Ixodes Scapularis monitoring data compiled from 7 studies

This dataset lists 289 blacklegged tick population datasets from 7 studies that record abundance. These datasets were found by inputing keywords <em>Ixodes Scapularis</em> and <em>tick </em>in data repositories including Long Term Ecological Research data portal, National Ecological Observatory Network data portal, Google Datasets, Data Dryad, and Data One. The types of tick data recorded from these studies include density (number per square meter for example), proportion of ticks, count of ticks found on people. The locations of the datasets range from New York, New Jersey, Iowa, Massachusetts, and Connecticut, and range from 9 to 24 years in length. These datasets vary in that some record different life stages, geographic scope (county/town/plot), sampling technique (dragging/surveying), and different study length. The impact of these study factors on study results is analyzed in our research. Funding: RMC is supported by the National Institute of General Medical Sciences of the National Institutes of the Health under Award Number R25GM122672. CAB, JP, and KSW are supported by the Office of Advanced Cyberinfrastructure in the National Science Foundation under Award Number #1838807. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the National Science Foundation.本数据集收录了来自7项种群丰度记录研究的289份黑腿硬蜱（blacklegged tick）种群数据集。本数据集通过在长期生态研究数据门户（Long Term Ecological Research data portal）、国家生态观测站网络数据门户（National Ecological Observatory Network data portal）、谷歌数据集（Google Datasets）、Dryad数字仓储（Data Dryad）以及Data One等数据仓储中，以关键词"Ixodes Scapularis（肩突硬蜱）"与"蜱"进行检索后获得。收录的蜱类数据类型包括种群密度（例如每平方米个体数量）、蜱虫占比以及人体体表发现的蜱虫计数等。数据集的覆盖区域涵盖美国纽约州、新泽西州、艾奥瓦州、马萨诸塞州与康涅狄格州，单份数据集的研究时长跨度为9至24年不等。各数据集间存在差异：部分数据集记录了不同的蜱虫生活史阶段、地理研究范围（县/镇/样地尺度）、采样技术（拖拽法/调查法）以及研究时长。本研究针对上述各项研究因素对研究结果的影响展开了分析。资助说明：RMC受美国国立卫生研究院（National Institutes of Health）下属普通医学科学研究所资助，项目编号为R25GM122672。CAB、JP与KSW受美国国家科学基金会先进计算基础设施办公室（Office of Advanced Cyberinfrastructure）资助，项目编号为#1838807。本文内容仅代表作者个人观点，不一定代表美国国立卫生研究院或美国国家科学基金会的官方立场。