# Pollinators in blackcurrant orchards: Spatio-temporal environmental effects and no evidence of competition with co-flowering resources

Mathieu Lachaise, Blanche Collard, Marie-Charlotte Anstett

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Mathieu Lachaise, Blanche Collard, Marie-Charlotte Anstett. Pollinators in blackcurrant orchards: Spatio-temporal environmental effects and no evidence of competition with co-flowering resources. 2026. hal-05497305

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1 **Title**

2 Pollinators in blackcurrant orchards: Spatio-temporal environmental effects and no evidence

3 of competition with co-flowering resources

4 **Author informations**

5 Mathieu Lachaiseª; Blanche Collardª; Marie-Charlotte Anstettᵇ

6

7 a Université Paris-Saclay, CNRS, AgroParisTech, UMR Ecologie Société Evolution, 91190,

8 Gif-sur-Yvette, France

9 ᵇUMR 6282 Biogéosciences, CNRS Université Bourgogne Europe 6 bd Gabriel-21 000

10 Dijon, France

11

12 **Corresponding author**

13 Mathieu Lachaise

14 IDEEV - UMR 8079 - ESE - 12 rue 128 - 91190 Gif-sur-Yvette, France

15 mathieu.lachaise.pro@gmail.com

16 ORCID: 0009-0004-7774-5219

17 **Acknowledgments**

18 We thank all the farmers who contributed to this study by sowing flowers within their orchards

19 and granting us access to their fields. We are grateful to M. Duchet-Annez, R. Perraud, M.

20 Mignot and T. Giorgi for their contribution to the data collection and we thank E. Baudry for

21 providing assistance with the revision of the article.

22
23

ABSTRACT

Agricultural intensification is threatening pollinators and associated ecosystem services. Flower strips and spontaneous floral cover are commonly recommended to support pollinators, but farmers often hesitate to adopt them, fearing competition with their crops. Here, we studied nine blackcurrant orchards in Burgundy, France, differing in local floral resources and surrounding landscape composition. We thus investigated (i) the potential competition for pollinators between blackcurrant flowers and flowers in adjacent inter-rows, and (ii) the effects of local and landscape factors through time on the abundance of five pollinator morpho-groups: *Bombus* spp., *Apis mellifera*, large bees, small bees, and hoverflies. We conducted transects in orchards at three different periods in spring to quantify the abundance of local flowers and pollinators. We characterised the landscape composition around sites within a 100 m and 500 m radii. We showed that in each morpho-group, pollinator abundance in blackcurrant bushes increased with pollinators in adjacent inter-rows and was unaffected by flower abundance there, suggesting an absence of competition. Pollinator morpho-groups responded differently to environmental factors, with variations throughout spring. Small bees were the most negatively affected by the distance from orchard edge, while hoverfly abundance highly increased with the number of flowers at the end of spring. Floral resources in the inter-row could support pollinators in spring, particularly hoverflies and poor dispersers like small bees. Given the variability in pollinator traits and rapid environmental changes, future research should focus on functional groups and fine-scale spatio-temporal analysis to better understand environmental impacts on pollinators and effectively guide conservation efforts.

**Implications for insect conservation:** Our findings highlight that conservation measures should account for guild-specific needs. We showed that small wild bees were strongly affected by distance from the orchard edge. Subdividing large blackcurrant orchards or incorporating
47 abundant wild floral resources during and beyond the blackcurrant flowering period could help
48 mitigate these constraints and facilitate movement within crops.

49 KEYWORDS

50 Floral resources - landscape composition - pollination services - agri-environment scheme –
51 agroecology

52 INTRODUCTION

53 Amid the ongoing decline in biodiversity, insects are experiencing a general loss (Wagner 2020;
54 Hailay Gebremariam 2024; Saunders et al. 2025). However, data remain insufficient for many
55 taxonomic groups (Hochkirch et al. 2021), and their conservation status has been assessed for
56 only a limited number of species (Edgar 2025). Although rare species are particularly at risk,
57 common biodiversity is also declining but remains mostly undocumented (Sánchez-Bayo and
58 Wyckhuys 2019). This loss translates into a decline in associated ecological services.
59 Interestingly, the first report of the Intergovernmental Science-Policy Platform on Biodiversity
60 and Ecosystem Services (IPBES, 2016) is related to pollination, which is threatened in many
61 ways (Potts et al. 2016). Pollination is a crucial ecological process that sustains both natural
62 and agricultural ecosystems, directly influencing food production, quality and security for both
63 humans and livestock and thereby supporting human well-being (Potts et al. 2016; Katumo et
64 al. 2022. Approximately 90% of flowering plants are pollinated by animals (Ollerton et al.
65 2011), while the yields of 28-61% of crop systems worldwide are pollinator limited nowadays
66 (Turo et al. 2024).

67 In this context, bees and hoverflies are essential crop pollinators (Klein et al. 2007; Doyle et al.
68 2020). Species within these taxa exhibit diverse ecological requirements (Doyle et al. 2020;
69 Tschanz et al. 2023) and may visit distinct flower assemblages, whether wild or cultivated
70 (Dellinger 2020; Junqueira et al. 2022). This functional diversity enhances the spatial and
temporal complementarity of pollination and is crucial for maintaining the productivity and
71
72 stability of natural and agricultural ecosystems (Klein et al. 2007; Junqueira et al. 2022) as well
73 as the resilience of pollination networks (Bascompte and Scheffer 2023). However, agricultural
74 intensification, leading to the destruction of natural habitats and the increasing use of
75 insecticides and pesticides worldwide (FAO 2024), has been identified as a major driver of
76 pollinator population declines (Dicks et al. 2020; Hailay Gebremariam 2024).

77 Increasing floral resources (spontaneous or cultivated) in agricultural plots is a common
78 measure undertaken to support wild pollinator communities and maintain pollination services
79 (Campbell et al. 2017; Knapp et al. 2019; Albrecht et al. 2020). Many studies demonstrated the
80 positive impact of these measures on pollinator communities (Feltham et al. 2015; Buhk et al.
81 2018; Knapp et al. 2019), but their effectiveness remains highly variable: it tends to improve
82 with the duration since the implementation of these flowering resources (Lowe et al. 2021;
83 Schmied et al. 2022), the coverage and functional diversity of flowers (Balzan et al. 2014;
84 Schoch et al. 2022; but see Uyttenbroeck et al. 2017) and along field margins (Campbell et al.
85 2017). However, the expected associated increase in crop pollination is not always observed
86 (Campbell et al. 2017; Albrecht et al. 2020; Azpiazu et al. 2020). These inconsistencies in
87 pollination benefits may stem from factors such as pollinator identity and behavior (e.g. floral
88 preferences), or competition for pollinator visits between crops and non-crop flowers, whether
89 they are spontaneous or sown (Desaegher et al. 2021; Carturan et al. 2023).

90 While increasing local flowering resources may benefit pollinator communities, pollinators also
91 respond to landscape factors, such as landscape configuration (e.g., mean field size, field edge
92 density, distance from semi-natural habitats), composition (e.g., area of flowering / non
93 flowering crops and semi-natural habitats) and heterogeneity (i.e., crop diversity) (Jauker et al.
94 2009; Sirami et al. 2019; Bottero et al. 2023; Priyadarshana et al. 2024; Neira et al. 2024).

95 Additionally, pollinator communities fluctuate over time due to seasonal dynamics (Rohde and

96 Pilliod 2021; Encinas-Viso et al. 2023; Schulte et al. 2025) and agricultural landscapes change

97 with the dynamics of spontaneous floral communities and the blooming of mass-flowering

98 crops (Eeraerts et al. 2021; Maurer et al. 2022; Ammann et al. 2024). However, the interactive

99 effects of these spatio-temporal changes are often overlooked (Senapathi et al. 2017).

100 Blackcurrants (*Ribes nigrum* L.), particularly the traditional variety of *Noir de Bourgogne*, are

101 highly dependent on bee pollination for fruit production (Anstett et al. 2019). Following modern

102 selection in the 1980s, only four remnant clones of this variety remain, co-planted with 15-20%

103 of a pollen donor variety, typically *Royal de Naples*, to ensure cross-pollination (Anstett et al.

