Evidence map›Paper›PMID 39114129›Full record

ArticleBiodiversity data journal2024

Synchronised monitoring of plant and insect diversity: a case study using automated Malaise traps and DNA-based methods.

Leighton J Thomas, Ameli Kirse, Hanna Raus, Kathrin Langen, Björn Nümann, Georg F Tschan, Birgit Gemeinholzer, J Wolfgang Wägele, Sarah J Bourlat

Abstract read
In one paragraph

Article in Biodiversity data journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Leighton J ThomasLeibniz Institute for the Analysis of Biodiversity Change, Museum Koenig, Bonn, Germany Leibniz Institute for the Analysis of Biodiversity Change, Museum Koenig Bonn Germany.
Ameli KirseLeibniz Institute for the Analysis of Biodiversity Change, Museum Koenig, Bonn, Germany Leibniz Institute for the Analysis of Biodiversity Change, Museum Koenig Bonn Germany.
Hanna RausUniversity of Kassel, Kassel, Germany University of Kassel Kassel Germany.
Kathrin LangenLeibniz Institute for the Analysis of Biodiversity Change, Museum Koenig, Bonn, Germany Leibniz Institute for the Analysis of Biodiversity Change, Museum Koenig Bonn Germany.
Björn NümannLeibniz Institute for the Analysis of Biodiversity Change, Museum Koenig, Bonn, Germany Leibniz Institute for the Analysis of Biodiversity Change, Museum Koenig Bonn Germany.
Georg F TschanLeibniz Institute for the Analysis of Biodiversity Change, Museum Koenig, Bonn, Germany Leibniz Institute for the Analysis of Biodiversity Change, Museum Koenig Bonn Germany.
Birgit GemeinholzerUniversity of Kassel, Kassel, Germany University of Kassel Kassel Germany.ORCID https://orcid.org/0000-0002-9145-9284
J Wolfgang WägeleLeibniz Institute for the Analysis of Biodiversity Change, Museum Koenig, Bonn, Germany Leibniz Institute for the Analysis of Biodiversity Change, Museum Koenig Bonn Germany.
Sarah J BourlatLeibniz Institute for the Analysis of Biodiversity Change, Museum Koenig, Bonn, Germany Leibniz Institute for the Analysis of Biodiversity Change, Museum Koenig Bonn Germany.ORCID https://orcid.org/0000-0003-0218-0298

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

automated SamplingbiomonitoringMalaise trapmetabarcodingphenologyplant-insect interactionplant traces

Identifiers

PMID39114129
PMCPMC11303846

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.