Background & Summary

Research methodologies based on functional trait measurements offer a robust framework for comparing the ecological differences among species across various scales and for describing their community structure characteristics1,2,3. These methodologies hold promising applications in unveiling the mechanisms of species coexistence within communities4,5. There is a strong correlation between environmental filtering and the functional traits of species; the loss of traits often reflects the local biological community’s response to environmental changes1,3. Therefore, studying the functional traits of organisms within a community can provide insights into the assembly patterns of the community6, aiding in the understanding of the correlation between the environment and the functional structure of biological communities3,7. This, in turn, offers novel insights into the mechanisms underlying community formation. By focusing on functional traits, researchers can not only elucidate the factors contributing to the formation of insect communities but also identify the driving forces behind the evolution of community structures8.

Over the past few decades, regional and global trait datasets for various biological taxa have been sequentially established, with traits becoming an increasingly utilized research element within the fields of ecology, biodiversity conservation, ecosystem restoration, and landscape management1,5,9,10. Despite global efforts to construct trait databases, the majority of existing databases are primarily focused on plants, birds, and amphibians, representing relatively small taxonomic groups11,12,13,14,15. In contrast, focusing on insect taxa presents a formidable challenge due to the vast number of species, making the collection of research-valuable trait data a daunting task. Additionally, much of the existing research on insect traits is based on characteristics derived from literature16,17,18,19,20, such as trophic-defined groups or binary long- and short-winged groups, which are discrete and lose critical information. This is suboptimal for analyzing the impact of abiotic environmental filters on the composition of functional communities1,21,22. Therefore, it is imperative to measure accurate and comprehensive morphological characteristics of insects and establish a morphological trait database.

The Heteroptera represents a vast group within the hemimetabolous insects, with over 45,000 species identified globally23. Characterized by their extensive distribution and morphological diversity, they serve as ideal subjects for ecological studies21,24,25,26,27,28,29. Gossner et al. established a database containing mean values of 23 morphometric measurements for 179 heteropteran species collected from German grasslands30. This database laid the foundation for the development of a trait database for the Heteroptera, instilling confidence in subsequent research efforts. To expand upon this existing database, we measured 34 morphological characteristics of 307 Heteroptera species collected from a biodiversity priority area in China. To ensure the standardization and availability of trait datasets, this study employed the same measurement techniques and trait classification methods utilized in the morphological trait database of Heteroptera from German grasslands30. Furthermore, the value of measuring diverse morphological traits for further analysis of functional responses has been demonstrated by individual studies on single taxonomic groups, such as the effect of mantis hind tibia width31 and lepidopteran wing area32,33 on flight performance. Therefore, acquiring additional trait information is necessary to detect the response of arthropod communities to environmental changes or the impact of trait variation on ecosystem function. Thus, our study incorporated additional measurements of features such as the tibia width and wing area, enhancing the dataset’s comprehensiveness.

Methods

Sites

This study conducted sampling within two areas, Xishuangbanna Prefecture and three counties of Honghe Prefecture, located in the “Xishuangbanna Priority Conservation Area (42,858 km2, including six national nature reserves)” in the southwest region of China. The sampling sites included five national nature reserves (Fig. 1a). The study areas have been subject to long-term human activity, resulting in a complex landscape structure interlaced with urban areas, forests, and farmlands34,35 (Fig. 1b).

Fig. 1
figure 1

Study sites. (a) Sampling sites; (b) Land-cover map of study sites at 30 m resolution; (c) Elevation.

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Xishuangbanna

Xishuangbanna Prefecture, located within Yunnan Province of China, encompasses an area of 19,124.5 km2, including two national nature reserves, with an elevation range from 477 meters to 2,429 meters (Fig. 1c). This region is characterized by a tropical monsoon climate.

Three cities in Honghe

Lüchun, Jinping, and Hekou are three counties located in the Honghe Prefecture of Yunnan Province, China, encompassing a total area of 8,105.86 km2, which includes three national nature reserves. Situated in a low-latitude subtropical plateau with a moist monsoon climate, their elevation ranges from 76.4 meters to 3,074 meters (Fig. 1c).

Experimental and sampling design

In this study, the research area was delineated into grid units of 10 kilometers each, with 1 to 2 sampling sites selected per working grid. At each sampling site, three transects of 100 meters in length were established. From July to October 2019, insect samples were collected using sweep netting and light trapping methods. Each study area underwent two rounds of sampling. All specimens collected were preserved in 75% ethanol solution and transported back to the laboratory for identification.

Traits acquisition and classification

We employed a stereoscopic dissecting microscope equipped with a ToupCam digital camera (1/1.8” Sony Exmor CMOS sensor) and the ToupTek ToupView 3.7 software to take morphometric measures, the measurement precision is 0.01 mm. A total of 34 morphometric measurements were performed on each individual, with measurement locations and definitions following previous studies23,30,36. For details see Table 1 and Fig. 2.