104 2019). Blackcurrants bloom in early spring, and their flowers are small, bell-shaped and have a

105 fairly small opening that limits access to pollen and nectar for the largest bees. Main visitors

106 are *Bombus* spp., *Apis mellifera* and *Andrena* spp. (Anstett et al. 2019; Mignot 2023). However,

107 *Bombus* spp. and *Apis mellifera* are not faithful pollinators of blackcurrant, as they prefer more

108 accessible crop resources (e.g., rapeseed, mustard, cherry). Faced with a sharp decline in

109 blackcurrant yields since 2015, farmers are currently developing an agroecological system in

110 which blackcurrant pollination is supported by both Osmia bicornis reared on the farm and

111 enhanced floral resources in the inter-rows, either spontaneous (by avoiding mowing) or sown

112 flower strips with local wildflowers. A barrier to adopting these measures to enhance floral

113 display is farmers' concern about potential competition for pollinators between blackcurrant

114 and inter-row flowers. If pollinators are preferentially attracted to alternative flowering

115 resources in agricultural orchards, this could further reduce the already insufficient pollination

116 of blackcurrants. The literature remains inconclusive on why alternative floral resources

117 sometimes enhance crop pollination through a spillover effect or, conversely, divert pollinators

118 away from the crop (Dornhaus and Houston 2024).
Here, we present findings based on surveys of five pollinator morpho-groups (Bombus spp., Apis mellifera, large wild bees, small wild bees, and hoverflies) conducted in nine blackcurrant orchards. We also recorded floral resources in the inter-rows and characterised landscape composition around each site. Blackcurrant blooms early in spring, and both pollinator and flower communities change markedly during its 3-4 week flowering period. To capture this temporal variation, we sampled pollinators in each orchard three times. We then analysed the effects of the local environment, including distance to the field margin and inter-row floral resources, as well as landscape composition, on pollinator morpho-groups during three periods in spring 2023. Our analysis addresses the following questions: (i) Is there competition for pollinators between blackcurrant flower and nearby co-flowering resources in the inter-rows? (ii) Which local and landscape variables can predict the abundance of different wild pollinator morpho-groups in orchards throughout the spring season? (iii) Do these predictors vary between morpho-groups and over time?

# 132 MATERIAL AND METHODS

## 133 Study sites

We collected data from nine blackcurrant orchards (also named sites) managed by farmers participating in the pollinator restoration project in Burgundy, France. Orchard size varied from 1.6 to 13.6 ha, with blackcurrant bushes (Ribes nigrum varieties: *Noir de Bourgogne*, *Royal de Naples* and *Andorine*) of different ages (3-13 years) planted in rows. In each orchard, flower strips were established in selected inter-rows with the perspective of enhancing future floral resources: in spring 2022 at four orchards and in autumn 2022 or spring 2023 at the remaining five orchards. The flowers sown in spring 2022 provided an enhanced floral resource, notably during the second half of blackcurrant bloom, while flowers sown in autumn 2022 and spring 2023 developed more slowly and flowered only after the end of our study. This resulted in
variation in floral abundance, both spontaneous and sown, within and between the orchards (see
Fig. S1 and section “Floral survey”). This mix (“mélange Cassis”, supplied by Nungesser)
consisted of 20% local wildflowers to provide resources for pollinators and 80% grass species
selected for their low competitiveness, thus aiming to avoid soil erosion, provide ground
bearing capacity, and ensure the longevity of the flower strips (Pfiffner et al. 2019). See Table
S1 for details on the seed mix composition and how the species were selected. In addition, the
flowering species were chosen for their varied phenologies to provide resources for wild
pollinators from the peak of blackcurrant flowering to September. To support pollination before
the restoration of wild pollinator populations, farmers also placed 700 Osmia bicornis cocoons
and a nesting box in the middle of the flower strips. A previous study by Anstett et al. (2022)
showed a 20-40% increase in blackcurrant yield within an 80 m radius of these nesting boxes.

154 Characterisation of the landscape composition

155 We characterised the landscape composition around the blackcurrant orchards using buffer
156 zones at both small (100 m radius) and medium (500 m radius) scales (Steffan-Dewenter et al.
157 2002). These two scales were chosen because the typical foraging distance of wild bees is
158 usually a few hundred meters, with variability between species (Zurbuchen et al. 2010; Kendall
159 et al. 2022). Given the complexity of the agricultural and semi-urban areas surrounding the
160 orchards, we manually characterised the landscape composition through photo-interpretation
161 using the Google Satellite 2023 layer in QGIS software (version 3.22, Białowieża), followed
162 by field verification (Fig. S2, which includes detailed maps of the landscape around the nine
163 orchards). This approach enabled us to identify four main landscape categories likely to
164 influence flower-visiting insects: natural and semi-natural habitat (e.g., forest, hedgerows,
165 grassland, aquatic environments), impervious surfaces (e.g., concrete surfaces and dwellings,
166 including anthropogenic mineral surfaces), mass flowering crops (crops in bloom during our
167

study) and non-flowering crops (crops not in bloom during our study). Table S2 gives further
information on each landscape category.

168

169

The nine orchards were distributed along a landscape gradient, ranging from intensive
agricultural landscapes characterised by a high proportion of large fields (Fig. 1a,c; Fig. S2) to
semi-natural and urban landscapes with a smaller crop proportion (Fig. 1b,c; Fig. S2).

170

171

<figure><img src="image_2.png" /></figure>

172

173

**Fig. 1** Maps of landscape composition within a 500 m radius for (a) Site 2, an intensive agricultural landscape and (b) Site 1, a more urban and semi-natural habitat landscape. White dots correspond to the central point of our experimental design in blackcurrant orchards. (c) Proportional area of each landscape category within a 500 m radius across the nine sites

174

175

176

177

**Experimental design implemented in blackcurrant orchards**
In each orchard, we delimited five 25 m sections where we conducted transects to sample flowers and pollinators in the inter-row spaces supplemented with floral resources (inter-row transect with sown and/or spontaneous flowers; Fig. 2) and pollinators in the adjacent blackcurrant rows (blackcurrant transect). Two sections were located at opposite edges of the orchard (0-25 m), two further inside (35-60 m), and the last at the centre of the inter-row (Fig. 2). We then replicated the same design in an inter-row with natural ground vegetation, and thus not supplemented with floral resources, as far as possible from the flower strip (56-149 m depending on orchard configuration). Flower abundance in the inter-row supplemented with flowers varied with the year of implementation and sampling date and was not consistently higher than in the inter-row with natural ground vegetation.

<figure><img src="image_3.png" /><figcaption>**Fig. 2** Experimental setup implemented in the nine blackcurrant orchards. Blue rectangles represent the sections where the surveys were conducted, both in the inter-row spaces (inter-row transect) and within the blackcurrant rows (blackcurrant transect): Edge section (0-25 m), Further inside section (35-60 m) and Centre section (distance from 2 to 180 m depending on</figcaption></figure>
192 plot configuration). As the blackcurrant orchard at Site 7 was too small, the central section was
193 excluded from all analyses

194 **Plant and pollinator surveys**

195 Data collection occurred during the blackcurrant flowering period between 19 Apr 2023 and
196 12 May 2023, under conditions suitable for pollinator activity: between 10:00 am and 4:00 pm
197 on sunny or brightly overcast days with temperatures above 13 °C. These conditions are not
198 easily met in early spring in Burgundy. By visiting the fields on every suitable day, we managed
199 to sample each orchard on three different dates or sampling rounds (beginning, middle, and late
200 blackcurrant flowering) to evaluate the effects of both local and landscape factors throughout
201 the flowering season.

