The spatio-temporal distribution of weed seed predation differs between conservation agriculture and conventional tillage

Agriculture, Ecosystems and Environment 188 (2014) 40–47

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The spatio-temporal distribution of weed seed predation differs between conservation agriculture and conventional tillage Aude Trichard a,b , Benoit Ricci a , Chantal Ducourtieux a,c , Sandrine Petit a,∗ a b c

INRA, UMR 1347 Agroécologie, BP 86510, F-21000 Dijon, France AgroParisTech, F-75005 Paris, France AgroSup Dijon, F-21000 Dijon, France

a r t i c l e

i n f o

Article history: Received 13 October 2013 Received in revised form 27 January 2014 Accepted 30 January 2014 Available online 12 March 2014 Keywords: Trophic guild No-tillage Cover crop Agroecology Biological regulation MAPCOMP Viola arvensis Capsella bursa-pastoris

a b s t r a c t One potentially important ecosystem service in agricultural fields is the regulation of weeds by carabid beetles, but the effect of agricultural management on the level of regulation has so far been poorly documented. In this study, we monitored weed seed predation rates of Viola arvensis and Capsella bursapastoris and carabids from March to September using a grid sampling in two adjacent winter-wheat fields, one in conventional tillage (T) and the other converted to direct drilling with cover-crop for five years (DD). At the field level, weed seed predation was positively correlated to the activity of granivores in the tilled field and was marginally higher in DD than in T during wheat growth. After harvest, granivores and predation rates declined sharply in the cover crop of the DD system whereas they increased in the bare tilled field. This result suggests that the dense cover crop set up after harvest was not suitable for the local pool of autumn-breeding granivores. Spatial aggregations of carabid and predation variables were detected using the MAPCOMP software; these spatial patterns differed between the two management systems and were temporally unstable but consistent over large intervals of spatial resolutions. There were significant spatial associations between trophic guilds and predation rates, i.e. predation rates were positively or negatively associated either to granivores or to omnivores, depending on the time and on the management system. These results highlight the spatial and temporal heterogeneity in the level of interactions taking place during a crop cycle, a complexity which explains the important variability in the delivery of ecosystem services such as weed seed predation. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Identifying management practices enhancing the provision of ecosystem services in farmland has become a critical issue in agriculture (Firbank et al., 2012). One potentially important ecosystem service in agricultural fields is the regulation of weeds by seed predation (Ichihara et al., 2011; Westerman et al., 2003). Seed-eating carabids in particular have been shown to consume substantial numbers of seeds in the field (Honek et al., 2007; Westerman et al., 2003) and their abundance has been related to seed predation level (Menalled et al., 2007; O’Rourke et al., 2006) and to the rate of depletion of the weed seed bank (Bohan et al., 2011). Conservation agriculture, a system that strongly reduces soil tillage operations, has been shown to positively affect carabid

∗ Corresponding author. Tel.: +33 3 80 69 30 32; fax: +33 3 80 69 32 62. E-mail addresses: [email protected] (A. Trichard), [email protected] (B. Ricci), [email protected] (C. Ducourtieux), [email protected] (S. Petit). http://dx.doi.org/10.1016/j.agee.2014.01.031 0167-8809/© 2014 Elsevier B.V. All rights reserved.

richness and abundance (House and Stinner, 1983) notably as tillage-induced mortality can be important for some carabid species (Shearin et al., 2007). Reduction in soil tillage also leads to an accumulation of weed seeds near the surface (Cardina et al., 2002; Yenish et al., 1992), thus providing available resources for potential seed predators. In addition to reduced tillage operations, conservation agriculture often promotes the set-up of cover crops during the intercropping period (Trichard et al., 2013a) and this vegetation cover may provide carabids with favourable habitat conditions (Shearin et al., 2008; Ward et al., 2011) and protection from hyperpredators (Harrison and Gallandt, 2012). Vegetation cover has also been shown to increase weed seed predation by invertebrates (Meiss et al., 2010). Although the effects of conservation agriculture on carabids are well documented, its impact on weed seed predation levels appears less consistent in the literature (Gallandt et al., 2005; Sanguankeo and Leon, 2011), possibly because weed seed predation levels often strongly vary over time (Saska et al., 2008; Westerman et al., 2003). Indeed, weed seed predation results from the activity of various omnivorous and granivorous species which may not have similar activity periods over the season. The

