Evidence map›Paper›PMID 42582896›Full record

ArticleEcology and evolution2026

Assessing Biodiversity in Agricultural Landscapes Through Drone-Based Environmental DNA Sampling.

Camille Albouy, Louise Humbert, Kerstin Niedermeier, Marc Chautem, Fabian Fopp, Martina Luthi, Sarah Thurnheer, Virginie Marques, Steffen Kirchgeorg, Christian Geckeler and 3 more

Abstract read
In one paragraph

Article in Ecology and evolution, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Camille AlbouyEcosystems and Landscape Evolution, Department of Environmental Systems Science ETH Zürich Zürich Switzerland.ORCID https://orcid.org/0000-0003-1629-2389
Louise HumbertEcosystems and Landscape Evolution, Department of Environmental Systems Science ETH Zürich Zürich Switzerland.
Kerstin NiedermeierEcosystems and Landscape Evolution, Department of Environmental Systems Science ETH Zürich Zürich Switzerland.
Marc ChautemAxa Climate Paris France.
Fabian FoppEcosystems and Landscape Evolution, Department of Environmental Systems Science ETH Zürich Zürich Switzerland.
Martina LuthiEcosystems and Landscape Evolution, Department of Environmental Systems Science ETH Zürich Zürich Switzerland.
Sarah ThurnheerEcosystems and Landscape Evolution, Department of Environmental Systems Science ETH Zürich Zürich Switzerland.
Virginie MarquesEcosystems and Landscape Evolution, Department of Environmental Systems Science ETH Zürich Zürich Switzerland.
Steffen KirchgeorgSwiss Federal Institute for Forest Snow and Landscape Research WSL Birmensdorf Switzerland.
Christian GeckelerSwiss Federal Institute for Forest Snow and Landscape Research WSL Birmensdorf Switzerland.
Ali NasrallahAxa Climate Paris France.
Stefano MintchevSwiss Federal Institute for Forest Snow and Landscape Research WSL Birmensdorf Switzerland.
Loïc PellissierEcosystems and Landscape Evolution, Department of Environmental Systems Science ETH Zürich Zürich Switzerland.ORCID https://orcid.org/0000-0002-2289-8259

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As agricultural intensification expands globally, there is an increasing concern about the impact of food production on global biodiversity. Biodiversity decline is problematic as species provide a wealth of benefits, including pollination, soil fertility, and protection against pests, within agrosystems. Many countries, especially across Europe, have implemented incentives for farmers to introduce biodiversity-friendly land management practices, from building hedgerows to planting pollinator fields. Quantifying the impacts of these measures on biodiversity at the farm scale is technically challenging. Here, we developed a method involving the collection of environmental DNA (eDNA) samples with drones from crops, demonstrated in a case study on rapeseed fields under three management types: conventional, biological, and IP Suisse. We analyzed swabbed material through metabarcoding of a 16S amplicon to detect the composition of hexapod in the field. After cleaning and taxonomic assignment, we obtained a total of 75 taxa assigned to 19 families, 23 genera, and 33 species. We found that the variance in recovered diversity was significantly higher for replicates between fields than for replicates within a field, suggesting that eDNA swabbing replicates provided consistent local results. We did not detect significant differences between treatments, possibly because of a landscape effect which causes spillover of species from neighboring seminatural habitats. Our results provide a direction for developing a toolbox for biodiversity measurements in agricultural fields, highlighting the potential for expanding these methodologies to suit the needs of scientists, farmers, and other stakeholders in understanding and fostering farm-scale biodiversity.

Identifiers

PMID42582896
PMCPMC13458982

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Registered trials

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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.