202 **Floral survey**

203 Because only the flower strips sown in spring 2022 bloomed during our survey period (Fig.
204 S1), we could not compare inter-row transects with and without supplementary flowers. We
205 therefore focused on the effect of the number of floral units on pollinators. On each sampling
206 date, we counted the number of floral units in every inter-row transect for all flowering species,
207 excluding Poaceae. We defined a floral unit as an individual flower or inflorescence that
208 required small pollinators to take flight to move to another unit (Baldock et al. 2015).
209 Specifically, inflorescences in capitula (e.g., Asteraceae) and spike-shaped inflorescences (e.g.,
210 *Onobrychis viciifolia*) were considered single floral units. Plants were identified to the species
211 level, or to the genus level in cases of uncertainty (e.g., *Ranunculus* spp., *Taraxacum* spp.,
212 *Veronica* spp.). For species not included in our seed mix, we used the PlantNet and iNaturalist
213 applications to confirm identification and ensure that they had been previously observed in the
region. The flowering plants identified to genus or species level and observed in inter-row
transects within orchards are provided in Table S3.

## Pollinator survey

Pollinators flying or foraging on flowers were recorded along each section for 1 minute, first in inter-row and then in blackcurrant transects (Fig. 2). Depending on the orchard exposure, we arbitrarily selected the adjacent blackcurrant rows to the right or left of the inter-row spaces to minimise the potential effects of sun exposure. All observations were conducted by the same person (ML). Pollinators were classified into eight easily identifiable morpho-groups: *Bombus* spp., *Apis mellifera*, large wild bees (>10 mm), small wild bees (<10 mm), parasitic bees, hoverflies, bee flies and butterflies. The Western honeybee, *Apis mellifera*, is classified as a distinct group among large wild bees due to the significant influence of human management on its distribution. We also excluded *Osmia bicornis* since their abundance will be related to the distance to the nesting boxes. These eight morpho-groups differ on account of their functional traits (e.g., body size, diet requirement), which can lead to different responses to local and landscape factors in agricultural environments (Jauker et al. 2009; MacInnis et al. 2020; Ockermüller et al. 2023).

## Statistical analysis

All data analyses were conducted in R (R core team 2023, Version 4.3.2).

## Competition or facilitation for pollinators among the blackcurrant bushes and nearby floral resources

For each morpho-group (*Bombus* spp., *Apis mellifera*, large wild bees, small wild bees and hoverflies), we tested the effect of both pollinator and flower abundance in the inter-row transects on pollinator abundance in the blackcurrant transects. We expected competition for
pollinators between co-flowering resources if pollinator abundance in the blackcurrant transects decreased with increasing flower abundance, whereas a positive relationship would suggest facilitation. We performed a generalised linear mixed model for each morpho-group with a Poisson distribution and log link function (glmmTMB package, Brooks et al. 2017) and orchard as a random factor.

## 242 Effect of the local and landscape factors on pollinator abundance

To study the impact of local and landscape factors (at 100 m and 500 m radii) on pollinator abundance, we focused on data from the inter-row transects, excluding those from blackcurrant transects, where the lower detection rate of pollinators could lead to less accurate assessments of actual abundance. We also excluded transects from the centre section, as the landscape within a 100 m radius was almost entirely composed of blackcurrant crops, particularly in large orchards. A model was fitted for each sampling round and for the following morpho-groups: *Bombus* spp., large wild bees, small wild bees, and hoverflies. No model was fitted for *Apis mellifera*, due to the predominant influence of nearby beehives, or for butterflies, parasitic bees, and bee flies, owing to their low abundance (n = 38, n = 8, and n = 1, respectively). For each morpho-group and sampling round, we used the *glmulti()* function (*glmulti* package, Calcagno and Mazancourt 2010) to select the combination of local and landscape variables (Table 1) that minimized the Akaike information criterion (AIC) for each GLMM (Poisson distribution with log link), with orchard (n = 9) included as a random factor. Given the strong correlation between impervious surface and semi-natural habitat within 500 m (Pearson's r = 0.81), we did not include impervious surface in model selection, as it exhibited lower variability among sites, providing less informative contrasts (Fig. 1, Table 1).

To address the substantial differences in scale among the environmental variables (e.g., mean and standard deviation of flower abundance were much smaller than those of the landscape
261 variables at 500 m), all quantitative explanatory variables were standardised using the *scale()* function.
262

263 **Table 1** Description and values of the explanatory variables used in the models, except
264 impervious surface within 500 m, which was removed due to its high correlation with semi-
265 natural habitat (Pearson's r = 0.81). For each quantitative variable, the mean, standard deviation
266 (S.D.), minimum (Min.) and maximum (Max.) values are presented, except for Edge distance,
267 which is categorical. Flower abundance is described only for sampling round 1, as it remains
268 consistent across all three rounds. Similarly, landscape variables are described only for the 100
269 m radius, as they are identical at the 500 m radius
270

<table><thead><tr><th>Scale</th><th>Variable</th><th>Description</th><th>Mean (± S.D.)</th><th>Min.</th><th>Max.</th></tr></thead><tbody><tr><td rowspan="4">Local variables</td><td>Edge distance</td><td>Distance from the orchard edge where flowers and pollinators were sampled (Edge vs Further inside)</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Flower abundance Sampling round 1</td><td>Number of floral units in each transect (count)</td><td>115 (± 260)</td><td>0</td><td>1,405</td></tr><tr><td>Flower abundance Sampling round 2</td><td>-</td><td>79 (± 117)</td><td>0</td><td>556</td></tr><tr><td>Flower abundance Sampling round 3</td><td>-</td><td>170 (± 372)</td><td>0</td><td>2,097</td></tr><tr><td rowspan="4">Landscape variables 100 m</td><td>Semi-natural habitat surface</td><td>Total area of woods, hedgerows, grasslands and aquatic environments (m²)</td><td>7,097 (± 5,080)</td><td>0</td><td>20,448</td></tr><tr><td>Impervious surface</td><td>Total area of dwellings, concrete surfaces and anthropogenic mineral surfaces (m²)</td><td>1,010 (± 1,741)</td><td>0</td><td>10,368</td></tr><tr><td>Flowering crop surface</td><td>Total area of crops in bloom during our study (m²)</td><td>18,425 (± 4,746)</td><td>9,553</td><td>29,818</td></tr><tr><td>Non-flowering crop surface</td><td>Total area of crops not in bloom during our study (m²)</td><td>4,947 (± 5,587)</td><td>0</td><td>19,324</td></tr></tbody></table>
<table><tr><td rowspan="4">Landscape variables 500 m</td><td>Semi-natural habitat surface</td><td>-</td><td>308,968 (± 132,399)</td><td>42,367</td><td>507,382</td></tr><tr><td>Impervious surface</td><td>-</td><td>49,205 (± 37,410)</td><td>7,047</td><td>102,538</td></tr><tr><td>Flowering crop surface</td><td>-</td><td>162,995 (± 105,207)</td><td>51,535</td><td>354,917</td></tr><tr><td>Non-flowering crop surface</td><td>-</td><td>265,718 (± 134,199)</td><td>0</td><td>440,337</td></tr></table>

271

## 272 Evaluation of model quality

We tested for residual overdispersion and zero inflation using the TestDispersion() and testZeroInflation() functions in the DHARMa package (Hartig 2022). We used a negative binomial distribution (family nbinom2 with log link function) when overdispersion was detected. No sign of zero inflation was observed in our models. To ensure that the explanatory variables were not collinear, we calculated variance inflation factors (VIFs) using the check_collinearity() function from the Performance package (Lüdecke et al. 2021). We removed all variables with a VIF > 3 from the final models (Zuur et al. 2010). We calculated the coefficient of determination R2<sub>GLMM</sub> following Nakagawa et al. (2017).

## 281 RESULTS

### 282 Pollinator communities observed in blackcurrant orchards

A total of 1,962 pollinators were observed during our survey, corresponding to an average of ~4 individuals per minute: small wild bees (624 individuals), *Apis mellifera* (415), hoverflies (361), large wild bees (264), *Bombus* spp. (251), butterflies (38), parasitic bees (8) and bee flies (1). We identified 46% of these individuals to the genus level: *Apis* (415), *Bombus* (251), *Andrena* (194), *Halictus* (15), *Anthophora* (7), *Lasioglossum* (7), *Nomada* (6), *Sphecodes* (2), *Colletes* (1) and *Eucera* (1) (Table S4). We only observed seven *Andrena fulva*, which was just
289 as abundant as *Bombus* spp. and *Apis mellifera* in an unpublished pollinator census on
290 blackcurrant orchards in 1981 (Anstett et al. 2019).

