NicholsonKnapp_etal_2023_BombusPesticideEffects

In each of eight European countries (Estonia, Germany, Ireland, Italy, Spain, Sweden, Switzerland, United Kingdom) we selected 16 sites split evenly between two focal crops (Apple: N = 64, Oilseed: N = 64) following a predefined PoshBee protocol (Schweiger et al. 2019). All sites were > 3 km apart to ensure spatial independence of bumblebee foraging ranges. Sites were selected to represent a gradient of agrochemical use and proportion of cropland. in the surrounding landscape The proportion of cropland coverage ranged from 3-98% within 1-km radius buffers. See Hodge et al. (2022) for setup of the study system using a multi-actor approach. Colonies were deployed between 2019-03-24 and 2019-05-12 depending on region and crop specific bloom times. Similarly, colonies were retrieved between 2019-05-06 and 2019-06-12. Colonies were weighed three times i) before installment at the field sites, ii) during the middle of flowering, iii) when the colonies are retrieved from the field sites. Total production, pesticide residue and pollen identity data collection happened after colonies were retrieved from the field.At each site we placed three colonies (N = 384) of Bombus terrestris terrestris, except in Ireland and the United Kingdom where the local subspecies Bombus terrestris audax was used. Colonies were all sourced through local providers. Before deployment colonies were checked for a natal queen and weighed (648 ± 70.9 g, mean ± SD). Colonies were deployed prior to crop bloom. Colonies were housed in protective structures. From each of these colonies we collected 1) metrics of colony performance and 2) pollen samples for pesticide residue analysis and palynological identification. For metrics of colony performance we determined the weight change and maximum weight achieved by individual colonies and colony total production. For weight, we measured each colony before, during, and after bloom and took the maximum value. For weight change, we calculated the natural-log response ratio for each colony as ln(g_max/g_initial), where g_initial is weight prior to bloom and g_max is the maximum weight achieved by a colony during its field placement. For colony production, we closed colonies after bloom and froze them (-20 C) for laboratory dissection. From dissected colonies we counted the number of intact and eclosed worker/male and queen cocoons, including the eclosed cocoons used for nectar and pollen storage. We sum these colony structures because individual counts may be unrepresentative due to absent colony members at the time of retrieval. After dissection, we extracted pollen stored in the colonies and pooled pollen evenly from all three colonies, aiming to obtain at least 15.0 g. Pollen samples were stored below -20 C. Samples were sent on dry ice to PIWet, where each site sample was homogenized and split for the analysis of pollen identity (1/5 sample amount) and pesticides residues (remaining sample amount). Analyses of residues were performed for samples in which quantity was at least 0.52 g (see Data Exclusions). For pesticide residue analysis, we used a previously described method (Kiljanek et al., 2021) that is validated according to SANTE/12682/2019 (European Commission et al., 2020) and accredited in accordance with the ISO 17025 standard. Reagent blanks and blank samples were analyzed in each batch. Recovery checks with samples spiked with pesticides at LOQ levels were performed in each analytical batch to meet SANTE/12682/2019 criteria. For pollen identification, palynological analyses were performed at the Research Centre for Agriculture and Environment (CREA) Bologna, Italy, a laboratory specialized in analyses of bees and bee products and accredited according to UNI CEI EN ISO/IEC 17025. Recognition of pollen