Skip to main content
Dryad logo

Data from: Evaluating the link between predation and pest control services in the mite world

Citation

Roy, Lise; Taudière, Adrien; Bonato, Olivier (2021), Data from: Evaluating the link between predation and pest control services in the mite world, Dryad, Dataset, https://doi.org/10.5061/dryad.nzs7h44pf

Abstract

Pest regulation by natural enemies has a strong potential to reduce the use of synthetic pesticides in agroecosystems. However, the effective role of predation as an ecosystem service remains largely speculative, especially with minute organisms such as mites.

Predatory mites are natural enemies for ectoparasites in livestock farms. We tested for an ecosystem-level control of the poultry pest Dermanyssus gallinae by other mites naturally present in manure in poultry farms, and investigated differences among farming practices (conventional, free-range and organic).

We used a multiscale approach involving (i) in-vitro behavioural predation experiments, (ii) arthropod inventories in henhouses with airborne DNA, (iii) a statistical model of covariations in mite abundances comparing farming practices.

Behavioural experiments revealed that three mites are prone to feed on D. gallinae. Accordingly, we observed covariations between the pest and these three taxa only, in airborne DNA at the henhouse level, and in mites sampled from manure. In most situations, covariations in abundances were high in magnitude and their sign was positive.

Predation on a pest happens naturally in livestock farms due to predatory mites. However, the complex dynamics of mite trophic network prevents the emergence of a consistent assemblage-level signal of predation. Based on these results, we suggest perspectives for mite-based pest control and warn against any possible disruption of ignored services through the application of veterinary drugs or pesticides.

Methods

The study was focused on the acarofauna of poultry manure. It was conducted in 20 barn henhouses distributed among 3 types of management practices (6 conventional, 8 free-range and 6 organic) and located half in eastern France down to Jura mounts (Ain region) and half in the South of the Rhône valley (Drôme region). We conducted four successive sampling campaigns in 2016 at 3-month intervals: March (13–22nd), June (9–15th), September (19–22nd) and December (12-15th). Henhouses not operating at the time of a given campaign (empty period for sanitation once a year) were excluded from this campaign and one henhouse was not sampled in September due to sanitary impediments. The start dates of the flocks (introduction of a new group of producing hens into a henhouse after a sanitary empty period) varied amongst farms; thus, the age of the flock varied between the farms at each sampling campaign (hereafter “flock age”). In addition, airborne DNA particles were sampled from 10 and 13 randomly selected points at once in two of the present henhouses (F4 and F7 resp.) to build accumulation curves and thus state how data from two points are representative of the whole henhouse communities.

During each sampling campaign and in each henhouse, we sampled airborne particles from two randomly selected points from ca. 30 cm above the slatted floor using a Coriolis® µ air sampler (Bertin Instruments, Montigny-le-Bretonneux, France). Airborne particles were collected into a PBS + 0.01% Tween32 medium at a rate of 0.1 m3 per min for 10 minutes. A 100-110 bp long DNA fragment of the variable region V7 in the gene coding the 18S rRNA from all Eukaryotes was amplified by PCR using the following primer pair: forward: 5′-TTTGTCTGSTTAATTSCG-3′ and reverse 5′-CACAGACCTGTTATTGC-3′ (Guardiola et al., 2015). The PCR products were sequenced via Illumina MiSeq by Spygen (Le Bourget-du-Lac, France). The obtained sequences were analyzed using the bioinformatics pipeline described in Supplementary material S2. In short, sequences were quality-filtered using Sickle (https://github.com/najoshi/sickle) and clustered into operational taxonomic units (OTUs) using vsearch (Rognes et al., 2016). Finally, each OTU was taxonomically classified using RDP-classifier (Wang et al., 2007).

Usage Notes

We provide a file presenting the entire pipeline developed for the analysis of data obtained by ILLUMINA sequencing (carried out by Spygen, Le Bourget du Lac) on our samples (Pipeline_air_DNA_analysis.pdf). In this file the different steps of the analysis are detailed, with information on the files generated during the analysis. We associate some of these files, so as to allow access to the main part of the data, from the filtered and de-replicated sequences file to the OTUs files associated with the classical taxonomic assignments and the assignments to the morphoespecies considered in the study.

Funding

European Agricultural Fund for Rural Development, Award: RRHA 160116CR0820011

French region Rhône-Alpes-Auvergne

French region Rhône-Alpes-Auvergne