Replication Data for: Functional Pattern of Benthic Epifauna in the Chukchi Borderland, Arctic Deep Sea

This dataset contains “traits by taxon”, “taxa by stations”, and “traits by stations” matrices for 106 benthic epifaunal taxa collected with a beam trawl and a Remotely Operated Vehicle (ROV) in the Chukchi Borderland (CBL), north of Alaska (74 - 78°N, 158 - 165°W) on-board USCGC Healy in July–August 2016 from 486 – 2610 m depth. The data were used to evaluate ecosystem functioning of the deep-sea Arctic CBL with the Biological Trait Analysis. Table S1 contains literature sources used for coding trait modalities. Table S2 contains the “traits by taxon” matrix for epifaunal taxa collected with both the ROV and the beam trawl across the study area. Nine traits with a total of 39 modalities, reflecting morphology (adult size, body form), behavior (living habitat, mobility, adult movement, feeding habit, substrate affinity), and life-cycle characteristics (larval development and reproduction) of the epifauna are included in this matrix. Every trait is coded for every taxon with a ‘fuzzy coding’ procedure (Chevenet et al., 1994). Tables S3, S4, and S5 are “taxa by stations” matrices, containing the following information: presence and absence of epifauna at each station sampled with both the ROV and the beam trawl (Table S3), proportional abundance of epifauna collected with the ROV (Table S4) and proportional abundance of epifauna collected with the beam trawl (Table S5) at each station. These tables (S3, S4, and S5) along with Table S2 were used to generate “traits by stations” matrices (i.e., Tables S6, S7, and S8) through multiplying corresponding matrices. Tables S6, S7, and S8 are “traits by stations” matrices containing weighted scores of traits based on presence and absence of epifauna sampled with the ROV and the beam trawl (Table S6), proportional abundance of epifauna sampled with the ROV (Table S7), and proportional abundance of epifauna sampled with the beam trawl (Table S8). Table S6 was used to identify dominant trait modalities represented in the epifauna of the study area. Tables S7 and S8 were used to identify: 1) variability in functional structure of epifauna between mid-depth and deeper stations with a fuzzy correspondence analysis and a non-parametric Kruskal-Wallis test, and 2) environmental factors influencing the functional structure of epifaunal communities in the study area by a canonical correspondence analysis. Tables S4 and S5 were used to calculate Simpson index (D). Tables S3, S4, and S5 along with the Table S2 were used to calculate Functional diversity (Rao's quadratic entropy, FD) and Functional Redundancy (1 – (FD/D)) indices to also check for functional difference between mid-depth and deep stations with a Kruskal-Wallis test.本数据集包含106个底栖表栖生物分类单元的"分类单元-性状""站位-分类单元"以及"站位-性状"三类矩阵。这些生物于2016年7-8月搭载美国海岸警卫队希利号（USCGC Healy），在阿拉斯加北部楚科奇边缘地带（CBL，74°N~78°N，158°W~165°W）海域，使用桁拖网与遥控无人潜水器（Remotely Operated Vehicle, ROV）采集自水深486~2610 m的站位。本数据集依托生物性状分析（Biological Trait Analysis），用于评估北极楚科奇边缘地带深海生态系统的功能运作。 表S1收录了用于编码性状状态的文献来源。表S2收录了研究区域内同时使用遥控无人潜水器与桁拖网采集的表栖生物分类单元的"分类单元-性状"矩阵。该矩阵共包含9类性状，总计39种性状状态，涵盖表栖生物的形态学特征（成体体型、躯体形态）、行为特征（栖息生境、移动能力、成体活动方式、摄食习性、底质亲和性）以及生活史特征（幼体发育与繁殖策略）。所有性状均通过模糊编码（fuzzy coding）流程为每个分类单元赋值（Chevenet等，1994）。 表S3、S4与S5均为"站位-分类单元"矩阵，包含以下信息：表S3记录了同时使用遥控无人潜水器与桁拖网采集的各采样站位的表栖生物存在/缺失情况；表S4记录了各站位使用遥控无人潜水器采集的表栖生物的相对丰度；表S5记录了各站位使用桁拖网采集的表栖生物的相对丰度。上述三张表格（S3、S4、S5）与表S2通过对应矩阵相乘的方式，生成了"站位-性状"矩阵（即表S6、S7与S8）。 表S6、S7与S8为"站位-性状"矩阵，其中表S6基于遥控无人潜水器与桁拖网采集的表栖生物存在/缺失情况计算性状加权得分；表S7基于遥控无人潜水器采集的表栖生物相对丰度计算性状加权得分；表S8基于桁拖网采集的表栖生物相对丰度计算性状加权得分。 表S6用于识别研究区域表栖生物群落中占优势的性状状态。表S7与S8用于开展两项分析：其一，通过模糊对应分析与非参数Kruskal-Wallis检验，解析中深层站位与深层站位间表栖生物功能结构的差异；其二，通过典范对应分析，识别影响研究区域表栖生物群落功能结构的环境因子。 表S4与S5用于计算辛普森多样性指数（D）。表S3、S4、S5与表S2还被用于计算功能多样性（Rao二次熵，FD）与功能冗余度（1 – (FD/D)）指数，并通过Kruskal-Wallis检验验证中深层与深层站位间的功能差异。