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DNA-based seed intake quantification for enhanced ecological risk assessment of small mammals

ORCID
0000-0001-6049-6325
Zugehörigkeit
Leiden University, Environmental Biology, Institute of Environmental Sciences, the Netherlands
Groen, Kevin;
GND
122411307
Zugehörigkeit
Julius Kühn-Institute (JKI), Institute for Epidemiology and Pathogen Diagnostics, Germany
Jacob, Jens;
ORCID
0000-0001-6765-2626
Zugehörigkeit
Leiden University, Environmental Biology, Institute of Environmental Sciences, the Netherlands
Hein, Susanne;
Zugehörigkeit
Leiden University, Environmental Biology, Institute of Environmental Sciences, the Netherlands
Didaskalou, Emilie A.;
Zugehörigkeit
Leiden University, Environmental Biology, Institute of Environmental Sciences, the Netherlands
van Bodegom, Peter M.;
Zugehörigkeit
Bayer AG, Crop Science Division, Terrestrial Vertebrates, Germany
Hahne, Joerg;
Zugehörigkeit
Leiden University, Environmental Biology, Institute of Environmental Sciences, the Netherlands
Trimbos, Krijn B.

To prevent the non-acceptable effects of agrochemicals on arable fields, Environmental Risk Assessment (ERA) aims to assess and protect against a wide range of risks due to stressors to non-target species. While exposure to stress is a key factor in ERA models, exposure values are difficult to obtain and rely on laboratory studies with often debatable relevance to field situations. To improve intake estimates, data from realistic field-based scenarios are needed. We developed calibration curves relating known seed numbers of up to 20 onion and carrot seeds consumed by wild-caught wood mice (Apodemus sylvaticus) to the seed DNA content in the feces. Based on these inferred quantitative relationships, a field trial was run to determine seed intake in a natural setting using realistic levels of seed spillage. Onion DNA was detected in the fecal samples of the wood mice caught in the field, which resembled a seed intake of up to 1 onion seed. No intake of carrot seeds was detected. This is the first-ever study to quantify seed intake in a realistic field scenario using a DNA-based analysis, showing that accurate seed intake estimates can be obtained. Our approach can help to improve risk assessment models through its minimally-invasive and accurate assessment of seed intake by ERA representative and non-target species, which would otherwise be undetectable with traditional methods. Our novel approach and its results are highly relevant to studies of food intake and diet composition for basic and applied research alike.

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