Data from Beyond MAP: A guide to dimensions of rainfall variability for tropical ecology

<b>Abstract</b><br/><p>Tropical ecologists have long recognized rainfall as the key climate filter shaping tropical ecosystem structure and function across space and time. Still, tropical ecologists have historically had a limited toolkit for characterizing rainfall, largely relying on simple metrics like mean annual precipitation (MAP) and dry season length to characterize rainfall regimes that vary along many more dimensions. Here, we review methods for quantifying dimensions of rainfall variability on multiple time scales, with a focus on ecological applications of these methods. We also discuss key considerations for tropical ecologists looking to use rainfall metrics that better align with hypothesized biological or ecological mechanisms or that more effectively describe rainfall variability in the systems we study, and provide a toolkit (R scripts and gridded datasets) to do so. We argue that incorporating more sophisticated approaches to quantify rainfall variability into study design and statistical analyses will enhance our understanding of past, ongoing, and future changes in tropical ecosystems.  </p>

摘要<br/><p>热带生态学家长期以来一直将降雨视为塑造热带生态系统时空结构与功能的关键气候过滤因子。尽管学界早已认可这一观点，但长期以来热带生态学家用于表征降雨的工具库十分有限，大多仅依赖年平均降水量（mean annual precipitation, MAP）、旱季时长这类简单指标，来描述本可从多维度变化的降雨格局。本文综述了多时间尺度下降雨变异性维度的量化方法，重点聚焦这些方法在生态学研究中的应用。同时，本文还针对热带生态学家的实际需求展开讨论：他们希望选用更贴合假说中生物学或生态学机制的降雨指标，或是能更精准刻画所研究系统降雨变异性的指标，并提供了配套工具包（R脚本与网格化数据集）以供使用。本文主张，在研究设计与统计分析中引入更精细化的降雨变异性量化方法，将有助于深化我们对热带生态系统过去、当前及未来变化的认知。</p>