The importance of accounting for landscape position when investigating grasslands: A multidisciplinary characterisation of a Californian coastal grassland

Data from the characterisation of the Point Reyes Field Site, published in AGU Earth's Future under the title: The importance of accounting for landscape position when investigating grasslands: A multidisciplinary characterisation of a Californian coastal grassland. This paper explored the effect of landscape position on the response of a Californian grassland to seasonal changes. All files are csv files. The EMI data contains 8 csv files with a metadata csv explaining the columns. The dataset also includes soil variables including total concentrations calculated from fused samples, then dissolved and measured on ICP-AES for whole-rock elements and ICP-MS for trace elements. Mineral composition was attained using X-ray diffraction at BL 11-3 at SSRL . Data was then run through the High Score database to characterise different mineral phases. total It also includes a table with bulk soil characteristics such as soil pH, cation exchange capacity, and soil textural data. Data from Teros 12 Meter soil moisture, electrical conductivity and temperature sensors are presented in SMS Csv file. While the WL bottom and top files contain data from Piezometers measuring the ground water table. We have included a csv file that contains soil CO2 efflux data from Feb 2021-Oct 2021 in the Point Reyes Grassland Experiment We have included the spatially orientated (easting northing) remotely sensed datasets that were used in the K-means clustering analysis conducted on our site with electrical conductivity, normalised difference vegetation index, elevation, slope, solar radiation, topographic position and wetness index, and a clustering score. Finally there is a list of all the identified grassland species at the site.For more information on flux data, please contact the corresponding author.

本数据集源自雷耶斯角野外站点（Point Reyes Field Site）的表征研究，该成果发表于美国地球物理联盟（American Geophysical Union, AGU）《AGU Earth's Future》期刊，论文标题为《探究草地研究中考虑景观位置的重要性：加利福尼亚沿海草地的多学科表征》。本研究探讨了景观位置对加利福尼亚草地响应季节变化的调控效应。所有数据文件均为逗号分隔值（Comma-Separated Values, CSV）格式。其中电磁感应（Electromagnetic Induction, EMI）数据集包含8个CSV文件，另有1个元数据CSV文件对各数据列的含义进行详细说明。本数据集还涵盖土壤变量数据：包括由熔融样品计算得到的全量元素浓度，后续通过电感耦合等离子体原子发射光谱法（Inductively Coupled Plasma Atomic Emission Spectroscopy, ICP-AES）测定全岩元素含量，通过电感耦合等离子体质谱法（Inductively Coupled Plasma Mass Spectrometry, ICP-MS）测定微量元素含量。矿物组成数据通过斯坦福同步辐射光源（Stanford Synchrotron Radiation Lightsource, SSRL）的BL 11-3光束线的X射线衍射技术获取，随后借助High Score数据库对不同矿物相进行表征分析。此外，数据集包含一套土壤整体特性表格，涵盖土壤pH值、阳离子交换量以及土壤质地数据。来自Teros 12型土壤水分、电导率及温度传感器的监测数据收录于SMS CSV文件中。WL底部与顶部文件则包含由地下水位测压计（Piezometer）获取的地下水位监测数据。本研究还添加了2021年2月至2021年10月期间雷耶斯角草地试验的土壤CO2排放通量数据CSV文件。数据集纳入了用于本研究区域K-means聚类分析的空间参考遥感数据集，包含东向、北向坐标信息，配套数据集包括电导率、归一化差分植被指数（Normalized Difference Vegetation Index, NDVI）、海拔、坡度、太阳辐射、地形位置指数以及湿度指数，同时附带聚类得分数据。最后，本数据集包含本研究区域内已鉴定的所有草地物种名录。关于土壤CO2通量数据的更多详细信息，请联系本文通讯作者。