Near-real-time Herbaceous Annual Cover in the Sagebrush Ecosystem, USA, July 2018

This dataset provides a near-real-time estimate of 2018 herbaceous annual cover with an emphasis on annual grass (Boyte and Wylie. 2016. Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015. Rangelands 38:278-284.) This estimate was based on remotely sensed enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) data gathered through July 1, 2018. This is the second iteration of an early estimate of herbaceous annual cover for 2018 over the same geographic area. The previous dataset used eMODIS NDVI data gathered through May 1 (https://doi.org/10.5066/P9KSR9Z4). The pixel values for this most recent estimate ranged from 0 to100% with an overall mean value of 9.23% and a standard deviation of +/-11.35. The model's test mean error rate (n = 1664), based on nine different randomizations, equaled 5.2% with a standard deviation of +/- 0.09. Overall statistics between the May and June datasets were similar. However, some individual pixel differences can be considerable and are attributed to changing conditions on the ground that are reflected in the satellite data. These changes can influence how the models relate the dependent variable to the independent variables. Both datasets were generated by integrating ground-truth measurements of annual herbaceous percent cover with 250-m spatial resolution eMODIS NDVI satellite derived data and geophysical variables into regression-tree software. The geographic coverage includes the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. We applied a mask to areas above 2250-m elevation because annual grasses are unlikely to exist at substantial cover above this threshold. To target likely sagebrush ecosystems, the mask also covered pixels classified as something other than shrub or grassland/herbaceous by the 2011 National Land Cover Dataset (NLCD). The model was not trained on any masked pixels. Cheatgrass (Bromus tectorum) is the most common annual grass in the study area, but red brome (Bromus rubens), medusahead (Taeniatherum caput-medusae), and ventenata (Ventenata dubia) are also problematic. They grow from seed, usually in spring, mature quickly, produce seed, and die. After dying, these annual grasses contribute fine fuels that facilitate fire ignition and spread throughout sagebrush ecosystems. These fires remove sagebrush stands. Increasing fire frequencies, land management practices, and development have all contributed to the fragmentation of the once expansive sagebrush ecosystems. These ecosystems are critical for water quality, reduced fire threats, and the survival of sagebrush-dependent wildlife.本数据集提供2018年一年生草本覆盖度的近实时估算结果，研究重点聚焦一年生禾草（引自Boyte与Wylie，2016年发表于《Rangelands》的《美国北大盆地2015年实时反演的雀麦覆盖百分比》，38卷：278-284页）。本次估算基于截至2018年7月1日收集的遥感增强型中分辨率成像光谱仪（enhanced Moderate Resolution Imaging Spectroradiometer, eMODIS）归一化植被指数（Normalized Difference Vegetation Index, NDVI）数据。本数据集为针对同一地理区域2018年一年生草本覆盖度早期估算的第二版成果，此前的数据集使用的是截至2018年5月1日收集的eMODIS NDVI数据（https://doi.org/10.5066/P9KSR9Z4）。本次最新估算的像素值取值区间为0至100%，整体均值为9.23%，标准差为±11.35；基于9次随机化分组得到的模型测试平均误差率（样本量n=1664）为5.2%，标准差为±0.09。5月版与6月版数据集的整体统计特征相近，但部分单个像素的差值较为显著，该差异源于卫星数据所捕捉的地表条件变化，此类变化会影响模型对因变量与自变量的关联建模。两款数据集均通过将一年生草本覆盖度的地面实测数据、250米空间分辨率的eMODIS NDVI卫星衍生数据与地球物理变量整合至回归树软件中生成。本数据集的地理覆盖范围包括大盆地、斯内克河平原、怀俄明州及其毗邻区域。我们针对海拔高于2250米的区域应用了掩膜处理，因一年生禾草难以在该海拔以上形成可观覆盖度；同时为聚焦潜在的灌丛草原生态系统，掩膜还排除了2011年全国土地覆盖数据集（National Land Cover Dataset, NLCD）中分类为灌丛或草原/草本以外的像素，且模型未在任何被掩膜的像素上进行训练。雀麦（Bromus tectorum）是研究区内最常见的一年生禾草，此外红雀麦（Bromus rubens）、美杜莎头草（Taeniatherum caput-medusae）与文塔纳草（Ventenata dubia）亦为入侵性有害物种。此类植物以种子萌发，通常于春季生长，快速成熟、结种并枯死；枯死的一年生禾草会形成细燃料，助力野火的引燃与蔓延，进而破坏灌丛草原生态系统。日益频繁的野火、土地管理措施与开发活动共同导致了曾广袤分布的灌丛草原生态系统出现碎片化，此类生态系统对于水质维持、降低野火风险以及依赖灌丛生存的野生动物存续均至关重要。