Table 1 Overview of all variables in data set 1: “HeteropteraMorphometricTraits_1.csv”.
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Fig. 2
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Illustration of morphometric measurements taken on each specimen. The numbers correspond to morphometric measurement codes in Table 1.

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For all sampled species within the Heteroptera, species with a sufficient number of individuals were subject to the morphological measurement of at least five specimens to incorporate intraspecific variability into our measurement of species characteristics. The sampling effort aimed to include both female and male individuals, with the sex ratio dependent on the sampling conditions. Individuals of different sexes were selected from the study samples and mounted on a work board using entomological pins to ensure the insect’s body remained parallel to the microscope objective. We disassembled the insect’s forelegs, hindlegs, antennae, and forewings for precise measurement, ensuring that the parts being measured were parallel to the objective to guarantee the reliability of the measurements. For species with an adequate number of samples, individuals with partial damage were excluded from measurement. For species with fewer than five individuals, only measurements of the damaged parts were omitted.

We identified 17 morphometric traits representing five characteristic categories30, including body size (body length, volume37,38), dispersal capability (relative wing length, ratio of membranous to leathery wing area, front tibia shape, hind tibia shape31, relative length of the hind femur39), resource utilization in feeding (relative rostrum length40,41,42,43, shape of the front femur44), habitat utilization (body size, relative length of the scutellum), and orientation ability (relative antenna length, relative eye size45). In addition to traits with demonstrated functionality, we incorporated several predictive traits, species with a greater proportion of membranous wing area are expected to exhibit enhanced dispersal capabilities32,33; anticipating the shape of the front tibia and hind tibia are related to dispersal capabilities, with species possessing broader tibiae exhibiting stronger dispersal abilities31; and significant morphological variation in the scutellum across different species of Heteroptera, its relative length is predicted to be associated with habitat utilization46,47,48. For more details see Table 2.

Table 2 Overview of all variables in data set 2: “HeteropteraMorphometricTraits_2.csv”.
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The 17 morphological traits were calculated from the 34 morphometric measurements (see Table 1). The detailed calculation formulas can be found in the “Description” column of Table 2. All computations were conducted using Microsoft Excel software.

Data Records

This dataset is a species-level data set of 34 morphometric measures from 4346 specimens of 307 species of Heteroptera. For 299 species (about 97%), at least five individuals were measured for each species. The comprehensive dataset is constituted by three discrete files: two of which are formatted in ‘.csv’ (Unicode UTF-8), and one in PDF format. All files are accessible via figshare49. Rows denote unique species records, while columns correspond to the variables provided.

HeteropteraMorphometricTraits_1

This file encompasses morphometric measurements conducted on both male and female specimens across 307 species within the Heteroptera, comprising 34 distinct morphological measurements. The file presents the mean, minimum, and maximum values of these measurements for the collective specimens of each species, as well as for individual female and male specimens, with all dimensions denoted in millimeters. Additionally, the dataset includes information on the number of individuals measured, as well as taxonomic data at the order and family levels.

HeteropteraMorphometricTraits_2

The morphological traits in the file, designated as HeteropteraMorphometricTraits_2 were derived through calculations based on 34 morphometric measurements (see Table 1) taken from specimens of 307 species within the Heteroptera. For each species, average, minimum, and maximum values were computed for the total specimens measured, as well as separately for female and male individuals, with all measurements presented in millimeters. Additionally, the file encompasses information on the number of individuals, as well as their respective orders and families.

HeteropteraFigures

This study presents a total of 310 photos of all measured species for verification purposes and to ensure the future usability of the data.

Technical Validation

All data contained within this dataset were provided by the authors. Field methods followed a standardized protocol (Supplementary Tables S1 and S2). To ensure comparability, future data reuse and synthesis, both the primary measurement methods and classification schemes for the traits were consistent with those of Gossner et al.30. Species identification was cross-checked by different taxonomic experts and at random by barcoding. Although the measurement of morphological traits involves a minimal degree of subjective intervention, the measurement of all trait data was conducted by the same individual to minimize subjective bias.

This study examined whether data for each trait contained abnormal values or outliers. In most instances, these issues were addressed by inspecting images of the species with attached scales and the specimens themselves. All specimens are stored in the Institute of Highland Forest Science, Chinese Academy of Forestry.

Usage Notes

The information allocated on the Figshare repository is a static version of the data last reviewed on June 2024, further updates and refinements planned for release within the same Figshare project, but the DOI could be different. A report record will be also included to control further updates. Anticipated future expansions include the incorporation of ecological trait dataset and site-specific information. Traits can be univocally linked to each species included in the latter datasets (or others) using the species Latin name.