Carole Chateil

Emmanuelle Porcher
email: porcher@mnhn.fr

LANDSCAPE FEATURES ARE A BETTER CORRELATE OF WILD PLANT POLLINATION THAN AGRICULTURAL PRACTICES IN AN INTENSIVE CROPPING SYSTEM

Keywords: Lotus corniculatus L., fruit set, bumblebees, organic farming, semi-natural habitats Highlights

Organic farming is commonly associated with increased pollinator diversity and abundance, but the net effects on pollination rates are less documented. Besides, organic farms are often surrounded by more diverse landscapes than conventional farms, such that the contributions of landscape diversity vs. farming practices to pollination rates are often confounded with each other. Here, the roles of local vs. landscape scale variables on pollination rates of experimental plants are examined in agricultural landscapes. To this end, fruit set and seed production were measured in the obligate insect-pollinated Lotus corniculatus. Plants were located in pairs of neighbouring organic vs. conventional farms, which were characterized by

Introduction

The ongoing loss of biodiversity in agricultural landscapes (e.g. [START_REF] Robinson | Post-war changes in arable farming and biodiversity in Great Britain[END_REF] is believed to alter animal pollination, an ecosystem service essential for food production [START_REF] Deguines | Large-scale trade-off between agricultural intensification and crop pollination services[END_REF][START_REF] Klein | Importance of pollinators in changing landscapes for world crops[END_REF] and for the sexual reproduction of many wild plants [START_REF] Kearns | Endangered mutualisms: The conservation of plant-pollinator interactions[END_REF][START_REF] Ollerton | How many flowering plants are pollinated by animals?[END_REF]. Beyond the simple effect of reduced numbers of pollinators, the pollination crisis may also be related to declines in the functional diversity of pollination networks, which can lower reproductive success and community persistence [START_REF] Fontaine | Functional diversity of plantpollinator interaction webs enhances the persistence of plant communities[END_REF]. Pollinator declines have been reported numerous times (Potts et al., 2010 for reviews;[START_REF] Steffan-Dewenter | Pollinator diversity and crop pollination services are at risk[END_REF][START_REF] Winfree | A meta-analysis of bees' responses to anthropogenic disturbance[END_REF], particularly in intensive agricultural landscapes, and the expected parallel declines of insect-pollinated plants are already observed at large scales in Europe [START_REF] Biesmeijer | Parallel declines in pollinators and insect-pollinated plants in Britain and the Netherlands[END_REF]. Plants provide food and habitats for many animal species involved in biological control for example, so that pollinator-induced changes in plant communities and their diversity could also have cascading effects on other ecosystem services [START_REF] Scherber | Bottom-up effects of plant diversity on multitrophic interactions in a biodiversity experiment[END_REF].

The design of efficient conservation schemes to reverse the loss of pollinators and pollination services in agroecosystems requires a complete understanding of the mechanisms responsible for this downward trend. Positive effects of organic farming on pollinator species richness and abundance have been documented numerous times [START_REF] Clough | Alpha and beta diversity of arthropods and plants in organically and conventionally managed wheat fields[END_REF][START_REF] Holzschuh | How do landscape composition and configuration, organic farming and fallow strips affect the diversity of bees, wasps and their parasitoids?[END_REF][START_REF] Holzschuh | Agricultural landscapes with organic crops support higher pollinator diversity[END_REF][START_REF] Holzschuh | Diversity of flowervisiting bees in cereal fields: effects of farming system, landscape composition and regional context[END_REF][START_REF] Kennedy | A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems[END_REF][START_REF] Kremen | Crop pollination from native bees at risk from agricultural intensification[END_REF]Rundlöf et al., 2008aRundlöf et al., , 2008b;;[START_REF] Rundlöf | The effect of organic farming on butterfly diversity depends on landscape context[END_REF], which suggests that agricultural practices in conventional fields are partly responsible for pollinator loss. Pesticide-free practices, together with abundant and diverse floral resources, likely provide higher quality crop and non-crop habitats and food sources in organic vs. conventional farms. Organic farms could therefore sometimes sustain populations of wild pollinators without requiring semi-natural habitats, thanks to high-quality foraging and nesting sites [START_REF] Williams | Resource distributions among habitats determine solitary bee offspring production in a mosaic landscape[END_REF].

However, the effective impact of organic farming on pollinators and pollination is still open to discussion. First, the actual effects of organic farming often depend on the landscape context, with higher benefits in intensive landscapes [START_REF] Holzschuh | Diversity of flowervisiting bees in cereal fields: effects of farming system, landscape composition and regional context[END_REF][START_REF] Rundlöf | The effect of organic farming on butterfly diversity depends on landscape context[END_REF]. Second, organic farms often encompass a larger proportion of semi-natural habitats (e.g. grassland, field boundaries or hedgerows) than conventional farms [START_REF] Feber | A comparison of butterfly populations on organically and conventionally managed farmland[END_REF][START_REF] Fuller | Benefits of organic farming to biodiversity vary among taxa[END_REF][START_REF] Gibson | Plant diversity and land use under organic and conventional agriculture: a whole-farm approach[END_REF][START_REF] Norton | Consequences of organic and non-organic farming practices for field, farm and landscape complexity[END_REF]. Pollinator abundance and diversity are known to depend on the presence and proximity of semi-natural habitats (reviewed in [START_REF] Ricketts | Landscape effects on crop pollination services: are there general patterns?[END_REF], which provide both nesting sites and foraging resources, so that the observed positive effects of organic farming on pollinators could be mostly attributable to a landscape effect, which has considerable implications to design conservation schemes. Finally, most studies of the impact of agricultural practices have focused on pollinator diversity and abundance [START_REF] Andersson | Organic farming improves pollination success in strawberries[END_REF] but see e.g. Brittain et al., 2010b;[START_REF] Carvalheiro | Pollination services decline with distance from natural habitat even in biodiversity-rich areas[END_REF], whereas pollinator abundance and pollination efficiency are sometimes only weakly correlated [START_REF] Ricketts | Landscape effects on crop pollination services: are there general patterns?[END_REF]. There is thus a need to (1) further disentangle the relative effects of in-field agricultural practices (influencing the quality of the agricultural matrix as a foraging and nesting resource) vs. landscape features (isolation from semi-natural habitat) on pollination, and (2) measure actual pollination efficiency as a necessary complement to pollinator abundance.

Here, the pollination rate of potted birdsfoot trefoil plants (Lotus corniculatus L., Fabaceae), estimated in terms of fruit and seed set, was compared across contrasting landscapes using a paired design (eight pairs of organic/conventional farms) in an intensive agricultural region in France. The following questions were specifically addressed: (1) Is wild plant pollination higher in organic vs. conventional farms regardless of landscape features? If organic practices favour pollinator survival and reproduction in the agricultural matrix, a positive effect of organic farming is expected irrespective of the distance to or proportion of semi-natural habitats in the surroundings. (2) How do semi-natural habitats influence pollination rates in farms? An increase in pollination rates is expected closer to semi-natural habitats (if the latter act as sources of pollinators) or with larger proportions of semi-natural habitats (as providers of food resources), at least in conventional farms.

Material and methods

The pollination of experimental plants was monitored in eight pairs of crop farms in the intensive agricultural region surrounding Paris, France. Each pair consisted of one conventional and one organic farm located close to each other (supplementary Fig. 1, mean distance between paired farms 2915 m; range: 490-6000 m). A farm is defined as a collection of fields managed by the same person, hence under identical practices. Organic farms are rare in the study region, such that their fields are often interspersed with conventional fields. To avoid confounding effects of neighbouring agricultural practices (e.g. contamination by pesticides from an adjacent conventional field) eight organic farms consisting of clustered fields were sampled first. A conventional farm of similar size was then selected within five km of each organic farm (supplementary Fig. 1). The eight pairs of farms were located in contrasting landscapes, which were described a posteriori by the quantity and proximity of semi-natural habitats (see section 2.2).

All farms grew mainly cereals, the dominant crops in the study region, except one organic farm that also included a few grasslands and a small sheep herd. Organic farms grew a significantly larger number of crops than conventional farms (Supplementary Table 1; mean ± SD: 9 ± 2.4 in organic farms vs. 5.6 ± 1.1 in conventional farms, Student"s test, P = 0.005). Some of the supernumerary crops grown in organic farms are pollinator-attractive plants, so that one may expect higher pollinator visitation rates in organic farms. Note however that pollinator-attractive crops represented a small proportion of arable land in both farming system, and that conventional farms also grew pollinator-attractive crops (e.g. oilseed rape, Supplementary Table 1).

