DOI: 10.5061/dryad.nzs7h44pf
title: Data from: Evaluating the link between predation and pest control services in the mite world

description: 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.
description: 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).
description: 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.