LAGOS Lake nutrient, carbon and chlororphyll data to evaluate biases in lake water quality sampling practices in a 17-state region of the US

This dataset includes data for eight major limnological variables in
LAGOS-NE_LIMNO v. 1.087.1 that were used to evaluate biases in lake
water quality sampling and implications for macroscale research
(Stanley et al. In Revision, Limnology and Oceanography). Most
observations came from LAGOS-NE_LIMNO v. 1.087.1, an integrated
database of lake ecosystems (Soranno et al. 2015, Soranno et al. 2017)
but were supplemented with additional data from the State of New
Hampshire. LAGOS-NE contains information on lakes great than or equal
to 1 ha (originally derived from the U.S. Geological Survey's 2013
National Hydrography Dataset) for a 17-state region of the U.S., and a
subset of the lakes has observational data on lake chemistry and
productivity. Approximately 87 different sources of data were compiled
for the LAGOS-NELIMNO v. 1.087.1 dataset and were mostly generated by
government agencies (state, federal, tribal) and universities. In this
analysis, we compiled data for eight major limnological variables
(Secchi disk depth, chlorophyll, total phosphorus, total nitrogen,
nitrate, ammonium, true water color, and dissolved organic carbon) and
geographic characteristics of lakes (location, lake area, depth,
perimeter, watershed area) to evaluate biases in different
limnological properties over space and time.

该数据集包含LAGOS-NE_LIMNO v.1.087.1中八个主要湖沼学变量（limnological variables）的数据，这些变量被用于评估湖泊水质采样偏差及其对宏观尺度研究的影响（Stanley等人，修订中，《湖沼学与海洋学》）。大部分观测数据源自LAGOS-NE_LIMNO v.1.087.1——一个整合的湖泊生态系统数据库（Soranno等人，2015；Soranno等人，2017），但补充了来自美国新罕布什尔州的额外数据。LAGOS-NE涵盖美国17州区域内面积≥1公顷的湖泊信息（原始数据来源于美国地质调查局2013年国家水文数据集（National Hydrography Dataset）），其中部分湖泊拥有湖泊化学（lake chemistry）和生产力（productivity）的观测数据。LAGOS-NE_LIMNO v.1.087.1数据集整合了约87个不同来源的数据，这些数据主要由政府机构（州、联邦、部落）和大学生成。在本分析中，我们整合了八个主要湖沼学变量（包括塞奇盘深度（Secchi disk depth）、叶绿素（chlorophyll）、总磷（total phosphorus）、总氮（total nitrogen）、硝酸盐（nitrate）、铵（ammonium）、真实水色（true water color）和溶解性有机碳（dissolved organic carbon））以及湖泊的地理特征（geographic characteristics）（位置、湖泊面积、深度、周长、流域面积）的数据，以评估不同湖沼学属性在空间和时间维度上的偏差。