Characterizing and predicting the response of terrestrial ecosystems to global change is part of the fundamental challenges of contemporary ecology and ecological conservation. The assessment of climate change impact on forest ecosystems has rarely used a multi-index fusion method for quantitative evaluation. We used forest distribution, net primary productivity, and vegetation coverage to establish an assessment model of the impact of climate change on forest ecosystems. We analyzed the change characteristics of these indicators in the Heilongjiang Province of China. Our results indicate the following: (1) from 2001 to 2019, the forest area in Heilongjiang Province ranged from 234,000 to 246,000 km². The forest net primary productivity (NPP) ranged from 4.40 to 5.55 MgC·ha^-1·yr^-1, and the vegetation coverage ranged from 42.42% to 67.64%. The forest NPP and the vegetation coverage showed a significant upward trend. (2) The values of forest ecological roles were significantly positively correlated with the climatic potential. (3) The contribution rate of climate change to forest ecosystem change was negatively correlated with forest coverage, which varied from 4.79% to 18.07% in different regions (cities) of the province. Study Implications: Assessing the influence of climate on forest ecosystems comprehensively and accurately before the government prepares ecological measures is necessary. However, the responses of vegetation coverage and net primary productivity to climate change may not be consistent, so climate studies that consider forest ecosystem change trends by a single indicator may have confounding results. We established a model for evaluating the impact of climate change on forest ecosystems to solve this problem. This knowledge may provide a reference for the response, adaptation, and vulnerability assessment of forest ecosystems to climate change.

Objective: This study aims to evaluate the soil rill erosion intensity in the Northeast Black Soil Region of China and explore the relationship between extreme precipitation events and soil erosion over the period from 1980 to 2020. Methods: The Revised Universal Soil Loss Equation (RUSLE) model was applied to estimate soil rill erosion values using a combination of meteorological observations, remote sensing, soil physicochemical properties, and Geographic Information Systems. A correlation analysis framework was developed to link soil rill erosion values with extreme precipitation indices, and the spatial-temporal dynamics were analyzed. Results: The annual soil rill erosion value in the region averaged 0.84 ± 0.22 t·ha ⁻¹ ·yr ⁻¹ , with no significant trend over four decades. The Eastern Mongolian subregion exhibited the highest erosion rates, exceeding 2.0 t·ha ⁻¹ ·yr ⁻¹ . Strong correlations were identified between soil rill erosion and factors such as consecutive rainy days, cumulative precipitation, and extreme rainfall events. Conclusions: Extreme precipitation events play a significant role in driving soil rill erosion, emphasizing the need for refined models that integrate hydrological processes. The study provides critical insights for regional soil conservation and climate adaptation strategies.

Agroclimatic regionalization is an effective way to utilize agricultural climate resources in a reasonable manner. Accurate and objective agroclimatic regionalization plays a great directive role in ecological layout and decision support for agriculture farming. The purpose of this article was to investigate the influence of climate change on agroclimatic regions in China. Following the same regionalization principle concept as the theory and techniques of agroclimatic regionalization, three agroclimatic regions, the Tibetan High Cold Region (THCR), Northwest Arid Region (NAR), and Eastern Monsoon Region (EMR) were identified in China. The changes in the three agroclimatic regions were analyzed from 1961 to 2020 in the past and from 2006 to 2060 in the future. Future changes in agroclimatic regions were estimated from 2006 to 2030 and from 2031 to 2060 under scenarios RCP2.6, RCP4.5, and RCP8.5 for greenhouse gas emissions. The borders of agoclimatic regions had changed as a result of global climate warming and precipitation variability. There was a surplus in the geographical displacement and range of agroclimatic region borders in 1991 to 2020, especially when compared to those in 1961–1990. The TCHR exhibited significant spatial variation, with its northeast corner shifting nearly 170 km to the southwest. In the future, the area ratio of the THCR will be 26% by 2031–2060 under the RCP8.5 scenario, with the highest decline (1% compared to that in the reference period of 1981–2005), while under the RCP4.5 and RCP2.6 scenarios it will stabilize the area ratio at 27%. The eastern boundary of the NAR will migrate south or east, while the center boundary will rise northward. Under all three climatic scenarios, the area ratio will be 25% (down 1%). The range of the EMR will expand. The area ratio of the EMR will increase by 1% under the RCP2.6 and RCP4.5 scenarios and by 2% under the RCP8.5 scenario. Overall, our study may facilitate an in-depth understanding of agroclimatic regions changes and thus provide a scientific reference for the distribution of agricultural production and sustainable development under climate change in China.