Kyle T Martins
email: kyle.martins@mcgill.ca

Ecile H Albert

Martin J Lechowicz

Andrew Gonzalez

Complementary crops and landscape features sustain wild bee communities

Keywords: apple, bees, blueberry, community ecology, complementarity, ecosystem services, landscape ecology, raspberry, wild pollinators

Wild bees, which are important for commercial pollination, depend on floral and nesting resources both at farms and in the surrounding landscape. Mass-flowering crops are only in bloom for a few weeks and unable to support bee populations that persist throughout the year. Farm fields and orchards that flower in succession potentially can extend the availability of floral resources for pollinators. However, it is unclear whether the same bee species or genera will forage from one crop to the next, which bees specialize on particular crops, and to what degree inter-crop visitation patterns will be mediated by landscape context. We therefore studied local-and landscape-level drivers of bee diversity and species turnover in apple orchards, blueberry fields, and raspberry fields that bloom sequentially in southern Quebec, Canada. Despite the presence of high bee species turnover, orchards and small fruit fields complemented each other phenologically by supporting two bee genera essential to their pollination: mining bees (Andrena spp.) and bumble bees (Bombus spp.). A number of bee species specialized on apple, blueberry, or raspberry blossoms, suggesting that all three crops could be used to promote regional bee diversity. Bee diversity (rarefied richness, wild bee abundance) was highest across crops in landscapes containing hedgerows, meadows, and suburban areas that provide ancillary nesting and floral resources throughout the spring and summer. Promoting phenological complementarity in floral resources at the farmstead and landscape scales is essential to sustaining diverse wild bee populations.

INTRODUCTION

There is growing evidence that wild bees provide essential pollination services that cannot easily be replaced by managed honey bees (Garibaldi et al. 2013, Mallinger and[START_REF] Mallinger | Species richness of wild bees, but not the use of managed honeybees, increases fruit set of a pollinator-dependent crop[END_REF]. For some crops (e.g., apple, blueberry, raspberry), wild species may even be more efficient pollinators than honeybees [START_REF] Kevan | Insect pollinators and sustainable agriculture[END_REF][START_REF] Willmer | The superiority of bumblebees to honeybees as pollinators: insect visits to raspberry flowers[END_REF][START_REF] Javorek | Comparative pollination effectiveness among bees (Hymenoptera: Apoidea) on lowbush blueberry (Ericaceae: Vaccinium angustifolium)[END_REF][START_REF] Moisan-Deserres | Pollen loads and specificity of native pollinators of lowbush blueberry[END_REF], Park et al. 2016). Diverse wild-bee communities can enhance the quantity, quality, and temporal stability of pollination [START_REF] Klein | Understanding the role of species richness for crop pollination services[END_REF][START_REF] Garibaldi | Stability of pollination services decreases with isolation from natural areas despite honey bee visits[END_REF][START_REF] Rader | Native bees buffer the negative impact of climate warming on honey bee pollination of watermelon crops[END_REF], as well as fruit production [START_REF] Brittain | Synergistic effects of non-Apis bees and honey bees for pollination services[END_REF][START_REF] Garibaldi | Wild pollinators enhance fruit set of crops regardless of honey bee abundance[END_REF], 2014[START_REF] Bartomeus | Contribution of insect pollinators to crop yield and quality varies with agricultural intensification[END_REF]. Wild bee richness predicts plant reproductive success better than bee abundance alone [START_REF] Fontaine | Functional diversity of plant-pollinator interaction webs enhances the persistence of plant communities[END_REF][START_REF] Hoehn | Functional group diversity of bee pollinators increases crop yield[END_REF][START_REF] Albrecht | Diverse pollinator communities enhance plant reproductive success[END_REF][START_REF] Rogers | Bee species diversity enhances productivity and stability in a perennial crop[END_REF][START_REF] Blitzer | Pollination services for apple are dependent on diverse wild bee communities[END_REF]. Given declines in wild bee populations [START_REF] Goulson | Decline and conservation of bumble bees[END_REF][START_REF] Potts | Global pollinator declines: trends, impacts and drivers[END_REF], Bartomeus et al. 2013, Carvalheiro et al. 2013), assessing the environmental determinants of their abundance and diversity at farms is critical to the sustainability of crop pollination [START_REF] Kremen | Pollination and other ecosystem services produced by mobile organisms: a conceptual framework for the effects of land-use change[END_REF].

To the extent that they mediate floral and nesting resource availability, both local agricultural management and landscape context influence wild bee populations in agroecosystems [START_REF] Ricketts | Landscape effects on crop pollination services: are there general patterns?[END_REF][START_REF] Lonsdorf | Modelling pollination services across agricultural landscapes[END_REF][START_REF] Kennedy | A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems[END_REF][START_REF] Garibaldi | From research to action: enhancing crop yield through wild pollinators[END_REF][START_REF] Mallinger | Diverse landscapes have a higher abundance and species richness of spring wild bees by providing complementary floral resources over bees' foraging periods[END_REF]. At the local scale, enhancing the density and diversity of flowers in hedgerows [START_REF] Payette | Diversit e et abondance des apoides (Hymenoptera: Apoidea) dans l'agro ecosyst eme de Saint-Hyacinthe, Qu ebec[END_REF]De Oliveira 1989, Schulp et al. 2014), field margins [START_REF] Rands | Effects of pollinator density-dependent preferences on field margin visitations in the midst of agricultural monocultures: A modelling approach[END_REF], flower strips [START_REF] Haaland | Sown wildflower strips for insect conservation: a review[END_REF][START_REF] Wratten | Pollinator habitat enhancement: benefits to other ecosystem services[END_REF], and (semi-) natural land nearby farms [START_REF] Martins | Pollination services are mediated by bee functional diversity and landscape context[END_REF] can increase wild bee abundance and diversity [START_REF] Garibaldi | From research to action: enhancing crop yield through wild pollinators[END_REF][START_REF] Venturini | Pollination reservoirs for wild bee habitat enhancement in cropping systems: a review[END_REF]. At the landscape scale, wild bees track resources from forests to agricultural fields and meadows throughout the year [START_REF] Mandelik | Complementary habitat use by wild bees in agro-natural landscapes[END_REF].

Indeed, the replacement of natural areas by croplands less hospitable to pollinators (e.g., monocultures) means that there is less floral forage over shorter periods [START_REF] Ollerton | Extinctions of aculeate pollinators in Britain and the role of large-scale agricultural changes[END_REF][START_REF] Scheper | Museum specimens reveal loss of pollen host plants as key factor driving wild bee decline in The Netherlands[END_REF]. Habitat loss driven by land use change may be one of the major causes of bee declines in North America [START_REF] Burkle | Plant-pollinator interactions over 120 years: loss of species, co-occurrence, and function[END_REF]. Bee densities can respond positively to mass-flowering crops in agricultural landscapes [START_REF] Westphal | Mass flowering crops enhance pollinator densities at a landscape scale[END_REF], 2009[START_REF] Todd | Mass flowering crops as a conservation resource for wild pollinators (Hymenoptera: Apoidea)[END_REF]), but these are often in bloom for just a few weeks and unable to support bee populations throughout the year.