291 Excluding *Apis mellifera*, whose presence is probably due to the proximity of hives (Sites 2, 7
292 and 8), the most represented morpho-group was small wild bees (32% of pollinators), followed
293 by hoverflies, large wild bees and *Bombus* spp. (accounting for 18%, 13% and 13% of
294 pollinators, respectively). We observed very few butterflies and parasitic bees. This trend was
295 consistent across all sites (Fig. 3), except at Site 2 where hoverflies were the dominant group
296 (73 individuals observed versus 34 small wild bees). Additionally, pollinator abundance and
297 morpho-group distribution varied highly between sites. We recorded the lowest number of
298 individuals at Site 5 and the highest at Site 7. However, excluding *Apis mellifera*, the maximum
299 number of individuals was observed at Site 4, which also exhibited the highest number of small
300 wild bees and *Bombus* spp. (Fig. 3).

<figure><img src="image_4.png" /></figure>
Fig. 3 Total abundance of each morpho-group observed across the nine sites. Sites are organised in ascending order according to the number of small wild bees, the most abundant morpho-group in our study

Pollinator abundance in blackcurrant bushes increases with that in
adjacent inter-rows but not with flower abundance

Generalised linear mixed models indicate that the number of pollinators in blackcurrant transects significantly increased with the number of pollinators in the adjacent inter-row transects for all morpho-groups (Fig. 4; see Table S5 for complete model results): *Apis mellifera* (Estimate = 0.1 ± 0.05, *P* = 0.025), *Bombus* spp. (Estimate = 0.27 ± 0.08, *P* = 0.00084), large wild bees (Estimate = 0.33 ± 0.08, *P* < 10⁻⁴), small wild bees (Estimate = 0.14 ± 0.05, *P* = 0.0091) and hoverflies (Estimate = 0.35 ± 0.06, *P* < 10⁻⁴). However, the number of flowers in the inter-row transects had no significant effect on the number of pollinators in blackcurrant crops: *Bombus* spp. (*P* = 0.11), *Apis mellifera* (*P* = 0.33), large wild bees (*P* = 0.39), small wild bees (*P* = 0.69) and hoverflies (*P* = 0.64).

<figure><img src="image_5.png" /></figure>

315
Fig. 4 Pollinator abundance in the blackcurrant bushes (blackcurrant transect) compared to pollinator abundance in adjacent inter-row spaces (inter-row transect) for *Apis mellifera* (light gray), *Bombus* spp. (yellow), large wild bees (dark blue), small wild bees (light blue) and hoverflies (dark gray). See Table S4 for the complete model results

Effect of local and landscape factors on pollinator abundance varies between morpho-groups and sampling rounds

The morpho-groups responded differently to local and landscape variables, with variations observed between sampling rounds within the same morpho-group (Table 2; see Table S6 for complete model results). Overall, pollinators were mostly impacted by the local variables except for *Bombus* spp. Landscape variables, both at 100 m and 500 m radius, were rarely significant for all morpho-groups. However, when significant, the effects generally indicated facilitation by favourable habitats within the landscape rather than dilution. Flowering crop surface and semi-natural habitat area had a positive effect on pollinator abundance in blackcurrant orchards (except for *Bombus* spp. during sampling round 3; see Table 2 and Table S6). In contrast, non-flowering crop area and impervious surface area had a negative effect (except for hoverflies during sampling round 1; see Table 2 and Table S6). Within a 100 m radius, semi-natural habitat area and impervious surface area were never significant, nor was flowering crop area within a 500 m radius (Table S6).

**Table 2** Final models selected based on Akaike information criterion for *Bombus* spp., large wild bees, small wild bees and hoverflies in each sampling round. “n” indicates the total number of pollinators counted at each sampling round. Only variables significant in at least one model are included: Flw ab (Flower abundance), Distance (Distance from the orchard edge), Flw crop (Flowering crop surface), Non flw crop (Non-flowering crop surface), SNH (Semi-natural habitat), Imper (Impervious surface). Estimates are provided (*P* < 0.05*, *P* < 0.01**, *P* <
0.001***), with positive effects shown in green and negative effects in red. Non-significant effects are represented by dots. R² (R²m) values are reported, except for large wild bees in sampling round 3, as none of the tested variables influenced them. See Table S6 for complete model results

<table><thead><tr><th rowspan="2">Morpho groups</th><th rowspan="2">Sampling rounds</th><th colspan="2">Local</th><th colspan="2">Landscape 100 m</th><th colspan="2">Landscape 500 m</th><th rowspan="2">R²m</th></tr><tr><th>Flw ab</th><th>Distance</th><th>Flw crop</th><th>Non flw crop</th><th>SNH</th><th>Non flw crop</th></tr></thead><tbody><tr><td rowspan="3">Bombus spp.</td><td>1<br>(n = 39)</td><td>.</td><td>.</td><td>0.38*</td><td>.</td><td>.</td><td>.</td><td>0.11</td></tr><tr><td>2<br>(n = 33)</td><td>.</td><td>.</td><td>.</td><td>.</td><td>.</td><td>.</td><td>0.05</td></tr><tr><td>3<br>(n = 44)</td><td>.</td><td>.</td><td>.</td><td>.</td><td>-0.47*</td><td>.</td><td>0.11</td></tr><tr><td rowspan="3">Large wild bee</td><td>1<br>n = 45)</td><td>.</td><td>-0.86**</td><td>.</td><td>-0.66**</td><td>.</td><td>.</td><td>0.17</td></tr><tr><td>2<br>(n = 51)</td><td>.</td><td>.</td><td>.</td><td>.</td><td>.</td><td>.</td><td>0.13</td></tr><tr><td>3<br>(n = 32)</td><td>.</td><td>.</td><td>.</td><td>.</td><td>.</td><td>.</td><td>.</td></tr><tr><td rowspan="3">Small wild bee</td><td>1<br>(n = 71)</td><td>0.25*</td><td>-1.20***</td><td>.</td><td>.</td><td>.</td><td>.</td><td>0.22</td></tr><tr><td>2<br>(n = 102)</td><td>.</td><td>-0.92***</td><td>.</td><td>.</td><td>0.35*</td><td>.</td><td>0.28</td></tr><tr><td>3<br>(n = 111)</td><td>.</td><td>-0.97***</td><td>0.39 ***</td><td>.</td><td>.</td><td>.</td><td>0.21</td></tr><tr><td rowspan="3">Hoverfly</td><td>1<br>(n = 17)</td><td>.</td><td>.</td><td>.</td><td>.</td><td>.</td><td>1.12**</td><td>0.06</td></tr><tr><td>2<br>(n = 33)</td><td>.</td><td>-0.83*</td><td>.</td><td>.</td><td>.</td><td>.</td><td>0.09</td></tr><tr><td>3<br>(n = 128)</td><td>0.34***</td><td>.</td><td>.</td><td>.</td><td>.</td><td>.</td><td>0.58</td></tr></tbody></table>

Bombus spp. abundance

Bumblebee abundance was influenced by the landscape during the first and third sampling rounds. Their abundance slightly increased with the flowering crop surface within a 100 m radius (Estimate = 0.38 ± 0.16, P = 0.018) and decreased with the semi-natural habitat surface
349 within a 500 m radius (Estimate = -0.47 ± 0.24, *P* = 0.048). Their abundance was never
350 associated with the local environment (Table 2, Table S6).

351 **Large wild bee abundance**

352 The abundance of large wild bees depended on the local and landscape variables only during
353 the first sampling round. Their abundance substantially decreased with the distance from the
354 edge orchard (Estimate = -0.86 ± 0.32, *P* = 0.0077) and with the non-flowering crop surface
355 within 100 m (Estimate = -0.66 ± 0.24, *P* = 0.0053) (Table 2, Table S6).

