Natural lakes and reservoirs chlorophyll responses to drought across the conterminous United States

These datasets were created to quantify how natural lakes (NLs) and reservoirs (RSVRs) across the conterminous U.S. (CONUS) with different levels of hydrologic connectivity respond to drought and how natural and human factors operating at multiple spatial scales affect lake responses. The data used in this study were from the LAGOS-US research platform (Cheruvelil et al. 2021; https://doi.org/10.1002/lol2.10203) that includes lake and landscape data for 479,950 lakes ≥ 1 ha across the CONUS. 

Project title: Sun, X., Cheruvelil, K.S., Hanly, P.J., &Soranno, P.A. Lake chlorophyll responses to drought are related to lake type, connectivity, and ecological context across the conterminous United States. 

Manuscript citation: Sun, X., Cheruvelil, K.S., Hanly, P.J., &Soranno, P.A. (2025). Lake chlorophyll responses to drought are related to lake type, connectivity, and ecological context across the conterminous United States. Limnology and Oceanography. doi: 10.1002/lno.12817

Three datasets are included:

SPI.csv: Dataset contains the standard precipitation index (SPI) values from January 2009 to December 2018 for 479,950 lakes across the conterminous U.S.

full_dataset_32predictors.csv: Dataset contains the response variables (ΔZ-score-median and directions of CHL responses) and 32 predictors (excluding lake maximum depth) for 62,927 lakes across the conterminous U.S.

depth_subset_33predictors.csv: Dataset contains the response variables (ΔZ-score-median and directions of CHL responses) and 33 predictors (including lake maximum depth) for 8,994 lakes across the conterminous U.S.

Some data were transformed and some variable names in the dataset are different from the names in the manuscript. Please see the Metadata file for the transformation and conversion of variable names. The 'lagoslakeid' (LAGOS-US unique identifier for each lake) is included in the dataset as a variable but was not used as a predictor in analyses.

本数据集旨在量化美国本土（conterminous U.S.，CONUS）范围内不同水文连通性水平的天然湖泊（Natural Lakes，NLs）与水库（Reservoirs，RSVRs）对干旱的响应规律，以及多空间尺度下自然与人为因子如何调控湖泊的响应过程。本研究所用数据来自LAGOS-US研究平台（Cheruvelil等，2021；https://doi.org/10.1002/lol2.10203），该平台涵盖了美国本土范围内479950个面积≥1公顷的湖泊及流域景观数据。

项目题名：Sun, X.、Cheruvelil, K.S.、Hanly, P.J. 及Soranno, P.A.：《美国本土范围内湖泊叶绿素（Chlorophyll，CHL）对干旱的响应与湖泊类型、连通性及生态背景的关联》

稿件引用：Sun, X., Cheruvelil, K.S., Hanly, P.J. 及Soranno, P.A. (2025). 美国本土范围内湖泊叶绿素对干旱的响应与湖泊类型、连通性及生态背景的关联. 《湖沼学与海洋学》. doi: 10.1002/lno.12817

本数据集包含三个文件：
1. SPI.csv：该数据集包含美国本土范围内479950个湖泊在2009年1月至2018年12月间的标准化降水指数（Standard Precipitation Index，SPI）值。
2. full_dataset_32predictors.csv：该数据集涵盖美国本土范围内62927个湖泊的响应变量（ΔZ-score-中位数与叶绿素响应方向），以及32个预测变量（不含湖泊最大深度）。
3. depth_subset_33predictors.csv：该数据集涵盖美国本土范围内8994个湖泊的响应变量（ΔZ-score-中位数与叶绿素响应方向），以及33个预测变量（包含湖泊最大深度）。

部分数据已完成转换，且数据集中的部分变量名称与稿件中存在差异。有关变量名称的转换规则与数据处理方法，请参阅元数据文件。数据集中包含lagoslakeid字段（LAGOS-US平台为每个湖泊分配的唯一标识符），但该字段未被用作分析中的预测变量。