Promoting the phenological complementarity of floral resources at local and landscape scales (e.g., floral strips, habitat management) can ensure that bee species have access to forage over the course of their respective activity periods, thus maintaining rich and diverse bee communities. From the bee's perspective, this complementarity pertains to the use of spatially disparate floral resources at different times by the same bee species or genera. This can occur when bees forage between different crops or between a given crop and flowers in the surrounding landscape. Beyond phenological differences that give rise to complementary resource use, the concept of "community complementarity" in the floral community suggests that interspecific variation in plant traits (e.g., floral morphology) can engender floral specialization and thus higher levels of diversity in the regional bee community as well [START_REF] Bl€ Uthgen | Functional complementarity and specialisation: the role of biodiversity in plant-pollinator interactions[END_REF]. This would imply a positive feedback on biodiversity between upper and lower levels in mutualistic networks, such as between plants and pollinators [START_REF] Fontaine | Functional diversity of plant-pollinator interaction webs enhances the persistence of plant communities[END_REF]. Spatially heterogeneous resources allow for further niche partitioning among bee species while increasing the impact of diversity on ecosystem functioning [START_REF] Loreau | Biodiversity as spatial insurance in heterogeneous landscapes[END_REF][START_REF] Fisher | Phenological floral resource complementarity is important for bee abundance[END_REF][START_REF] Venjakob | Plant diversity increases spatio-temporal niche complementarity in plant-pollinator interactions[END_REF]: an example of the spatial insurance hypothesis [START_REF] Loreau | Biodiversity as spatial insurance in heterogeneous landscapes[END_REF].

To date, many studies have focused on phenological complementarity between individual crops and nearby (semi-) natural habitats [START_REF] Kennedy | A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems[END_REF]). These studies have mostly concerned temperate agroecosystems as opposed to those in the tropics where spatiotemporal availability of food resources is very high. An understudied means for extending floral resource availability for pollinators is the planting of commercial crops that flower in succession [START_REF] Rao | Abundance and diversity of native bumble bees associated with agricultural crops: The Willamette Valley Experience[END_REF]. This would benefit bee conservation efforts by providing complementary resources over time and space for long-lived generalist bees (e.g., bumble bees) that forage from multiple crops (Bl€ uthgen and [START_REF] Bl€ Uthgen | Functional complementarity and specialisation: the role of biodiversity in plant-pollinator interactions[END_REF][START_REF] Shackelford | Comparison of pollinators and natural enemies: a meta-analysis of landscape and local effects on abundance and richness in crops[END_REF][START_REF] Rundl€ Of | Late-season mass-flowering red clover increases bumble bee queen and male densities[END_REF]. On the other hand, if the pollination of a crop were dependent on bees that were short-lived and associated with a specific crop, then temporal complementarity would be less important. The degree to which landscape elements and successively blooming crops complement each other in supporting comparable bee species and genera, or in sustaining regional bee diversity, is not well understood [START_REF] Garibaldi | From research to action: enhancing crop yield through wild pollinators[END_REF].

Here, we study wild bee diversity in three pollinatordependent crops that flower in a sequence from mid-to latespring in southern Quebec, Canada: apple orchards (Malus domestica), blueberry (Vaccinium corymbosum) farms, and raspberry (Rubus ideaus) farms. We use field inventories and landscape modelling to address three questions about the role of complementarity in crop blossoming time for sustaining bee populations: (1) Do the three crops exhibit phenological complementarity for bees? (2) Do these crops promote regional bee community diversity through floral specialization? (3) Does landscape-level availability of floral and nesting resources predict bee community composition and diversity across crops? We predict that the three crops will exhibit phenological complementarity by supporting comparable levels of bee diversity (abundance and richness), the same bee species or genera will visit more than one crop, and bee community composition will not differ among the crops. Alternatively, bee species will specialize on only a single crop thus promoting regional bee community diversity. We expect that bee diversity and abundance will be highest in landscapes with diverse habitats for pollinators.

MATERIALS AND METHODS

Field site selection

We studied 20 apple orchards, 18 blueberry fields, and 20 raspberry fields in the Mont er egie district of southern Quebec, Canada (Fig. 1) in 2012. The Mont er egie, the second most populated region (1.4 million) in Quebec after Montreal, covers ~11,000 km 2 and has high levels of biodiversity for the province [START_REF] Tardif | Atlas de la biodiversit e du Qu ebec: les esp eces menac ees ou vuln erables. Gouvernement du Qu ebec[END_REF]. A recent shift away from dairy farming to intensive agriculture has led to more annual crops, fewer farms, and increases in chemical interventions (B elanger andGrenier 2002, Jobin et al. 2010).

The landscape surrounding the study sites was dominated by cropland (e.g., corn and soybean), neighboring apple orchards or deciduous forests. We spaced sites of the same crop at least 1,000 m apart, beyond the foraging range of most bee species in our area [START_REF] Greenleaf | Bee foraging ranges and their relationship to body size[END_REF]). To better examine inter-crop complementarity in floral resource provisions for wild bees, we set no minimum distance separating sites with different crops. The three crops were largely phenologically distinct, apples blooming first in mid-May, blueberries in late May, and raspberries in early June. In all cases, our analyses considered possible effects of spatial autocorrelation.

The three crops differ in their requirements for insect pollination: apples cannot set fruit or seed without pollination [START_REF] Brault | Seed number and an asymmetry index of McIntosh Apples[END_REF], blueberries are partially parthenocarpic but mostly not self-pollinating [START_REF] Eck | Blueberry science[END_REF][START_REF] Mackenzie | Pollination requirements of three highbush blueberry (Vaccinium corymbosum L.) cultivars[END_REF], while cultivated raspberries are self-fertile [START_REF] Colbert | Influence of pollen variety on raspberry (Rubus idaeus L.) development[END_REF]. However, for all three crops, pollination is associated with increased fruit set and mass [START_REF] Delaplane | Crop pollination by bees[END_REF][START_REF] Cane | Pollination potential of the bee Osmia aglaia for cultivated red raspberries and blackberries (Rubus: Rosaceae)[END_REF][START_REF] Isaacs | Pollination services provided to small and large highbush blueberry fields by wild and managed bees[END_REF][START_REF] Sheffield | Pollination, seed set and fruit quality in apple: studies with Osmia lignaria (Hymenoptera: Megachilidae) in the Annapolis Valley, Nova Scotia, Canada[END_REF], both of which increase the value of the crop for growers [START_REF] Garratt | Avoiding a bad apple: Insect pollination enhances fruit quality and economic value[END_REF]. In apple orchards, we focused on McIntosh trees, the leading cultivar in the northeastern United States and eastern Canada [START_REF] Hampson | Characteristics of important commercial apple cultivars[END_REF]. Small fruit fields included various cultivars of blueberry (Bluecrop, Duke, Elliot, Patriot) and raspberry (Nova, Madawaske). Two of the 18 blueberry growers rented commercially available nests of the common eastern bumble bee (Bombus impatiens). All sites were within flight distance of an orchard that rented honey bees at some point in the spring. All apple orchardists practiced integrative pest management, applying pesticides only when economically justifiable while minimizing risk to human health and the environment. Small fruit growers used low-input management, spraying fungicides and insecticides fewer than six times throughout the season.

