DOI: 10.6084/m9.figshare.20390751
title: Supporting Data: Ecological traits interact with landscape context to determine bees' pesticide risk

description: <strong>Rationale</strong> We conducted our study in Scania, Southern Sweden, an intensively farmed European production region. The selected sites cover multiple mass-flowering crops and agricultural contexts representing temperate agricultural landscapes and different pesticide use patterns. In addition, our three bee species exemplify different life-history traits that determine their activity. Both these aspects are important since bees are predicted to encounter pesticides as their activity intersects pesticide use patterns. The three bee species were <em>Apis mellifera</em>, <em>Bombus terrestris</em> and <em>Osmia bicornis,</em> representing extensive, intermediate and limited bee foragers. <strong>Study design</strong> We selected 24 sites centred on three bee-attractive flowering crops that flower sequentially: oilseed rape (8 sites), apple (8 sites) and red clover (8 sites), and are common in the region. We selected sites based on their surrounding proportion of agricultural land (2km radius) to ensure an even gradient (for each crop type) of agricultural land and, therefore, anticipated pesticide use. We placed multiple colonies and seeding cocoons within sites to facilitate the collection of bees (for nectar extraction) and pollen sufficient for pesticide residue quantification. We sampled pollen from (1) <em>A. mellifera </em>using pollen traps attached to two hives for 24 hours, (2) <em>B. terrestris </em>by capturing foragers (~20 across all six colonies) and euthanising them on dry ice as they returned to their colonies, and (3) multiple <em>O. bicornis</em> brood cells collected by females over the second half of the bloom period. We sampled pollen from <em>A. mellifera</em> and <em>B. terrestris</em> at two sampling intervals, coinciding with (1) the peak of crop bloom and (2) after crop bloom and for <em>O. bicornis</em> only at the end of crop bloom (evenly from all the available pollen). In total, we collected 48 samples (595 g) of <em>A. mellifera</em>-, 44 samples (11 g) of <em>B. terrestris-</em>, and 16 samples (70 g) of <em>O. bicornis</em>- collected pollen. During and after bloom, samples were pooled for both <em>A. mellifera</em> and <em>B. terrestris</em>, resulting in 24 samples of <em>A. mellifera</em>-, 22 samples of <em>B. terrestris</em>- (all colonies died at two sites), and 16 samples of<em> O. bicornis-</em>collected pollen. We did not pool <em>O. bicornis</em> pollen since this species already combined pollen provisions for the bloom period on our behalf. To explore exposure between sample materials, we sampled additional returning foragers of <em>A. mellifera</em> (n = ~100) and <em>B. terrestris</em> (n = ~20) 1-2, 4-6 and 12-16 days after a known pesticide application at four oilseed rape, two apple and seven red clover sites (Table S2). Corbicular pollen and nectar stomach content were collected from these foragers to produce paired pollen and nectar samples for each site and collection time point (n = 54). We froze pollen and bee samples for subsequent nectar collection, at -20oC before screening for pesticide compounds included in the Swedish national monitoring scheme (Table S3), following established protocols at the Laboratory for Organic Environmental Chemistry (SLU) (See Manuscript). <strong>Pesticide Risk Calculation</strong> We use toxicity-weighted exposure (<em>TWE</em>) as a basis for indicating bees' pesticide risk, whereby the <em>TWE</em> for each compound (<em>TWEi</em>) was the ratio between a detected compound's concentration in bee-collected pollen or nectar and its respective acute toxicity endpoint (<em>LD50i</em> - the dose required to cause 50% mortality in the test population) (PPDB 2019). Then, following a concentration addition approach - the recommended default for mixture environmental risk assessment (even though some compound classes may synergise), we summed <em>TWE</em>s, to calculate the additive toxicity-weighted exposure of all compounds within a sample, per site and bee species. We refer to this metric, an indicator of environmental pesticide-related risk, as "risk". <strong>Statistical methods</strong> We conducted three primary analyses to understand agricultural pesticide exposure and risk to bee species, followed by a supporting multivariate analysis of the compound composition: <br> Exposure/risk <em>and</em> use of agricultural pollen in relation to the focal crop, bee species and the proportion of agricultural land. <strong>See "AgriculturalLandPollenExposureRiskKnappEtAl2022.xlsx"</strong> We used LMMs to explore (1) risk from pollen and (2) use of agricultural pollen, with focal crop and bee species interacting with the proportion of agricultural land as fixed effects and site as a random intercept. We included an interaction between bee species and crop for both analyses, but this was non-significant and thus removed. Exposure/risk in relation to sampling round, focal crop and bee species. <strong>See "TimePointExposureRiskKnappEtAl2022.xlsx"</strong> We tested whether risk varied between the different sampling rounds via LMM with sample round, focal crop and bee species included as fixed effects and site as a random intercept. <br> Exposure and risk among bee species <strong>See "AgriculturalLandPollenExposureRiskKnappEtAl2022.xlsx"</strong> We examined risk relationships among bee species' site-specific pollen collection using three linear models, one for each species. We included the remaining bee species and focal crop as fixed effects; however, the focal crop was non-significant in all models (<em>P </em> &gt; 0.05). <br> Exposure and risk between pollen and nectar <strong>See "PollenNectarExposureRiskKnappEtAl2022.xlsx"</strong> We used data from the paired pollen-nectar collections to test for a difference in risk between sample materials (pollen vs nectar), using LMMs with sample material, focal crop and bee species as fixed effects, and sampling round nested in the site as a random effect. In addition, we examined risk relationships among sample material collections, using LMMs with nectar risk specified as the response variable and pollen risk, focal crop and bee species as fixed effects, and sampling round nested in the site as a random intercept. <br> Differences in compound composition <strong>See "</strong> <strong>KnappEtAl2022PesticideAdjacencyMatrix.xlsx"</strong> We used PERMANOVA to compare the composition of compounds between focal crops and bee species using a Bray-Curtis dissimilarity index based on a Hellinger standardised community matrix of risk values using the 'adonis2()' function in 'vegan'. We used non-metric multidimensional scaling (NMDS) to visualise different clusters of compounds. We tested for differences in dispersion between focal crops or bee species using the 'betadisper()' function in 'vegan'. We detected no differences in the dispersion of compounds between crops. However, we found different dispersion of compounds between bee species (<em>P</em> = 0.03); therefore, we should interpret these community differences cautiously.