356 **Small wild bee abundance**

357 Small bee abundance decreased significantly with the distance from the orchard edge in each
358 sampling round (consistently *P* < 10⁻⁴). Their abundance also slightly increased with flower
359 abundance during the first sampling round (Estimate = 0.25 ± 0.11, *P* = 0.017) and varied with
360 other landscape variables: positively correlated with the area of semi-natural habitats within
361 500 m during the second sampling round (Estimate = 0.35 ± 0.15, *P* = 0.018) and positively
362 correlated with the area of flowering crops within 100 m during the third sampling round
363 (Estimate = 0.39 ± 0.10, *P* = 0.00015) (Table 2, Table S6).

364 **Hoverfly abundance**

365 Hoverfly abundance increased with the non-flowering crop surface within 500 m during the
366 first sampling round (Estimate = 1.12 ± 0.38, *P* = 0.0034). Their abundance was influenced by
367 the local environment: negatively correlated with distance from the edge during the second
368 sampling round (Estimate = -0.83 ± 0.38, *P* = 0.028) and positively correlated with flower
369 abundance during the third sampling round (Estimate = 0.34 ± 0.09, *P* < 10⁻⁴) (Table 2, Table
370 S6).
371 **DISCUSSION**

372 The addition of floral resources within and around crop fields is often recommended to support
373 pollinators in fragmented agricultural landscapes. However, farmers may be concerned about
374 potential competition between these floral resources and their crops. Here, we show that (i) the
375 pollinator abundance in blackcurrant transects does not vary with nearby flower abundance but
376 instead increases with pollinator abundance in adjacent inter-row transects, a pattern that
377 remains consistent across all morpho-groups: *Bombus* spp., *Apis mellifera*, large wild bees,
378 small wild bees and hoverflies. Moreover, we found that (ii) pollinator morpho-groups in inter-
379 row transects responded differently to local and landscape environmental factors surrounding
380 blackcurrant orchards and that (iii) these responses changed rapidly throughout spring within
381 the same morpho-groups. Notably, small wild bees were the only group strongly affected by
382 the distance from the orchard edge in all sampling rounds. Hoverfly abundance substantially
383 increased with the number of flowers at the end of spring.

384 **Absence of competition for pollinators between blackcurrant bushes**
385 **and nearby floral resources**

386 We identified a positive relationship between pollinator abundance in blackcurrant bushes and
387 adjacent inter-row transects for each pollinator morpho-group. Our results also showed that
388 pollinator abundance in blackcurrant transects does not vary with the abundance of flowers in
389 adjacent inter-row transects. This suggests that (i) there is neither competition nor facilitation
390 for pollinators between blackcurrant bushes and nearby floral resources and that (ii) in
391 blackcurrant orchards, other environmental factors such as field structure and landscape
392 composition have a greater impact on pollinator distribution rather than nearby flower
393 abundance. Klein et al. (2012) reported higher visitation frequencies of wild bees and hoverflies
on almond flowers in orchards adjacent to riparian vegetation strips and in those located in landscapes containing a greater proportion of semi-natural habitat. This highlights the importance of providing suitable habitats that offer not only floral resources but also nesting and mating sites for pollinators in order to enhance potential pollination services (Bailey et al. 2014). Indeed, models developed by Desaegher et al. 2021 and Nicholson et al. 2019 predicted that while adding co-flowering resources near crops can potentially lead to competition for pollinators, this effect can be significantly reduced or even reversed when nesting sites are provided.

The absence of a relationship between pollinator abundance in blackcurrant bushes and nearby flower abundance may be due to the relatively low number of flowers in the inter-row compared to the number of blackcurrant flowers despite their potentially greater attractiveness for several pollinator species. Indeed, several blackcurrant farmers in this study usually sow grass mixtures to limit the presence of wild flowering plants in the inter-rows. Furthermore, only the flower strips sown in spring 2022 bloomed, predominantly during the third sampling round (Fig. S1). Flower strips may take time to become effective due to either the delay required to provide sufficient resources, or the time needed for pollinators to colonise the habitats (Blaauw and Isaacs 2014; Schmied et al. 2022; but see Albrecht et al. 2021). This study documented the relationship between flower availability and pollinator abundance at the beginning of a longer study on pollinator restauration. It would be interesting to determine in the following years whether facilitation or competition occurs when nearby flowers become more abundant and whether other environmental factors continue to primarily drive the distribution of pollinator communities in blackcurrant bushes. Moreover, we used pollinator abundance, related to pollination service capacity (Bartholomée and Lavorel 2019), to analyse the potential competition for pollination between blackcurrant bushes and nearby co-flowering resources.
418 To better understand this relationship, measuring blackcurrant fruit traits (e.g., fruit set, weight,
419 sugar content) would be relevant to provide more direct insights into this potential competition.

420 **Effect of local and landscape factors on pollinator abundance varies**
421 **between morpho-groups**

422 Our results showed that pollinator morpho-groups responded differently to local and landscape
423 environmental factors in blackcurrant orchards. *Bombus* spp. was the only morpho-group whose
424 abundance did not vary with local factors (flower abundance and distance from the orchard
425 edge). This pattern may be explained by the ability of bumblebees to forage over long distances
426 across diverse floral resources and their relatively flexible nesting site requirements compared
427 to other pollinators (Westphal et al. 2003; but see Redhead et al. 2016). The study by Westphal
428 et al. 2003 in Germany specifically showed that bumblebees depend on resource availability at
429 a broad landscape scale (2,500-3,000 m radius). In our study, we focused our analysis on
430 smaller scales of 100 m and 500 m radii. To further investigate the landscape effects on *Bombus*
431 spp., it would be interesting to examine the influence of landscape composition at broader
432 spatial scales.

433 Among local factors, morpho-group abundance was mainly driven by the distance from the
434 orchard edge, especially for small wild bees. It is the only morpho-group whose abundance
435 decreased drastically beyond 35 m from the orchard edge across all sampling rounds. MacInnis
436 et al. 2020 also reported a significant decline in small wild bee abundance in the centre of
437 strawberry fields, while *Apis mellifera* and larger wild bees remained unaffected. This pattern
438 may be explained by the limited foraging range of small wild bees (Greenleaf et al. 2007),
439 which restricts their ability to disperse from the orchard margins toward the interior contrary to
440 larger bees.
Our results indicated that hoverflies were the only morpho group positively associated with the area of non-flowering crops within a 500 m radius during the first sampling round. This trend could be explained by the presence of crop-dwelling hoverflies such as *Episyrphus balteatus*, whose larvae feed on aphids unlike bees that only rely on nectar and pollen (Doyle et al. 2020). Aphids, often highly abundant in cereal crops (Thies et al. 2005), may thus benefit crop-dwelling hoverfly species in such landscapes (Meyer et al. 2009; Raymond et al. 2014). These results are in line with the study of Desaegher et al. 2023, which highlighted the maximum species richness of hoverflies in agricultural-dominated landscapes in contrast to bees.

## Effect of local and landscape factors on pollinator abundance varies between sampling rounds

Beyond the influence of local and landscape environmental factors, our study also highlights that their effects on pollinator morpho-groups vary throughout the spring season. Notably, hoverfly abundance increased significantly with flower abundance but only during the third sampling round. During this period, hoverfly abundance was approximately four to seven times higher than during the first and second sampling rounds (from *n* = 17 and *n* = 33 to *n* = 128; Table 2). Simultaneously, many flowers bloomed, both from the seed mix sown in spring 2022 and from the natural vegetation such as *Leucanthemum vulgare* and *Matricaria* spp.. These plant species have large inflorescences and shallow open flowers, traits that favour hoverfly visits (Branquart and Hemptinne 2000), particularly the highly abundant crop-dweller *Episyrphus balteatus* due to its short proboscis (Schirmel et al. 2018; Doyle et al. 2020). These results indicate that the benefits of both spontaneous and sown floral resources for pollinators may vary throughout the season, depending on flower composition (Ouvrard et al. 2018).
463

Conserving pollinators for blackcurrant farmers and implications for
future research

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Our results suggest that there is no evidence of competition or facilitation for pollinators between blackcurrant bushes and nearby co-flowering flowers. Since pollinator abundance in blackcurrant bushes and adjacent inter-rows are positively correlated, implementing agroecological measures that support pollinator communities would enhance pollinator abundance in both inter-row spaces and blackcurrant bushes. Our contrasting findings on the effects of environmental factors across pollinator morpho-groups emphasise the need for management strategies that address the specific requirements of different pollinator guilds (Jauker et al. 2009). Bee species vary in their needs for floral resources and nesting sites (Tschanz et al. 2023), and hoverflies highly depend on specific micro-habitats during their larval stage (Meyer et al. 2009; Moquet et al. 2018; Doyle et al. 2020). Given our findings on the significant decline in small wild bee abundance with distance from the orchard edge, subdividing large blackcurrant orchards or incorporating linear habitats such as woody hedgerows (Kremen et al. 2019; but see Bishop et al. 2023) or well-established flower strips (Schmied et al. 2022; von Königslöw et al. 2022) could provide ecological corridors and enhance access to the whole orchard.