In each farm two experimental sites were selected in each of two habitats: set-asides and margins of cereal fields. One conventional farm (C6) contained no set-aside that year; all sites were thus located in margins of cereal fields. Set-asides contain numerous pollinatorattractive flowers in contrast to margins of cereal fields; the two habitats can be compared to evaluate the influence of local resource availability on pollination rates. Within a farm, experimental sites were chosen so that they were widely distributed over the farm area, yet never adjacent to a conventional field in organic farms (and vice versa) or to mass-flowering crops such as oilseed rape or buckwheat. No managed honeybee hive was present within the studied farms. The mean distance between two sites within a farm was 750 m (range: 175-2040 m).

Measurement of pollination efficiency

The self-compatible, strictly entomogamous [START_REF] Ollerton | Relationships between flowering phenology, plant size and reproductive success in Lotus corniculatus (Fabaceae)[END_REF] corniculatus is common in the study region (although it was not found in the direct vicinity of the experimental sites, see below) but was not cultivated as a crop in the study area.

All plants were first grown together in an insect-proof greenhouse from April to June 2009. A total of 256 pots, each containing three to five individuals of either variety (Leo, 128 pots; Baco; 128 pots) were used for this experiment. Just before flowering, potted plants were moved to experimental sites, with four individual pots per site (two pots of each variety to prevent potential self-incompatibility among individuals of the same variety). No native L. corniculatus plants were found in the close vicinity of the sites. After two weeks in the field, i.e. just before farmers started harvesting fields and mowing set-asides, plants were brought back to the insect-free greenhouse. Every inflorescence was labelled and the number of flowers counted. At pod maturity, fruits of each inflorescence were counted, harvested and opened to count seeds.

A substantial number of plants were lost in the field, due either to water deprivation or to the destruction of pots by farmers or wild boars: only 93 pots from 51 (instead of 64) sites were retrieved. This loss created two imbalances in the dataset: there were many more pots of the Baco than of the Leo variety (78 vs. 15) and data were available for one habitat only in two farms (C5 and C8, see Supplementary Fig. 1), in addition to farm C6. However, discarding the Leo variety or the farm pairs 5, 6 and 8 did not modify our main results.

Results presented here are therefore based on the full dataset.

During the experiment, positive and negative controls were grown outside and inside the greenhouse. The negative controls consisted of 12 pots of each variety kept in the insectfree greenhouse during the flowering period. Inflorescences were labelled and flowers counted (total: 694 flowers on 200 inflorescences). At the end of the experiment, no fruit was found on any of the marked branches. The positive controls consisted of three sites of four pots (two of each variety, as in the farms) located in a grassland nearby the greenhouse, surrounded by natural habitats. In the positive controls, the number of fruits and seeds per fruit was counted on each inflorescence. The between-variety difference in fruit and seed production was tested using generalized linear mixed-effects models (glmer, R package lme4), with the number of fruits or seeds as response variables and with a Poisson error and log-link function. The models included "Site", "Pot" (and "Inflorescence" for seed production) as random factors, and "Variety" as a fixed factor. Analyst extension. Within farm pairs, there was no significant difference in landscape features (distance to semi-natural habitat and proportion of semi-natural habitats) between organic and conventional farms (linear models with "Farming type" and "Habitat" as fixed factors, P > 0.2).

Landscape metrics

Statistical analyses

We first selected the most relevant landscape scale to study the relationship between pollination and proportion of semi-natural habitats around the sites following the approach of [START_REF] Holzschuh | Agricultural landscapes with organic crops support higher pollinator diversity[END_REF]. To this end, single-factor generalized linear mixed-effect models (glmer, R package lme4) were used to model two response variables: (1) fruit set, the proportion of flowers setting fruits on an inflorescence, with a binomial error and a logit-link function and (2) seed set, the number of seeds per fruit, with a Poisson error and log-link function. Both types of models contained "Pot", "Site" and "Farm pair" as nested random factors; an "Inflorescence" random factor was also included in the model for seed set. In this preliminary approach, the only fixed factor was "Proportion of semi-natural habitats". The four buffer radii (250, 500, 750 and 1000 m) were analysed separately. The scale maximizing the variance calculated from the fixed effect component was retained: 250 m for fruit set and 500 m for seed set.

The relationship between pollination and environmental variables was examined using the generalized linear mixed-effects models above, with the same random factors but more fixed factors. The models included the following main fixed effects: Farming system (organic vs. conventional), Local habitat (field margin vs. set-aside), Distance to the nearest seminatural habitat, and Proportion of semi-natural habitats. A number of fixed-effect covariates potentially influencing pollination or seed production were added: L. corniculatus variety (Baco vs. Leo), Number of flowers per pot at harvesting (as a measure of pollinator attraction of a site), and Number of L. corniculatus varieties per site (which was 1 when both pots of a variety were destroyed in a site). The latter variable was used as a conservative estimate of availability of compatible pollen. For fruit set, the model also included an interaction between flower number and variety number. Two-way interactions between farming system and landscape metrics, as well as between farming system and local habitat, were never significant and were omitted without affecting the outcomes of the models. For both models marginal and conditional R², the percentage of variance explained by fixed factors alone or by fixed and random factors, respectively, were calculated using the formulae of [START_REF] Nakagawa | A general and simple method for obtaining R 2 from generalized linear mixed-effects models[END_REF] for generalized linear mixed-effects models.

Results

The negative controls grown in an insect-proof greenhouse confirmed that seed production in L. corniculatus requires visitation by pollinators: none of the 694 flowers examined set fruit. In the positive controls with open pollination, the number of fruits per inflorescence and per pot differed between varieties (mean ± SD: 2.9 ± 1 fruits per inflorescence in Leo vs. 1.9 ± 1 in Baco; 20 ± 19 fruits per pot in Leo vs. 11 ± 8 in Baco), but the number of seeds per fruit was similar (8.3 ± 4 in Leo vs. 8.6 ± 4 in Baco).

Plants grown two weeks in field sites exhibited smaller fruit sets (0.7 ± 1 fruits per inflorescence; 3.4 ± 6 fruits per pot) than positive controls, with no difference between varieties (Table 1). Fruit set correlated with some local field site characteristics: it was significantly higher in set-asides than in field margins and in sites where both L. corniculatus varieties remained until the end of the experiment than in sites where the two pots of a given variety were destroyed (Table 1). Overall, fruit set was not related with the total number of L. corniculatus flowers per sites, but there was a significant interaction between number of flowers and number of varieties (Table 1): fruit set was positively related to the number of flowers in sites with a single variety, but was unrelated to flower number in sites with two varieties. There was no difference in fruit set between organic and conventional farming, regardless of local habitat type and surrounding landscape (no significant interactions between farming system and local habitat type or landscape variables). Finally, fruit set was partly predicted by landscape variables (Table 1): it decreased with increasing the proportion of semi-natural habitats surrounding the sites and with increasing isolation from semi-natural habitats (Fig. 1).

In the fields, the number of seeds per fruit was comparable to that of the positive controls (8.5 ± 6 seeds per fruit) and was explained by none of the local or landscape-scale fixed factors (Table 1). Most variation occurred at a very fine scale, i.e. among inflorescences within a pot (conditional R², R² GLMM(c) ≈ 67%, most of which is explained by variance among inflorescences, Table 1). Note that this fine scale variation also explained an appreciable fraction of variance in fruit set (large among-pots variance, Table 1).

Discussion

This study aimed to separate the relative effects of local farming practices (organic vs. conventional farming; field margin vs. set-aside habitat) and landscape (distance to and proportion of semi-natural habitat) on pollination provided to wild plants in agricultural areas.

The comparison of pairs of farms located in the same landscape showed a combination of local and landscape-scale effects, but no detectable effect of organic vs. conventional farming, on the fruit set of L. corniculatus. The number of seeds per fruit was unrelated to any environmental variable.

In our experiment, fruit and seed set were used as proxys for pollination efficiency.

Although no data on pollinator abundance and visitation rates were available (in contrast to Brittain et al., 2010b), part of variation in fruit set can be interpreted in terms of pollinator visitation rates. Bearing in mind that pollinator visitation is required for fertilization in L. corniculatus (no self-fertilization, as confirmed by the caged control plants setting no fruits, see also [START_REF] Ollerton | Relationships between flowering phenology, plant size and reproductive success in Lotus corniculatus (Fabaceae)[END_REF] and that no wild conspecifics were found in the study area, differences in fruit set should only be caused by one of the following: (1) differences in pollinator visitation rates; (2) differences in heterospecific pollen loads on pollinators, which, when large, may dilute small amounts of L. corniculatus pollen and impede pollen transfer [START_REF] Ashman | Toward a predictive understanding of the fitness costs of heterospecific pollen receipt and its importance in co-flowering communities[END_REF]; and (3) differences in the availability of compatible L. corniculatus pollen within sites. We observed the latter effect, i.e. a negative relationship between fruit set and compatible pollen availability, as estimated conservatively by the number of L. corniculatus varieties remaining in a site (Table 1). However, the number of varieties per site was unrelated to other environmental variables and should not be responsible for the relationship of the latter with fruit set. Below we therefore discuss how environmental variables influence pollinator visitation and, to a lesser extent, pollen loads across spatial scales.