A. Trichard et al. / Agriculture, Ecosystems and Environment 188 (2014) 40–47

effect of richness and abundance in each trophic group on predation levels, as well the role of potential positive or negative interactions between and among guilds, are not fully understood (Gaines and Gratton, 2010; Trichard et al., 2013b). One way to deepen our understanding of the processes underlying weed seed predation may spur from a thorough spatial analysis of the movement and distribution of seed predators and predation through time in field conditions. Different spatial analysis methods are available to link ecological processes to spatial patterns such as the spatial analysis by distance indices (SADIE, Perry, 1998; Perry and Dixon, 2002) and map comparison method (MAPCOMP, Lavigne et al., 2010). These methods enable to identify significant aggregation patterns of species spatial measures and significant associations between two spatial distributions. For example, they were used to analyse spatial pattern and association between arthropods (Thomas et al., 2001), to evidence spatial association between predators and preys (Winder et al., 2001) or to analyse the temporal evolution of the spatial pattern of insect pests within fields (Ricci et al., 2011). In this paper, we studied weed seed predation and seed-eating carabids, measured over a seven months study, in two adjacent cropping systems: direct drilling with cover crop (DD) and Tillage (T). We first conducted a global analysis of the two adjacent systems using linear models to test the hypothesis that seed predation and carabids differ between the DD and the T systems and that these differences vary over time. Second, we performed spatial analyses of the distribution of weed seed predation and seed eating carabids over time within each system. We hypothesized that (i) the spatial distributions of predation rates and carabids are clustered; (ii) the distributions of carabids and predation rates vary over time but are spatially associated; (iii) there are associations/segregations between carabid trophic guilds that vary over time and (iv) aggregation patterns and spatial associations differed between the two cropping systems.

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faba bean and runnage pea) resulting in a cover crop that was successively 0.10 m high on August 30, 1.20 m on September 16 and 1.50 m high on September 23. 2.1. Estimation of carabid activity and weed seed predation rates Within each one of the two zones, 33 measure plots were positioned five or ten m apart (Fig. 1). Each plot was 1-m side square with two pitfall traps and two vertebrate exclosure cages placed each one at a given corner. Pitfall traps were made of plastic containers of 10 cm depth and 8 cm diameter and filled with 150 ml of a mixture of anti-freeze and salted water and protected from the rain by plastic roofs above the traps on 10 cm legs. Those plastic containers were placed inside plastic tube settled in the soil to allow the replacement of containers without disturbing the surrounding soil. Carabids collected in the two traps of each plot were pooled and identified at species level and assigned to a trophic guild i.e. carnivores, omnivores or granivores (Brooks et al., 2012). Activitydensity and richness were computed for each plot per trophic guild. Seed predation by invertebrates was quantified by exposing seed cards protected by vertebrate exclosure cages (18 × 11 × 9, 1 cm wire mesh) using a standard protocol developed by Westerman et al. (2003). Two bundles of 50 seeds of two species commonly occurring within the study area (Viola arvensis (Murr.) and Capsella bursa-pastoris (L. Medicus) were glued onto 6 per 14 cm cards of brown sand paper (grain size 10). The two weed species differed in size: V. arvensis, 0.9–1.0 × 1.4–1.9 mm and C. bursa-pastoris, 0.3–0.5 × 0.6–1.0 mm, covering the potential range of seed preferences of carabids of different body sizes (Honek et al., 2007). Seed predation rate per plot was calculated as the average percentage of seeds lost on the two cards. At each one of the eight sessions of measure, seed cards and pitfall traps were simultaneously placed and then left in place seven days. 2.2. Spatial and statistical analysis