Wild bee inventories

We sampled bees once at each site during the peak bloom of each crop (apple, 11-14 May; blueberry, 29 May-1 June; raspberry, 1-16 June). Our sampling sites within each orchard were 100 m in length and 50 m in width, with placement determined by the availability of McIntosh trees in apple orchards and away from field edges in small fruit farms. We observed bees under clear to lightly overcast conditions from 9:00 to 18:00 EST when ambient air temperatures were above 15°C and wind speeds <3.3 m/s. Environmental covariates including temperature, time of day, relative humidity, and wind speed were recorded at each site using a Kestrel 3500 Pocket Wind Meter (Kestrel Meters, Minneapolis, Minnesota, USA). To attain suitable weather conditions, raspberry sites had to be sampled over a longer time frame than apple or blueberry.

A single observer sampled bees during 40 min in apple orchards, while two observers sampled bees during 20 min in small fruit fields. Observers moved throughout the study site, maintaining a constant pace and sampling flower clusters of the crop as encountered and ignoring other flower species growing along field margins or between rows. To ensure that the entire site was surveyed evenly, they refrained from spending more than five minutes at particularly productive flower patches. Instead, they first surveyed the entire area and then returned to all areas with high levels of bee activity. Honey bees were identified on the fly and tallied using a counter; wild bees were caught with a sweep net, later frozen at the lab and processed for species-level identification.

Captured bees were identified to species or genus using pertinent literature [START_REF] Mitchell | Bees of the eastern United States[END_REF][START_REF] Mitchell | Bees of the eastern United States[END_REF], Packer et al. 2007[START_REF] Gibbs | Revision of the metallic species of Lasioglossum (Dialictus) in Canada (Hymenoptera, Halictidae, Halictini)[END_REF]) as well as online resources.4 Specialists John Ascher, Bryan Danforth, and Jason Gibbs verified species identifications. Voucher specimens are deposited at the Lyman Entomological Museum at McGill University.

Data analysis

To address our questions and test our set of hypotheses, we measured bee diversity and abundance, analyzed patterns of bee specialization, and explained both bee community composition and diversity with spatial, environmental, and landscape variables. All statistical analyses were conducted with R version 3.2.3. (R Core Team 2015), ArcMap 10.2.0.3348 (ESRI, Redlands, California, USA) and Python 2.7.6 (Python Software Foundation, Amsterdam, The Netherlands).

Measuring bee diversity.-We used rarefied species richness, wild bee abundance, and the abundance of bees in two important genera (sum of individuals in Andrena or Bombus) as the primary response variables describing bee diversity. These two genera were chosen because of their high prevalence at sites, their proven efficacy in pollinating all three crops [START_REF] Willmer | The superiority of bumblebees to honeybees as pollinators: insect visits to raspberry flowers[END_REF][START_REF] Tuell | Wild bees (Hymenoptera: Apoidea: Anthophila) of the Michigan highbush blueberry agroecosystem[END_REF][START_REF] Martins | Pollination services are mediated by bee functional diversity and landscape context[END_REF], and their contrasting life history traits representative of a wide array of bee species in our region (Bombus are long-lived generalists and Andrena short-lived specialists). As the number of bees sampled at each site varied substantially, we corrected our estimates of species richness through rarefaction to standardize sample size across sites [START_REF] Russo | The challenge of accurately documenting bee species richness in agroecosystems: bee diversity in eastern apple orchards[END_REF]. Following [START_REF] Chao | Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies[END_REF], we interpolated values to the minimum number of observations (including all bees, irrespective of their origins) made across sites after having excluded sites with fewer than 10 bee observations; ultimately, only one site was removed prior to the analysis of bee richness. We defined wild bee abundance as the frequency of undomesticated bees visiting a given site, excluding both bumble bees when they were introduced and honey bees in general. Domesticated bumble bees consisted exclusively of worker B. impatiens whereas wild bumble bees of the same species were nearly all queens at the time of sampling. Wild and domesticated honey bees could not be distinguished.

Intercrop floral specialization.-We examined the degree to which bee species foraged from all three crops using a bipartite analysis of the network linking bee species with the flowers that they visited [START_REF] Dormann | How to be a specialist? Quantifying specialisation in pollination networks[END_REF]. From a table of bee species frequencies on each crop, we calculated the Paired Difference Index (PDI) for each species in this network to estimate their degree of generalism [START_REF] Poisot | A comparative study of ecological specialization estimators[END_REF]. The index contrasts the link between a species' most visited floral host against its links with all remaining resources. A high frequency of generalist species in this network (PDI > 0.5) would suggest that the three crops supported comparable bee communities. We tested the significance of PDI values for all species that had at least 20 samples (18 of 74 species) by contrasting observed visitations against expectations from a null model using code taken from [START_REF] Dormann | How to be a specialist? Quantifying specialisation in pollination networks[END_REF]. The null model scattered the observed number of interactions over all flowering plant species while keeping the number of links constant and the marginal totals identical to those observed at each site.

We also evaluated the degree to which the bee species in the bipartite network specialized on any of the three crops or their pairwise combinations (e.g., apple-blueberry, appleraspberry, blueberry-raspberry) using an indicator value (IndVal) analysis [START_REF] Dufrene | Species assemblages and indicator species: the need for a flexible asymmetrical approach[END_REF][START_REF] De C Aceres | Associations between species and groups of sites: indices and statistical inference[END_REF][START_REF] De C Aceres | Improving indicator species analysis by combining groups of sites[END_REF]. The method involved testing the association of each species with all six possible combinations of the three crops to identify species with significant indicator values (P < 0.05) after 9,999 random permutations and a Holm correction for multiple tests.

Modeling landscape resource availability.-We approximated landscape-level floral and nesting resource availability by parameterizing the spatially explicit model of wild bee abundance from [START_REF] Lonsdorf | Modelling pollination services across agricultural landscapes[END_REF], which has been found to effectively predict wild bee diversity across crops [START_REF] Kennedy | A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems[END_REF]. Using information on pollinator nesting resources, floral resources, and foraging distances, this model generates from land cover data an index of relative wild bee abundance at each spatial unit (e.g., 30 9 30 m pixel) on the landscape [START_REF] Lonsdorf | Modelling pollination services across agricultural landscapes[END_REF][START_REF] Albert | Applying network theory to prioritize multi-species habitat networks that are robust to climate and land-use change[END_REF], hereafter referred to as the Landscape Resource Index (LRI). Details on the land cover map and the parameterization process in which each land cover class was attributed floral and nesting suitability scores are summarized in Appendix S3. We tested the robustness of model parameters using a sensitivity analysis in which the foraging distance used to calculate LRI was varied at four "floral extents" (i.e., spatial scales), restricting the available resources within 580 m, 830 m, 1,330 m, and 2,000 m of site centroids.