Local and landscape scale effects on fruit set

Apart from the effect of the number of varieties per site, variation in fruit set was mostly explained by local variables related to availability of floral resources and by landscape variables; both effects can be interpreted in terms of pollinator attraction and abundance. At the local scale, fruit set was higher in the more flower-rich set-asides than in field margins and in sites with more L. corniculatus flowers (although the latter relationship was significant only in sites with a single L. corniculatus variety), regardless of farming system. In other words, sites with more floral resources (either L. corniculatus or other weed species) were more attractive to pollinators and received more visits, which is consistent with the wellknown positive effects of floral resource availability on pollinator visitation rate and behaviour [START_REF] Kunin | Population biology and rarity: on the complexity of densitydependence in insect-plant interactions[END_REF].

At the landscape scale, fruit set decreased with increasing the distance to semi-natural habitats, which again is a well-documented pattern (see [START_REF] Ricketts | Landscape effects on crop pollination services: are there general patterns?[END_REF] for a metaanalysis) that may be explained by higher visitation rates in the vicinity of semi-natural habitats. Pollinator abundance and richness are known to depend on the proximity of seminatural habitats, which provide nesting sites for many pollinator species [START_REF] Farwig | Isolation from forest reduces pollination, seed predation and insect scavenging in Swiss farmland[END_REF][START_REF] Ockinger | Semi-natural grasslands as population sources for pollinating insects in agricultural landscapes[END_REF], although the consequences on seed set are often weaker [START_REF] Farwig | Isolation from forest reduces pollination, seed predation and insect scavenging in Swiss farmland[END_REF][START_REF] Kohler | At what spatial scale do high-quality habitats enhance the diversity of forbs and pollinators in intensively farmed landscapes?[END_REF][START_REF] Steffan-Dewenter | Effects of habitat isolation on pollinator communities and seed set[END_REF], especially with flowering crop pollination [START_REF] Ricketts | Landscape effects on crop pollination services: are there general patterns?[END_REF].

More surprisingly, the proportion of semi-natural habitats and fruit set were negatively related, which contradicted the general expectation that semi-natural habitats, as a source of pollinators, would increase pollination service [START_REF] Kremen | The area requirements of an ecosystem service: crop pollination by native bee communities in California[END_REF]. This counterintuitive pattern was however already observed elsewhere (Brittain et al., 2010b;[START_REF] Winfree | Effect of human disturbance on bee communities in a forested ecosystem[END_REF] and could be attributable to several phenomena. The explanation put forward by [START_REF] Winfree | Effect of human disturbance on bee communities in a forested ecosystem[END_REF], that semi-natural habitats may be of lower quality than agricultural habitats in terms of pollinator nesting sites and food sources, can immediately be dismissed here. [START_REF] Winfree | Effect of human disturbance on bee communities in a forested ecosystem[END_REF] observed lower bee abundance in forest vs. agricultural or urban areas, which created a negative relationship between pollinator diversity or abundance and forest cover in the surrounding landscape. In the present study, pollination was generally higher next to seminatural habitats (Fig. 1), which consisted in a combination of forests and grassland; these habitats are therefore unlikely to be of lower quality than intensively managed farmland.

Alternatively, semi-natural habitats may offer abundant foraging resources to pollinators; they would therefore be more attractive than agricultural areas. Small patches of plants isolated in an otherwise hostile agricultural matrix should therefore receive few visits if abundant resources are available in the surrounding semi-natural habitats [START_REF] Dauber | Effects of patch size and density on flower visitation and seed set of wild plants: a pan-European approach[END_REF][START_REF] Wilcock | Pollination failure in plants: why it happens and when it matters[END_REF]. The attractive effects of semi-natural habitats should depend strongly on pollinator foraging distance [START_REF] Wilcock | Pollination failure in plants: why it happens and when it matters[END_REF]. Bumblebees, the main pollinators of L. corniculatus, are large insects with potentially long foraging distances, but they depend on the presence of nearby foraging resources (optimal foraging theory). Their foraging distance can thus become short (less than 300 m, the buffer radius in our study) if floral resources are available in the nest vicinity [START_REF] Wolf | Foraging distance in Bombus terrestris L. (Hymenoptera : Apidae)[END_REF], so that they may prefer foraging in nearby flower-rich semi-natural habitats than in the flower-poor agricultural matrix. In addition, the diversity of floral resources associated with more abundant seminatural habitats may increase pollen limitation via the deposition of heterospecific pollen [START_REF] Wilcock | Pollination failure in plants: why it happens and when it matters[END_REF].

Organic farming is not associated with increased fruit set

The absence of a relationship between fruit or seed production in L. corniculatus and farming system may appear at odds with numerous previous observations of higher pollinator richness and abundance, and sometimes seed or fruit production, in organic vs. conventional farms [START_REF] Andersson | Organic farming improves pollination success in strawberries[END_REF][START_REF] Bengtsson | The effects of organic agriculture on biodiversity and abundance: a meta-analysis[END_REF] for a meta-analysis; [START_REF] Holzschuh | Agricultural landscapes with organic crops support higher pollinator diversity[END_REF][START_REF] Kennedy | A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems[END_REF]. However, in these studies, organic farms sometimes differed in many respects from conventional farms, including field management (use of synthetic inputs), farm-scale diversity (number of crops, presence of non-crop vegetation) and landscape configuration or composition, all of which can influence pollinator abundance and behaviour.

Importantly, these studies showed that local and landscape factors can interact, such that for example the benefits of organic management should be highest in simplified landscapes (e.g. [START_REF] Bengtsson | The effects of organic agriculture on biodiversity and abundance: a meta-analysis[END_REF][START_REF] Kennedy | A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems[END_REF] or landscape effects should be highest as farms become increasingly simplified [START_REF] Kennedy | A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems[END_REF]). The former interaction was not observed in the present study (no significant interaction between landscape variables and farming type). However, this and other studies are consistent with a predominant role of landscape variables over farming system in simplified farms, characterized by low habitat or weed diversity: [START_REF] Kremen | Crop pollination from native bees at risk from agricultural intensification[END_REF] in Californian watermelon fields, [START_REF] Winfree | Wild bee pollinators provide the majority of crop visitation across land-use gradients in New Jersey and Pennsylvania, USA[END_REF] in four crops of North-Eastern USA, Brittain et al. (2010b) in Italian vine fields, or [START_REF] Carvalheiro | Pollination services decline with distance from natural habitat even in biodiversity-rich areas[END_REF] in South-African mango fields. In this study, farming was intensive and characterized by a low diversity of crop and non-crop habitats, even in organic farms.

Although the number of crops was higher in organic than in conventional farms, cereals were the dominant crop and pollinator-attractive crops represented small proportions of cropland in both farming types. Hedgerows, field margins, and permanent set-asides were rare and weeds were controlled in both farming systems, although with different methods (e.g. set-asides were frequently mown in organic farms). As a consequence, pollinator visits were generally rare in agricultural habitats, especially in margins of cereal field: fruit set, but not seed production per fruit, was lower than that of positive controls, and lower than that of similar L. corniculatus pots located in urban areas [START_REF] Pellissier | Pollination success of Lotus corniculatus (L.) in an urban context[END_REF].

This study therefore corroborates earlier results indicating that at a local scale, the beneficial effects of organic farming on pollinators are attributable to the diversity of habitat and food sources they provide, much more than to the absence of pesticides. For example, [START_REF] Holzschuh | Agricultural landscapes with organic crops support higher pollinator diversity[END_REF] showed that "species richness of flowering plants" or "flower cover" could be substituted for "farming system" in models explaining variation in pollinator abundance in fallow strips and detected no significant effect of insecticides. Similarly, [START_REF] Carvalheiro | Natural and within-farmland biodiversity enhances crop productivity[END_REF] demonstrated that the presence of weeds allowed pollinators to persist in sunflower fields, sometimes reversing the negative effects of distance to natural habitats. In the organic farms studied here, which were little diversified, exclusion of pesticides is therefore unlikely to benefit pollinators, because the latter do not use organic crops or non-crop elements much as habitats. Conversely, pesticide applications in conventional farms are likely to have limited, transient negative impacts on pollinators by affecting only a small fraction of foraging individuals (see Brittain et al., 2010a for an example of such transient decrease in pollinator visitation rates after pesticide application).