type was based on comparison between the observed pollen forms and those present in the CREA collection of reference slides (developed using anthers of identified plant species). For each pollen type, the percentage with respect to the total number of counted pollen grains was calculated. Land use data is based on high resolution images provided by World Imagery (ESRI) land cover features were classified at a consistent scale of 1:2500. World Imagery provides one meter satellite and aerial imagery, typically within 3-5 years of currency, using a combination of imagery sources such as 2.5m SPOT imagery and 0.5m resolution imagery from DigitalGlobe. While performance metrics are replicated at the colony level, pesticide, pollen and landscape data are replicated at the site level. To accommodate this hierarchical data structure we used mixed effects models with site nested within country as a random factor References: Kiljanek, T., Niewiadowska, A., Małysiak, M., & Posyniak, A. (2021). Miniaturized multiresidue method for determination of 267 pesticides, their metabolites and polychlorinated biphenyls in low mass beebread samples by liquid and gas chromatography coupled with tandem mass spectrometry. Talanta, 235, 122721. European Commission. Analytical Quality Control and Method Validation Procedures for Pesticide Residues Analysis in Food and Feed. (2020) SANTE/12682/2019 Schweiger, O., Hodge, S., Rundlöf, M., Dominik, C. (2019) WP1.1.1 Field site selection. PoshBee protocol. Hodge, S., Schweiger, O., Klein, A. M., Potts, S. G., Costa, C., Albrecht, M., ... & Stout, J. C. (2022). Design and planning of a transdisciplinary investigation into farmland pollinators: rationale, co-design, and lessons learned. Sustainability, 14(17), 10549.本研究在8个欧洲国家（爱沙尼亚、德国、爱尔兰、意大利、西班牙、瑞典、瑞士、英国）共选取16个样点，两种目标作物（苹果：N=64；油料作物：N=64）的样点数量均分，所有样点选取均遵循预先设定的PoshBee方案（Schweiger等，2019）。所有样点间距均大于3km，以确保熊蜂（bumblebee）觅食范围的空间独立性。样点选取需覆盖农业化学品使用强度与周边农田占比的梯度，其周边1km缓冲区内的农田覆盖率范围为3%~98%。有关研究系统的多参与方搭建细节，详见Hodge等（2022）。 蜂群部署时间为2019年3月24日至2019年5月12日，具体日期依据区域与作物的具体开花期调整；蜂群回收时间则为2019年5月6日至2019年6月12日。蜂群共称重三次：① 野外安置前；② 开花中期；③ 从野外回收时。蜂群被回收后，开展蜂群总产出、农药残留及花粉种类的数据采集。 每个样点放置3群欧洲熊蜂指名亚种（Bombus terrestris terrestris），但爱尔兰与英国地区使用当地亚种欧洲熊蜂奥达克斯亚种（Bombus terrestris audax）。所有蜂群均通过本地供应商采购。部署前，检查蜂群是否带有原生蜂王并称重，初始重量为648±70.9g（均值±标准差）。蜂群于作物开花前完成部署，并置于防护装置中。 从每群蜂中采集两类样本：1）蜂群性能指标；2）用于农药残留分析与孢粉学鉴定的花粉样本。蜂群性能指标包括蜂群重量变化、单群最大重量及蜂群总产出。重量测量分别在开花前、开花期及开花后进行，取测量值中的最大值。重量变化通过自然对数响应比计算，公式为ln(g_max/g_initial)，其中g_initial为开花前的初始重量，g_max为蜂群野外放置期间达到的最大重量。 待开花结束后封闭蜂群，将其置于-20℃冰箱冷冻以待实验室解剖。解剖后计数完整的、已羽化的工蜂/雄蜂及蜂王茧，包括用于储存花蜜与花粉的已羽化茧。由于回收时可能存在蜂群成员缺失的情况，故将各类蜂群结构的数量求和，以避免单个计数缺乏代表性。解剖后提取蜂群内储存的花粉，将单个样点下3群蜂的花粉均匀混合，目标获取至少15.0g的花粉样本。花粉样本保存于-20℃以下环境，通过干冰运输至PIWet实验室。在该实验室中，每个样点的花粉样本均经过均质化处理，分为两份：1/5的样本量用于花粉种类鉴定，剩余样本量用于农药残留分析。 仅当样本质量≥0.52g时，才开展对应分析（详见数据排除标准）。农药残留分析采用已发表的方法（Kiljanek等，2021），该方法依据欧盟委员会（2020）发布的SANTE/12682/2019标准完成验证，并符合ISO 17025标准的认可要求。每一批次分析均设置试剂空白与空白样本对照；每一批次均使用添加了定量限（LOQ）级农药的样本开展回收率检测，以满足SANTE/12682/2019标准的要求。 花粉种类鉴定由意大利博洛尼亚农业与环境研究中心（CREA）完成，该实验室专注于蜂类及蜂产品分析，且通过UNI CEI EN ISO/IEC 17025标准认可。花粉类型的识别通过将观测到的花粉形态与CREA参考玻片库（由已鉴定植物物种的花药制备）中的样本比对实现。对每一种花粉类型，计算其占所计数花粉总粒数的百分比。 土地利用数据基于世界影像（World Imagery，ESRI）提供的高分辨率影像，土地覆盖特征以1:2500的统一比例尺进行分类。World Imagery提供1米分辨率的卫星及航空影像，通常时效性在3~5年以内，整合了包括2.5m分辨率SPOT影像及DigitalGlobe提供的0.5m分辨率影像在内的多种影像源。 由于蜂群性能指标以蜂群为重复单元，而农药、花粉及景观数据以样点为重复单元，为适配这种分层数据结构，本研究采用混合效应模型，将样点嵌套于国家作为随机因子。 参考文献： 1. Kiljanek, T., Niewiadowska, A., Małysiak, M., & Posyniak, A. (2021). 采用液相与气相色谱-串联质谱法测定低质量蜂粮样品中267种农药、其代谢物及多氯联苯的微型多残留方法. Talanta, 235, 122721. 2. 欧盟委员会. 食品与饲料中农药残留分析的分析质量控制与方法验证程序. (2020) SANTE/12682/2019 3. Schweiger, O., Hodge, S., Rundlöf, M., Dominik, C. (2019) WP1.1.1 样地选择. PoshBee方案 4. Hodge, S., Schweiger, O., Klein, A. M., Potts, S. G., Costa, C., Albrecht, M., et al. (2022). 农田传粉者跨学科调查的设计与规划：理论依据、协同设计及经验教训. Sustainability, 14(17), 10549.