Landscape predictors and intercrop patterns of community composition.-We used partial redundancy analysis (RDA; Legendre andLegendre 2012, Oksanen et al. 2015) to examine patterns of bee community compositions across crops (site by bee species occurrence table, including native and nonnative species). This was done while accounting for spatial autocorrelation (Principal Coordinate of Neighbor Matrices [PCNM; [START_REF] Borcard | All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices[END_REF] analysis), crop type (apple, blueberry, raspberry), environmental conditions during sampling (relative humidity, temperature, time of day, wind speed), and LRI (separate stepwise model selection for each floral extent). We tested the significance of the best model, each of its constrained axes and each of its terms by permutation (9,999 permutations). We used variation partitioning to determine the contribution of each explanatory variable and their interactions to the ordinal space [START_REF] Peres-Neto | Variation partitioning of species data matrices: estimation and comparison of fractions[END_REF], and projected 95% confidence ellipses for each crop type onto the RDA triplot to illustrate differences in bee community composition. Refer to Appendix S3 for additional details on the testing procedure.

Landscape predictors and intercrop patterns of bee diversity and abundance.-We used linear modelling (GLM) analyses to study how measures of bee diversity (rarefied species richness, total wild bee abundance, Andrena abundance, and Bombus abundance) were influenced by environmental covariates (relative humidity, temperature, time of day, wind speed), crop type (apple, blueberry, raspberry), and LRI. We checked the spatial independence of sites by comparing generalized linear models including all explanatory variables with and without a random effect coding for spatial proximity; the random effect was non-significant in each case (likelihood ratio test P > 0.05) so GLM was used. We also tested the significance of a factor coding for whether the crop was grown in isolation (25 replicates) or paired with one (26 replicates) or two (seven replicates) crops of interest (apple, blueberry, or raspberry) within 1,000 m of sites. Collinearity between variables was verified using variation inflation factors, but ultimately none were removed [START_REF] Bolker | Generalized linear mixed models: a practical guide for ecology and evolution[END_REF]. Bee abundance data were fitted with a negative binomial distribution to control for overdispersion, while rarefied species richness (expressed as non-integer values) was fitted with a Gaussian distribution. Again, model selection was run separately for each GLM of the four floral extents (LRI).

We used the model averaging approach of [START_REF] Johnson | Model selection in ecology and evolution[END_REF] to study the uncertainty associated with each coefficient. Following [START_REF] Kennedy | A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems[END_REF], we first generated a candidate model set including all possible combinations of the covariates and their respective interactions with crop type, allowing no more than four parameters to avoid overfitting each model. The candidate model set was balanced, in that each covariate appeared 53 times and each interaction term six times, with a total of 134 possible models. We then ranked models according to their AIC values and estimated their Akaike weights and relative importance scores (Barto n 2014); the subset of models and their covariates within two AIC units of the best model were retained as a "top model set." The floral extent that resulted in the lowest AIC value overall then was subjected to model averaging. We estimated the model-averaged partial regression coefficients of each of the retained covariates in the top model set at the selected spatial scale as well as their 95% confidence intervals. Covariates were considered important if their summed Akaike weights were above 0.60 and significant if their confidence intervals did not include zero. Models with the lowest AIC values overall were subjected to standard diagnostic testing. This included testing model residuals for spatial-autocorrelation using Moran's I autocorrelation coefficient and visual assessments of sample variograms [START_REF] Gittleman | Adaptation: statistics and a null model for estimating phylogenetic effects[END_REF]Kot 1990, Paradis et al. 2004).

RESULTS

Field sampling results

In total, 8,276 bees were observed in apple orchards (2,348 observations), blueberry fields (781), and raspberry fields (5,147), of which 6,601 were honey bees and 1,675 wild bees (Appendix S1: Table S3). Honey bees were most prevalent at raspberry fields (4,344 samples, 84% of all bees), followed by apple orchards (2,134; 90%), and blueberry fields (123; 16%). The proportion of honey bees to wild bees changed from crop to crop (10:1 apples, 1:5 blueberries, 5:1 raspberries). The most abundant wild bee species across crops was B. griseocollis (293 samples), followed by B. bimaculatus (281), and B. impatiens (179). A total of 74 species were observed across 16 genera and five families, the most species rich genus being Andrena (27 species), followed by Lasioglossum (15) and Bombus (8). Excluding honey bees, the most abundant genus at each crop was Andrena in apple orchards (135 samples; 63% of all wild bees), Bombus in blueberry fields (527; 80%), and both Bombus (304; 38%) and Andrena (258; 32%) in raspberry fields. Patterns of species level diversity across crops are discussed in the subsection Intercrop floral specialization.

Intercrop floral specialization

The bipartite network analysis (Table 1, Fig. 2; Appendix S1: Table S3) linking the bees to the crops they visited established that few species are shared among apple orchards and small fruit farms. In fact, only Bombus impatiens, the common eastern bumble bee, exhibited significant levels of floral generalism in this system (PDI 0.46, P = 0.015). The IndVal analysis (Table 1, Fig. 2; Appendix S1: Table S3) also indicated that most bee species inventoried in this study prefer foraging exclusively from either apple, blueberry, or raspberry blossoms. Of the wild bees, only the bumble bee species (B. bimaculatus, B. griseocollis, B. impatiens, B. rufocinctus, B. ternarius) forage preferentially from more than one crop, namely raspberries and blueberries. As for honey bees, they were found in high numbers on both apple and raspberry blossoms.

Modeling landscape resource availability

The optimized nesting and floral suitability scores associated with each land cover class deviated in some instances from our original expectations based on the literature (Appendix S1: Table S2). Meadows and hedgerows obtained final scores that were higher than initially specified for both nesting and floral resources, and orchards lower than initially expected. Suitability scores for urban areas tended to be higher for floral resources but lower for nesting resources in dense urban areas. Forest had lower scores for nesting resources, especially coniferous forests. Changes in suitability scores for remaining land cover classes had little influence on the fit between predicted and observed wild bee abundances. In general, smaller dispersal distances led to higher correlations between predicted and observed values (Appendix S2: Fig. S1).

Landscape predictors and intercrop patterns of community composition

None of the PCNM eigenvectors approximating spatial autocorrelation significantly modelled the variance in the site by bee species response matrix (P > 0.05), and neither did our quantification of landscape resource availability (LRI). Crop type (R 2 adj = 0.39, P < 0.001) and temperature (R 2 adj = 0.004, P = 0.031) were the only significant variables in the best model (R 2 adj = 0.41, P < 0.001; Fig. 3). None of the variance was shared among these predictor variables. The variance explained by RDA1 (39%, P < 0.001) and RDA2 (3%, P = 0.002) was significant. In the resulting triplot (Fig. 3), the effect of temperature is partialled out to focus on the relationship between crop type in the ordinal space. RDA1 polarizes blueberry sites against both raspberry and apple sites, the former being associated with bumble bee species (B. bimaculatus, B. griseocollis, and B. impatiens) and the latter with honey bees. The 95% confidence ellipses of the sampling sites partitioned by crop type confirm that species-level community composition among the three crops is for the most part distinct.

Landscape predictors and intercrop patterns of bee diversity and abundance

Model averaging could not be performed for rarefied species richness, wild bee abundance, and bumble bee abundance as, in each case, only a single model was within two AIC units of the top models. Richness was best predicted by LRI at a floral extent of 830 m (b = 0.37 AE 0.12, t = 3.18, P = 0.003), temperature (b = 0.54 AE 0.22, t = 2.44, P = 0.018), crop type, and the interaction between crop type and temperature (Table 2, Fig. 4; Appendix S2: Fig. S1).