Regardless of pesticide effects, the patterns observed here are consistent with the prediction of [START_REF] Kennedy | A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems[END_REF] that transition to organic monocultures, with little on-farm habitat diversity, may be detrimental for pollinators.

Limitations and perspectives

Our study showing significant effect of landscape variables, but no effect of farming system, on pollination rates was restricted in space, time and pollination type. First, the dominant effect of landscape and semi-natural habitats on pollination rates may be of special significance for L. corniculatus, a specialist plant pollinated by a large generalist pollinator, because many other plant species may satisfy the foraging needs of bumblebees in seminatural habitats. Contrasting patterns could be observed for plants visited by different pollinator communities (e.g. generalist plants pollinated, among others, by specialist pollinators). For example, the effects of local practices may be stronger for smaller pollinators, which usually have smaller foraging distances [START_REF] Benjamin | Pollinator body size mediates the scale at which land use drives crop pollination services[END_REF]. Second, there was no significant effect of organic farming on pollination over a two-week period, which suggests identical pollinator visitation rates over this time frame. However, pollination rates may differ at other times (e.g. just after pesticide applications, Brittain et al. 2010a), which could result in a lower cumulative reproductive success of wild plants over the longer term. [START_REF] Gabriel | Insect pollinated plants benefit from organic farming[END_REF] showed for example a higher proportion of insectpollinated arable weeds in field edge and field centre of organic vs. conventional farms, suggesting such a long-term benefit of organic farming. This effect of organic farming could be mediated by the diversity of floral resources and habitats, but longer-term studies are nonetheless needed to assess plant reproductive success in both farming systems, with quantification of pollinator abundance, visitation rate and floral resources in cultivated as well as non-cultivated areas.

FIGURE CAPTIONS

  birdsfoot trefoil was used to quantify pollination by several Bombus species, which are abundant in the study area. The cultivated forage crop varieties Leo and Baco were chosen to minimize individual variation in morphological traits such as number of flowers per inflorescence. Wild L.

  We used digital land-use maps (Mode d"Occupation des Sols, Institute for Planning and Development of the Île-de-France Region 2003, http://www.iaurif.org) and ArcGIS 9.2 software (ESRI 2006, Redlands) to identify artificial (arable land, other non-grassland agricultural land, built area and open urban area) vs. semi-natural habitats (woodland, perennial grassland, water bodies and non-agricultural rural land). The distance to the nearest patch of semi-natural habitat (range: 1-698 m) and the proportion of semi-natural habitat in circular buffers around each study point (250 m, 500 m, 750 m and 1000 m radius, range: 0-56 % of semi-natural habitat) were calculated for each experimental site with the Patch

Figure 1 :

 1 Figure 1: Relationship between L. corniculatus fruit set and landscape variables. Fruit set is

Acknowledgements

We thank Richard Luis Ibanez and Fabien Verfaillie for help with L. corniculatus cultivation, and Léa Tarallo for field assistance. We also thank Ingrid Lair from the Groupement des Agriculteurs Biologiques d"Île-de-France, and all farmers for their involvement in the experiment. This work was partly supported by a grant from the Balzan Foundation.

Tables

 Table 1:Mixed-effects modelling of the effects of local and landscape variables on fruit and seed set of L. corniculatus. Stars indicate significance levels: * = 0.01 < P < 0.05; ** = 0.001 < P < 0.01; *** = P < 0.001. R² GLMM(m) and R² GLMM(c) are the marginal and conditional R-squared, i.e. the variance explained by fixed factors alone or by fixed and random factors, respectively in generalized linear mixed-effects models [START_REF] Nakagawa | A general and simple method for obtaining R 2 from generalized linear mixed-effects models[END_REF].

Fruit set

Seed set

.99 [-11.1;-4.86] 1.66 [1.08;2.25] Farming system (conventional) 0.20 [-0.70;1.11] 0.24 [-0.079;0.55] Local habitat type (set-aside) 1.35 ** [0.42;2.28] 0.23 [-0.07;0.52] Distance to semi-natural habitats -0.0039 * [-7.3 10 -2 ;-4.6 10 -4 ] 7.2 10 -4 [-1.7 10 -3 ;2.5 10 -4 ]

Proportion semi-natural habitats -6.25 ** [-9.9;-2.6] -0.84 [-2.0;0.31] Variety (Leo) -0.25 [-1.3;0.76] -0.11 [-0.49;0.27] Number of flowers 0.070 [0.023;0.12] 2.2 10 -3 [-2.7 10 -3 ;7.110 -3 ] Number of varieties 4.51 *** [2.6;6.4] 0.057 [-0.24;0.35] Nb. flowers × Nb. varieties -0.039


Florence Dubs
email: florence.dubs@gmail.com

Alan Vergnes

Emilie Mirlicourtois

Isabelle Le Viol

Christian Kerbiriou

Jérémie Goulnik

Soumaya Belghali

Laure Bentze

Sébastien Barot

Emmanuelle Porcher

Positive effects of wheat variety mixtures on aboveground arthropods are weak and variable

Keywords: cultivar mixtures, farmland biodiversity, ground beetles, plant-insect interactions, rove beetles, spiders, winter wheat

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ө These authors contributed equally to this work.

Highlights

Abstract

Although modern agriculture generally relies on homogeneous varieties that are usually grown in pure stands, crop variety mixtures have been used for a long time, notably to improve resistance to fungal diseases. A growing number of studies suggest that intraspecific plant diversity may also enhance the abundance and diversity of wild species and thereby some ecosystem services such as biological control by natural predators. However, positive effects of the genetic diversity of plant species on the diversity of associated communities have mostly been documented in natural systems, with only a handful of studies targeting crop species in agroecosystems. Here, we investigated the ecological effects of the number of winter wheat varieties (Triticum aestivum) on aboveground arthropods and particularly predatory species. We manipulated the number of wheat varieties (1, 2, 4 or 8) in 120 plots (80 m² each) to examine how wheat diversity and stand characteristics impact communities of three dominant aboveground arthropod groups that include many predatory species: ground beetles, rove beetles and spiders. The number of wheat varieties had a weak, but positive effect on predator abundance, notably spider abundance. In contrast, wheat functional diversity, as assessed by the number of wheat functional groups, was only negatively related to the diversity of spiders. Among wheat stand characteristics, the variance in plant height, wheat biomass and the Green Area Index were weakly correlated with ground beetle, rove beetle and predatory diversity, respectively. The Green Area Index was also weakly correlated with ground beetle abundance. Our study suggests that wheat variety mixtures have variable and limited effects on aboveground arthropods and probably low effectiveness to enhance biological control, but these results should be further tested under low-input agriculture in real fields.

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Introduction

Intensive agriculture is based on substantial use of synthetic inputs such as pesticides, combined with high-yield, genetically homogeneous varieties that are usually grown in pure stands, i.e. with a single variety per field [START_REF] Gaba | Multiple cropping systems as drivers for providing multiple ecosystem services: from concepts to design[END_REF]. Such cropping systems are still widely used because of their high productivity but are now often considered unsustainable, at least because of side effects of inputs (e.g. impacts of pesticides on non-targeted species) and the dependence on fossil fuels [START_REF] Shennan | Biotic interactions, ecological knowledge and agriculture[END_REF]. Moreover, there are hints that crop yields are now plateauing after several decades of steady increase (Lobell et al., 2011). Alternative agricultural practices are thus developing and many authors plead for the application of ecological and evolutionary knowledge to agriculture (Loeuille et al., 2013;[START_REF] Gaba | Ecology for sustainable and multifunctional agriculture[END_REF].

Of particular interest is the use of both interspecific and intraspecific crop diversity in the field (Mijatović et al., 2013). Because low species and genetic diversities often lead to a low resilience to environmental changes, questions arise about the opportunity to go on using genetically homogeneous monocultures in an era of rapid global change (Tilman et al., 2001).

Numerous ecological studies on communities of wild plants suggest that increasing plant species or genetic diversity tends to improve ecosystem functioning [START_REF] Hughes | Ecological consequences of genetic diversity[END_REF].

The most documented effect of plant species diversity and genetic diversity is an increase in primary production, total plant biomass [START_REF] Cook-Patton | A direct comparison of the consequences of plant genotypic and species diversity on communities and ecosystem function[END_REF][START_REF] Hajjar | The utility of crop genetic diversity in maintaining ecosystem services[END_REF] and in the stability of primary production through time (Nyfeler et al., 2009;Tilman & Downing, 1996). The positive relationship between plant diversity and productivity is caused by a combination of complementarity (i.e. decrease in competition among individual plants) and (Prieto et al., 2015) that can also stabilize production through differences between species or genotypes in their response to environmental conditions and perturbations (Loreau & Mazancourt, 2013). This benefit of within-field cultivated diversity explains the recent regain of interest for agricultural practices such as intercropping or variety mixtures [START_REF] Barot | Designing mixtures of varieties for multifunctional agriculture with the help of ecology. A review[END_REF][START_REF] Gaba | Multiple cropping systems as drivers for providing multiple ecosystem services: from concepts to design[END_REF], both of which potentially allowing the use of lower amounts of fertilizers.

