As an important barrier against desert invasion in Northwest China, Helan Mountains (HL), Luoshan Mountains (LS) and their natural forests have an extremely important ecological status. It is of great significance to study the relationship between forest growth and climate in this region under the background of global change. At present, relevant research mostly focuses on the Chinese pine (Pinus tabulaeformis Carr.), and little is known about how Qinghai spruce (Picea crassifolia Kom.) responds to climate change. To investigate the potential relationships between radial growth of P. crassifolia and climatic conditions in Ningxia, China, we collected tree-ring samples from P. crassifolia growing in the HL and LS and then established the standard tree-ring width chronologies for the two sites. Correlation analysis together with multivariate linear regression and relative contribution analyses were used, and results showed that radial growth in the HL was determined by the precipitation in the previous September, by the standardized evapotranspiration index (SPEI) in the current March and June, and by the maximum air temperature in the current September. The maximum air temperature in the current September contributed the most (0.348) to the radial growth in the HL. In the LS, radial growth was determined by the precipitation in the previous September and in the current March and by the minimum air temperature in the current July. The factor that made the most contribution was the precipitation in the current March (0.489). Our results suggested that in the wetting and warming future, growth of P. crassifolia in the HL will increase while that in the LS needs further investigation. Our results also provide a basis for predicting how P. crassifolia in northwest China will grow under the background of future climate change and provide a reference for formulating relevant management measures to achieve ecological protection and sustainable development policies.

To understand the impact of climate change on the tree radial growth in Southeast China’s subtropical evergreen broadleaved forest, comparative research on the radial growth–climate associations of Schima superba was conducted. This dominant evergreen broadleaved tree species was examined at both its southern and northern distribution margins through dendroclimatology. The results showed that the radial growth of S. superba stands at a high elevation in the southern margin and stands in the northern margin were positively correlated with springtime temperatures, mostly in April (e.g., mean temperature: r = 0.630, p < 0.05) and May (e.g., maximum temperature: r = 0.335, p < 0.05), respectively. Meanwhile, the temperature in the late rainy season had a significant negative effect on the radial growth of S. superba stands in the southern margin, including high-elevation stands (e.g., the mean temperature in previous and current September: r = −0.437 and −0.383, p < 0.05) and low-elevation stands (e.g., the mean temperature in previous August and October: r = −0.577 and −0.348, p < 0.05). It was shown that temperature was the key climatic factor affecting the radial growth of S. superba, and the response of radial growth to temperature had obvious spatial differences. The findings indicate that the radial growth of S. superba stands in warm growth environments will be negatively impacted by future climate warming. On the contrary, the radial growth of S. superba stands growing in relatively cold growth environments may benefit from warmer spring. The results enhance the understanding of tree growth responses to climate change in the subtropical forests of China.

Climate warming and subsequent drought are predicted to alter local forest production and carbon budgets, the sensitivity of which may be site- and species-specific. Although a warmer and drier climate often constrains tree growth, whether trees grown in cool, wet regions across the Siberian forest can in turn be promoted remains unknown. Here, we aimed to investigate the historical growth tendency of Siberian forests in the Sayan Mountain areas and to explore how climate interacts to regulate their growth. We used ring-width data from Siberian pine (Pinus sibirica Du Tour) sampled from three sites in this area to establish a regional chronology and calculate percentage growth change (%GC) over the past 250 years. Bootstrapped correlation analysis between the regional ring-width chronology and climatic factors indicates the mean air temperature, though not precipitation, is more often positively linked to the radial growth of Siberian pines. The %GC series shows that, from 1966 to 2006, the rising temperatures in May resulted in a significant increase in the radial-growth rate of Siberian pines (r = 0.47, p < 0.05). Our study suggests that the positive growth rate anomaly is more likely to occur as temperatures rise in Southern Siberia.

Whether the tree growth–climate relationship is consistent in subtropical China has not yet been reported. To fill this gap, we chose Pinus taiwanensis which grow on Lushan Mountain in a subtropical region of China as the target tree species, established a standard tree-ring width chronology, and conducted a moving correlation analysis with climatic factors. The results showed that the relationship between radial growth of P. taiwanensis and climate changed significantly during 1980–1990. From 1955 to 1985, tree rings were negatively affected mainly by precipitation in September of the current growing season. From 1990 to 2014, however, a significant negative correlation appeared between tree rings and sunshine duration from March to April in the growing season. Our results suggest the need to pay attention to this growth–climate inconsistency when conducting dendroclimatology studies in subtropical China. However, the causes of the inconsistency still require further confirmation.

Soil moisture (SM) plays a pivotal role in regulating terrestrial energy-water exchanges and exerts substantial influence on agricultural productivity. In this study, a high-resolution soil moisture (HRSM) dataset (16 m) was generated by integrating multi-source remote sensing data from SMAP, HJ-2, Sentinel-2, and Gaofen-6, together with the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model. The data assimilation (DA) method was implemented for assimilating HRSM within the Ensemble Kalman Filter (EnKF) framework using the Noah-MP model at a spatial resolution of 1 km. To enhance the spatial detail of SM, HRSM and its relative uncertainties derived from the three-cornered hat (TCH) method were used to update the observation error and Kalman gain in the EnKF framework, thereby improving SM profile estimates at a 16 m resolution. The performance of the DA method was evaluated against in situ measurements during the spring drought period in central Yunnan Province, China. The results show that assimilating HRSM (DA_HRSM) significantly improves surface and root-zone SM estimates in the Noah-MP model. The simulated SM from the DA_HRSM method demonstrates lower relative uncertainty. Compared to the assimilation of SMAP SM, the DA_HRSM method provides higher-resolution spatial features of SM and enhances spatial heterogeneity across 20 irrigation districts. The DA_HRSM method effectively captured the spring drought in central Yunnan, demonstrating good agreement with the Palmer Drought Severity Index (PDSI). The result highlights the advantages of incorporating high-resolution SM data into agricultural and drought monitoring systems.