Arsenic, a common metalloid contaminant in soil, can enter the terrestrial food chain through plant uptake. While soil arsenic contamination can lead to long-term exposure that affects multiple generations, the multigenerational impacts on terrestrial plantherbivore systems remain poorly understood. This study examined the effects of soil arsenate (As(V)) transferred to pepper plants on Myzus persicae over three generations (F0-F2). We measured adult body length (AL), development time (DT), and offspring body length (OL) of M. persicae after rearing them on peppers cultivated in soil treated with four concentrations (0, 2, 4, and 6 mg kg-1) of As(V). In the F0 generation, the As(V) treatment significantly affected AL and DT (p<0.05), but no significant effect on OL was detected (p= 0.83). In the F1 and F2 generations, however, significant differences between treatments were observed in OL (p<0.05), along with AL and DT. Notably, in the F0 generation, As(V)- exposed individuals exhibited consistently stimulated growth and development, while responses became inconsistent in the F1 and F2 generations across various treatment conditions. These findings suggest that the effects of As(V) on M. persicae through multigenerational exposure are more complex than those observed within a single generation. This study highlights the importance of multigenerational approaches to accurately assess the ecological impacts of soil As(V) contamination on terrestrial ecosystems.

Springtails (class Collembola) play a crucial role in soil ecosystems. They are commonly used as standard species in soil toxicity assessments. According to the ISO 11267 guidelines established by the International Organization for Standardization (ISO), Allonychiurus kimi uses adult survival and juvenile production as toxicity assessment endpoint. Conventional toxicity assessment methods require manually counting adults and larvae under a microscope after experiments, which is time-consuming and laborintensive. To overcome these limitations, this study developed a model using YOLOv8 to detect and count both adults and juveniles of A. kimi. An AI model was trained using a training dataset and evaluated using a validation dataset. Both training and validation datasets used for AI model were created by picturing plate images that included adults and larvae. Statistical comparison of validation dataset showed no significant difference between manual and automatic counts. Additionally, the model achieved high accuracies (Precision=1.0, Recall=0.95 for adults; Precision=0.95, Recall=0.83 for juveniles). This indicates that the model can successfully detect objects. Additionally, the system can automatically measure body areas of individuals, enabling more detailed assessments related to growth and development. Therefore, this study establishes that AI-based counting methods in toxicity assessments with offer high levels of accuracy and efficiency can effectively replace traditional manual counting methods. This method significantly enhances the efficiency of large-scale toxicity evaluations while reducing researcher workload.

Ecosystems provide various ecosystem services based on biodiversity. However, biodiversity is facing crises due to anthropogenic factors such as pollution, land use change, and climate change. Threats to biodiversity can significantly impact the provision and stability of ecosystem services, extending beyond simple species decline. To address threats to biodiversity, it is crucial to evaluate how anthropogenic factors affect not only biodiversity but also ecosystem services. This study aims to investigate the energy flux in a post-mining area based on the biodiversity of soil ecosystems and assess its suitability as an evaluation metric. It was observed that as the concentration of the primary pollutant, arsenic, increased, both the biomass of soil organisms and energy flux decreased. Furthermore, soil ecosystem multifunctionality may be negatively affected by pollution. These findings contribute to understanding the impact of pollution on soil ecosystem biodiversity and energy flux in post-mining areas and provide important information for more effective conservation and management of ecosystem services.