FIG. 2. The network links wild bee species, excluding naturalized honey bees, listed in the upper portion of the figure (c.f. species codes in Appendix S1: Table S3) to the crops (base of the figure) that they visited. The size of each box is scaled to the frequency of a given bee species or the number of visits made to a given crop. The percentage of bee-flower interactions is indicated by the thickness of the connecting lines. Bee species are labeled and color-coded if significantly (P < 0.05) associated with (Table 1) apples (red), blueberries (blue), raspberries (red), or both blueberries and raspberries (purple); all remaining species are in gray. Bombus impatiens is highlighted in light purple, as it was a significant associated with blueberries and raspberries in addition to showing significant levels of generalism for the three crops (paired difference index [PDI] < 0.5; Table 1). FIG. 3. Redundancy analysis (RDA) triplot showing the distribution of bee species and sites as a function of crop type (ellipses). Species scores have been divided by the standard deviation of each species and multiplied with an equalizing constant. Species with the highest species scores are labeled (see Appendix S1: Table S3 for codes).

Bee species richness in blueberry fields (b = 0.80 AE 0.29, t = 2.73, P = 0.009) and raspberry fields (b = 0.65 AE 0.31, t = 2.11, P = 0.04) was significantly higher than that in apple orchards, but richness in blueberry and raspberry fields was the same on average (b = 0.14 AE 0.28, t = 0.51, P = 0.61). The positive relationship between richness and temperature was significantly less pronounced in raspberry fields (b = À0.97 AE 0.29, t = À3.32, P = 0.002) than in apple orchards or blueberry fields.

Wild bee abundance was best predicted by LRI at a floral extent of 580 m (b = 0.26 AE 0.07, z = 3.86, P < 0.001), temperature (b = 0.62 AE 0.16, z = 3.91, P < 0.001), crop type, and the interaction between crop type and temperature (Table 2, Fig. 4; Appendix S2: Fig. S2). It was significantly higher in blueberry fields (b = 1.11 AE 0.18, z = 6.31, P < 0.001) and raspberry fields (b = 1.47 AE 0.19, z = 7.84, P < 0.001) than in apple orchards. Bee abundance in raspberry fields was significantly higher than in blueberry fields (b = 0.36 AE 0.16, z = À2.25, P = 0.02). The positive relationship between bee abundance and temperature was significantly less pronounced in blueberry fields (b = À0.60 AE 0.19, z = 3.20, P = 0.001) and raspberry fields (b = À0.89 AE 0.19, z = À4.59, P < 0.001) than in apple orchards.

Bumble bee abundance was significantly higher in blueberry (b = 2.98 AE 0.28, z = 10.53, P < 0.001) and raspberry fields (b = 2.48 AE 0.30, z = 8.26, P < 0.001) than in apple orchards; abundance in blueberry fields was also higher than in raspberry fields (b = 0.50 AE 0.20, z = 2.51, P = 0.01) (Table 2, Fig. 4; Appendix S2: Fig. S1). LRI at a floral extent of 580 m best predicted bumble bee abundance (b = 0.35 AE 0.10, z = 3.59, P < 0.001). The positive relationship between bumble bee abundance and temperature was significantly less pronounced in raspberry fields (b = À1.33 AE 0.32, z = À4.23, P < 0.001).

Mining bee (Andrena) abundance was significantly lower in blueberry fields (importance value (Imp.) = 1.00, b = À1.25 AE 0.36) than in raspberry fields, but their abundance in either raspberry fields or blueberry fields did not differ from that in apple orchards (Table 2, Fig. 4; Appendix S2: Fig. S1). Their numbers were also driven by temperature (Imp. = 1.00, b = 0.56 AE 0.16) and LRI (Imp. = 0.79, b = 0.42 AE 0.20).

DISCUSSION

We compared bee diversity across mass-flowering crops that bloom in sequence while assessing the importance of surrounding nesting and floral resource availability. Bee diversity at apple orchards and small fruit farms was highest when diverse and abundant nesting and floral resources were available in the surrounding landscape. Crops exhibited phenological complementarity by sustaining certain bee genera (Andrena and Bombus) throughout the spring but few bee species visited more than one crop. Our approach mirrors that of [START_REF] Mandelik | Complementary habitat use by wild bees in agro-natural landscapes[END_REF] and [START_REF] Mallinger | Diverse landscapes have a higher abundance and species richness of spring wild bees by providing complementary floral resources over bees' foraging periods[END_REF] in its appraisal of complementary habitat use by bees to understand how they persist in a humanaltered landscape. However, like [START_REF] Winfree | Wild bee pollinators provide the majority of crop visitation across land-use gradients in New Jersey and Pennsylvania, USA[END_REF] and [START_REF] Adamson | From April to August-wild bees pollinating crops through the growing season in Virginia, USA[END_REF], our focus is on intercrop visitation patterns of wild bee species that can inform regional pollinator conservation initiatives and the cropping strategies employed by agriculturalists. We extend previous work by comparing both intercrop and landscape-level complementarities in bee resource provisions, while also assessing community turnover across our study region.

Do apple, blueberry, and raspberry crops exhibit phenological complementarity for bees?

At the bee species level, apple orchards, blueberry fields, and raspberry fields did not demonstrate phenological complementarity since they supported distinct bee communities in our study system, as also reported by [START_REF] Adamson | From April to August-wild bees pollinating crops through the growing season in Virginia, USA[END_REF]. In fact, only a single bee species, the common eastern Notes: Significant values (CI not including zero) are shown in boldface type; importance values could not be calculated for bee richness, wild bee abundance, and bumble bee abundance because only a single model was included in the top model set (DAIC < 2). Only variables in the top model sets are given. LRI, land resource index; temp. temperature. A factor coding for "apple orchard site" was used as the reference group to minimize the size of the table; see section Landscape predictors and intercrop patterns of bee diversity and abundance for results specific to apple orchards. bumble bee (B. impatiens), foraged from all three crops in large numbers. Even the spatial proximity or presence of neighboring orchards and small fruit fields could not predict bee community composition as well as could crop type alone. This likely reflects the turnover of bee activity periods as well as interspecific floral preferences.

Apple orchards, blueberry fields, and raspberry fields did demonstrate phenological complementarity at the genus level, sustaining wild bumble bees (Bombus) and mining bees (Andrena) that foraged from at least two of the crops. Moreover, bee richness and wild bee abundance in raspberry and blueberry sites were comparable, both being higher than that in apple orchards. Despite the brief period during which the three crops flower in sequence, this result may reflect phenology as sufficient time has elapsed for some bee taxa (e.g., bumble bees) to grow in numbers and build their colonies by the time small fruit fields bloom. Since apple orchard area is negatively associated with bee diversity in our region [START_REF] Martins | Pollination services are mediated by bee functional diversity and landscape context[END_REF], the smaller size of small fruit fields may also influence results as the demand for wild pollinators likely scales with forage supply.

