Supplementary data from: Monitoring insect biodiversity and comparison of sampling strategies using metabarcoding: a case study in the Yanshan Mountains, China

Insects are the richest and most diverse group of animals and yet there remains a lack, not only of systematic research into their distribution across some key regions of the planet, but of standardized sampling strategies for their study. The Yanshan Mountains, being the boundary range between the Inner Mongolian Plateau and the North China Plain, present an indispensable piece of the insect biodiversity puzzle: both requiring systematic study and offering opportunities for the development of standardized methodologies. This is the first use of DNA metabarcoding to survey the insect biodiversity of the Yanshan Mountains. The study focuses on differences of community composition among samples collected via different methods and from different habitat types. In total, 74 bulk samples were collected from five habitat types (scrubland, woodland, wetland, farmland, and grassland) using three collection methods (sweep netting, Malaise traps, and light traps). After DNA extraction, PCR amplif..., , , , # Supplementary data from: Monitoring insect biodiversity and comparison of sampling strategies using metabarcoding: a case study in the Yanshan Mountains, China

Dataset DOI: 10.5061/dryad.x3ffbg7p7

## Description of the data and file structure

A total of 74 bulk samples were collected from five habitat types (scrubland, woodland, wetland, farmland, and grassland) using three collection methods (sweep netting, Malaise traps, and light traps) from the Yanshan Mountains, China. After DNA extraction, PCR amplification, sequencing, and diversity analysis were performed. Nonmetric multidimensional scaling (NMDS) analysis based on Bray–Curtis distances revealed highly divergent estimates of insect community composition among samples differentiated by the collection method, but nonsignificant difference among samples differentiated according to habitat.

### Files and variables

#### Table_S1__The_details_of_the_sampling_localities.xlsx

**Description**: S: sweep netting group, MT: Malaise ...,