Biodiv Sci ›› 2026, Vol. 34 ›› Issue (4): 25409.  DOI: 10.17520/biods.2025409  cstr: 32101.14.biods.2025409

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Dataset of arthropod specimen images and DNA barcodes in forest ecosystem of the Xinglong Mountains of Gansu Province

Dexi Zhang1,2, Qian Zhou1,2, Xuezhu Pei1,2, Hongyong Zhang3, Yingtai Pei3, Shan Sun1,2, Mingxin Liu1,2*, Lixun Zhang1,2, Changming Zhao1,2   

  1. 1 State Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, College of Ecology, Lanzhou University, Lanzhou 730000, China 

    2 Yuzhong Mountain Ecosystem Observation and Research Station, Lanzhou University, Lanzhou 730000, China 

    3 Management Centre of Xinglong Mountains National Nature Reserve of Gansu, Yuzhong, Gansu 730117, China

  • Received:2025-10-13 Revised:2026-01-19 Accepted:2026-02-26 Online:2026-04-20
  • Contact: Mingxin Liu

Abstract: Arthropods play crucial ecological roles in forest ecosystems, including pollination, decomposition, and regulation of community structure. They are a key biological group supporting ecosystem stability and productivity. However, compared with plants and vertebrates, the systematic accumulation of arthropod diversity datasets remains limited, and baseline information at regional scales is particularly scarce. Here, we conducted a comprehensive survey in the typical forest ecosystems of the Xinglong Mountains National Nature Reserve during July–August of 2023 and 2024. Across 27 sampling plots, we collected 20,564 arthropod specimens using three complementary methods: beating sheet, Malaise trap, and pitfall trap. Based on DNA sequencing complemented with morphospecies sorting, a total of 1,060 arthropod species were identified, including 882 insect species in 14 orders, 146 families, and 551 genera, 164 species of arachnid species in 3 orders, 21 families, and 68 genera, and 14 species from other arthropod classes in 4 orders, 5 families, and 8 genera. This dataset systematically compiles a checklist of arthropod species, specimen images, and associated DNA barcodes, providing valuable support for rapid species identification, functional trait measurement, detection of cryptic species, biodiversity conservation, and ecological research.

Key words: passive collecting, DNA barcoding, species checklist, cryptic species, biodiversity