Mining bees specialize on the rosaceous pollen [START_REF] Gardner | Notes on the native bee pollinators in New York apple orchards[END_REF] of apple and raspberry blossoms while the preference of bumble bees for the ericaceous pollen of blueberry flowers is well documented [START_REF] Desjardins | Commercial bumble bee Bombus impatiens (Hymenoptera: Apidae) as a pollinator in lowbush blueberry (Ericale: Ericaceae) fields[END_REF]De Oliveira 2006, Moisan-Deserres et al. 2014). Bumble bees are also likely attracted by the rich nectar rewards of raspberry blossoms [START_REF] Simidchiev | Study on the nectar and honey productivity of red raspberry (Rubus idaeus L.) and European blackberry (Rubus fructicosus L.). Gradinarska I Lozarska[END_REF], as many species in our study specialized on and are effective pollinators of both raspberry and blueberry flowers [START_REF] Willmer | The superiority of bumblebees to honeybees as pollinators: insect visits to raspberry flowers[END_REF][START_REF] Tuell | Wild bees (Hymenoptera: Apoidea: Anthophila) of the Michigan highbush blueberry agroecosystem[END_REF]. Diverse nectar and pollen sources may enhance the nutrient balance and health of bees, but research to date has focused only on honey bees [START_REF] Roulston | Pollen nutritional content and digestibility for animals[END_REF]. Raspberry is an ideal complement to both apple and blueberry as it supports bee genera found in the other crops. Raspberry also blossoms for the longest period of time, well into the late summer when many other mass-flowering crops and natural habitats (e.g., deciduous forests) in our region are depauperate in floral resources [START_REF] Whitney | The reproductive biology of raspberries and plant-pollinator community structure[END_REF]. Raspberry crops potentially can reduce year-to-year variance in bee population abundance as the availability of late season forage positively predicts bumble bee colony success the following spring [START_REF] Rundl€ Of | Late-season mass-flowering red clover increases bumble bee queen and male densities[END_REF]. The abundance of mining and bumble bees is relevant not only to pollinator conservation, but also crop pollination and fruit production. For example, mining bees are abundant in apple orchards and deposit more pollen per visit than other bees, but are relatively slow moving; bumble bees are infrequent, but visit many more blossoms per minute than mining bees [START_REF] Park | Per-visit pollinator performance and regional importance of wild Bombus and Andrena (Melandrena) compared to the managed honey bee in New York apple orchards[END_REF]. From the plant's perspective, a combination of mining bees and bumble bees maximizes both the delivery and quality of apple pollination [START_REF] Martins | Pollination services are mediated by bee functional diversity and landscape context[END_REF]. In the case of both apple orchards and small fruit fields, wild bees (e.g., bumble bees) compensate for the inactivity of domesticated honey bees during inclement weather conditions [START_REF] Rogers | Bee species diversity enhances productivity and stability in a perennial crop[END_REF][START_REF] Martins | Pollination services are mediated by bee functional diversity and landscape context[END_REF] and for their inefficiency as pollinators [START_REF] Willmer | The superiority of bumblebees to honeybees as pollinators: insect visits to raspberry flowers[END_REF][START_REF] Javorek | Comparative pollination effectiveness among bees (Hymenoptera: Apoidea) on lowbush blueberry (Ericaceae: Vaccinium angustifolium)[END_REF], Park et al. 2016). However, importing honey bee colonies to farms can offset year to year variance in natural bee populations [START_REF] Delaplane | Crop pollination by bees[END_REF] and may be required to satisfy commercially relevant levels of pollination [START_REF] Isaacs | Pollination services provided to small and large highbush blueberry fields by wild and managed bees[END_REF]. Planting apple, blueberry, and raspberry at the farmstead and landscape scales can potentially promote fruit yield by sustaining functionally diverse bee communities, but this has yet to be verified empirically. Do apple, blueberry, and raspberry crops promote regional bee community diversity through floral specialization?

Each of the three crops or combinations thereof (e.g., blueberry and raspberry) exhibited high degrees of floral specialization by bee species. These results may reflect turnover in bee activity periods during the spring, as our study did not attempt to control for interspecific differences in bee phenology. Consistent with [START_REF] Gardner | Notes on the native bee pollinators in New York apple orchards[END_REF], specialists on apple blossoms tended to include Andrena and Colletes spp. that are active early in the spring and prefer rosaceous pollen. Andrena carolina, a known Vaccinium specialist [START_REF] Tuell | Wild bees (Hymenoptera: Apoidea: Anthophila) of the Michigan highbush blueberry agroecosystem[END_REF]) and abundant in blueberry fields in northern Quebec (Moisan-Deserres et al. 2014), was prevalent at blueberry sites with local features favorable to ground-nesting bees such as sandy soil and exposed field margins. As previously mentioned, bumble bees typically foraged on blueberry and raspberry blossoms. Finally, raspberry supported a high diversity of stem (e.g., Ceratina spp.) and social ground nesting (e.g., Lasioglossum) bees. Ceratina spp. are known to nest in raspberry canes [START_REF] Vickruck | Nesting biology and DNA barcode analysis of Ceratina dupla and C. mikmaqi, and comparisons with C. calcarata (Hymenoptera: Apidae: Xylocopinae)[END_REF] and were observed doing so at our field sites. Lasioglossum spp. were also abundant in raspberry fields studied by [START_REF] Adamson | From April to August-wild bees pollinating crops through the growing season in Virginia, USA[END_REF] in Virginia, USA. These results suggest that agricultural management that promotes the intercropping of apples, blueberries and raspberries should support bee diversity both in terms of local and regional bee community diversity. Further research is needed to compare the degree of complementarity of these three crops with others that bloom sequentially or at the same time, such as tomato and squash. Does landscape-level availability of complementary floral and nesting resources predict bee community composition and diversity across crops?

Diverse and abundant nesting and floral resources in the surrounding landscape promoted bee diversity at apple orchards and small fruit farms. This was true at a spatial scale typical of bee foraging distances and the one used to previously study the landscape ecology of bee diversity [START_REF] Martins | Pollination services are mediated by bee functional diversity and landscape context[END_REF][START_REF] Koh | Modeling the status, trends, and impacts of wild bee abundance in the United States[END_REF]. The Landscape Resource Index (LRI) was a better predictor of bee diversity and abundance than the presence of nearby orchards or small fruit fields, suggesting that resource availability beyond the orchard context is more important than adjacency of complementary flowering crops. As has been found through global meta-analysis [START_REF] Kennedy | A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems[END_REF], the relationship between LRI and bee diversity and abundance was the same across the three crops despite each being exploited by distinct bee communities. We add to their work by assessing a region (southern Quebec) and a crop (raspberry) that had not been covered in their analysis. From our results, we infer that the spatial complementarity of floral and nesting resources is critical to sustaining bee populations in our study region.

