Abstract:

Aims: Temporal dynamics of arthropod communities in agricultural ecosystems are fundamental for understanding trophic interactions, evaluating the potential contribution of natural enemies to pest suppression, and improving ecologically based integrated pest management strategies. In crop rotation systems, seasonal crop succession is often accompanied by changes in vegetation structure, resource availability, microhabitat conditions, and meteorological background, all of which may influence arthropod community composition and the relative dominance of different functional taxa. However, continuous multi-year monitoring data for arthropod communities in sorghum-wheat rotation fields remain limited. In this study, we used DNA metabarcoding to investigate arthropod community dynamics in a long-term fixed monitoring field under sorghum-wheat rotation in Suqian, Jiangsu Province, China, from 2019 to 2023. Specifically, we aimed to describe temporal variation in arthropod community composition and diversity across years, seasons, and crop stages, and to preliminarily explore the associations between major arthropod taxa and meteorological factors. 

Methods: Arthropods were collected using a Malaise trap from a fixed monitoring site located in a sorghum-wheat rotation field in Siyang County, Suqian, Jiangsu Province. Sorghum was cultivated from June to October, and winter wheat was cultivated from November to May of the following year. A total of 64 arthropod samples were collected during the five-year monitoring period. DNA was extracted from each sample, and the mitochondrial cytochrome c oxidase subunit I gene (COI) was amplified and sequenced for metabarcoding analysis. Operational taxonomic units (OTUs) were clustered at 97% sequence similarity and taxonomically annotated using the BOLD database. Because of limitations in public reference databases and potential uncertainties in species-level assignment, subsequent analyses focused mainly on order- and family-level taxonomic composition rather than species-level identification. Arthropod community composition was summarized by year, season, and crop stage. Alpha diversity was estimated using the Shannon index based on the OTU composition matrix. Beta diversity was evaluated using Bray-Curtis dissimilarity followed by principal coordinates analysis (PCoA), and group differences were tested using analysis of similarities (ANOSIM). Monthly meteorological variables, including precipitation, temperature-related indices, and sunshine duration, were matched with arthropod community data. Spearman rank correlation analysis was used to explore associations between environmental factors and the relative abundance of major arthropod taxa. In addition, mixed-effects models were used to evaluate the effects of crop type, season, year, and their interactions on community relative abundance patterns. 

Results: Diptera was the dominant arthropod order throughout the monitoring period, indicating its consistently high relative abundance in this field. At the family level, Syrphidae and Coccinellidae were identified as important natural enemy taxa, although their relative abundance varied among years and seasons. OTU-level alpha diversity did not differ significantly among years (P > 0.05), suggesting relatively stable interannual diversity at the monitored site. In contrast, alpha diversity differed significantly among seasons (P < 0.05), with a relatively higher Shannon index in summer. Alpha diversity was positively correlated with temperature-related variables (P < 0.01). Beta diversity analysis based on Bray-Curtis dissimilarity showed clear differences in community composition between the sorghum and wheat seasons, and ANOSIM confirmed that this difference was statistically significant (P < 0.001). Meteorological factors were associated with variation in the relative abundance of several major taxa. The relative abundance of Syrphidae was positively correlated with sunshine duration (P < 0.05), but negatively correlated with precipitation and temperature-related variables (P < 0.01). The relative abundance of Coccinellidae showed more evident seasonal fluctuations. The mixed-effects model showed that, after including year as a random effect, the single main effects of crop type and season were not significant. However, different crop - season combinations exhibited divergent temporal trends from 2019 to 2023, suggesting that arthropod community dynamics at this site may be jointly influenced by crop succession, seasonal transitions, and interannual environmental fluctuations. 

Conclusion: This study provides a five-year time-series dataset describing arthropod community composition, OTU-level diversity, and the relative abundance dynamics of major natural enemy taxa in a sorghum-wheat rotation field in Suqian, Jiangsu Province. The results suggest that arthropod community structure and natural enemy taxa in this monitored field were associated with crop-season transitions and meteorological variation. However, this study was conducted at a single fixed monitoring site without spatial replication or control fields. In addition, relative abundance derived from DNA metabarcoding may be affected by primer bias, DNA extraction efficiency, biomass differences, mitochondrial copy number variation, and reference database completeness, and therefore should not be interpreted as equivalent to individual abundance obtained from traditional morphological surveys. Thus, the findings should be regarded as field-specific temporal patterns rather than general rules for all sorghum-wheat rotation systems. Future studies should incorporate replicated monitoring across multiple sites, morphological validation, pest population data, functional group classification, and finer-resolution environmental measurements to further clarify the mechanisms shaping arthropod communities in crop rotation farmlands.

Key words: DNA metabarcoding, sorghum-wheat rotation, arthropod community, long-term monitoring, natural enemies, meteorological factors