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Diversity and conservation of endemic true bugs for four family groups in China

Citation

Jiang, Kun et al. (2022), Diversity and conservation of endemic true bugs for four family groups in China, Dryad, Dataset, https://doi.org/10.5061/dryad.9cnp5hqmr

Abstract

Aim: Protected areas in China have typically been designed by considering one or several focal taxa (e.g., relict plant and vertebrate species), but the effectiveness of these “protective umbrellas” in safeguarding insects remains unclear. In this study, we aim to investigate the distribution and diversity of endemic true bugs for four family groups (i.e., Miridae, Lygaeoidea, Pentatomidae, and Reduviidae) in China, the environment factors shaping these diversity patterns, as well as the effectiveness of China’s protected areas (PAs) in safeguarding their diversity.

Location: China.

Methods: We mapped the spatial distributions of 1028 endemic true bugs in China using stacked species distribution models and pixel grids of observed points. Environment factors that influence diversity patterns across China were explored by generalized linear models and random forest models. The effectiveness of PAs in safeguarding species distribution was evaluated by the Zonation platform.

Results: We found that most (84.9%) diversity hotspots for total species located in mountainous areas of southern China. Additionally, the diversity pattern is shaped by the combined effects of different environment factors, with the minimum temperature of the coldest month, annual precipitation and elevation showing the strongest effects. On average, Chinese PAs covered 10.2% distribution areas of these endemic true bugs.

Main conclusions: In general, our research identifies the important roles of mountainous areas in southern China in maintaining the species diversity. Moreover, our research also suggests that PAs in China couldn’t provide sufficient protection for this diversity. Protecting these endemic true bugs diversity should be valued more in southern China's mountainous areas.

Funding

National Natural Science Foundation of China, Award: 31820103013

National Natural Science Foundation of China, Award: 32130014