Stem-mapped forest stands offer important opportunities for investigating the fine-scale spatial processes occurring in forest ecosystems. These stands are areas of the forest where the precise locations and repeated size measurements of each tree are recorded, thereby enabling the calculation of spatially-explicit metrics of individual growth rates and of the entire tree community. The most common use of these datasets is to investigate the drivers of variation in forest processes by modeling tree growth rate or mortality as a function of these neighborhood metrics. However, neighborhood metrics could also serve as important covariates of many other spatially variable forest processes, including seedling recruitment, herbivory and soil microbial community composition. Widespread use of stem-mapped forest stand datasets is currently hampered by the lack of standardized, efficient and easy-to-use tools to calculate tree dynamics (e.g. growth, mortality) and the neighborhood metrics that impact them. We present the forestexplorR package that facilitates the munging, exploration, visualization and analysis of stem-mapped forest stands. By providing flexible, user-friendly functions that calculate neighborhood metrics and implement a recently-developed rapid-fitting tree growth and mortality model, forestexplorR broadens the accessibility of stem-mapped forest stand data. We demonstrate the functionality of forestexplorR by using it to investigate how the species identity of neighboring trees influences the growth rates of three common tree species in Mt Rainier National Park, WA, USA. forestexplorR is designed to facilitate researchers to incorporate spatially-explicit descriptions of tree communities in their studies and we expect this increased diversity of contributors to develop exciting new ways of using stem-mapped forest stand data.

中文翻译：

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ForestexplorR：一个用于探索和分析茎映射林分数据的 R 包

干制森林林分为研究森林生态系统中发生的精细空间过程提供了重要机会。这些林分是记录每棵树的精确位置和重复大小测量的森林区域，从而能够计算单个生长率和整个树木群落的空间明确指标。这些数据集最常见的用途是通过将树木生长率或死亡率建模为这些邻域指标的函数来研究森林过程变化的驱动因素。然而，邻域指标也可以作为许多其他空间可变森林过程的重要协变量，包括幼苗补充、食草和土壤微生物群落组成。目前，由于缺乏标准化、高效且易于使用的工具来计算树木动态（例如生长、死亡率）和影响它们的邻域指标，因此阻碍了广泛使用树干测绘的林分数据集。我们展示了 ForestexplorR 软件包，该软件包有助于对茎映射的林分进行整理、探索、可视化和分析。通过提供灵活、用户友好的功能来计算邻域指标并实施最近开发的快速拟合树木生长和死亡率模型，forestexplorR 拓宽了茎映射林分数据的可访问性。我们通过使用它来研究邻近树木的物种特性如何影响美国华盛顿州雷尼尔山国家公园的三种常见树种的生长速率来展示 ForestexplorR 的功能。