We developed two tree-ring width chronologies of Mongolian Scots pine (Pinus sylvestris var. mongolica) from the low elevation forest of the northern Daxing’anling Mountains of Inner Mongolia. Although the two chronologies come from different sampling sites, significant correlations existed among the chronologies (r = 0.318), and the first principal component (PC1) accounted for 65.9% of total variance over their common period 1792–2016. Climate-growth correlation analysis revealed that the previous June and July Palmer drought severity index (PDSI_p6-7) was the main climatic factor controlling tree-ring growth. Using a linear regression model, we reconstructed the PDSI_p6-7 for the past 225 years (1792–2016). The reconstruction satisfied required statistical calibration and validation tests, and represented 38.6% of the PDSI variance recorded by instruments over the period 1955–2016. Six wet and five dry periods were revealed during these 225 years. The drought of 1903–1927 was the most severe drought in the study area in the last 225 years. Comparison with other tree-ring-based moisture-sensitive sequences from nearby regions confirmed a high degree of confidence in our reconstruction. The results of a spatial climate correlation analysis with a gridded PDSI dataset revealed that our reconstructions contained strong regional drought signals for the southern Stanovoy Range and the northern Daxing’anling Mountains. The power spectrum revealed the existence of significant frequency cycles, which may be linked to large-scale atmospheric-oceanic variability, such as the El Niño-Southern Oscillation, solar activity, and the North Atlantic Oscillation.

Subtropical forest productivity is significantly affected by both natural disturbances (local and regional climate changes) and anthropogenic activities (harvesting and planting). Monthly measures of forest aboveground productivity from natural forests (primary and secondary forests) and plantations (mixed and single-species forests) were developed to explore the sensitivity of subtropical mountain productivity to the fluctuating characteristics of climate change in South China, spanning the 35-year period from 1981 to 2015. Statistical analysis showed that climate regulation differed across different forest types. The monthly average maximum temperature, precipitation, and streamflow were positively correlated with primary and mixed-forest aboveground net primary productivity (ANPP) and its components: Wood productivity (WP) and canopy productivity (CP). However, the monthly average maximum temperature, precipitation, and streamflow were negatively correlated with secondary and single-species forest ANPP and its components. The number of dry days and minimum temperature were positively associated with secondary and single-species forest productivity, but inversely associated with primary and mixed forest productivity. The multivariate ENSO (EI Niño-Southern Oscillation) index (MEI), computed based on sea level pressure, surface temperature, surface air temperature, and cloudiness over the tropical Pacific Ocean, was significantly correlated with local monthly maximum and minimum temperatures (Tmax and Tmin), precipitation (PRE), streamflow (FLO), and the number of dry days (DD), as well as the monthly means of primary and mixed forest aboveground productivity. In particular, the mean maximum temperature increased by 2.5, 0.9, 6.5, and 0.9 °C, and the total forest aboveground productivity decreased by an average of 5.7%, 3.0%, 2.4%, and 7.8% in response to the increased extreme high temperatures and drought events during the 1986/1988, 1997/1998, 2006/2007, and 2009/2010 EI Niño periods, respectively. Subsequently, the total aboveground productivity values increased by an average of 1.1%, 3.0%, 0.3%, and 8.6% because of lagged effects after the wet La Niña periods. The main conclusions of this study demonstrated that the influence of local and regional climatic fluctuations on subtropical forest productivity significantly differed across different forests, and community position and plant diversity differences among different forest types may prevent the uniform response of subtropical mountain aboveground productivity to regional climate anomalies. Therefore, these findings may be useful for forecasting climate-induced variation in forest aboveground productivity as well as for selecting tree species for planting in reforestation practices.