Data from: Divergence of Arctic shrub growth associated with sea ice decline

AbstractArctic sea ice extent (SIE) is declining at an accelerating rate with a wide range of ecological consequences. However, determining sea ice effects on tundra vegetation remains a challenge. In this study, we examined the universality or lack thereof in tundra shrub growth responses to changes in SIE and summer climate across the Pan-Arctic, taking advantage of 23 tundra shrub-ring chronologies from 19 widely distributed sites (56⁰-83⁰N)., MethodsWe acquired both published and unpublished deciduous shrub-ring chronologies that were distributed throughout the Arctic region and covered, if possible, the entire 40 year-long period of passive microwave satellite-based estimates of arctic sea ice extent (SIE) (1979-present). In order to perform a comparable study at the biome level, our synthesis focused on two shrub genera of commonly studied and widespread deciduous shrubs: Betula and Salix. Shrub-ring data were included in our analyses if the corresponding chronologies i) covered the common period (1979-2008) and ii) had an EPS (a theoretical indicator of how well the chronology represents the population mean) greater than 0.75. Our final dataset consisted of 23 chronologies (9 Betula spp. chronologies and 14 Salix spp. chronologies), 641 shrubs (306 Betula shrubs and 335 Salix shrubs), and 753 cross-sections. This dataset consists of 23 RWL files for 23 shrub ring chronologies. Each RWL file (Tucson format, unit = mm, resolution 0.001) contains raw data for all individual shrub growth series used to established each site chronology. Raw data are averaged at the plant level for the shrubs that were subjected to serial sectioning or when more than one cross-section was sampled per individual shrub. These are raw individual shrub data, not detrended or standardized., Usage notesReadMe_v01: File description for manuscript Buchwal et al. 2020: Divergence of Arctic shrub growth associated with sea ice decline. https://www.pnas.org/content/early/2020/12/09/2013311117 Version_01 Date: November 22, 2020 Contact person: Agata Buchwal, Adam Mickiewicz University Poznan, Poland, ORCID ID: 0000-0001-6879-6656; [e-mail] This repository consist of: #1: Table 1: Metadata file for 23 shrub ring chronologies used in the Buchwal et al. (2020) synthesis #2: 23 RWL files for 23 shrub ring chronologies. Each RWL file (Tucson format, unit = mm, resolution 0.001) contains raw data for all individual shrub growth series used to established each site chronology. Raw data are averaged at the plant level for the shrubs that were subjected to serial sectioning or when more than one cross-section was sampled per individual shrub. These data are not detrended or standardized. If You need shrub ring data at the cross-sectional level, please contact a relevant data contributor/-s (Table 1, column Q). In order to open RWL files (.rwl) you can use ‘read.rwl’ function in dplR package (Bunn 2008) in R (R Core Team). List of RWL files attached: AF_SAR.rwl BL_BGL.rwl BS_BGL.rwl BT_BGL.rwl DE_SGL.rwl DK_BNA.rwl EB_SPO.rwl GR_BGL.rwl HE_SAR.rwl HE_SRI.rwl KG_BNA.rwl KG_SGL.rwl KY_BNA.rwl KY_SPU.rwl LA_SAR.rwl LB_SRI.rwl PL_SAR.rwl RE_SAR.rwl TL_BNA.rwl UM_BGL.rwl VA_SRI.rwl YR_SRI.rwl ZA_SAR.rwl References: A. G. Bunn, A dendrochronology program library in R (dplR). Dendrochronologia 26, 115-124 (2008). R Core Team R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.URL https://www.R-project.org/ (2018).摘要 北极海冰范围（Sea Ice Extent, SIE）正以不断加快的速率衰减，并引发一系列广泛的生态后果。然而，明确海冰对苔原植被的影响仍是一项极具挑战性的工作。本研究依托分布于泛北极区域19个广泛样点（北纬56°至83°）的23条苔原灌木年轮年表，探究了苔原灌木生长对海冰范围与夏季气候变化的响应是否具有普遍性。 方法 我们收集了已发表及未发表的落叶灌木年轮年表，这些年表覆盖整个北极区域，且尽可能涵盖了被动微波卫星估算北极海冰范围的完整40年时段（1979年至今）。为在生物群系层面开展可比研究，本综合分析聚焦于两类被广泛研究且分布普遍的落叶灌木属：桦木属（Betula）与柳属（Salix）。纳入本分析的灌木年轮数据需满足两项条件：i）覆盖共同研究时段（1979-2008年）；ii）EPS（表征年表对总体均值代表性的理论指标）大于0.75。最终数据集包含23条年表（9条桦木属年表与14条柳属年表）、641株灌木（306株桦木属灌木与335株柳属灌木）以及753个横切面。本数据集包含对应23条灌木年轮年表的23个RWL文件。每个RWL文件采用图森格式，单位为毫米，分辨率为0.001，包含用于构建每个样点年表的所有单株灌木生长序列的原始数据。对于经连续切片处理或单株灌木采样多个横切面的样本，原始数据已按植株水平进行平均。这些为原始单株灌木数据，未经过去趋势或标准化处理。 使用说明 ReadMe_v01：对应论文Buchwal等人2020年的《与海冰衰减相关的北极灌木生长分化》，链接：https://www.pnas.org/content/early/2020/12/09/2013311117 版本01，日期：2020年11月22日 联系人：Agata Buchwal，波兰波兹南亚当·密茨凯维奇大学，ORCID编号：0000-0001-6879-6656；邮箱：[e-mail] 本仓库包含： #1：表1：Buchwal等人（2020）综合分析中所用的23条灌木年轮年表的元数据文件 #2：对应23条灌木年轮年表的23个RWL文件。每个RWL文件采用图森格式，单位为毫米，分辨率为0.001，包含用于构建每个样点年表的所有单株灌木生长序列的原始数据。对于经连续切片处理或单株灌木采样多个横切面的样本，原始数据已按植株水平进行平均。这些数据未经过去趋势或标准化处理。若您需要横切面层面的灌木年轮数据，请联系相关数据贡献者（见表1第Q列）。 可使用R语言中dplR包（Bunn 2008）的read.rwl函数打开RWL文件（.rwl格式）。 附RWL文件列表：AF_SAR.rwl、BL_BGL.rwl、BS_BGL.rwl、BT_BGL.rwl、DE_SGL.rwl、DK_BNA.rwl、EB_SPO.rwl、GR_BGL.rwl、HE_SAR.rwl、HE_SRI.rwl、KG_BNA.rwl、KG_SGL.rwl、KY_BNA.rwl、KY_SPU.rwl、LA_SAR.rwl、LB_SRI.rwl、PL_SAR.rwl、RE_SAR.rwl、TL_BNA.rwl、UM_BGL.rwl、VA_SRI.rwl、YR_SRI.rwl、ZA_SAR.rwl 参考文献 [1] Bunn A G. A dendrochronology program library in R (dplR)[J]. Dendrochronologia, 2008, 26: 115-124. [2] R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 链接：https://www.R-project.org/ (2018).