2. Material and methods This study was performed in 2011 in two adjacent calcisol wheat fields that were managed by two different farmers, 50 km North West of the city of Dijon in North-eastern France (47◦ 36 12 N, 4◦ 35 32 E). The first 5.72 ha field was conducted with traditional tillage operations (T: Tillage) and the second 18.78 ha field had been conducted in direct drilling with cover-crop for five years (DD: direct drilling with cover crop).This technique associates no tillage and no superficial soil management with a cover crop (mix species) during the intercrop period. These differences in soil management over the years resulted into two clearly different soil profiles (Curmi, pers. com.). The T field had a strong contrast between its first two horizons, with a first level from 0 to 15 cm of very fine structures due to tillage, then from 15 to 20 cm angular and compact clusters with large cracks, and below 20 cm, the C horizon exhibited clays decarbonation. Conversely, the DD field had many stones on the surface, better water infiltration and good distribution of roots, and from 0 to 20 cm rough elements of various sizes, less angular, finer in surface, and stronger macroporosity. The protocol was set up in two contiguous zones of 100 × 100 m, one within each field, which received no insecticide or fungicide. The margin strip adjacent to the fields consisted of a grassy path and herbaceous borders. The DD and T systems shared the same landscape of semi-natural habitats and, consequently, a common pool of carabid beetles. Measures were performed during eight consecutive sessions, five during the wheat growing season (March 21, April 18, May 16, June 15 and July 11) and three after harvest (August 30, September 16 and September 23). After harvest, the T field was tilled and stubble ploughed while the DD field was sown with a vegetation mixture of six species (flax, sunflower, vetch, phacelia,

Linear mixed effects models (LMMs) were applied to analyse predation rates of each weed species in relation to session, soil tillage management (T or DD) and the different carabid counts (activity-density and species richness of granivores, omnivores and carnivores). When a qualitative factor had a significant effect on predation rates, multiple comparisons tests were performed to identify the different groups of factor levels (Pinheiro and Bates, 2000). The plot number was included as random factor due to experimentation i.e. temporal and spatial pseudo-replications. Models were fitted by restricted maximum likelihood (REML) and the suitability of assumptions was assessed by checking for normality and randomness of residuals. Mixed models were performed with the lme package and multiple comparisons with the multcomp package (Hothorn et al., 2008) under the R 2.14.1 software (R Development Core Team, 2010). A comparison of predation rates and carabid counts between the T and DD systems for each session was performed using Mann–Witney tests, with XLStat Pro 2012.1.02 (Copyright Addinsoft 1995–2012). The MAPCOMP method, a density map comparison approach developed by Lavigne et al. (2010) was used to explore the spatial distribution of predation rates and carabid counts. In this method, the interpolation of a spatial distribution includes a bandwidth parameter h which can be used to explore heterogeneity at various spatial scales. The range of h values is constrained by the distances between sampling points and by the size of the sampled area. First, we used the MAPCOMP method to assess the intra-field spatial distribution of each variable Xis (V. arvensis predation rate, C. bursa-pastoris predation rates, granivores activity-density, granivores richness, omnivores activity-density, omnivores richness, carnivores activity-density and carnivores richness) at each session

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A. Trichard et al. / Agriculture, Ecosystems and Environment 188 (2014) 40–47

Fig. 1. Experimental design.

s within each system. MAPCOMP produces a kernel-interpolated map of Xis and compares this interpolated map with the density of the traps or the cards using the Hellinger distance between maps. The hypothesis H0 : “Xis is uniform” vs. H1 = “The spatial distribution of Xis is not homogeneous and presents clustering patterns” was then tested using a non-parametric test based on 10,000 permutations of the values of the variable Xis on the sampling points. The analyses were performed for bandwidth values ranging from h = 15 m to h = 40 m with incremental 1 m steps (see Appendix A). Heterogeneity was deemed significant when significantly detected for at least two successive h values, so that the two instances where heterogeneity was only detected for a single h value were considered as uniformly distributed. Second, within each system, for the variables that were identified as heterogeneous, MAPCOMP was used to assess the temporal stability in the distribution of individual variables from one measure session to the next (V1 = Xis and V2 = Xis+1 ) and to evaluate spatial associations in the distribution of two distinct variables (V1 = Xis and V2 = Xjs+1 ), here between the distribution of carabid counts and predation rates as well as between the distribution of

the three carabid trophic guilds. The two interpolated maps of V1 and V2 were compared using the Hellinger distance and the hypothesis H0 : “The spatial intensities of V1 and V2 are independent” vs. H1 = “V1 and V2 are spatially correlated” was tested using a nonparametric test based on 10,000 permutations of the values of V1 on the sampling points. Spatial associations were deemed significant when detected for at least two successive h values. 3. Results Seed predation rate per session and plot ranged from 0% to 100% and averaged 34.87% for V. arvensis and 52.52% for C. bursa-pastoris. A total of 3919 beetles were caught of which 25.1% were omnivores, 43.2% carnivores and 31.7% granivores. They belonged to 55 species, of which six were omnivores (Main species: Calathus fuscipes Goeze; Pterostichus melanarius Illiger; P. cupreus Linnaeus; P. madidus Fabricius), 25 were carnivores (Main species: Carabus convexus Fabricius; C. coriaceus Linnaeus; Brachinus crepitans Linnaeus; Ocys harpaloides Audinet-Serville) and 24 were granivorous (Main species: Pseudoophonus rufipes De Geer;