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Crop diversity, particularly variety mixtures, can also lower the use of pesticides, via an increase in resistance to pathogens (Finckh et al., 2000) and perhaps in the abundance and diversity of predatory arthropod species present in the field (Ratnadass et al., 2012;[START_REF] Siemann | Experimental tests of the dependence of arthropod diversity on plant diversity[END_REF]. The role of natural predators as potential biological control agents in variety mixtures has been recognized only recently. Experimental approaches in biodiversityecosystem functioning (reviewed by [START_REF] Cook-Patton | A direct comparison of the consequences of plant genotypic and species diversity on communities and ecosystem function[END_REF] and community genetics [START_REF] Hersch-Green | Community genetics: what have we accomplished and where should we be going?[END_REF] have demonstrated that the positive effects of plant diversity on plant biomass can cascade through trophic levels and result in a larger biomass of herbivores and predatory species (Yee & Juliano, 2007). This effect can be caused by a general increase in resource availability for consumers and has been coined the "more individuals" hypothesis [START_REF] Srivastava | Why more productive sites have more species: an experimental test of theory using tree-hole communities[END_REF]. Alternatively, plant diversity may also lead to more diverse arthropod communities via an increase in the diversity of available resources (food or habitats, "more diversity" hypothesis, [START_REF] Southwood | The relationships of plant and insect diversities in succession[END_REF].

Although the relationship between plant genetic diversity and arthropod communities has been extensively explored in natural systems, few studies have examined the effect of crop diversity on communities of aboveground arthropods (but see [START_REF] Chateil | Crop genetic diversity benefits farmland biodiversity in cultivated fields[END_REF][START_REF] Crutsinger | Plant genotypic diversity predicts community structure and governs an ecosystem process[END_REF]. However, a number of aboveground arthropod groups found in cultivated fields include predatory species that may act as biological control agents. Among them, ground beetles, rove beetles and spiders represent an important part of the aboveground generalist Scheu, 2002) and their role as biological control agents has been recognized [START_REF] Andersen | Carabidae and Staphylinidae (Col.) as predators of eggs of the turnip root fly Delia floralis Fallén (Diptera, Anthomyiidae) in cage experiments[END_REF][START_REF] Bryan | The responses of polyphagous predators to prey spatial heterogeneity -aggregation by carabid and staphylinid beetles to their cereal aphid prey[END_REF][START_REF] Harwood | Living where the food is: web location by linyphiid spiders in relation to prey availability in winter wheat[END_REF][START_REF] Hatteland | Predation by beetles (Carabidae, Staphylinidae) on eggs and juveniles of the Iberian slug Arion lusitanicus in the laboratory[END_REF][START_REF] Kromp | Carabid beetles in sustainable agriculture: a review on pest control efficacy, cultivation impacts and enhancement[END_REF][START_REF] Lang | Intraguild interference and biocontrol effects of generalist predators in a winter wheat field[END_REF]Nyffeler & Sunderland, 2003;[START_REF] Symondson | Coleoptera (Carabidae, Staphylinidae, Lampyridae, Drilidae and Silphidae) as predators of terrestrial gastropods[END_REF]. By analogy with the well documented effects of vegetation on arthropods (reviewed by [START_REF] Langellotto | Responses of invertebrate natural enemies to complex-structured habitats: a meta-analytical synthesis[END_REF][START_REF] Tews | Animal species diversity driven by habitat heterogeneity/diversity: the importance of keystone structures[END_REF], we have the following expectation: (1) The abundance of ground-dwelling arthropods should increase with indices of wheat biomass or leaf area, which can be seen as a proxy for primary resources, with potential cascading effects along food chains, from herbivores to predators. Such effects would be consistent with the "more individuals" hypothesis [START_REF] Srivastava | Why more productive sites have more species: an experimental test of theory using tree-hole communities[END_REF]. ( 2) Variance in stem height should enhance the diversity of ground-dwelling arthropods due to its positive effects on microclimatic and habitat diversity as demonstrated for rove beetles [START_REF] Bohac | Staphylinid beetles as bioindicators[END_REF], ground beetles [START_REF] Langellotto | Responses of invertebrate natural enemies to complex-structured habitats: a meta-analytical synthesis[END_REF][START_REF] Brose | Bottom-up control of carabid beetle communities in early successional wetlands: mediated by vegetation structure or plant diversity?[END_REF] and cursorial spiders [START_REF] Tews | Animal species diversity driven by habitat heterogeneity/diversity: the importance of keystone structures[END_REF].

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Such effects would be consistent with the "more diversity" hypothesis.

Here, we used an experimental approach at the field scale to assess the effect of intraspecific crop diversity and stand characteristics on aboveground arthropod communities, with a focus on predatory species. We studied bread wheat (Triticum aestivum) as the dominant crop in northern France, and examined whether the identity and number of wheat varieties, hence the wheat stand characteristics, affected the diversity and abundance of predatory arthropods in the field.

Materials and methods

Site location, pedoclimatic conditions and experimental design

The field site was located at the French National Institute for Agricultural Research experimental station in Versailles, France (48°81' N, 2°09' E, Fig. 1A). The experimental station is surrounded by hedgerows and neighboured by woody patches on the northern side.

The field site is surrounded by grassy paths. Sixteen T. aestivum (winter wheat) varieties were used for the experiment. These varieties were chosen from an initial collection of 57 varieties representing different breeding histories (from local landraces to modern elite varieties) and a large diversity of above-and belowground morphological, phenological and physiological traits. The 57 varieties were classified into four "functional groups" on the basis of their traits using ascending hierarchical classification (see Appendix A for details). Four varieties were chosen within each functional group for the field experiment. In a 2.6 ha field, 120 plots were randomly chosen (Fig. 1B) to be seeded with 1, 2, 4, or 8 varieties, with respectively 48 (three replicates of each monoculture), 24, 28 and 20 replicates for each number of varieties. We also varied the number of functional groups for each number of varieties above 1: there were "homogeneous" (a single functional group) vs. heterogeneous (two or more functional groups) mixtures (see Appendix A for the list of all variety mixtures). Functional group mixtures were therefore replicated in the experimental site, while variety mixtures were not. In November, all plots were sown with 250 g of seeds per m 2 . Varieties in a mixture were seeded in equal densities.

All plots were of identical size (10.5 m x 8.0 m) except three monoculture plots that were halved in size (10.5 m x 4 m) due to limited seed availability. This size difference was, however, not a major issue because monocultures were replicated thrice, such that we could check that the small-size plots were not outliers. Each plot was buffered from adjacent plots or the field edge by a 1.75 m-wide row of triticale (x Triticosecale, Fig. 1C). The plots were managed conventionally, but with relatively low input levels. At the beginning of measurements, all plots had received one herbicide spray (Archipel® and Harmony Extra®) in mid-March and relatively low doses of a nitrogen fertilizer (ammonium-nitrate) applied in February (40 kgN.ha -1 ) and mid-April (80 kgN.ha -1 ).

Wheat stand characteristics

In each plot, several stand characteristics likely influencing the presence and abundance of

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arthropods were measured: wheat biomass, the Green Area Index (GAI) and the mean and variance of plant height in the mixture. The GAI, an index of vegetation cover, was measured in May 2015 using the gap fraction method (hemispherical photography, [START_REF] Baret | GAI estimates of row crops from downward looking digital photos taken perpendicular to rows at zenith angle: Theoretical considerations based on 3D architecture models and application to wheat crops[END_REF].

In June 2015, wheat biomass was harvested at the onset of flowering in sub-plots of 50 x 52.5 cm centred on three rows by uprooting whole plants. Roots were separated from shoots and samples were dried 72 hours at 65 °C and weighed. At the same time, the height of 10 wheat stalks was measured in the field to obtain the mean and coefficient of variation of plant height in each plot.

