To identify the species of Collembola that harm Morchella and to screen for pesticides that are effective in controlling these pests with minimal inhibition of mycelial growth, a five-point sampling method was used to investigate the population of Collembola and its damaging effects on Morchella and to analyze its spatial distribution in the soil. The indoor control efficacy of ten insecticides was determined using the mushroom disc immersion method and the pesticide film method. The most effective insecticides were then selected for field testing. The effect of the best-performing field pesticides on the mycelial growth of Morchella was measured using the Petri dish mycelial growth rate method, and pesticide residues were detected using chromatography. The survey revealed that in three Morchella greenhouses, the average Collembola population was 220,333 individuals/m3. The spatial distribution of Collembola was uniform. The collected Collembola specimens were identified as Oligaphorura ursi from the family Onychiuridae. Through the lab and field screening of pesticides, it was found that 40% phoxim EC, 1.8% abamectin EC, 2.5% lambda-cyhalothrin EW, and 4.5% beta-cypermethrin EC had the best efficacy. Meanwhile, residues of these four pesticides were not detected. Mycelial growth inhibition experiments showed that 2.5% lambda-cyhalothrin EW, 1.8% abamectin EC, and 4.5% beta-cypermethrin EC exhibit low inhibition of mycelial growth and can be used as control pesticides for Collembola on Morchella, providing a technical reference for the green pesticide control of Collembola on Morchella in the study region.

A traditional grid model for soil sampling may suffer from poor efficiency and low accuracy. With a nonferrous metal processing plant as the study area, a three-dimensional kriging interpolation model was built based on this plant's preliminary investigation data for arsenic (As), and a detailed survey sampling programme was proposed. The sampling density at the pollution interval of the surface soil was estimated by the coefficient of variation method, and the sampling depth was determined by the pollution interval of the vertical prediction results. The results showed that the encrypted soil sampling distribution optimisation method obtains greater pointing accuracy with fewer points. The sampling accuracy was 87.62% after optimising the depth of pointing. Moreover, this approach could save 66.13% of the sampling costs and 56.93% of the testing costs compared to a full deployment programme. This study provides a new and cost-effective method for predicting the extent of contamination exceedance at a site and provides valuable information to guide post-remediation strategies for contaminated sites.