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486

Future research should (i) prioritise a functional approach (Fisogni et al. 2025) by distinguishing pollinators based on functional traits (e.g., flight capacity, diet composition and specialisation, nesting strategy, sociality), which may shape their responses to crop configuration and landscape composition (Jauker et al. 2009; MacInnis et al. 2020; Ockermüller et al. 2023). (ii) The weak landscape effect observed in our results may result from our broad categories of composition. Focusing on a more detailed characterisation of landscape elements (e.g., hedgerows, isolated trees, forests, ponds) would be relevant. Finally, (iii) accounting for
487 temporal dynamics by replicating sampling at different periods of the year seems necessary
488 given the rapid changes in the agricultural environment throughout the year (Eeraerts et al.
489 2021; Ammann et al. 2024). However, these methodological strategies require a significant
490 sampling effort, considering the number of sampling points required, both spatially and
491 temporally, as well as precise data collection. Developing a citizen science project based on the
492 approach of Appenfeller et al. (2020) or Garratt et al. (2019) with the involvement of volunteer
493 farmers could effectively address this constraint while raising awareness about pollinator
494 community conservation.

495 **DECLARATION**

496 **Funding**

497 This research was supported by EIP-AGRI (EU CAP Network), FEADER, and the Bourgogne
498 Franche-Comté region through the following grants awarded to MCA: FEADER
499 RBOU160118CR0260011 (2018-2021) and FEADER RBOU160121CR0260003 (2022-2023),
500 as part of the project *Pérennité et développement de la filière cassis en Bourgogne*.

501 **Competing interests**

502 The authors declare no conflict of interest.

503 **Ethics approval**

504 Not applicable.

505 **Consent to participate**

506 Not applicable.

507 **Consent for publication**
508 Not applicable.

509 **Availability of data and material**

510 The data and material used and analysed during the current study will be made available in a
511 publicly accessible repository if the article is accepted. During the review process, reviewers
512 can request access directly from the corresponding author (ML, email:
513 mathieu.lachaise.pro@gmail.com).

514 **Code availability**

515 The codes used for the analysis will be made available in a publicly accessible repository if the
516 article is accepted. During the review process, reviewers can request access directly from the
517 corresponding author (ML, email: mathieu.lachaise.pro@gmail.com).

518 **Authors' contributions**

519 ML and MCA contributed to the study conception and design and performed the data collection
520 and analysis. The first draft of the manuscript was written by ML and MCA in consultation
521 with BC. All authors commented on previous versions of the manuscript. All authors read and
522 approved the final manuscript.

523

524 **REFERENCES**

525 Albrecht M, Kleijn D, Williams NM, et al (2020) The effectiveness of flower strips and hedgerows on pest control, pollination services and crop yield: a quantitative synthesis. Ecology Letters 23:1488-1498. https://doi.org/10.1111/ele.13576

528 Albrecht M, Knecht A, Riesen M, et al (2021) Time since establishment drives bee and hoverfly diversity, abundance of crop-pollinating bees and aphidophagous hoverflies in perennial wildflower strips. Basic and Applied Ecology 57:102-114.
529
530
531 https://doi.org/10.1016/j.baae.2021.10.003
532 Ammann L, Bosem-Baillod A, Herzog F, et al (2024) Spatio-temporal complementarity of
533 floral resources sustains wild bee pollinators in agricultural landscapes. Agriculture,
534 Ecosystems & Environment 359:108754. https://doi.org/10.1016/j.agee.2023.108754

535 Anstett M-C, Duchet-Annez M, Denis C (2022) Projet Cassis : Approche pluridisciplinaire pour
des mesures agro écologiques. Bourgogne-Franche-Comté Nature

537 Anstett M-C, Léon de Treveret M, Louapre P (2019) La pollinisation du cassis : État des lieux
dans un contexte de changements anthropiques. Bourgogne-Franche-Comté Nature
538
539 29:194-205

540 Appenfeller LR, Lloyd S, Szendrei Z (2020) Citizen science improves our understanding of the
541 impact of soil management on wild pollinator abundance in agroecosystems. PLoS ONE
542 15:e0230007. https://doi.org/10.1371/journal.pone.0230007

543 Azpiazu C, Medina P, Adán Á, et al (2020) The Role of Annual Flowering Plant Strips on a
544 Melon Crop in Central Spain. Influence on Pollinators and Crop. Insects 11:66.
545 https://doi.org/10.3390/insects11010066

546 Bailey S, Requier F, Nusillard B, et al (2014) Distance from forest edge affects bee pollinators
547 in oilseed rape fields. Ecology and Evolution 4:370-380.
548 https://doi.org/10.1002/ece3.924

549 Baldock KCR, Goddard MA, Hicks DM, et al (2015) Where is the UK's pollinator biodiversity?
550 The importance of urban areas for flower-visiting insects. Proceedings of the Royal
551 Society B: Biological Sciences 282:20142849. https://doi.org/10.1098/rspb.2014.2849

552 Balzan MV, Bocci G, Moonen A-C (2014) Augmenting flower trait diversity in wildflower
553 strips to optimise the conservation of arthropod functional groups for multiple
554 agroecosystem services. J Insect Conserv

555 Bartholomée O, Lavorel S (2019) Disentangling the diversity of definitions for the pollination
556 ecosystem service and associated estimation methods. Ecological Indicators
557 107:105576. https://doi.org/10.1016/j.ecolind.2019.105576

558 Bascompte J, Scheffer M (2023) The Resilience of Plant-Pollinator Networks. Annu Rev
559 Entomol 68:363-380. https://doi.org/10.1146/annurev-ento-120120-102424

560 Bishop GA, Fijen TPM, Desposato BN, et al (2023) Hedgerows have contrasting effects on
561 pollinators and natural enemies and limited spillover effects on apple production.
562 Agriculture, Ecosystems & Environment 346:108364.
563 https://doi.org/10.1016/j.agee.2023.108364

564 Blaauw BR, Isaacs R (2014) Flower plantings increase wild bee abundance and the pollination
565 services provided to a pollination-dependent crop. Journal of Applied Ecology 51:890-
566 898. https://doi.org/10.1111/1365-2664.12257

567 Bottero I, Dominik C, Schweiger O, et al (2023) Impact of landscape configuration and
568 composition on pollinator communities across different European biogeographic
569 regions. Front Ecol Evol 11:1128228. https://doi.org/10.3389/fevo.2023.1128228
570 Branquart E, Hemptinne J-L (2000) Selectivity in the exploitation of floral resources by hoverflies (Diptera: Syrphinae). *Ecography* 23:732-742.
571
572 https://doi.org/10.1111/j.1600-0587.2000.tb00316.x

573 Brooks M, Kristensen K, Benthem K van, et al (2017) glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling. *The R Journal*

576 Buhk C, Oppermann R, Schanowski A, et al (2018) Flower strip networks offer promising long term effects on pollinator species richness in intensively cultivated agricultural areas. *BMC Ecol* 18:55. https://doi.org/10.1186/s12898-018-0210-z

579 Calcagno V, Mazancourt C de (2010) *glmulti: An R Package for Easy Automated Model Selection with (Generalized) Linear Models*. *Journal of Statistical Software* 34:1–29.
580
581 https://doi.org/10.18637/jss.v034.i12