Sampling and identification of aboveground arthropods

Aboveground arthropods were sampled during the peak of activity of most western European species (Lövei & Sárospataki, 1990), May 5-18 2015. Exposure time of about 15 days is commonly used in the study of soil aboveground arthropods in agricultural environments [START_REF] Bohan | National-scale regulation of the weed seedbank by carabid predators[END_REF][START_REF] Chateil | Crop genetic diversity benefits farmland biodiversity in cultivated fields[END_REF][START_REF] Schmidt | Capture efficiency and preservation attributes of different fluids in pitfall traps[END_REF]Vergnes et al., 2013). One plastic pitfall trap (8 cm diameter, 500 cm 3 , half-filled with propylene glycol) was dug into the ground with its rim flush with the ground surface in the centre of each plot. Propylene glycol is a preservative solution that is neither attractive nor toxic to invertebrates (Thomas, 2008). A plastic roof (10 x 10 cm) was installed at approximately 2 cm above each pitfall trap to prevent rain and debris from entering the traps.

All spiders, adult ground beetles (Carabidae) and adult rove beetles (Staphylinidae) were identified to species level where possible, except for immature spiders, which were identified to morphospecies level and Aleocharinae individuals (45% of total rove beetles), which were identified to subfamily level only (hereafter Aleocharinae spp). Spiders were identified using the keys of Roberts ( 2001), ground beetles with the keys of Roger et al. (2013) and[START_REF] Hůrka | Carabidae of the Czech and Slovak Republics[END_REF] and rove beetles with the keys of Lot ( 2009) and [START_REF] Eyre | Strategic explanations of carabid species distributions in northern England[END_REF]. Contrary to spiders that are all predatory, ground beetles and rove beetles have various diets: predatory,

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phytophagous, detritivore or polyphagous [START_REF] Bohac | Staphylinid beetles as bioindicators[END_REF][START_REF] Larochelle | Food of carabid beetles[END_REF]. Predatory species were identified using various bibliographic sources (see Appendix B: Table S1 for details).

Data analysis

Aboveground arthropod communities in each plot were characterized by (1) the abundance (number of individuals) of each species observed, (2) the total number of species observed (species richness) and ( 3) the evenness of species abundances using Pielou's index (Shannon index /log(species richness)), (Vegan package, Oksanen et al., 2016). These three types of response variable were calculated for each taxonomic group of aboveground arthropods separately (ground beetles, rove beetles and spiders) and for the phylogenetically heterogeneous group of predatory species including all spiders and exclusively predatory ground and rove beetle species.

On each of these three response variables, we tested the impact of different types of variables characterizing crop diversity and composition, (1) the number of wheat varieties (a proxy for crop genetic diversity), (2) the number of wheat functional groups (a proxy for crop trait diversity) and (3) the stand characteristics GAI, shoot biomass, the mean and the coefficient of variation of plant height. For all models, the spatial coordinates (longitude and latitude) of plots were included to account for the possibility of spatial gradients in arthropod community characteristics due to border effects.

Analyses were conducted in three steps. First, the effects of the number of wheat varieties were tested (~ Longitude + Latitude + Number of wheat varieties). Second, the effects of the number of functional groups were tested in separate models (~ Longitude + Latitude + Number of functional groups) because of its correlation with the number of wheat varieties (Fig. 2). Finally, the effects of wheat stand characteristics were tested simultaneously in a single model (~ Longitude + Latitude + Wheat biomass + Mean plant height + Variance of plant height + GAI) but without including the number of varieties or the number of functional

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groups because of correlations between stand characteristics and numbers of varieties or functional groups (Fig. 2). In models analysing wheat mixture characteristics, forward model selection was applied using the AIC (Akaike Information Criterion) before testing the significance of effects and the goodness of fit.

Depending on the type of response variable, we used three types of statistical models. For species richness, we used generalized linear models (GLMs) with a Poisson error distribution [START_REF] Crawley | The R book[END_REF] and checked for overdispersion [START_REF] Cameron | Regression-based tests for overdispersion in the Poisson model[END_REF]. Because the number of species observed in a sample is known to increase with the number of individuals sampled [START_REF] Gotelli | Estimating species richness[END_REF], the total abundance was added as a fixed covariate in the model to partly disentangle species richness from total abundance. This partly allowed us to test the "more diversity" hypothesis, under which we expect more invertebrate species associated with more wheat varieties, all else being equal (in particular, with the same total abundance). We checked that there were no multicollinearity issues between explanatory variables (squared variance inflation factors (VIF) < 2, Zuur et al., 2010). To study the abundance of species, the abundances of all species were studied together in a single model We used only species observed in at least ten percent of samples in order to avoid issues related to different distributions among species and the ensuing zero inflation in GLMM, (Zuur et al. 2012), including species identity as a random effect to control for differences in abundance across species. To do so we used mixed models (GLMMs) with Poisson error or negative binomial error distribution [START_REF] Bolker | Generalized linear mixed models: a practical guide for ecology and evolution[END_REF] and checked for overdispersion with the overdisp_fun function (http://bbolker.github.io/mixedmodels-misc/glmmFAQ.html). In GLMMs, the best fit between Poisson, negative binomial, zero-inflated Poisson and zeroinflated negative binomial models was selected on the basis of the AIC. Finally, for the Pielou index, the rank-transformation [START_REF] Akritas | The rank-transformation method in some two-factor designs[END_REF] was applied to reach a normal distribution of residuals and then analysed with linear models (LMs). When the normality was still not The significance of effects was calculated using type II sums of squares for unbalanced designs [START_REF] Bolker | Generalized linear mixed models: a practical guide for ecology and evolution[END_REF]. The goodness of fit of each model was calculated as an adjusted R² for LMs, conditional R² (the total variance explained by random and fixed effects) and marginal R² (the variance explained by fixed effects alone) for GLMMs, and a pseudo R 2 for GLMs.

All data analyses were performed using the R software (version 3.4.1, R Development Core Team, 2017) and the car (for unbalanced design, Fox & Weisberg, 2011), lme4 and glmADMB (for GLMMs, [START_REF] Bates | Fitting linear mixed-effects models using lme4[END_REF][START_REF] Fournier | AD Model builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models[END_REF][START_REF] Skaug | Generalized linear mixed models using 'AD Model Builder[END_REF], MuMin (for forward model selection, [START_REF] Barton | MuMIn: Multi-Model Inference[END_REF], piecewiseSEM (to compute coefficient of determination for GLMMs, [START_REF] Lefcheck | piecewiseSEM: piecewise structural equation modelling in R for ecology, evolution, and systematics[END_REF] and AER (for GLM overdispersion test, [START_REF] Kleiber | Applied econometrics with R[END_REF] packages.

Results

Description of aboveground arthropod communities and wheat stands

Overall, 86 species were captured (1271 individuals from 25 species for ground beetles, 1436 individuals from 25 morphospecies of rove beetles and 542 individuals from 36 morphospecies for spiders), 67 of which were predatory. In each group, the most abundant species are commonly observed in European agroecosystems. The number of wheat varieties and the number of functional groups were highly correlated (Spearman correlation coefficient = 0.84). The number of wheat varieties was positively correlated with the mean and coefficient of variation of wheat height (0.23 and 0.72, respectively). The number of functional groups was also positively related to the mean and coefficient of variation of wheat height (0.22 and 0.73, respectively) but negatively correlated with wheat shoot biomass (-0.21). Wheat shoot biomass was negatively correlated with the coefficient of variation of the

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height of wheat stalks (-0.21) but positively correlated with the GAI (0.22). Finally, the mean and coefficient of variation of the height of wheat stalks were positively correlated (0.30) (Fig. 2).

Effect of wheat intraspecific diversity on the abundance and diversity of aboveground arthropod communities

Overall, wheat diversity had limited effect on aboveground arthropods, which differed across taxonomic groups and species within a group (see Appendix B: Tables S5-S8 for detailed values across wheat diversity treatments). The number of wheat varieties had a positive, but small effect on spider abundance (β = 0.052 ± 0.023, P = 0.027, marginal R² = 0.051, see Appendix B: Table S2). This effect was variable across species, with the most impacted species being Oedothorax apicatus, Tenuiphantes tenuis, Erigone atra, Oedothorax retusus and Pardosa prativaga (Fig. 3). These species are among the most abundant species and all belong to the Linyphiidae family with the exception of P. prativaga (Lycosidae) (Appendix B: Fig. S1C). Most likely as a result of the increased abundance of dominant species, the number of varieties had a negative effect on the evenness of spiders (i.e. Pielou index, β = -0.20 ± 0.10, P = 0.038, adjusted R² = 0.09, see Appendix B: Table S3A). The number of wheat varieties also had a positive, but small effect on predator abundance (β = 0.025 ± 0.010, P = 0.012, marginal R² = 0.012, see Appendix B: Table S2). This effect was variable across species, with the most affected taxa being the two most abundant rove beetle taxa: Aleocharinae spp, and Tachyporus hypnorum and the three most abundant ground beetle species Poecilus cupreus, Phyla obtusa and Clivina fossor (Fig. 4, Appendix B: Figs. S1A andB). In contrast, none of the other aboveground arthropods (ground beetles or rove beetles) were impacted by the number of wheat varieties, regardless of the dependent variable considered (species abundance, richness or evenness) (see Appendix B: Tables S2 andS4).