A. Trichard et al. / Agriculture, Ecosystems and Environment 188 (2014) 40–47

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Table 1 Results of mixed models fitted by REML for predation rates. Factor/variable

Levels

Viola arvensis Value

±SE

p/group

Value

±SE

p/group

Management

Tillage Direct Drilling March 21 April 18 May 16 June 15 July 11 August 30 September 16 September 23

16.77 24.02 11.11 11.27 50.67 67.74 8.96 50.60 16.77 19.68 0.99 1.44 0.23 −2.14 0.05 −0.63

±3.68 ±5.73 ±7.83 ±7.33 ±7.36 ±7.39 ±7.58 ±7.27 ±3.68 ±7.14 ±0.44 ±1.39 ±0.45 ±1.46 ±0.31 ±1.10

A B A A B C A B A A

42.03 40.57 33.28 12.12 57.05 71.56 44.28 84.89 42.03 42.17 0.70 1.21 0.39 0.25 −0.10 1.04

±3.40 ±5.30 ±7.24 ±6.77 ±6.81 ±6.83 ±7.01 ±6.72 ±3.40 ±6.60 ±0.41 ±1.29 ±0.42 ±1.35 ±0.29 ±1.02

ns ns A A D C A B A A ns ns ns ns ns ns

Session

Granivores Omnivores Carnivores

AD R AD R AD R

Capsella bursa-pastoris

*

ns ns ns ns ns

Fixed terms are soil management, measure session and carabid counts (AD activity-density, R richness) and measure plot is as random term (df = 449). Value ± SE are the mean predation rates and associated standard errors. For qualitative factors, letters indicate significant differences at p < 0.05 in the effect of different modalities of a single factor For quantitative factors, * p < 0.05.

Harpalus dimidiatus P. Rossi; Amara consularis Duftschmid; H. affinis Schrank). All species were caught in both fields except for some only observed in the T field (Nebria brevicollis Fabricius; Amara apricaria Paykull; Zabrus tenebrioides Goeze; Amara familiaris Duftschmid and Harpalus tardus Panzer) and Amara nitida (Sturm) only observed in the DD field. The complete list of species is provided in Appendix A. 3.1. Weed seed predation and carabid counts Session had a significant effect on predation rates with higher levels in June, then May and August for the two weed species. Soil management had a significant effect on the predation rate of V. arvensis with higher rates in the DD system (Table 1). The activitydensity of granivores was the sole carabid count that was related to predation, for V. arvensis only (Table 1). The predation rate of the two species were generally significantly higher in DD than in T before harvest but became lower in DD than in T after harvest (Fig. 2a and b and Fig. 3). Granivorous carabids exhibited a temporal pattern quite similar to the predation patterns and similar in both systems before harvest. Conversely, the activity-density and richness of granivorous strongly differed between the two systems after harvest. Granivorous counts were very low in the DD system whereas they increased and reached a peak in the T system (Fig. 2c and d, Fig. 3). The activity-density and richness of omnivores were constantly higher in DD than in T except for the last session (Fig. 2e and f, Fig. 3). The activity-density and richness of carnivores declined with harvest, then raised in September at initial level, and differed in T and DD but without clear preferences for one system or the other, through more variability was observed in the T system. 3.2. Spatial patterns and associations within each system Heterogeneous distributions of predation rates and carabid counts were detected in DD and T. Each variable was aggregated at least once in the experiment but patterns did not appear systematically in both systems during the same session (Fig. 3). Spatial structures were detected at several bandwidth values with ranges that varied for a given variable (Appendix B). In most cases, there was no spatial association in the distribution of individual variables from one measure session to the next (Fig. 3) but spatial patterns that were detected were not necessarily identical in the T and DD systems. The spatial distribution

