Tenthredinidae represents one of the external feeders of the most diverse superfamily, Tenthredinoidea, with diverse host plant utilization. In this study, four complete mitochondrial genomes (mitogenomes), those of Cladiucha punctata, Cladiucha magnoliae, Megabeleses magnoliae, and Megabeleses liriodendrovorax, are newly sequenced and comparatively analyzed with previously reported tenthredinid mitogenomes. The close investigation of mitogenomes and the phylogeny of Tenthredinidae leads us to the following conclusions: The subfamilial relationships and phylogenetic placements within Tenthredinidae are mostly found to be similar to the previously suggested phylogenies. However, the present phylogeny supports the monophyly of Megabelesesinae as a subfamily, with the sister-group placement of Cladiucha and Megabeleses outside of Allantinae. The occurrence of the same type of tRNA rearrangements (MQI and ANS1ERF) in the mitogenomes of Megabelesesinae species and the presence of apomorphic morphological characters also provide robust evidence for this new subfamily. The divergence and diversification times of the subfamilies appear to be directly related to colonization of the flowering plants following the Early Cretaceous. The origin time and diversification patterns of Megabelesesinae were also well matched with the divergence times of their host plants from Magnoliaceae.

Generative Adversarial Networks (GANs) possess a significant ability to generate novel images that adhere to specific guidelines across multiple domains. GAN-assisted generative design is a design method that can automatically generate design schemes without the constraints of human conditions. However, more research on complex objects with weak regularity, such as parks, is required. In this study, parks were selected as the research object, and we conducted our experiment as follows: (1) data preparation and collection; (2) pre-train the two neural network, then create the design layout generation system and the design plan generation system; (3) realize the data augmentation and enhanced hundred level dataset to thousand level dataset; (4) optimized training; (5) test the optimized training model. Experimental results show that (1) the machine learning model can acquire specific park layout patterns, quickly generate well-laid-out plan layout plans, and create innovative designs that differ from the human designer’s style within reasonable limits; (2) GAN-driven data augmentation methods can significantly improve the generative ability of algorithms, reduce generative pressure, and achieve better generative results; (3) pix2pix is prone to mode collapse, and CycleGAN has fixed rule errors in expressing certain design elements; and (4) GAN has the ability to mine design rules in the same way as humans.

In the arid zone of northwest China, the Heihe River Basin (HRB), as a typical inland river basin, has a fragile regional ecological environment, obvious ecological degradation characteristics, and extremely serious problems in the utilization of agricultural land resources. Meanwhile, the shortage of water resources, the low reduction of land quality, and excessive agricultural activities have greatly increased the local water and land pressure. In this paper, firstly, using the Malmquist DEA model and coupling coordination degree model, the agroecological risk assessment system on account of the coupling of water and land resources (WLR) is constructed. Secondly, taking HRB from 1995 to 2020 as an example, we carry out spatial correlation analysis based on the degree of risk-correlated WLR. Thirdly, we analyze the evolution process and spatial correlation of ecological risk of agricultural WLR in the HRB at the county scale, then we conclude and put forward policy suggestions for improvement. The results show that: (1) On the whole, the average ecological risk of agricultural water resources in the HRB from 1995 to 2020 was 0.933, indicating that the risk was declining; the average ecological risk of agricultural land resources in the HRB from 1995 to 2020 was 0.938, indicating that the risk was declining also. (2) The degree of ecological risk coupling and coordination of agricultural soil and water resources upstream of the HRB is on the rise, while that in the middle and lower reaches is on the decline. (3) Through panel model analysis, the matching suitability of WLR drives agroecological risk. The correlation between them is positive. In conclusion, this method can effectively evaluate the agroecological risk of WLR and provide technical support for agricultural production and management in arid areas.