Finally, the number of wheat functional groups, a proxy for trait diversity, also had a limited S3A).

Effects of wheat stand characteristics

The characteristics of wheat stands had in some cases an effect on the diversity of arthropods, but never on their abundance (see Appendix B: Table S5 for detailed values across wheat diversity treatments). Wheat shoot biomass had a positive effect on the evenness of ground beetles (Pielou index, β = 0.31 ± 0.09, P = 0.001, adjusted R² =0.10, see Appendix B: Table S3A) and predators as a whole (β = 0.23 ± 0.09, P = 0.012, adjusted R² =0.05, see Appendix B: Table S3A), while the GAI had a positive effect on ground beetle abundance (β = 0.082 ± 0.042, P = 0.050, marginal R² = 0.019, see Appendix B: Table S2) and on rove beetle species richness (β = 0.221 ± 0.102, P = 0.039, pseudo R² = 0.31, see Appendix B: Table S4) and the variance of plant height had a negative effect on the evenness of rove beetles (Pielou index, β = -0.21 ± 0.09, P = 0.017, adjusted R² = 0.12, see Appendix B: Table S3A).

Weak signal of wheat mixture but stronger border effects

In addition to the few and generally weak effects of the crop (0.025 < │β│ < 0.307), there was a stronger North-South gradient 0.139 < │β│ < 0.309) in the abundance and diversity of arthropod communities, with significantly more individuals and less even abundances at the northern end of the field site (significant positive, respectively negative "latitude" effect, Tables S2-S4), which lies closer to the woody patches (Figs 1A andB). Longitude had also, in fewer cases, a significant but weak negative effect (see Appendix B: Tables S2 andS4).

Discussion

Our experiment manipulated wheat intraspecific diversity and combinations of wheat traits to examine their impact on aboveground arthropods, with a focus on predatory species. We observed limited effects that can be summarized as a positive effect of the number of varieties

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on the abundance of the most common spider species, as well as on the abundance of the most common predatory species (ground and rove beetles) and a few more significant relationships between wheat stand characteristics and (1) the abundance of ground beetles, (2) predators as a whole, (3) the diversity of ground and rove beetles and (4) the diversity of exclusive predator communities. Below, we discuss how these results compare to similar experiments in more natural settings, and whether crop variety mixtures can be expected to improve biological control in agroecosystems.

Positive effect of wheat intraspecific diversity on several spider species and consequences on spider diversity

The observation of an increased abundance of several spider species in plots with multiple varieties is consistent with previous experiments examining the effect of the genetic diversity of plant species on arthropod communities, although the mechanisms involved may differ. For example, [START_REF] Crutsinger | Plant genotypic diversity predicts community structure and governs an ecosystem process[END_REF] (2013) in T. aestivum showed that higher plant genetic diversity was associated with higher abundance and/or species diversity of invertebrate taxa (mainly spiders). In our experiment, however, increased spider abundance was associated with decreased spider diversity (as indicated by a significant negative effect of the number of wheat varieties on the Pielou index, see Appendix B: Table S4). Although species diversity was not always measured with the same indices, this pattern contrasts with most previous findings that plant genetic diversity tends to increase arthropod diversity [START_REF] Chateil | Crop genetic diversity benefits farmland biodiversity in cultivated fields[END_REF][START_REF] Crutsinger | Plant genotypic diversity predicts community structure and governs an ecosystem process[END_REF]Moreira & Mooney, 2013).

Two main mechanisms are generally invoked to explain the positive relationship between plant genetic diversity and the abundance/diversity of invertebrates: (1) increased primary productivity resulting in more resources for herbivores and subsequently for the upper trophic Srivastava & Lauwton, 1998), which may increase species diversity via sampling effects or (2) increased diversity of resources for herbivores or increased diversity of microhabitats for all groups ("more diversity" hypothesis, [START_REF] Southwood | The relationships of plant and insect diversities in succession[END_REF]. Here, this later mechanism is unlikely to be at play. First, wheat diversity was associated with decreased spider diversity (decreased evenness), whereas the opposite pattern is expected under the "more diversity" hypothesis. Second, we did not observe any significant relationship between spider abundance/diversity and wheat stand characteristics that are known to have a direct influence on spider communities. For example, complex vegetation structure is sometimes associated with increased spider abundance [START_REF] Langellotto | Responses of invertebrate natural enemies to complex-structured habitats: a meta-analytical synthesis[END_REF]) via the diversity of available microhabitats. However, the variance in plant height within a plot, a proxy for the complexity of vegetation structure, was not related to spider abundance or diversity (see Appendix B: Tables S2-S4). Higher spider abundance in variety mixtures is therefore likely an indirect consequence of higher primary productivity, mediated by the abundance of herbivorous preys, although the evidence for this mechanism is mixed.

For example, increasing the number of wheat varieties increased plant height, but not shoot biomass (Fig. 2).

The negative effect of intraspecific wheat diversity on spider evenness and the positive effect of intraspecific wheat diversity on spider abundance affecting preferentially the most abundant species may be explained by species-specific dispersal abilities. These abundant species were mostly Linyphiidae (O. apicatus, T. tenuis or E. atra, Fig. 3), which dominated spider communities, as is often the case in agroecosystems in northern-temperate Europe (Nyffeler & Sunderland, 2003). Linyphiids are small spiders (often less than 2 mm), which are capable of mass aerial dispersal [START_REF] Bell | Ballooning dispersal using silk: world fauna, phylogenies, genetics and models[END_REF]. This dispersal strategy, coupled with their rapid population growth during spring time (Roberts, 2001), allows Linyphiidae to move to and thrive in areas of the fields that offer suitable micro-local conditions and higher prey

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densities [START_REF] Harwood | Living where the food is: web location by linyphiid spiders in relation to prey availability in winter wheat[END_REF]. This may explain their higher sensitivity to wheat diversity than other spiders, also observed in [START_REF] Chateil | Crop genetic diversity benefits farmland biodiversity in cultivated fields[END_REF]. In our case, the effect of intraspecific wheat diversity seems limited to the more dispersive species, which are according to environmental filtering theory [START_REF] Keddy | Assembly and response rules: two goals for predictive community ecology[END_REF]) not filtered by landscape and so may colonize the experimental field and may spend more time foraging in the resourceful plots where they are captured in higher abundance. Species with lower dispersal ability may be absent from resourceful plots. This would be the case for wolf spiders (Lycosidae) [START_REF] Blandenier | Balloning of spiders (Araneae) in Switzerland; general results from an eleven-year survey[END_REF], which are medium-sized predators (around 5 mm) capturing their prey by foraging on the ground. They were relatively frequent in our experimental site (as in [START_REF] Lang | Intraguild interference and biocontrol effects of generalist predators in a winter wheat field[END_REF], but were less sensitive to crop diversity (except for P. prativaga).

Although the number of wheat varieties tended to increase the abundance of some spider species, the stand characteristics responsible for such effect were difficult to identify. This is exemplified first by the absence of a significant relation between any of the stand characteristics we studied and spider abundance, and second by the absence of a significant relationship between the number of wheat functional groups and spider abundance or species richness except evenness. Some authors have emphasized that trait or phenotypic diversity should matter more than genetic diversity per se in explaining the effects of plant species on their associated communities [START_REF] Hersch-Green | Community genetics: what have we accomplished and where should we be going?[END_REF][START_REF] Hughes | Ecological consequences of genetic diversity[END_REF]. Yet, few studies have successfully identified traits responsible for the effects of genotypic diversity (Crustinger, 2016). Here, we used the number of functional groups as a proxy for phenotypic diversity: these groups of varieties were built on the basis of a large number of traits, covering components of plant shoot and root morphology, plant phenology, disease resistance, metabolism and yield. Because variety mixtures could contain more than one variety from the same functional group, the number of functional groups should have been a better driver of arthropod community abundance and diversity than the number of varieties. Yet the opposite

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was observed. Besides, stand characteristics that had been chosen for their a priori expected effects on arthropods were poorly related to spider abundance and diversity. All these observations suggest that the most important stand characteristics and wheat traits driving the positive effect of the number of varieties on spider abundance remain to be identified.