In parameterizing our model, we identified landscape features essential for bees in apple orchards and small fruit fields including meadows, hedgerows, and low-density urban areas (e.g., suburbs). Notably, bees track floral resources from hedgerows to meadows in southern Quebec as they have complementary floral phenologies [START_REF] Payette | Diversit e et abondance des apoides (Hymenoptera: Apoidea) dans l'agro ecosyst eme de Saint-Hyacinthe, Qu ebec[END_REF]; hedgerows are characterized by shrubs that blossom in the spring (e.g., Salix discolor, Amelanchier spp., Prunus spp.), and meadows by forbs that blossom in the mid to late summer (e.g., Trifolium spp., Vicia cracca, Melilotus alba, Solidago spp.). In New Jersey and Pennsylvania, USA, similar phenological synchrony was observed between agricultural lots and old fields [START_REF] Mandelik | Complementary habitat use by wild bees in agro-natural landscapes[END_REF]. Hedgerows also act as windbreaks, promoting homogeneous distribution of wild pollinators in blueberry fields [START_REF] Moisan-Deserres | Influence of windbreaks and forest borders on abundance and species richness of native pollinators in lowbush blueberry fields in Qu ebec, Canada[END_REF], as well as corridors for bee dispersal [START_REF] Cranmer | Landscape structure influences pollinator movements and directly affects plant reproductive success[END_REF]. Similarly, conditions favorable for pollinators in urban settings pertain to continuous floral and nesting resource levels in residential gardens and parks [START_REF] Fetridge | The bee fauna of residential gardens in a suburb of New York City (Hymenoptera: Apoidea)[END_REF][START_REF] Osborne | Quantifying and comparing bumblebee nest densities in gardens and countryside habitats[END_REF][START_REF] Banaszak-Cibicka | Features of urban green space favourable for large and diverse bee populations (Hymenoptera: Apoidea: Apiformes)[END_REF][START_REF] Martins | Patterns of pollinator turnover and increasing diversity associated with urban habitats[END_REF], low pesticide levels [START_REF] Lawrence | Survey and risk assessment of Apis mellifera (Hymenoptera: Apidae) exposure to neonicotinoid pesticides in urban, rural, and agricultural settings[END_REF][START_REF] Bot Ias | Quantifying exposure of wild bumblebees to mixtures of agrochemicals in agricultural and urban landscapes[END_REF], heterogeneity in land cover [START_REF] Senapathi | The impact of over 80 years of land cover changes on bee and wasp pollinator communities in England[END_REF], and warmer temperatures induced by the heat island effect (Banaszak-Cibicka 2014). It is reasonable to consider meadows, hedgerows and suburbs as sources of native bees for adjacent crop fields [START_REF] Goulson | Effects of land use at a landscape scale on bumblebee nest density and survival[END_REF][START_REF] Morandin | Hedgerow restoration promotes pollinator populations and exports native bees to adjacent fields[END_REF][START_REF] Sheffield | Bee (Hymenoptera: Apoidea) diversity within apple orchards and old fields in the Annapolis Valley, Nova Scotia, Canada[END_REF].

CONCLUSION

Managing apple orchards and small fruit fields to maximize their spatiotemporal asynchrony can help to conserve bees while securing fruit pollination. This would provide spatial insurance for bee diversity, pollination functioning and ecosystem services within the landscape [START_REF] Loreau | Biodiversity as spatial insurance in heterogeneous landscapes[END_REF]. In our study system, each crop complements the others in their flowering phenology to sustain important wild pollinators, regional community diversity and a total of 74 bee species. Ensuring the availability of floral and nesting resources beyond the orchard context in the surrounding landscape is critical to ecosystem services provisions by wild pollinators. Our findings underscore the importance of an integrated conservation approach for wild pollinators and sustained pollination services including diversified cropping strategies and protecting meadows and hedgerows in agroecosystems, as well as improving the quality of suburban habitats for bees. Developing an integrated conservation approach on these lines will require refining the spatial resolution of the underlying landscape processes [START_REF] Lonsdorf | Modelling pollination services across agricultural landscapes[END_REF], parsing the landscape classes to better reflect plant species distributions [START_REF] Koh | Modeling the status, trends, and impacts of wild bee abundance in the United States[END_REF]) and bee nesting habitats [START_REF] Sardinas | Evaluating nesting microhabitat for ground-nesting bees using emergence traps[END_REF], studying inter-year variance in pollinator turnover across crops, investigating phenological complementarity between crops that blossom simultaneously and factoring in the effects of pesticide exposure [START_REF] Park | Negative effects of pesticides on wild bee communities can be buffered by landscape context[END_REF].

FIG. 1 .

 1 FIG.1. Map and inset show locations of sampling sites within the broader regional context of southern Quebec, Canada.

FIG. 4 .

 4 FIG. 4. Partial effects graphs showing the relationship between (a) rarefied species richness, (b) wild bee abundance, (c) mining bee abundance, and (d) bumble bee abundance as a function of landscape resource index (LRI) at apple orchards and small fruit fields. The models have been scaled to bring out the linear relationship between predictor and response variables. Full models are described in Table 2. Land resource index (LRI) was calculated at a floral extent distance of 830 m for species richness (a) and 580 m for all other models (b-d).

TABLE 1 .

 1 Significant indicator species for crops (A, apple; B, blueberry; R, raspberry) and their combinations, as well as their families, Paired Difference Index values (PDI), Indicator Species Values (IndVal), and IndVal P values.

	Family and species	PDI Crop IndVal	P
	Apidae
	Apis mellifera Linnaeus 1758	0.74 AR	0.99	0.005
	Bombus bimaculatus Cresson,	0.82	BR	0.89	0.005
	1863
	B. griseocollis (DeGeer, 1773)	0.67	BR	0.86	0.005
	B. impatiens Cresson, 1863	0.46	BR	0.81	0.005
	B. rufocinctus Cresson, 1863	0.78	BR	0.61	0.01
	B. ternarius Say, 1837	0.63	BR	0.56	0.035
	Halictidae
	Lasioglossum coriaceum	1.00	R	0.59	0.005
	(Smith, 1853)
	Andrenidae
	Andrena bisalicis Viereck, 1908	1.00	R	0.59	0.01
	A. carolina Viereck, 1909	1.00	B	0.67	0.005
	A. commoda Smith, 1879	0.99	R	0.66	0.005
	A. crataegi Robertson, 1893	0.84	R	0.7	0.005
	A. dunningi Cockerell, 1898	1.00	A	0.67	0.005
	A. hippotes Robertson, 1895	0.96	A	0.48	0.015
	A. milwaukeensis Graenicher, 1903 0.96	A	0.64	0.005
	A. miranda Smith, 1879	1.00	R	0.81	0.005
	A. nivalis Smith, 1853	1.00	R	0.45	0.03
	A. rufosignata Cockerell, 1902	1.00	A	0.50	0.025
	A. rugosa Robertson, 1891	0.90	A	0.65	0.005
	A. wheeleri Graenicher, 1904	1.00	R	0.55	0.005
	A. wilkella (Kirby, 1802)	0.93	R	0.69	0.005
	Colletidae
	Colletes inaequalis Say, 1837	1.00	A	0.55	0.005
	Halictidae
	Lasioglossum quebecense	1.00	A	0.45	0.04
	(Crawford, 1907)
	Apidae
	Ceratina calcarata Robertson, 1900 1.00	R	0.63	0.005
	C. mikmaqi Rehan & Sheffiel, 2011 1.00	R	0.77	0.005
	Colletidae
	Hyleus mesillae (Cockerell, 1896)	1.00	R	0.45	0.035
	Notes: Significant PDI values (P < 0.05) are shown in boldface
	type. See Supporting Information for PDI values of remaining bee
	species.

