Abiotic stresses such as drought and salinity constantly threaten food security. Biochar as a soil amendment has the potential to ameliorate soil and alleviate drought and salinity stress. Multiple studies have been conducted to evaluate the effect of biochar in alleviating independent drought or salinity stress. However, the potential of biochar in mitigating the combined drought and salinity stress on plants has not been studied so far. Therefore, a pot experiment was conducted in the climate-controlled chamber with the objective to investigate the effect of biochar on growth, physiology, and yield of quinoa under independent and combined drought and salinity stress. Quinoa plants were subjected to three irrigation treatments i.e., full irrigation (FI), deficit irrigation (DI), and alternate root-zone drying irrigation (ARD), two saline water treatments (0 and 400 mM) and two levels of biochar (0% and 5% by weight). In the FI treatment, plants were irrigated daily to maintain pot water-holding capacity. In limited irrigation treatments, 70% water of FI was applied either to the whole pot in DI or to one side of the pot alternating in ARD, respectively. The results showed that combined drought and salinity stress drastically affected growth and performance of quinoa compared to the independent drought or salinity stress. However, soil amendment with biochar had positive effect in mitigating both independent and combined effect of drought and salinity on quinoa plants. Furthermore, biochar amendment in ARD under salinity significantly enhanced plant height, shoot biomass, and grain by 11.7%, 18.8%, and 10.2% as compared with DI under salinity, respectively. In addition, leaf photosynthetic rate (A_n) and stomatal conductance (g_s) decreased under limited saline irrigation. Moreover, the interactive effect of biochar and ARD efficiently adjusted the balance between chemical signal (leaf ABA) and hydraulic signal (leaf water potential). Thus, intrinsic water use efficiency (WUE_i) and yield in ARD were significantly enhanced compared to DI, especially under salinity stress. Overall, biochar in combination with ARD might be a wise approach for sustaining crop productivity in salt affected and drought stressed areas of the world to ensure food security.

Ecological compensation for cultivated land is a prominent means to coordinate the protection and utilization of cultivated land ecosystems. This study assessed the ecological compensation for cultivated land, considering both the ecological footprint and value of ecosystem services. We used the ecological footprint model to calculate the ecological footprint and ecological carrying capacity of cultivated land, combined with the value of its ecosystem services, with a focus on estimating its ecological compensation standard, and we analyzed the temporal and spatial distribution characteristics of Northeast China. We found that the ecological footprint and ecological carrying capacity of cultivated land showed a fluctuating growth trend in Northeast China from 2000 to 2020, increasing by 288.83 × 10⁵ ha and 131.37 × 10⁵ ha, respectively. The spatial distribution of cultivated land’s ecological footprint and ecological carrying capacity showed growth from the southwest to the northeast. The value of its ecosystem services presented an overall trend of growth over the past 20 years, increasing by CNY 13.64 billion, or an increase of 12.47%. In terms of spatial distribution, the trends of the ecological compensation for cultivated land showed obvious differences. This study mainly focused on black soil cultivated land, and its results are helpful for governments in different countries solving similar problems in terms of the ecological compensation for cultivated land. This study will provide a valuable reference to measure the compensation standard scientifically and to provide policy recommendations for sustainable cultivated land’s protection and utilization.

Understanding the factors influencing the vulnerability of forested areas is crucial for human well-being and effective governance of ecosystem supply and demand. Based on remote sensing data, this study also considered ten natural and human variables as indexes to explore the main influencing factors that may impact the vulnerability of the Thies region’s forested areas. The 2005, 2010, 2015, and 2020 satellite image data were processed using ArcGIS 10.6 and ENVI 5.1 software. The methodology includes using the transfer matrix approach and calculating the geographic landscape index to describe the dominant morphology of forested areas. Furthermore, a mixed linear regression model was built to establish the connection between forested areas and the potential contributing components. Our study revealed that the forested areas led to relative fragmentation, with an average of 88 patches for Aggregation Index (AI), 3.25 for Largest Patch Index (LPI), 2.50 for Patch Density (PD), and 112 for Landscape Shape Index (LSI) between 2005 and 2020. In addition, the transfer matrix indicated that the loss of forestry areas was about −78.8 km² for agricultural land, −127.8 km² for bare land, and −65.3 km² for artificial surfaces. The most critical factors that influenced forested areas were agricultural and manufactural added value, rainfall (p < 0.05), slope, distance to the road, and agricultural sown area (p < 0.001). Overall, this investigation has revealed that the effective management of forested areas in the Thies region requires an understandable assessment. It was observed that both human anthropogenic and natural factors significantly contribute to the decline in forested areas.