of predation rates differed between consecutive sessions between July and August corresponding to harvest time as well as between March and April, April and May, corresponding to a high increase in mean field values. The spatial distribution of granivores was not affected by harvest in DD but statistical changes were observed in the distribution of omnivores in the T system (Fig. 3). Clear shifts in the spatial distribution of granivores and omnivores were detected in the DD system between March and April. There were five instances where a clustered distribution of a predation rate coincided with a clustered distribution of a carabid trophic guild (Table 2). Three of those occurred in the DD system, of which two were spatially associated. The distributions of C. bursa-pastoris predation rate and activity-density of omnivores were significantly similar in DD in March whereas in September, the distribution of predation rates was significantly dissimilar to the distribution of granivores. Two instances occurred in the T system but no spatial association could be detected. There were eight instances where two trophic guilds exhibited a clustered distribution during the same measure session, four in each system (Table 2). The distributions of granivores and omnivores were similar in DD and T, respectively, in April and May. In the T system, the distribution of granivores and carnivores were significantly dissimilar in May whereas the distribution of omnivores and carnivores were similar in September. 4. Discussion 4.1. Effect of soil management Our results suggest that weed seed predation as well as activitydensity of granivores in the DD system were only marginally higher during the wheat growing season and significantly lower after harvest, in comparison to the adjacent conventional T field. Although the comparison of pitfall data collected in two habitats where the mobility of carabids might have been differentially affected by habitat structure requires caution (Thomas and Marshall, 1999), our result is not in line with the markedly higher activity-density of seed-eating carabids observed by pitfall trapping and weed seed predation rates observed in no-tilled soybean during late summer (Menalled et al., 2007). Yet, other studies using pitfall trapping suggest a variability in the response of granivores and predation rates according for example to the type of cover crop used in conservation agriculture and highlight the fact that higher densities of granivores does not necessarily translate into higher weed seed

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Fig. 2. Predation rates of V. arvensis and C. bursa-pastoris and activity density and richness of granivores, omnivores and carnivores over time. Comparisons tests (Mann Witney) between DD (direct drilling, solid line) and T (Tillage, dotted line) are presented for each sampling session (ns = not significant; * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).

predation rates (Gallandt et al., 2005). In our case, during the wheat growing season, the dominant granivorous species H. dimidiatus and P. rufipes occurred in the two systems, although catches of P. rufipes were slightly higher in the DD system. At the same time, the richness and activity-density of omnivores, mostly P. melanarius and P. cupreus, were consistently higher in the DD system compared to the T system. After harvest a predation peak was observed in the two systems and subsequently weed seed predation became lower in the DD system than in the conventional T field. Simultaneously, the activity-density of granivores decreased sharply in the DD and increased markedly in the T system. This shift in the

distribution of granivores appears to result from several processes; the spring-breeder H. dimidiatus, which dominated in both systems before harvest, became naturally much less active in the two systems in late summer; the autumn-breeding granivorous species A. consularis and A. apricaria appeared in large numbers but solely in the T system, probably because the dense cover crop that was in place the DD system did not suit these typical ‘open habitat’ species and finally, P. rufipes almost entirely disappeared from the DD field but became active in the T system, suggesting that individuals actively moved from the DD to the adjacent T system after harvest. Simultaneously, the activity-density of omnivores, mostly

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Fig. 3. Density maps of predation rate of V. arvensis and C. bursa-pastoris and activity-density of granivores and omnivores represented for the bandwidth value h = 30 m in the Tilled system (T on the left) and the direct drilling system with cover crop (DD on the right). An asterix positioned after the letter representing the management system (T or DD) indicates the p value of the spatial clustering (* p < 0.05; ** p < 0.01; *** p < 0.001). Barred parallel lines with a d letter denote a significant dissimilarity and parallel lines with a s letter indicate a significant similarity in the distribution of the variable from one session to the next.

