Analysing spatio-temporal patterns of non-native fish in a biodiversity hotspot across decades

Aim: Analysing the spatio-temporal patterns and dynamics of non-native species is essential to understanding the mechanisms underlying successful invasions and developing effective management strategies. Yet, such analyses generally neglect the influence of receiving ecosystem types and non-native species sources (i.e. alien species, non-natives originating outside the concerned region; translocated species, nonnatives introduced to locations outside their historical range within the concerned region). Location: Yunnan, China. Methods: We analysed long-term (1950–2022) spatio-temporal patterns and potential underlying dynamics of non-native fishes in a biodiversity hotspot (Yunnan, China), paying special attention to waterbody types receiving non-native species and comparing alien and translocated species. We did this through compiling a highly comprehensive occurrence dataset of native and non-native fishes. Results: We recorded 783 native species and 94 non-native species (49 alien s..., , , # Analysing spatio-temporal patterns of non-native fish in a biodiversity hotspot across decades The spreadsheet compilations (yunnan--fish.xlsx) include a list of the underlying data used in this paper: \"Analysing spatio-temporal patterns of non-native fish in a biodiversity hotspot across decades\". ## Description of the data and file structure Data includes worksheet: \"References\", worksheet: \"Occurrences\", worksheet: \"Clarification\". In \"References\", this table provides all the reference sources used in this dataset, which are available in both Chinese and English sources. In \"Occurrences\", here we provide detailed occurrence information for 829 Yunnan fish species, of which the detailed coordinates of endangered species have been converted with the aim of studying them while and promoting their better conservation. Species Endangered class are derived from Chen et al., 2023 (\"Assessing the conservation status of Chinese freshwater fish using deep learning\"). In \"Clarification\"...研究目标：解析外来物种（non-native species）的时空格局与动态，是阐明成功入侵机制、制定有效管理策略的核心前提。然而，现有此类分析普遍忽略了接收生态系统类型以及外来物种来源的影响：前者为外来种（alien species），即起源于研究区域之外的非本土物种；后者为移殖种（translocated species），即被引入至研究区域内其历史分布范围之外的非本土物种。 研究区域：中国云南省。 研究方法：本研究针对生物多样性热点地区（biodiversity hotspot）——中国云南省的外来鱼类展开分析，时间跨度为1950年至2022年，解析其时空格局与潜在内在动态；重点关注接纳外来物种的水体类型，并对比外来种与移殖种的差异。本次分析通过整合一套覆盖极广的本土与外来鱼类出现记录数据集完成。 研究结果：本次调查共记录到本土鱼类783种，外来鱼类94种（其中外来种49种……）。 # 数十年间生物多样性热点地区外来鱼类的时空格局解析 本研究编制的电子表格数据集（yunnan--fish.xlsx）包含本论文所依托的全部原始数据，该论文标题为"Analysing spatio-temporal patterns of non-native fish in a biodiversity hotspot across decades"。 ## 数据与文件结构说明 本数据集包含三个工作表：「参考文献（References）」、「出现记录（Occurrences）」与「说明（Clarification）」。 在「参考文献（References）」工作表中，本表格列出了本数据集所使用的全部参考文献来源，相关文献涵盖中文与英文两种语种。 在「出现记录（Occurrences）」工作表中，我们提供了云南省829种鱼类的详细出现记录信息；为在开展研究的同时推动濒危物种保护，所有濒危物种的精确坐标均已进行脱敏转换处理。鱼类濒危等级的划分依据Chen等人2023年发表的《利用深度学习评估中国淡水鱼类保护现状》（*Assessing the conservation status of Chinese freshwater fish using deep learning*）确定。 在「说明（Clarification）」工作表中……