Vegetation trends

These datasets were used in 1) Distribution, drivers and restoration priorities of plant invasions in India (Mungi, Qureshi, Jhala. 2023); 2) Role of species richness and human impacts in resisting invasive species in tropical forests (Mungi, Qureshi, Jhala. 2021); 3) Expansion of invasive plants with changing climate, land-use, and biodiversity (Mungi et al. in review). These studies modeled vegetation dynamics, trends in plants, their co-occurrence with fauna, and relationship with environmental variables at spatio-temporal scale. The dataset named "trend1" includes variables on vegetation changes from 2006 to 2022 and site characteristics at 25 km2 grid scale. There were in total five sampling cycles between this period that were used to assess all trends. All variables are provided as standardized values per grid cell. Intermediate steps during the vegetation community analysis are given as matrix in other datasets (mat1, mat2, mat3, mat4, rsq_int_sit). All preliminary names for plant species are provided in "species_pool". Details on the methodology, data source, and resolution are provided in the peer-reviewed study in review and https://doi.org/10.1111/1365-2745.13751 The dataset named "data1" includes vegetation variables and correlated variables on climate, fire, habitat characteristics, human-use, faunal occurrence, and occurrence of invasive plants. These variables were sampled during the year 2018 at 25 km2 grid scale, while environmental variables were obtained from remote sensing derivatives. All variables are provided as standardized values per grid cell. Details on the methodology, data source, and resolution can be found in the peer-reviewed study https://doi.org/10.1038/s41559-023-02181-y and https://doi.org/10.1111/1365-2664.14506本数据集系列应用于以下三项研究：1）《印度植物入侵的分布、驱动因子与修复优先级》（Mungi、Qureshi、Jhala，2023）；2）《物种丰富度与人类影响在热带森林抵御入侵物种中的作用》（Mungi、Qureshi、Jhala，2021）；3）《随气候、土地利用与生物多样性变化的入侵植物扩张》（Mungi等，待刊）。上述研究在时空尺度上对植被动态、植物种群趋势、其与动物类群的共现关系以及与环境变量的关联关系开展了建模分析。 名为trend1的数据集包含2006年至2022年的植被变化变量，以及25 km²网格尺度下的样地特征。该时段内共设置5个采样周期，用于评估所有趋势。所有变量均以标准化值形式按每个网格单元提供。植被群落分析过程中的中间步骤以矩阵形式存储于其他数据集（mat1、mat2、mat3、mat4、rsq_int_sit）中。植物物种的暂定名称均收录于species_pool数据集中。研究方法、数据来源与分辨率细节详见待刊同行评议论文及https://doi.org/10.1111/1365-2745.13751。 名为data1的数据集包含植被变量，以及与气候、火灾、生境特征、人类活动、动物出现情况和入侵植物出现情况相关的关联变量。这些变量于2018年以25 km²网格尺度进行采样，环境变量则源自遥感衍生数据。所有变量均以标准化值形式按每个网格单元提供。研究方法、数据来源与分辨率细节可参阅以下同行评议论文：https://doi.org/10.1038/s41559-023-02181-y 与 https://doi.org/10.1111/1365-2664.14506。