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Synchronised monitoring of plant and insect diversity

AutorInnen: 
Thomas, L., Kirse, A., Raus, H., Langen, K., Nümann, B., Tschan, G. F., Gemeinholzer, B., Wägele, J. W., Bourlat, S. J.
Erscheinungsjahr: 
2024
Vollständiger Titel: 
Synchronised monitoring of plant and insect diversity: a case study using automated Malaise traps and DNA-based methods
Publiziert in: 
Biodiversity Data Journal
Publikationstyp: 
Zeitschriftenaufsatz
DOI Name: 
10.3897/BDJ.12.e127669
Keywords: 
Metabarcoding, plant traces, plant-insect interaction, automated Sampling, Malaise trap, biomonitoring, phenology
Bibliographische Angaben: 
Thomas, L., Kirse, A., Raus, H., Langen, K., Nümann, B., Tschan, G. F., Gemeinholzer, B., Wägele, J. W., Bourlat, S. J. (2024): Synchronised monitoring of plant and insect diversity: a case study using automated Malaise traps and DNA-based methods. - Biodiversity Data Journal 12: e127669.
Abstract: 

The occurrence and distribution of insects and their possible associations with plant species are largely unknown in Germany and baseline data to monitor future trends are urgently needed. Using newly-designed automated Malaise trap multi-samplers, the occurrence of insect species and their potential associations with plants was monitored synchronously at two contrasting field sites in Germany: an urban botanical garden and a forest research station. Taxa were identified by metabarcoding of the insects and the plant traces present in the preservative ethanol of the Malaise trap samples. For comparison, a botanical survey was conducted in the vicinity of the traps. Across both sites, we identified a total of 1290 exact sequence variants (ESVs) assigned to Insecta, of which 205 are known to be pollinators. In the botanical garden, we detected the occurrence of 128 plant taxa, of which 41 also had one of their known insect pollinator species detected. Insect species richness was highest in May, mainly attributed to an increase in Diptera. These results present a case study of the applicability of automated sampling and DNA-based methods to monitor the timings of flowering and corresponding activity of plant-visiting insects.

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