Human–wildlife conflicts are becoming increasingly common worldwide and are a challenge to biodiversity management. Compared with compensatory management, which often focuses on solving emergency conflicts, mitigation management allows decision-makers to better understand where the damage is distributed, how the species are distributed and when the species conduct their activity. Here, we integrated data collected from 90 districts/counties’ damage surveys and 1271 camera traps to understand the damage status, abundance, density and activity rhythms of wild boar (Sus scrofa) in Zhejiang, Eastern China, from January 2019 to August 2023. We found that (1) wild boar–human conflicts were mainly distributed in the northwest and southwest mountainous regions of Zhejiang Province; (2) the total abundance of wild boar was 115,156 ± 24,072 individuals, indicating a growing trend over the past decade and a higher density in the western and southern regions; (3) wild boar exhibited different activity patterns across different damage regions, and the periods around 7:00, 11:00 and 16:00 represented activity peaks for wild boar in seriously damaged regions. The damage distribution, density, distribution and activity rhythms provide specific priority regions and activity intensity peaks for conflict mitigation. We believe that these findings based on the damage, distribution and activity could provide a scientific basis for mitigation management at the county level and enrich the framework of human–wildlife conflict mitigation.

As apex predators, wolves (Canis lupus) play a vital role in balancing and stabilizing ecosystems. However, the scarcity of empirical data on the population size and spatial ecology of wolves in Qinghai Province, China, poses significant challenges to the design of targeted conservation measures, with cascading effects on both regional ecosystem integrity and the long-term viability of this ecologically critical species. To address this knowledge gap, we deployed a systematic grid of 150 camera traps across Dulan County, Qinghai Province, from July 2021 to July 2022. The survey effort totaled 41,610 camera-days, yielding 392 independent wolf detections, defined as events separated by ≥24 h at the same location. The random encounter model estimated wolf density across three habitat types in Dulan County as follows: alpine meadows (4.87 ± 0.87 individuals/100 km²), bare rock areas (21.39 ± 3.79 individuals/100 km²), and alpine shrub (7.81 ± 1.31 individuals/100 km²). Wolves exhibited significant habitat selection (χ² = 23.6, p < 0.001), with 78% of detections occurring in alpine meadows and bare rocks at elevations of 4200–4300 m. The total wolf population was estimated to range from 2137 to 9169 individuals. Kernel density estimation (KDE) revealed a diurnal activity rhythm in wolves with minimal seasonal variation (Δ₄ = 0.88). Peak activity intensity occurred between 8:00 and 15:00, and 17:00 and 21:00, during the cold season, and between 10:00 and 15:00, and 18:00–22:00, in the warm season. The study provides a scientific basis for more effective management and conservation, enhancing understanding of wolf populations in Qinghai and peripheral regions.