An overall limited effect of crop diversity and composition on aboveground arthropods

Although we did detect a weak effect of intraspecific wheat diversity on spiders and on predatory species, in general the community of aboveground arthropods was little impacted by the number or functional diversity of wheat varieties in each plot, which conflicts with previous similar studies (see [START_REF] Crutsinger | A community genetics perspective: opportunities for the coming decade[END_REF] for some examples). In some cases, the effect of plant genetic diversity on arthropod communities was even larger than the effect of interspecific plant diversity [START_REF] Crawford | Genetic diversity within a dominant plant outweighs plant species diversity in structuring an arthropod community[END_REF]. Assuming that there is no bias against negative results in the literature (but see Parker et al., 2016), so that the large number of articles reporting a significant effect of plant genetic diversity are representative of its true impact in nature, the possible causes for the limited effect of crop genetic diversity on predator communities observed here can be manifold. Below we discuss three of the most likely causes that are related to the ecology of the organisms studied and to agricultural practices.

First, detecting an effect of plant (genetic) diversity on animal communities is a matter of appropriate spatial and temporal scales. The experiment should be designed such that the targeted taxonomic groups have ample time to reach their preferred plots and stay there or to multiply in the more favourable plots. In the case of an annual crop such as wheat, we were limited by crop rotation, such that the experiment could last no more than a few months at the maximum. As a result, the effects of wheat on arthropod communities were strongly dependent on the dispersal ability of the sampled organisms. We were also limited in plot size, with a strong trade-off between plot size and the number of replicates per mixture

A C C E P T E D M A N U S C R I P T treatment (i.
e. number of varieties or functional groups). The size and time frame of this experiment was, however, comparable to other studies with a strong effect of genetic diversity on arthropod communities (e.g. Crutsinger et al., 2006, 1 m²-plots, one growing season). Yet, whether the time frame of the experiment was sufficient to detect an effect of wheat diversity on arthropod communities depends on the dispersal ability of the regional pool of species. The aboveground arthropod species trapped in this study (spiders, ground beetles and rove beetles) are generally representative of communities observed in European farmland and, as such, are thought to be able to colonize and to thrive in an open and non-permanent habitat, ploughed and harvested every year [START_REF] Eyre | Strategic explanations of carabid species distributions in northern England[END_REF]. Regardless of the alleged good dispersal abilities of the various species, the size and time frame of our experiment was long enough for all of the species to forage in or disperse to the plots. However, we detected a strong border effect on either the abundance or the diversity of all taxa, suggesting source/sink dynamics between the border and the centre of the field, within the time frame of our study. In either case, these phenomena limited the abundance of arthropods in the experimental plots and may have masked a possible effect of mixture treatments.

Second, if a plant species influences predatory arthropod communities through indirect, bottom-up effects, via e.g. more abundant or more diverse food sources for herbivorous preys, the bottom-up effects of both intra-and interspecific plant diversity on arthropods may be buffered down in higher trophic levels because of a top-down control by predators [START_REF] Terborgh | Toward a trophic theory of species diversity[END_REF]. Pitfall traps are not the best setup to assess herbivore abundance, because they also live on vegetation. Here the herbivores captured in the pitfall traps were not numerous enough to test whether the effect of the number of wheat varieties was stronger on herbivores or on predators and the possibility of a top-down control. However, several studies (e.g. [START_REF] Johnson | Additive and interactive effects of plant genotypic diversity on arthropod communities and plant fitness[END_REF]Moreira & Mooney, 2013) Third, most previous experiments on the impact of plant genetic diversity on arthropods were performed in ecological research stations (e.g. [START_REF] Abdala-Roberts | Biotic and abiotic factors associated with altitudinal variation in plant traits and herbivory in a dominant oak species[END_REF][START_REF] Crutsinger | Plant genotypic diversity predicts community structure and governs an ecosystem process[END_REF]Moreira & Mooney, 2013) or under organic farming [START_REF] Chateil | Crop genetic diversity benefits farmland biodiversity in cultivated fields[END_REF], whereas this experiment was conducted under conventional farming, with moderate use of pesticides and fertilizers in the year of the experiment, but with a long history of more intensive farming in this agronomy research station. Intensive conventional farming is known to have strong negative effects on the abundance of most species and on the diversity of communities (see Kremen & Miles, 2012 for reviews;Pfiffner & Niggli, 1996) via the effects of synthetic inputs and ploughing [START_REF] Bouthier | Impact du travail du sol sur son fonctionnement biologique[END_REF]. We observed much lower abundances of spiders and ground beetles in this experiment under conventional farming than in an earlier comparable experiment with bread wheat under organic farming [START_REF] Chateil | Crop genetic diversity benefits farmland biodiversity in cultivated fields[END_REF] and larger experimental plots but with a comparable sampling design: same period and duration of pitfall trapping (2-weeks trapping session in May, same density of pitfall traps): the mean (± standard error) number of individuals per trap in this experiment vs. [START_REF] Chateil | Crop genetic diversity benefits farmland biodiversity in cultivated fields[END_REF] was 4.4 ± 0.3 vs. 25.6 ± 1.6 for spiders and 10.6 ± 0.4 vs. 38.9 ± 2.5 for ground beetles. In contrast, the number of rove beetles was similar in both experiments (12.0 ± 0.5 vs. 11.7 ± 0.75). With a single replicate per farming type, we cannot conclude that farming system is the main driver of such differences in abundances, but the trend is consistent with the widely demonstrated negative impact of conventional farming on biodiversity [START_REF] Lichtenberg | A global synthesis of the effects of diversified farming systems on arthropod diversity within fields and across agricultural landscapes[END_REF]. Nevertheless, the low number of arthropod individuals observed in this experiment has likely lowered our ability to detect an effect of crop variety mixtures on predator communities.

Conclusions

In general we found congruent, but much weaker effects of crop genetic diversity than in

A C C E P T E D M A N U S C R I P T
previous similar studies: only a few spider species exhibited increased abundance when the number of wheat varieties increased, whereas ground and rove beetles were largely unaffected by the crop structure and diversity. In particular, the distance to the field edge had a stronger effect on arthropod communities than the crop itself, which is consistent with the welldocumented general role of the landscape scale for aboveground arthropods and predation in farmland (Tscharntke et al., 2007). We were not able to conclude on the exact mechanism explaining the difference between our and previous studies, but part of the reason may be linked with conventional farming lowering the general abundance and diversity of arthropods in the field. Our results therefore suggest that wheat variety mixtures are unlikely to benefit aboveground arthropods, hence to improve biological control, under conventional farming.

However this prediction needs to be tested with new experiments directly comparing the impact of the same mixtures between conventional farming, low-input farming and organic agriculture. Finally, further investigations are also needed to upscale the study of crop variety mixtures and examine whether within-field genetic diversity has stronger positive impacts on the diversity and abundance of arthropod predators on the longer term or at the farm scale, as suggested by [START_REF] Cardinale | The functional role of producer diversity in ecosystems[END_REF].



  Wheat variety mixtures have contrasting effects on aboveground arthropod communities  Wheat intraspecific diversity have a weak positive effect on predator abundances  Wheat intraspecific and functional diversity have a weak negative effect on spider evenness Few wheat stand characteristics have effects on ground or rove beetles

  verified, we used a Kruskal-Wallis test.

  arthropods with only a negative effect on the evenness of spiders (β = -0.22 ± 0.10, P = 0.026, adjusted R² = 0.1, see Appendix B: Table

  in Solidago altissima, Moreira and Mooney (2013) in Baccharis salicifolia, Abdala-Roberts et al. (2016) in Phaseolus lunatus or Chateil et al.

  more individuals" hypothesis,

  did detect strong direct or indirect effects of plant genetic diversity on predators or parasitoids.

A

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FiguresFig. 1 .

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Fig. 2 .

 2 Fig.2. Spearman correlations between the number of wheat varieties, the number of

Fig. 3 .

 3 Fig. 3. Predicted abundance of spider species as a function of the number of wheat varieties.

Fig. 4 .

 4 Fig. 4. Predicted abundance of predatory species as a function of the number of wheat

  Fig. 3.

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Acknowledgments

This work was supported by the ANR WHEATAMIX project, grant ANR-13-AGRO-0008 of the French National Research Agency. We thank all the persons who were involved in the management of the field experiment, and particularly Sébastien Saint-Jean, Christophe Montagnier and Pauline Lusley. We are also grateful to Pauline Lusley for technical assistance to obtain GAI data and Romain Angeleri for insightful comments. We would also like to thank anonymous reviewers for their useful comments that helped us improve the quality of the manuscript.

Authors' Contributions

S. Ba. and E. P. contributed to the experimental design; S. Ba., L. B., J. G, E. M. and A. V. collected the data; S. Be., J. G., I. L. V., E. M., and A. V. identified the aboveground arthropods; A. V, E. M. and F. D. analysed the data set; E. P. and C. K. assisted in the data analysis; S. Ba., F. D., E. P., and A. V. wrote the paper; C. K. and I. L. V. made valuable comments on the writing. All authors contributed critically to the drafts and gave final approval for publication.