Knowing the effect of thinning on forest ecosystem services is an important aspect of sustainable forest management. This study analyzed the traditional thinning on tree growth and soil nutrients in the Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) plantations. The Chinese fir plantations were 11 years old with different initial densities in Jinji (4000 tree·ha−1), and Yingde (3000 tree·ha−1), Xiaolong (2000 tree·ha−1) forest farms, and 20 years old in Yangmei (2000 tree·ha−1) forest farm. The thinning intensity was 35% in Yangmei and Xiaolong forest farms, and 43% in Jinji and Yingde forest farms. Tree growth was measured as the increment of diameter at breast height and stand volume; soil nutrients were measured as pH, soil carbon and nitrogen contents at 0–10 cm soil. The thinning led to an increase in the diameter of trees in all study plots, with the fastest growth rate in Jinji (22.02%) forest farm. The stand volume growth rate was higher in thinning plots than in control plots, with the highest volume growth rate in Xiaolong (27.8%), due to its higher leaf area index and lower density. There was an increasing pattern of C and N contents in the higher initial density plots after thinning (Jinji and Yingde forest farms). During the extreme drought year in 2021, the thinning mitigated the changes in soil acidity and soil moisture, which indicated that thinning could also increase drought tolerance in the short term. Thinning response studies frequently focus on the long-term effect; our results demonstrate how thinning promotes tree growth in the short term.

Understanding future changes in water supply and requirement under climate change is of great significance for long-term water resource management and agricultural planning. In this study, daily minimum temperature (Tmin), maximum temperature (Tmax), solar radiation (Rad), and precipitation for 26 meteorological stations under RCP4.5 and RCP8.5 of MIRCO5 for the future period 2021–2080 were downscaled by the LARS-WG model, daily average relative humidity (RH) was estimated using the method recommended by FAO-56, and reference crop evapotranspiration (ET0), crop water requirement (ETc), irrigation water requirement (Ir), effective precipitation (Pe), and coupling degree of ETc and Pe (CD) for soybean during the growth period were calculated by the CROPWAT model in Heilongjiang Province, China. The spatial and temporal distribution of these variables and meteorological factors were analyzed, and the response of soybean water supply and requirement to climate change was explored. The result showed that the average Tmin, Tmax, and Rad under RCP4.5 and RCP8.5 increased by 0.2656 and 0.5368 °C, 0.3509 and 0.5897 °C, and 0.0830 and 0.0465 MJ/m², respectively, while the average RH decreased by 0.0920% and 0.0870% per decade from 2021 to 2080. The annual average ET0, ETc, Pe, and Ir under RCP4.5 for 2021–2080 were 542.89, 414.35, 354.10, and 102.44 mm, respectively, and they increased by 1.92%, 1.64%, 2.33%, and −2.12% under the RCP8.5, respectively. The ranges of CD under RCP4.5 and RCP8.5 were 0.66–0.95 and 0.66–0.96, respectively, with an average value of 0.84 for 2021–2080. Spatially, the CD showed a general trend of increasing first and then decreasing from west to east. In addition, ET0, ETc, and Pe increased by 9.55, 7.16, and 8.77 mm per decade, respectively, under RCP8.5, while Ir decreased by 0.65 mm per decade. Under RCP4.5 and RCP8.5, ETc, Pe, and Ir showed an overall increasing trend from 2021 to 2080. This study provides a basis for water resources management policy in Heilongjiang Province, China.

Crop water production function models (WPFMs) are a required method to study the relationships between yield and water consumption under regulated deficit irrigation (RDI). In this study, a pot experiment was established to study the effect of water deficit during both individual growth stages and across two consecutive growth stages of rice on yield, water consumption, and water use efficiency (WUE) in 2017 and 2018. Light, medium, and severe water deficits were set as 80~90%, 70~80%, and 60~70% of fully saturated soil moisture content, respectively. The accuracies of five WPFMs were tested based on the experimental results. The results showed that yields and WUE of a light water deficit were higher than those of medium and severe water deficits at each growth stage. The yields and WUE of light drought stress treatments in the flowering and milky stages were higher than the fully saturated soil moisture control by 4~7.4% and 5.3~20.6%, respectively. Water consumption decreased with increasing water deficit across two consecutive growth stages. The Minhas model had the highest simulation accuracy of the five WPFMs, with relatively lower AE, RMSE, Cv, CRM, and higher R2, which were 0.0002, 0.0634, 6.9965, 0.0002, and 0.9951 in 2017 and 0.0110, 0.0760, 8.9882, 0.0131, and 0.9923 in 2018, respectively. The sensitivity indices for the Minhas model more accurately reflected the sensitivity of rice yield to water deficit at different growth stages in 2017 and 2018, compared with the Jensen model, Stewart model, Blank model, and Singh model. Rice yield was most sensitive to water deficit at the jointing and booting stage. The results indicate that the Minhas model is the most suitable WPFM for guiding rice irrigation practices in cold black soil regions of China.