Table 2 Spatial associations between couples of variables that present clustered distribution in the same system and at the same session. Variable A Direct drilling March 21

Predation

April 18 July 11

Granivores Granivores

August 30 September16

Omnivores Predation

Tillage May 16

Granivores

August 30 September 16 September 23

Predation Predation Granivores Omnivores

Variable B V. arvensis C. bursa-pastoris

Omnivores Omnivores

AD AD R AD V. arvensis

Omnivores Carnivores Carnivores Carnivores Granivores

AD R V. arvensis V. arvensis R AD

Carnivores Carnivores Granivores Omnivores Omnivores Carnivores

Association AD AD R AD AD R AD AD R

ns S* Ns S* ns ns ns D ** D*

AD R AD AD R AD

ns ns ns s S *** S **

I

hc

15:16

2

15:26

12

20:40 33:40

20 8

18:40 15:27

23 13

D: distributions are significantly dissimilar and S: distributions are significantly similar (* p < 0.05; ** p < 0.01; *** p < 0.001); ns: no significant spatial association between the two variables. I and hc are, respectively, the interval of the bandwidth parameter h and the number of steps over which the association is significant.

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P. melanarius, increased in both systems. Some caution is of course necessary in the interpretation of pitfall trapping data as bias could be induced by differences in the mobility and/or catchability of particular species (Baars, 1979; Thomas et al., 1998) and differences between the two systems, e.g. the occurrence of crop residues in the DD system that could have impeded individual movements or differences in prey availability levels which can affect the propensity of individuals to move (Firle et al., 1998). Spatial analyses provided us with additional information on processes at play. First, our results indicate discrepancies in the functional response of the two trophic guilds in the two systems. The spatial distribution of omnivores in the T system was significantly different before and after harvest, i.e. omnivores occupied different portions of the field before and after harvest. Conversely, and despite a drastic drop in their activity-density, the spatial distribution of granivores in the DD system was similar before and after harvest, i.e. they occupied space in the same way before and after harvest. Second, the spatial distribution of carabids was clustered at different times in the T system and in the DD system. We identified patterns inside fields that were not synchronized in both systems, which would suggest different dispersal dynamics of predators. Finally, we expected to observe clustered distributions of carabid trophic guilds that would reflect potential spatial segregation that may have been caused by direct predation (Currie et al., 1996) or behavioural avoidance (Prasad and Snyder, 2004). Our results indicate that there was widespread space sharing between trophic guilds in both systems over the whole duration of the experiment, hence that intra-guild predation is unlikely to be a major factor shaping the distribution of carabids in the fields. Carabid distribution is more likely to be driven by species-specific ecological requirements, e.g. vicinity to a field boundary or field cores (Holland et al., 2007) or by animal prey availability, e.g. aphids (Bryan and Wratten, 1984; Winder et al., 2005) or the spatial distribution of competitors (Hawes et al., 2013). 4.2. Linking carabids to weed seed predation levels The notion that increasing seed-eating predators abundance may lead to enhanced weed suppression is widespread yet, while in some instances seed-eating carabid abundance has been positively related to seed predation level (Menalled et al., 2007; O’Rourke et al., 2006) or depletion of the weed seed bank (Bohan et al., 2011), other studies have failed to evidence such links (Davis and Raghu, 2010; Gaines and Gratton, 2010; Mauchline et al., 2005; Saska et al., 2008). Here, a general statistical analysis highlights the prime importance of granivores in the delivery of weed seed predation in the T system, as established in other studies (Brooks et al., 2012; Trichard et al., 2013b) but a lack of significant effect of omnivores on seed predation. However, the spatial analysis of the fine-scale distribution of carabids and predation rates highlighted only a limited number of spatial associations between predation levels and one or both seed-eaters trophic guilds and suggest that these links vary according to the session and the management system. We were able to identify significant similarities as well as dissimilarities in the distribution of trophic group of seed predators and predation, and hence to spot which guild was consuming or not consuming the seeds at different times during the course of the experiment. Interestingly, we failed to detect significant associations during predation peaks, possibly because carabids were busy consuming weed seeds and as such were not very mobile and thus unlikely to be trapped. It is also possible that in the changing ratio densities of seeds exposed on predation cards and seeds naturally present, for example after crop harvest. It is possible that the chance of carabids to locate the predation cards decreased when naturally occurring seeds were in excess. There was a great deal of temporal changes in the distribution of variables in this study, i.e. patterns were often not maintained from one sampling date to the next,

