The goal of this study is to analyze the land use and land cover change (LUCC) in the Northeast Sandy Land from 1990 to 2023 and reveal the characteristics of the changes in the value of ecosystem services in the area, aiming to provide scientific references for the ecological sustainable development of the Northeast Sandy Land. Using Landsat series remote sensing images from 1990 to 2023, we endeavored to obtain the information mapping of LUCC in the study area in four periods (1990, 2000, 2010, and 2023), applied GIS spatial analysis and numerical statistical analysis methods to study the LUCC in the area, and calculated the resulting changes in ecosystem service value (ESV) based on the table of ESV coefficients. The results show that: (1) in the past 33 years, LUCC in the Northeast Sandy Land has changed significantly, with an increase in the area of farmland, sandy land, and other lands, and a decrease in the area of forest, grassland, and water; (2) the value of ecosystem services has increased from CNY 1,624,557.77 billion in 1990 to CNY 173,999.99 billion in 2023, the average annual growth rate is 0.24%/a; (3) in the single ESV, the ESV of biodiversity increase is the greatest, with an increase of 0.72%/a; (4) LUCC is obvious in the Northeast Sandy Land, and LUCC is the main reason affecting the change in regional ESV.

Soybean bacterial blight disease is a threat to soybean production. Multispectral technology has shown good potential in detecting this disease and can overcome the limitations of traditional methods. The aim of this study was to perform field monitoring of the dynamics of this disease in Northeast China in 2022. The correlation between the soybean chlorophyll content index (CCI) and disease grade was obtained using artificial inoculation of the pathogen. The correlation between the soybean CCI, disease grade, green normalized difference vegetation index (GNDVI), and soybean yield was analyzed using a drone-mounted spectrometer platform for image acquisition and preprocessing. The soybean CCI was negatively correlated with the disease grade. The GNDVI declined with disease progression, which allowed for an indirect determination of the disease grade. The soybean yield loss was significant at disease grade 4 for soybean bacterial blight disease. The random forest regression model was more accurate than the regression model in estimating the yield based on the GNDVI. Therefore, the GNDVI could be used to survey the disease class and estimate the yield using the random forest model. This study provides support for field trials of drone-mounted multispectral equipment. This surveillance approach holds the potential to bring about precision plant protection in the future.

Mycterothrips glycines Okamoto (1911) (Thysanoptera: Thripidae) is rapidly increasing in fields, posing a new and potentially serious threat to soybean production in Northeast China. To clarify the population dynamics and screen effective insecticides against M. glycines, systematic monitoring and pesticide evaluation were conducted from 2024 to 2025. Occurrence dynamics were continuously monitored using yellow and blue sticky boards, while ten commonly used commercial insecticide formulations (thiamethoxam, clothianidin, sulfoxaflor, acetamiprid, imidacloprid, fenthion, pyridaben, abamectin, beta-cypermethrin, spinetoram) were hierarchically screened through laboratory bioassays, pot trials, and field spraying experiments. The results revealed a distinct ‘rise-and-fall’ occurrence pattern, with the initial, peak, and late occurrence periods occurring in mid-July, late July to early August, and mid-to-late August, respectively. Thiamethoxam and clothianidin exhibited the strongest toxicity against M. glycines (LC₅₀ values of 12.87 mg/L and 13.46 mg/L, respectively), achieving field control efficacies exceeding 85%, which were significantly superior to conventional agents such as imidacloprid and abamectin. The study identified the soybean flowering stage as the critical window for control, recommending preventive interventions when sticky trap monitoring indicates the initial population peak (around mid-July). This research fills the technical gaps regarding the occurrence dynamics of M. glycines and the lack of registered control products in China, providing essential support for precision monitoring and management of soybean thrips.