Search Results (7)

With accelerating urbanization and agricultural modernization, the scale, structure, and land use conditions of rural settlements in China’s three northeastern provinces (TNPs) have changed dramatically, impacting regional food production and sustainable rural development. Based on multitemporal land use datasets and socioeconomic statistics, we used spatial pattern analysis, machine learning models, and the Shapley additive explanation (SHAP) method to investigate the spatial evolutionary characteristics and driving factors of rural settlements in China’s TNPs from 1980 to 2020. The results show that (1) the spatial evolution of rural settlements followed a four-stage “expansion–stabilization–re-expansion–restabilization” trend; arable land conversion was the primary source of expansion, with limited conversion from forests, grasslands, and water bodies. (2) Rural settlements demonstrated marked agglomeration, with the spatial distribution evolving from “single-center clustering” to “multiregional contiguous clustering”. Rural settlements in the Sanjiang Plain evolved into large patch clusters, while those in the lower Liaohe River Basin became small patch clusters. (3) Rural settlements at low elevations and near roads and waterways presented a large-scale, agglomerative distribution, while settlements at high elevations and far from rivers and roads showed a small-scale, high-agglomeration pattern. (4) The rural population, total power of agricultural machinery, total grain output, and primary industry value added predominantly drove settlement spatial expansion, with an “initial suppression, then promotion” trend, while the urbanization rate and GDP per capita had a negative impact, with the opposite trend. The interaction effects among high-contributing factors transitioned from suppressive to promoting. Our results provide theoretical insights for spatial planning and sustainable development in agricultural rural settlements. Full article

Land-use systems (LUSs) and soil types (STs) are strongly related to factors that influence soil degradation and carbon (C) loss. However, the way in which land use and soil type affects the soil organic C (SOC) pools, and soil aggregation in the Sanjiang Plain, has not been thoroughly investigated. Therefore, this study aimed to investigate soil physic–ochemical properties, soil aggregates, and C management index (CMI) in three different LUSs (grassland, dryland, and paddy field) under two STs (meadow soil and albic soil) of the Sanjiang Plain in northeast China. A total of 60 composite soil samples were collected for laboratory analyses. The results were as follows: soil properties were affected by LUS and ST, especially soil chemical properties; ST had no significant effect on soil aggregates but significantly affected its SOC content, while LUS had a significant effect on soil aggregates (p < 0.01), except for small macro-aggregates (2–0.25 mm); the mean weight diameter (MWD) and SOC in meadow soil was significantly different under different land uses, with grassland being the highest and dryland the lowest. However, there was no significant difference in albic soil. The heterogeneity of grassland, dryland, and paddy field showed that different LUSs had particular effects on SOC and its active components because LUS had significant effects on C pool index (CPI) and CMI, but ST and its interaction had no significant effects on CPI and CMI. Overall, the results showed that LUS was an important factor affecting CMI in the Sanjiang Plain, rather than ST, and the paddy field CMI was optimal in the Sanjiang Plain. Full article

An evaluation of soil quality sustainability can support decision making for the sustainable use of land resources. However, certain current problems associated with these evaluations remain unaddressed, e.g., the evaluation indicators do not fully reflect soil quality risks and the evaluation scale is not sufficiently small. In this study, 25,000 spatial grids of dimensions 3 km × 3 km are used to divide the major grain-producing regions in China, namely, the Sanjiang Plain and the Songnen Plain of Heilongjiang. Then, the soil erosion modulus, nutrient balance index, soil organic carbon (SOC) storage, heavy metal soil pollution index and crop productivity are calculated for each grid using the RULSE model, nutrient balance index model, soil type method, geoaccumulation index method and mechanism method, respectively. A spatial grid cluster analysis method is used to thoroughly evaluate and analyze the sustainability of soil quality in each grid. The results show that the overall soil status of the study area is good. The soil and water conservation levels are high, the soils show low levels of contamination, the crop production potential is high and the ratio of highly sustainable to moderately sustainable soils is approximately 2:1. Only 2.74% of the land is rated extremely unsustainable and needs to be restored to a basic level of productivity before subsequent functional restoration can be carried out. This study provides a new method for the fine-scale evaluation of soil quality and contributes to the management of land resources. Full article