which would suggest that the sampling interval used here (two weeks in general) was not sufficient to resolve changes in spatial patterns through time. As a result, the associations between trophic guilds and predation rates were not stable, a within-field pattern already evidenced in other studies (Pearce and Zalucki, 2006). The spatial resolution at which aggregations and associations occurred could be fully explored here as the MAPCOMP method enables to test the whole range of scales at which significant spatial patterns could emerge. Our results indeed indicate that aggregation could be detected at various scales, probably reflecting the variability in the mobility and behaviour among species composing the seed-eating carabid community in each system and at each session. Acknowledgements We thank Cyrille Auguste for his assistance in the field and Pierre Curmi who examined the soil profiles. We are particularly grateful to Benoît Lavier and Jean Claude Philisot who lent us part of their fields for this experiment. Finally, Claire Lavigne provided us with very useful insights for the use of the MAPCOMP method. This work was partly funded by the ANR project ADVHERB (ANR-STRA08-02) and the ANR project PEERLESS (ANR-12-AGRO-0006). Aude Trichard benefited from a PhD studentship funded by the French Ministry of Agriculture. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.agee.2014.01.031. References Baars, M.A., 1979. Catches in pitfall traps in relation to mean densities of carabid beetles. Oecologia 41, 25–46. Bohan, D.A., Boursault, A., Brooks, D.R., Petit, S., 2011. National scale regulation of the weed seed bank by carabid predators. J. Appl. Ecol. 48, 888–898. Brooks, D.R., Storkey, J., Clark, S.J., Firbank, L.G., Petit, S., Woiwod, I.P., 2012. Trophic links between functional groups of arable plants and beetles are stable at a national scale. J. Anim. Ecol. 81, 4–13. Bryan, K.M., Wratten, S.D., 1984. The responses of polyphagous predators to prey spatial heterogeneity: aggregation by carabid and staphylinid beetles to their cereal aphid prey. Ecol. Entomol. 9, 251–259. Cardina, J., Herms, C.P., Doohan, D.J., 2002. Crop rotation and tillage system effects on weed seed banks. Weed Sci. 50, 448–460. Currie, C.R., Spence, J.R., Niemelä, J., 1996. Competition, cannibalism and intraguild predation among ground beetles (Coleoptera: Carabidae): a laboratory study. Coleopt. Bull. 50, 135–148. Davis, A.S., Raghu, S., 2010. Weighing abiotic and biotic influences on weed seed predation. Weed Res. 50, 402–412. Firbank, L., Bradbury, R.B., McCracken, D.I., Stoate, C., 2012. Delivering multiple ecosystem services from enclosed farmland in the UK. Agric. Ecosyst. Environ. 166, 65–75. Firle, S., Bommarco, R., Ekbom, B., Natiello, M., 1998. The influence of movement and resting behavior on the range of three carabid beetles. Ecology 79, 2113–2122. Gaines, H.R., Gratton, C., 2010. Seed predation increases with ground beetle diversity in a Wisconsin (USA) potato agroecosystem. Agric. Ecosyst. Environ. 137, 329–336. Gallandt, E.R., Molloy, T., Lynch, R.P., Drummond, F.A., 2005. Effect of cover-cropping systems on invertebrate seed predation. Weed Sci. 53, 69–76. Harrison, S., Gallandt, E.R., 2012. Behavioural Studies of Harpalus rufipes De Geer: an important weed seed predator in northeastern US agroecosystems. Int. J. Ecol. 12, doi:10.1155/2012/846546. Hawes, C., Evans, H.F., Stewart, A.J., 2013. Interference competition, not predation, explains the negative association between wood ants (Formica rufa) and abundance of ground beetles (Coleoptera: Carabidae). Ecol. Entomol. 38, 315–322. Holland, J.M., Thomas, C.F., Birkett, T., Southway, S., 2007. Spatio-temporal distribution and emergence of beetles in arable fields in relation to soil moisture. Bull. Entomol. Res. 97, 89–100. Honek, A., Martinkova, Z., Saska, P., Pekar, S., 2007. Size and taxonomic constraints determine the seed preferences of Carabidae (Coleoptera). Basic Appl. Ecol. 8, 343–353. Hothorn, T., Bretz, F., Westfall, P., 2008. Simultaneous inference in general parametric models. Biomet. J. 50, 346–363. House, G.J., Stinner, B.R., 1983. Arthropods in no-tillage soybean agroecosystems: community composition and ecosystem interactions. Environ. Manage. 7, 23–28.

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