DOI: 10.5061/dryad.95x69p8hq
title: The shape of the predator biomass distribution affects biological pest control services in agricultural landscapes

description: 1. Understanding how community composition of service-providing organisms
 affects ecosystem functioning is a key challenge in ecology. Although it
 has been proposed that taxonomic diversity and functional traits mediate
 this relationship, how several facets of community structure affect the
 delivery of key ecosystem services remains to be explored. 2. In this
 study, we investigated how abundance, taxonomic richness as well as the
 shape of biomass distribution in predator communities affect biological
 pest control services in vineyard landscapes. Our analyses were based on a
 dataset combining samples of arthropod predators, measures of predation
 rates of grape pests and characterization of environmental covariables for
 42 fields located in South-Western France. 3. We found that beside the
 abundance or the taxonomic richness of predators, the shape of biomass
 distribution (mean, variance, skewness and kurtosis of the distribution)
 influences the level of biological control. Predator communities largely
 dominated by low biomass species provided the bulk of biological control
 services. Lower levels of predation resulted from increased proportions of
 large biomass species and more evenly distributed biomass values in the
 communities. 4. Our results indicate that the top-down control provided by
 low biomass species decreases as the relative proportion of large biomass
 species increases in the predator community. This suggests that biological
 control may be affected by negative interactions (e.g., intraguild
 predation, behavioural interactions) between predators arising from the
 recruitment of large individuals in the community. 5. Our study revealed
 that the shape of biomass distribution is a major aspect of functional
 diversity in predator communities providing insights into the mechanisms
 that link biodiversity and ecosystem services. While our study focuses on
 biomass, considering other traits involved in trophic interactions may
 increase our ability to predict the level of biological control in
 ecosystems.
description: (a) Experimental design Our study sites were
 located in a vineyard-dominated region in south-western France
 (44°81’0°14′W). Our study design consisted of 21 pairs of organic and
 conventional vineyards (42 fields). The pairs were selected along two
 uncorrelated landscape gradients: a gradient of proportion of organic
 farming (ranging from 2% to 25%) and a gradient of proportion of
 semi-natural habitats (ranging from 1% to 75%) in a 1-km radius around the
 centre of the field. Such an experimental design allows to disentangle the
 relative effects of local farming systems from the proportion of
 semi-natural habitats and farming systems at the landscape scale.
 Landscape variables were calculated using ArcGIS 10.1 (ESRI).
 (b) Predator community sampling Predator
 communities of the vineyard foliage were sampled three times in 2015
 (between June and September) (N = 124: 3 × 42 vineyards and 2 plots with
 missing values). At each sampling date, predators were sampled by beating
 30 vine stocks in each vineyard (Muneret et al., 2019a). All predators
 were stored in 70% ethanol and individuals were identified at the lowest
 possible taxonomic resolution. Araneidae and Opiliones were identified at
 the species level while Dermaptera and Neuroptera were identified at the
 family level. (c) Community metrics Several metrics were calculated
 to characterize each predator community at each date: the overall
 abundance of individuals, the taxonomic richness as well as the four
 moments of the biomass distribution. Biomass distribution of the community
 was obtained by multiplying the number of individuals of each taxonomic
 unit by its average dry biomass (hereafter biomass distribution refers to
 the weighted biomass distribution). To calculate average values of dry
 biomass for each taxonomic unit, stage (adult or juvenile for spiders) and
 sex (for adult spiders and harvestmen), we randomly selected 10
 individuals among all the individuals sampled (all sampling dates
 combined) and measured their dry biomass. For spiders with a dry body mass
 lower than 0.01 mg, we estimated the dry body mass using length–mass
 regression of the form: body mass = exp (a + b *log(length of
 cephalothorax)) (Barnes et al., 2016, see supplementary materials Fig.
 S1). When the abundance of each taxonomic unit, stage and sex was lower
 than 10 individuals, we measured all the specimens available to calculate
 the average biomass values. For each vineyard and sampling date, the mean,
 variance, skewness and kurtosis of each biomass distribution, were
 calculated following the formula in Gross et al. (2017). All the four
 moments were calculated on log-transformed data for each field at each
 sampling date. (d) Biological pest control
 service We used a sentinel approach to measure levels
 of biological pest control at three dates in 2015 concomitantly with the
 predator sampling (Birkhofer et al., 2017). Sentinel cards consisted of 10
 eggs of the grape berry moth, <i>L. botrana</i>, which is the
 most damaging insect pest in the studied region. Eggs of <i>L.
 botrana </i>laid on parchment paper (1 × 3 cm card previously glued
 on felt) by laboratory-reared females were cut and glued on plastic cards
 (1 × 8 cm). Each card was attached to a vine shoot on one vine stock. In
 each field, 10 sentinel cards were exposed to predation for 4- or 5-days,
 depending of the sampling date. All the cards were settled at least 10 m
 away from the edge or from any other card. At the end of the 5-day
 exposure, the cards were collected (N=1207) and the number of remaining
 eggs per card was assessed using a microscope (Muneret et al., 2019b). We
 then estimated predation rates for each card as the ratio of the number of
 eggs predated to the total number of eggs initially exposed. In very few
 cases, eggs were damaged due to climatic conditions and the ratio was
 therefore calculated on the number of eggs initially exposed minus the
 number of damaged eggs. This variable was used as a proxy for biological
 pest control services.