This work aims to separate antimicrobial lipopeptides from fermentation by Aureobasidium pullulans PA-2, and verify its antimicrobial activity and the optimum condition of lipopeptide production. Using high performance liquid chromatography (H...

Species distribution models (SDMs) grapple with uncertainty. To address this, a parameter-optimized MaxEnt model was used to predict habitat suitability for Elsholtzia densa, a predominant agricultural weed on the Tibetan Plateau. Through multiparameter optimization with 149 occurrence points and three climate variable sets, we systematically evaluated how the three MaxEnt extrapolation approaches (Free Extrapolation, Extrapolation with Clamping, No Extrapolation) influenced model outputs. The results showed the following: (1) Model optimization using the Kuenm R package version (1.1.10) identified seven critical bioclimatic variables (Feature Combinations = LQTH, Regularization Multipliers = 2.5), with optimized models demonstrating high accuracy (Area Under Curve > 0.9). (2) Extrapolation approaches exhibited negligible effects on variable selection, though four bioclimatic variables “bio1 (annual mean temperature)”, “bio12 (annual precipitation)”, “bio2 (mean diurnal range)”, and “bio7 (temperature annual range)” predominantly drove model predictions. (3) Current high-suitability areas are clustered in the eastern and southern regions of the Tibetan Plateau, and with Free Extrapolation yielding the broadest current distribution. Climate change projections suggest habitat expansion, particularly under conditions of No Extrapolation. (4) Multivariate Environmental Similarity Surface (MESS) and Most Dissimilar Variable (MoD) are not affected by the extrapolation method, and extrapolation risk analyses indicate that future climate anomalies are mainly concentrated in the western and southern parts of the Tibetan Plateau and that future warming will further increase the unsuitability of these regions. (5) Variance analysis showed that the extrapolation methods did not significantly affect the 10-replicate results but influenced the parameter and emission scenarios, with No Extrapolation methods showing minimal variance changes. Our findings validate that multiparameter optimization improves species distribution model robustness, systematically characterizes extrapolation impacts on distribution projections, and provides a conceptual framework and early warning systems for agricultural weed management on the Tibetan Plateau.

Objective This study aims to investigate the distribution characteristics of droplet deposition and weed control effect of plant protection UAV in weeding operation of oat field by changing flight height，flight speed and spray width. Method DJI T30 plant protection drone was selected as a test instrument to determine the droplet deposition rule of oat leaves by three factors and three levels orthogonal test of working height，speed and spray width design.In addition，field experiments were conducted to determine the control effect of herbicide spraying on target weeds in oat mixed sowing field. Result The test results showed that when the spraying parameters were 4 m/mL，the working height was 1.5 m，and the working speed was 5 m/s（i.e.，treatment 7），the fog droplet coverage rate on oat leaves was 6.98%，and the droplet deposition density was 107.80 cm².With an average droplet diameter of 1 447 μm，it was the highest of all the treatments set.The analysis showed that the main factors affecting the fog coverage and deposition density of oat leaves were working height，working speed and spraying amplitude，while the factors affecting the fog drop diameter were working speed，spraying amplitude and working height.The optimal flight parameters were 4 m spray width，1.5 m flight height and 5 m/s flight speed for T30 plant protection UAV.The plant control efficiency was 87.07% and fresh weight control efficiency was 91.45% at 40 d after application.Compared with the control，the yield increase was 437.47 kg/hm²，with an increase of 10.09%. Conclusion The study reveals the distribution of droplet deposition and its effect on weeding in oat field when the plant protection UAV T30 was sprayed with 480 g/L Bentazone AS，which provides data support and technical support for the extensive application of the plant protection UAV in the agricultural field.