582 Campbell AJ, Wilby A, Sutton P, Wäckers FL (2017) Do sown flower strips boost wild pollinator abundance and pollination services in a spring-flowering crop? A case study from UK cider apple orchards. *Agriculture, Ecosystems & Environment* 239:20–29.
583
584
585 https://doi.org/10.1016/j.agee.2017.01.005

586 Carturan BS, Siewe N, Cobbold CA, Tyson RC (2023) Bumble bee pollination and the wildflower/crop trade-off: When do wildflower enhancements improve crop yield? *Ecological Modelling* 484:110447. https://doi.org/10.1016/j.ecolmodel.2023.110447

589 Dellinger AS (2020) Pollination syndromes in the 21st century: where do we stand and where may we go? *New Phytologist* 228:1193–1213. https://doi.org/10.1111/nph.16793

591 Desaegher J, Chiron F, Bessa-Gomes C (2023) Nationwide study of the triple landscape gradient across natural, agricultural and urban areas for the richness of flower-visiting insects. *Biological Conservation* 288:110355.
592
593
594 https://doi.org/10.1016/j.biocon.2023.110355

595 Desaegher J, Sheeren D, Ouin A (2021) Optimising spatial distribution of mass-flowering patches at the landscape scale to increase crop pollination. *Journal of Applied Ecology* 58:1876–1887. https://doi.org/10.1111/1365-2664.13949

598 Dicks L, Breeze T, Ngo H, et al (2020) A global assessment of drivers and risks associated with pollinator decline

600 Dornhaus A, Houston AI (2024) Optimal competitors: the balance of attraction and choices of mutualists, like pollinators, drives facilitation and may promote crop pollination

602 Doyle T, Hawkes WLS, Massy R, et al (2020) Pollination by hoverflies in the Anthropocene. *Proceedings of the Royal Society B: Biological Sciences* 287:20200508.
603
604 https://doi.org/10.1098/rspb.2020.0508

605 Edgar GJ (2025) IUCN Red List criteria fail to recognise most threatened and extinct species. *Biological Conservation* 301:110880. https://doi.org/10.1016/j.biocon.2024.110880

607 Eeraerts M, Van Den Berge S, Proesmans W, et al (2021) Fruit orchards and woody semi-natural habitat provide complementary resources for pollinators in agricultural
609 landscapes. Landscape Ecol 36:1377-1390. https://doi.org/10.1007/s10980-021-01220-y
610

611 Encinas-Viso F, Bovill J, Albrecht DE, et al (2023) Pollen DNA metabarcoding reveals cryptic diversity and high spatial turnover in alpine plant-pollinator networks. Molecular Ecology 32:6377-6393. https://doi.org/10.1111/mec.16682

614 FAO (2024) *Pesticides use and trade – 1990–2022*. FAOSTAT Analytical Briefs, No. 89.
615 Rome.
616

617 Feltham H, Park K, Minderman J, Goulson D (2015) Experimental evidence that wildflower strips increase pollinator visits to crops. Ecology and Evolution 5:3523-3530.
618
619 https://doi.org/10.1002/ece3.1444

620 Fisogni A, Piquot Y, Michez D, et al (2025) Biotic homogenization and functional restructuring of bee communities in northern France: implications for conservation priorities. Biodivers Conserv 34:987-1013. https://doi.org/10.1007/s10531-024-03005-6

623 Garratt MPD, Potts SG, Banks G, et al (2019) Capacity and willingness of farmers and citizen scientists to monitor crop pollinators and pollination services. Global Ecology and Conservation 20:e00781. https://doi.org/10.1016/j.gecco.2019.e00781

626 Greenleaf SS, Williams NM, Winfree R, Kremen C (2007) Bee foraging ranges and their relationship to body size. Oecologia 153:589-596. https://doi.org/10.1007/s00442-007-0752-9

629 Hailay Gebremariam G (2024) A Systematic Review of Insect Decline and Discovery: Trends, Drivers, and Conservation Strategies over the past Two Decades. Psyche: A Journal of Entomology 2024:5998962. https://doi.org/10.1155/2024/5998962

632 Hartig, F. (2022) DHARMA: residual diagnostics for hierarchical (multi-level/mixed) regression models. R package version 0.4. 6.

635 Hochkirch A, Samways MJ, Gerlach J, et al (2021) A strategy for the next decade to address data deficiency in neglected biodiversity. Conservation Biology 35:502-509.
636
637 https://doi.org/10.1111/cobi.13589

638 Jauker F, Diekötter T, Schwarzbach F, Wolters V (2009) Pollinator dispersal in an agricultural matrix: opposing responses of wild bees and hoverflies to landscape structure and distance from main habitat. Landscape Ecol 24:547-555.
639
640
641 https://doi.org/10.1007/s10980-009-9331-2

642 Junqueira CN, Pereira RAS, da Silva RC, et al (2022) Do Apis and non-bees provide a similar contribution to crop production with different levels of pollination dependency? A review using meta-analysis. Ecological Entomology 47:76-83.
643
644
645 https://doi.org/10.1111/een.13092

646 Katumo DM, Liang H, Ochola AC, et al (2022) Pollinator diversity benefits natural and agricultural ecosystems, environmental health, and human welfare. Plant Diversity 44:429-435. https://doi.org/10.1016/j.pld.2022.01.005
647
648
649 Kendall LK, Mola JM, Portman ZM, et al (2022) The potential and realized foraging
650 movements of bees are differentially determined by body size and sociality. Ecology
651 103:e3809. https://doi.org/10.1002/ecy.3809

652 Klein A-M, Brittain C, Hendrix SD, et al (2012) Wild pollination services to California almond
653 rely on semi-natural habitat. Journal of Applied Ecology 49:723-732.
654 https://doi.org/10.1111/j.1365-2664.2012.02144.x

655 Klein A-M, Vaissière BE, Cane JH, et al (2007) Importance of pollinators in changing
656 landscapes for world crops. Proc R Soc B 274:303-313.
657 https://doi.org/10.1098/rspb.2006.3721

658 Knapp JL, Shaw RF, Osborne JL (2019) Pollinator visitation to mass-flowering courgette and
659 co-flowering wild flowers: Implications for pollination and bee conservation on farms.
660 Basic and Applied Ecology 34:85-94. https://doi.org/10.1016/j.baae.2018.09.003

661 Kremen C, Albrecht M, Ponisio L (2019) Restoring pollinator communities and pollination
662 services in hedgerows in intensively managed agricultural landscapes. In: The Ecology
663 of Hedgerows and Field Margins. Routledge

664 Lowe EB, Groves R, Gratton C (2021) Impacts of field-edge flower plantings on pollinator
665 conservation and ecosystem service delivery – A meta-analysis. Agriculture,
666 Ecosystems & Environment 310:107290. https://doi.org/10.1016/j.agee.2020.107290

667 Lüdecke D, Ben-Shachar M, Patil I, et al (2021) performance: An R Package for Assessment,
668 Comparison and Testing of Statistical Models. JOSS 6:3139.
669 https://doi.org/10.21105/joss.03139

670 MacInnis G, Buddle CM, Forrest JRK (2020) Small wild bee abundance declines with distance
671 into strawberry crops regardless of field margin habitat. Basic and Applied Ecology
672 44:14-23. https://doi.org/10.1016/j.baae.2020.02.007

673 Maurer C, Sutter L, Martínez-Núñez C, et al (2022) Different types of semi-natural habitat are
674 required to sustain diverse wild bee communities across agricultural landscapes. Journal
675 of Applied Ecology 59:2604-2615. https://doi.org/10.1111/1365-2664.14260

676 Meyer B, Jauker F, Steffan-Dewenter I (2009) Contrasting resource-dependent responses of
677 hoverfly richness and density to landscape structure. Basic and Applied Ecology
678 10:178-186. https://doi.org/10.1016/j.baae.2008.01.001