Land use change accounts for a large proportion of the carbon emissions produced each year, especially in highly developed traditional heavy industry and agriculture areas. In this study, we estimated the carbon emissions from land use in the Black Soil Region of Northeast China (BSRNC) from 1990 to 2020. We utilized seven periods of land use remote sensing image data spanning the years 1990, 1995, 2000, 2005, 2010, 2015, and 2020, with a 30-m grid resolution. Additionally, socio-economic data was incorporated into the analysis. The preprocessing of the remote sensing images involved several steps using ENVI 5.5, including radiometric correction, fusion, mosaic, and cropping. The land types were classified into six major categories: cropland, forest land, grassland, water area, construction land, and unused land, using the LUCC classification system. The IPCC coefficient method was used to calculate the trends in carbon emissions from land use, and the logarithmic mean Divisia index (LMDI) method was applied to analyze the influencing factors. The main conclusions are as follows: (1) From 1990 to 2020, the net carbon emissions from land use in the BSRNC increased from 11.91 × 10⁴ t to 253.29 × 10⁴ t, with an annual growth rate of 8.04%. (2) Spatially, land use carbon emissions exhibited an agglomeration pattern that gradually weakened and the regional emission differences gradually narrowed. (3) Income level was identified as the most important factor influencing land use carbon emissions in the BSRNC from 1990 to 2020. Land use efficiency had a inhibitory effect on net carbon emissions, reducing land use carbon emissions by 1730.63 × 10⁴ t.

A better understanding of the dynamic variation in the ecosystem service value (ESV) under land use/cover change (LUCC) is conductive to improving ecosystem services and environmental protection. The present study took Landsat TM/ETM remote sensing images and socio-economic statistic data as data sources and extracted land-use data using RS and GIS technology at 5-year intervals from 1990 to 2020. Then, we interpreted the spatio-temporal characteristics of LUCC and analyzed ESV changes using the value equivalence method in the black soil region of northeastern China (BSRNC). The main results showed that land use changed significantly during the study period. Cultivated land continued to expand, especially paddy areas, which increased by 1.72 × 10⁶ ha, with a relative change of 60.9% over 30 years. However, grassland decreased by 2.47 × 10⁶ ha, with a relative change of −60.6% over 30 years. The ESV showed a declining trend, which decreased by CNY 607.96 million during 1990–2020. The decline in forest and grassland caused a significant decline in the ESV. Furthermore, the ESV sensitivity coefficients were less than one for all of the different categories of ecosystem services. LUCC has a considerable impact on ESV in the BSRNC, resulting in ecosystem function degradation. As a result, future policies must emphasize the relationship between food security and environmental protection in situations of significant land-use change.

Cultivated land quality (CLQ) is at the core of the trinity protection of cultivated land in China. Scientific evaluation of CLQ and identification of its obstacle factors are the foundation for the construction and improvement of the quality of cultivated land. The main objective of this study was to evaluate CLQ and identify its obstacle factors, and Quzhou County, an intensive agricultural region in the North China Plain (NCP), was selected as a case study. The evaluation index system of CLQ was constructed based on five dimensions, including climate condition, topographic characteristic, soil property, farming status, and environmental condition, by analyzing the logical evolution of elements, processes, functions, and quality of cultivated land. A methodological system based on the Weighted Summation Method (WSM) and the “1 + X” model was developed to evaluate the CLQ. Then, the obstacle diagnosis model constructed based on the Cask Law and relevant academic studies was used to identify the obstacle factors of CLQ. The results showed that the proportion of high-, medium-, and low-quality cultivated land in Quzhou County was 36.19%, 33.60%, and 30.21%, respectively, and the average grade of CLQ was 2.97, which was considered to be at a medium level. Moran’s I of global spatial autocorrelation in Quzhou County was 0.8782, indicating a significant positive autocorrelation of the cultivated land quality index (CLQI). The main obstacle factors of CLQ in Quzhou County were soil profile constitution, irrigation guarantee rate, groundwater depth, and soil microbial biomass carbon. Therefore, based on the stable and dynamic characteristics of the obstacle factors, suggestions were provided to improve the quality of cultivated land in terms of strengthening the consolidation of cultivated land, transforming the concept of agricultural fertilization, and carrying out cultivated land recuperation. This study provides a new perspective on the cognition, evaluation, and identification of obstacle factors of CLQ, and the findings of this study can provide a reference for the consolidation and improvement of CLQ in the NCP.