Groundwater resources are an essential component of global water resources. Long-term consumption of groundwater exceeding the standard levels for iron and manganese can lead to chronic diseases, posing a threat to human health. The Sanjiang Plain is the largest swamp wetland area in China and has high levels of iron and manganese in the groundwater, but the cause still needs to be clarified. Based on the results of water quality tests of 41 groundwater samples in the Eastern Sanjiang Plain, this paper analyzes the distribution characteristics and causes of iron and manganese from the perspectives of the original strata environment, redox conditions, pH conditions, and hydrochemical indicator factors in the research area, using statistical methods and GIS technology. The results show that high iron and manganese content in groundwater is prevalent in the Eastern Sanjiang Plain, and the exceedance rate of manganese is higher than that of iron (87.80% and 82.90%, respectively). The primary sources of iron and manganese in groundwater are iron and manganese minerals in the original strata environment. Influenced by factors such as acidic conditions, reducing environment, and rich organic matter, insoluble high-valent iron and manganese oxides are reduced to low-valent and soluble divalent iron and manganese. At the same time, groundwater’s high mineralization and evaporation concentration are conducive to increased iron and manganese content, while the influence of human activities is small. Full article

Converting natural ecosystems to cultivated land, driven by human activities, has been considered a significant driver of limiting the delivery of ecosystem services (ES). The ES loss in the past was mainly caused by agricultural activities that have been taken to meet people’s needs in Northeast China. Quantifying historical declining ecosystem service values is essential to facilitate sustainable development. In this study, remote sensing images were used to investigate the history of cultivated land expansion over the last five decades. Additionally, ES variations caused by agricultural expansion since 1965 were quantified in the Small Sanjiang Plain (SSP), Northeast China. From the results, cultivated land expanded from 3.97% of the total SSP area to 66.40% from 1965 to 2015 (approximately 898.23 million ha), of which paddy field expanded drastically from 0% to 55.93%. Variations in cultivated land resulted in a loss of ecosystem service values by 11,893.85 million dollars, of which 62.98 million dollars were caused by the internal conversion between cultivation during 1965–2015. Agricultural expansion accelerated the export of agricultural products function, while it decreased almost all other functions, especially hydrological regulation and freshwater supply function. For future sustainability of the SSP, some suggestions, such as restoring natural ecosystems, planting trees between cultivated land, coculture systems, and winter-flooding of paddy rice were provided in our study. Full article

Monitoring wetland dynamics and related land-use changes over long-time periods is essential to understanding wetland evolution and supporting knowledge-based conservation policies. Combining multi-source remote sensing images, this study identifies the dynamics of marshes, a core part of wetlands, in the Small Sanjiang Plain (SSP), from 1965 to 2015. The influence of human activities on marsh patterns is estimated quantitatively by the trajectory analysis method. The results indicate that the marsh area decreased drastically by 53.17% of the total SSP area during the study period, which covered the last five decades. The marsh mostly transformed to paddy field and dry farmland in the SSP from 1965 to 2015, indicating that agricultural encroachment was the dominant contributor to marsh degradation in the area. Analysis of the landscape indexes indicates that marsh fragmentation was aggravated during the past five decades in the SSP. Trajectory analysis also indicated that human activities have acted as the primary driving force of marsh changes in the SSP since 1965. This study provides scientific information to better understand the evolution of the wetland and to implement ecological conservation and sustainable management of the wetlands in the future. Full article

As a crop with high water consumption, rice is an important measure of efforts to improve agricultural irrigation efficiency and alleviate the contradiction between the supply and demand of agricultural water resources. This paper takes the Longtouqiao irrigation district, in the hinterland of the Sanjiang Plain, a major rice-producing area in northern China, as an example, and the AquaCrop crop growth model and entropy-cloud model are jointly used to develop a rice irrigation schedule optimization model based on three kinds of typical rainfall years. Different irrigation schemes are established and evaluated by using the model built based on images. The results showed that the yield’s normalized root mean square error (NRMSE) value of the AquaCrop model was 9.949% (< 10%) after calibration, and the our model results showed a good agreement with observed data, which indicated that the calibrated model was suitable for rice growth simulation in the research area. For the same irrigation water amount, rice was irrigated to a great extent at the tillering stage, and a small amount of irrigation water at the regreening stage of rice could improve rice yield. During irrigation, rice production can also be promoted by regulating the irrigation amount according to the rainfall in each growth period, and the optimal irrigation water amount can be controlled between 20 and 60 mm each time. Under the three typical annual scenarios of dry, normal and wet years, the respective optimal quantification results for the field capacity, total irrigation water amount and irrigation times in the rice growth period to attain the optimal irrigation effect were 25%, 425 mm, and 17 times, respectively; 25%, 450 mm, and 14 times; respectively, and 25%, 425 mm, and 17 times, respectively. The research results can provide a decision-making basis for water-saving measures and efficient rice irrigation water management. Full article