679 Mignot M (2023) BILAN - Inventaires des abeilles sauvages dans les cassissiers de Bourgogne
680 Franche-Comté

681 Moquet L, Laurent E, Bacchetta R, Jacquemart A-L (2018) Conservation of hoverflies (Diptera,
682 Syrphidae) requires complementary resources at the landscape and local scales. Insect
683 Conservation and Diversity 11:72-87. https://doi.org/10.1111/icad.12245

684 Nakagawa S, Johnson PCD, Schielzeth H (2017) The coefficient of determination R2 and intra-
685 class correlation coefficient from generalized linear mixed-effects models revisited and
686 expanded
687 Neira P, Blanco-Moreno JM, Olave M, et al (2024) Effects of agricultural landscape heterogeneity on pollinator visitation rates in Mediterranean oilseed rape. Agriculture, 688 Ecosystems & Environment 363:108869. https://doi.org/10.1016/j.agee.2023.108869

690 Nicholson CC, Ricketts TH, Koh I, et al (2019) Flowering resources distract pollinators from crops: Model predictions from landscape simulations. Journal of Applied Ecology 691 56:618-628. https://doi.org/10.1111/1365-2664.13333

693 Ockermüller E, Kratschmer S, Hainz-Renetzeder C, et al (2023) Agricultural land-use and landscape composition: Response of wild bee species in relation to their characteristic traits. Agriculture, Ecosystems & Environment 353:108540. 696 https://doi.org/10.1016/j.agee.2023.108540

697 Ollerton J, Winfree R, Tarrant S (2011) How many flowering plants are pollinated by animals? 698 Oikos 120:321-326. https://doi.org/10.1111/j.1600-0706.2010.18644.x

699 Ouvrard P, Transon J, Jacquemart A-L (2018) Flower-strip agri-environment schemes provide diverse and valuable summer flower resources for pollinating insects. Biodivers 700 Conserv 27:2193-2216. https://doi.org/10.1007/s10531-018-1531-0

702 Pfiffner L, Cahenzli F, Steinemann B, et al (2019) Design, implementation and management of perennial flower strips to promote functional agrobiodiversity in organic apple orchards: A pan-European study. Agriculture Ecosystems & Environment 278:61-71. 705 https://doi.org/10.1016/j.agee.2019.03.005

706 Potts SG, Imperatriz-Fonseca VL, Ngo HT, et al (2016) The assessment report on pollinators, pollination and food production: summary for policymakers. Secretariat of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, 709 Bonn, Germany

710 Priyadarshana TS, Martin EA, Sirami C, et al (2024) Crop and landscape heterogeneity increase biodiversity in agricultural landscapes: A global review and meta-analysis. Ecology 711 Letters 27:e14412. https://doi.org/10.1111/ele.14412

713 Raymond L, Sarthou J-P, Plantegenest M, et al (2014) Immature hoverflies overwinter in cultivated fields and may significantly control aphid populations in autumn. Agriculture, Ecosystems & Environment 185:99-105. 716 https://doi.org/10.1016/j.agee.2013.12.019

717 Redhead JW, Dreier S, Bourke AFG, et al (2016) Effects of habitat composition and landscape structure on worker foraging distances of five bumble bee species. Ecological Applications 26:726-739. https://doi.org/10.1890/15-0546

720 Rohde AT, Pilliod DS (2021) Spatiotemporal dynamics of insect pollinator communities in sagebrush steppe associated with weather and vegetation. Global Ecology and Conservation 29:e01691. https://doi.org/10.1016/j.gecco.2021.e01691

723 Sánchez-Bayo F, Wyckhuys KAG (2019) Worldwide decline of the entomofauna: A review of its drivers. Biological Conservation 232:8-27. 725 https://doi.org/10.1016/j.biocon.2019.01.020
726 Saunders ME, Lees AC, Grames EM (2025) Understanding and counteracting the denial of insect biodiversity loss. Current Opinion in Insect Science 68:101338.
727 https://doi.org/10.1016/j.cois.2025.101338
728

729 Schirmel J, Albrecht M, Bauer P-M, et al (2018) Landscape complexity promotes hoverflies across different types of semi-natural habitats in farmland. Journal of Applied Ecology
730
731 55:1747-1758. https://doi.org/10.1111/1365-2664.13095

732 Schmied H, Getrost L, Diestelhorst O, et al (2022) Between perfect habitat and ecological trap: even wildflower strips mulched annually increase pollinating insect numbers in intensively used agricultural landscapes. J Insect Conserv 26:425-434.
733
734
735 https://doi.org/10.1007/s10841-022-00383-6

736 Schoch K, Tschumi M, Lutter S, et al (2022) Competition and Facilitation Effects of Semi-Natural Habitats Drive Total Insect and Pollinator Abundance in Flower Strips. Front Ecol Evol 10:854058. https://doi.org/10.3389/fevo.2022.854058

739 Schulte KD, Wilson CJ, Tawril A, Jamieson MA (2025) Spatiotemporal variability and functional redundancy obscure effects of urbanization on strawberry pollinators. Ecosphere 16:e70133. https://doi.org/10.1002/ecs2.70133

742 Senapathi D, Goddard MA, Kunin WE, Baldock KCR (2017) Landscape impacts on pollinator communities in temperate systems: evidence and knowledge gaps. Functional Ecology
743
744 31:26-37. https://doi.org/10.1111/1365-2435.12809

745 Sirami C, Gross N, Baillod AB, et al (2019) Increasing crop heterogeneity enhances multitrophic diversity across agricultural regions. Proc Natl Acad Sci USA 116:16442-16447. https://doi.org/10.1073/pnas.1906419116

748 Steffan-Dewenter I, Münzenberg U, Bürger C, et al (2002) Scale-Dependent Effects of Landscape Context on Three Pollinator Guilds. Ecology 83:1421-1432.
749
750 https://doi.org/10.1890/0012-9658(2002)083[1421:SDEOLC]2.0.CO;2

751 Thies C, Roschewitz I, Tscharntke T (2005) The landscape context of cereal aphid-parasitoid interactions. Proceedings of the Royal Society B: Biological Sciences 272:203-210.
752
753 https://doi.org/10.1098/rspb.2004.2902

754 Tschanz P, Vogel S, Walter A, et al (2023) Nesting of ground-nesting bees in arable fields is not associated with tillage system per se, but with distance to field edge, crop cover, soil and landscape context. Journal of Applied Ecology 60:158-169.
755
756
757 https://doi.org/10.1111/1365-2664.14317

758 Turo KJ, Reilly JR, Fijen TPM, et al (2024) Insufficient pollinator visitation often limits yield in crop systems worldwide. Nat Ecol Evol 8:1612-1622.
759
760 https://doi.org/10.1038/s41559-024-02460-2

761 Uyttenbroeck R, Piqueray J, Hatt S, et al (2017) Increasing plant functional diversity is not the key for supporting pollinators in wildflower strips. Agriculture, Ecosystems & Environment 249:144-155. https://doi.org/10.1016/j.agee.2017.08.014
764 von Königslöw V, Fornoff F, Klein A-M (2022) Pollinator enhancement in agriculture: comparing sown flower strips, hedges and sown hedge herb layers in apple orchards.
765
766 Biodivers Conserv 31:433–451. https://doi.org/10.1007/s10531-021-02338-w

767 Wagner DL (2020) Insect Declines in the Anthropocene. Annual Review of Entomology 65:457–480. https://doi.org/10.1146/annurev-ento-011019-025151

769 Westphal C, Steffan-Dewenter I, Tscharntke T (2003) Mass flowering crops enhance pollinator densities at a landscape scale. Ecology Letters 6:961–965.
770
771 https://doi.org/10.1046/j.1461-0248.2003.00523.x

772 Zurbuchen A, Cheesman S, Klaiber J, et al (2010) Long foraging distances impose high costs on offspring production in solitary bees. Journal of Animal Ecology 79:674–681.
773
774 https://doi.org/10.1111/j.1365-2656.2010.01675.x

775 Zuur AF, Ieno EN, Elphick CS (2010) A protocol for data exploration to avoid common statistical problems. Methods in Ecology and Evolution 1:3–14.
776
777 https://doi.org/10.1111/j.2041-210X.2009.00001.x

778