55.5, and 5-46.1 cm, respectively. We classified all the trees into three classes based on DBH: small (6-12 cm), medium (12-14 cm), and large (>26 cm). The average annual DBH growth of S. superba and Q. glauca was the highest on semi-shady slope and shady slope, with increases of 2.9%-15.7% and 1.1%-41.2%, respectively. The average annual DBH growth of large-diameter S. superba, L. glaber, C. eyrei and C. sclerophylla decreased with the increase of slope, with a maximum decrease of 27.0% for S. superba, with no significant difference among small- and medium-diameter trees as a whole. The slope position did not affect the annual DBH growth of small-diameter trees, while that of medium- and large-diameter S. superba, Q. glauca, and large-diameter Q. fabri, L. glaber decreased with the change of slope position from downhill, mesoslope, uphill to ridge, with a maximum decrease of 28.1% for L. glabe, and the major-diameter C. eyrei was on the contrary. Appropriate increase in the mingling was beneficial to the average annual DBH growth of medium- and large-diameter trees. Moderate mixing was suitable for S. superba, while low degree mixing and moderate mixing was suitable for Q. glauca, Q. fabri and L. glaber, and intensive mixing was suitable for C. eyrei and C. sclerophylla. No significant difference was observed for minor-diameter trees under the mingling. The neighborhood comparison only had a significant effect on the average annual DBH growth of large-diameter Q. glauca, Q. fabri, and L. glaber, which was significantly higher under subdominance-moderation than moderation-inferiority. The average annual DBH growth in the study area was mainly affected by aspect and mixing degree.

Asunto(s)

Pinus , Quercus , Árboles , Bosques , China

RESUMEN

Changes in tree species composition are one of the key aspects of forest succession. In recent decades, significant changes have occurred in the tree species composition of subtropical forests in China, with a decrease in coniferous trees and an increase in broad-leaved trees. This study focuses on Zhejiang Province, located in the subtropical region of China, and utilizes seven inventories from the National Continuous Forest Inventory (NCFI) System spanning 30 years (1989-2019) for modeling and analysis. We categorized tree species into three groups: pine, fir, and broadleaf. We used the proportion of biomass in a sample plot as a measure of the relative abundance of each tree species group. A novel nonlinear difference equation system (NDES) model was proposed. A NDES model was established based on two consecutive survey datasets. A total of six models were established in this study. The results indicated that during the first two re-examination periods (1989-1994, 1994-1999), there was significant fluctuation in the trend of tree species abundance, with no consistent pattern of change. During the latter four re-examination periods (1999-2004, 2004-2009, 2009-2014, 2014-2019), a consistent trend was observed, whereby the abundance of the pine group and the fir group decreased while the abundance of the broad-leaved group increased. Moreover, over time, this pattern became increasingly stable. Although the abundances of the pine group and the fir group have been steadily declining, neither group is expected to become extinct. The NDES model not only facilitates short-term, medium-term, and even long-term predictions but also employs limit analysis to reveal currently obscure changing trends in tree species composition.

RESUMEN

Subtropical forests play an important role in global carbon cycle and in mitigating climate change. Knowledge on the abiotic and biotic driving factors that affect vegetation carbon stocks in subtropical forest ecosystems is needed to take full advantage of the carbon sequestration potential. We used a large-scale database from national forest continuous inventory in Zhejiang Province, and combined the Random Forest analysis (RF) and structural equation modeling (SEM) to quantify the contribution of biotic and abiotic driving factors on vegetation carbon stocks, and to evaluate the direct and indirect effects of the main driving factors. The RF model explained 50% of the variation in vegetation carbon stocks; canopy density accounted for 17.9%, and forest age accounted for 7.0%. Moreover, the SEM explained 52% of the variation in vegetation carbon stocks; the value of standardized total effects of canopy density and forest age were 0.469 and 0.327, respectively, suggesting that they were the most crucial driving factors of vegetation carbon stocks. Since the forests in our study were relatively young, the forests had a large potential for carbon sequestration. Overall, our study provided new insights into the sensitivity and potential response of subtropical forest ecosystems carbon cycle to climate change.