TABLE 2 .

 2 The results of model selection including importance values (Imp.), standardized partial regression coefficients (b), standard error values (SE), and 95% confidence intervals (CI) for each predictor variable.

	Response and predictor				Lower	Upper
	variables	Imp.	b	SE	CI	CI
	Species richness
	LRI (830 m)		0.37 0.12	0.14	0.60
	Temp.		0.54 0.22	0.10	0.99
	Temp. 3 Blueberry		À0.19 0.28	À0.75	0.38
	Blueberry		0.80 0.29	0.21	1.39
	Temp. 3 Raspberry		À0.97 0.29	À1.56	À0.38
	Raspberry		0.66 0.31	0.03	1.29
	Wild bee abundance
	LRI (580 m)		0.26 0.07	0.13	0.40
	Temp.		0.62 0.16	0.32	0.93
	Blueberry		1.11 0.18	0.77	1.46
	Temp. 3 Blueberry		À0.60 0.19	À0.97	À0.24
	Raspberry		1.47 0.19	1.09	1.85
	Temp. 3 Raspberry		À0.89 0.19	À1.26	À0.52
	Bumble bee abundance
	LRI (580 m)		0.35 0.10	0.16	0.55
	Temperature		0.02 0.26	À0.51	0.56
	Blueberry		2.98 0.28	2.43	3.56
	Temp. 3 Blueberry		À0.12 0.29	À0.71	0.46
	Raspberry		2.48 0.30	1.90	3.10
	Temp. 3 Raspberry		À1.33 0.32	À1.97	À0.72
	Mining bee abundance
	Temperature	1	0.56 0.16	0.24	0.88
	Raspberry	1	0.49 0.37	À0.23	1.21
	Blueberry	1	À0.76 0.41	À1.57	0.05
	LRI (580 m)	0.79	0.42 0.20	0.03	0.81
	Time of Day	0.73	À0.18 0.34	À0.85	0.49
	LRI 3 Raspberry	0.27	À0.26 0.31	À0.88	0.35
	LRI 3 Blueberry	0.27	0.61 0.38	À0.13	1.35
	Time of Day 3	0.21	À0.49 0.35	À1.17	0.20
	Raspberry
	Time of Day 3	0.21	À1.33 0.39	À2.09	À0.56
	Blueberry

http://www.Discoverlife.org/

ACKNOWLEDGMENTS

We gratefully acknowledge the Natural Science and Engineering Research Council of Canada, the Fonds de Recherche Nature et Technologies Qu ebec, the Quebec Centre for Biodiversity Science and the F ed eration des Producteurs de Pommes du Qu ebec for funding and support. A. Gonzalez was supported by the Canada Research Chair program, a Killam Fellowship and the Liber Ero Chair in Conservation Biology. We thank the apple, blueberry, and raspberry growers in the Mont er egie for their willingness to provide access to their orchards; McGill University for permission to work at the Gault Nature Reserve; Julien Mass e-Jodoin, Natasha Salter, and Sarah Saldahna for field assistance; John Ascher, Bryan Danforth, and Jason Gibbs for their help with insect identification; and Maria Dumitru for assisting with GIS data. This work contributes to the Labex OT-Med (no. ANR-11-LABX-0061) funded by the French Government through the A*MIDEX project (no. ANR-11-IDEX-0001-02).

LITERATURE CITED


Villafaña López

E Clavijo Rivera

Shuli Liu

Patrick Bourseau

Estelle Couallier

M Frappart

L Villafaña-López

E Clavijo

Shear-enhanced membrane filtration of synthetic microalgae lipids for applications in biorefinery

INTRODUCTION

Cell disruption and lipid extraction from harvested microalgae cells are two critical steps in the third generation biofuel production. Lipid recovery from disrupted cells can be improved using filtration methods applying the wet pathway, thus reducing the energy consumption. These methods can be automated and can treat large volumes of suspensions while avoiding the use of solvents and chemicals. Recently, the shear-enhanced or dynamic filtration technique has emerged as a promising option that reduces membrane fouling and provides high permeate fluxes at a steady shear rate, with good separation performance and low energy requirements.

THEORY MATERIALS & METHODS

Biomass

Supernatant

Cellular debris

Model emulsion

The model emulsion is a mix of vegetable oils (2 %) + surfactant molecules. The emulsion presents a polynomial distribution showing peaks at 0.15 µm, 2.3 µm (major), and 10.5 µm.

The model emulsion was formulated to emulate the lipid profile of the starved and grinded P. kessleri supernatant after centrifugation.

Polymer MWCO P c (bar) %RFR %

Cleanability %R Fouling Lp Water (Lh -1 m -2 bar -1 ) The global objective is to to define separation strategies for real biomass. In this work, we evaluated the feasibility of dynamic filtration for the concentration of lipids with four different membranes. The concentration experiments were conducted at a pressure bellow the critical pressure to limit the fouling.

Lp i Emulsion (Lh -1 m -2 bar -1 )
We compare the filtration performances (relative flux reduction % RFR, oil retention rate % R, % cleanability, and global fouling resistance R Fouling ) of both the crossflow and shear enhanced filtration modules during lipid recovery from a model emulsion.

Crossflow and shear-enhanced filtrations, for the PAN 500 kDa membrane, were compared in the same conditions (v=1 m/s, and T=30°C). All conditions lead to a % R greater than 97 %. PAN membrane performance is similar in both systems.

RESULTS

• The membrane screening suggests that PVDF and PAN polymers are the most viable options for effective lipid recovery by concentration.

• Membrane fouling is lower for the RD than the crossflow module. However, at low velocity (1 m/s), filtration performance remains fairly close and both modules are more readily cleanable as the fouling seems mostly superficial. • At higher velocity, the fouling process is still unclear as the cleanability and fouling resistance are lowered. Further studies must be conducted in order to clarify the fouling mechanism as function of fluid velocities and/or shear rates.

Graphical determination of P c . Comparison of J Emulsion /J Water in the critical pressure (Pc) determination for the PAN 500 kDa membrane using the crossflow and rotating disk modules. The values differ slightly from the table; this calculation uses data from the Pc determination, while the table corresponds to the final value of the concentration experiment. The error bars correspond to experimental replicates.

Crossflow module (Orelis Rayflow

 The RD appears to have same performance as the crossflow technique at similar velocity conditions.  Membrane performance seems slightly enhanced with the RD velocity by increasing Pc and reducing R Fouling .

Screening characteristics for different commercial membranes used in the rotating disk module at 800 rpm (T=30°C). All membranes present a % R greater than 94 %. The PAN 500 kDa and PVDF 0.4 µm membranes seem to be the most promising candidates for oil droplet concentration.

The crossflow filtration results also suggest that the PAN 500 kDa membrane presents the best concentration characteristics.

CONCLUSION

  factor (smooth disk = 0.42, vaned disk= 0.89)[Bouzerar et al. 1999],[Frappart et al.