Trait space and compactness: A new perspective on explaining variations in primary productivity

The dataset include the data of trait space, compactness, productivity from different source (modis-based GPP,  GPP based on a vegetation photosynthesis model,  enhanced vegetation index,  sun-induced chlorophyll fluorescence), and productivity stability in  64 naturally assembled communities (including forests, grasslands, and deserts) in China. Specially, trait space was calculated with nine leaf traits, including leaf area (LA), leaf thickness (LT), specific leaf area (SLA), leaf nitrogen concentration (LN), leaf phosphorus concentration (LP), leaf water content (LWC), stomatal area (SA), stomatal density (SD), and maximum stomatal conductance (gmax).

本数据集包含来自多源的性状空间（trait space）、群落紧致性、生产力数据，以及中国境内64个自然组装群落（涵盖森林、草原与荒漠）的生产力稳定性数据。其数据来源包括基于MODIS的总初级生产力（Gross Primary Productivity, GPP）、基于植被光合模型的GPP、增强型植被指数（Enhanced Vegetation Index, EVI）以及日光诱导叶绿素荧光（Sun-Induced Chlorophyll Fluorescence, SIF）。特别地，本数据集的性状空间通过9种叶片性状计算得到，分别为叶面积（Leaf Area, LA）、叶厚度（Leaf Thickness, LT）、比叶面积（Specific Leaf Area, SLA）、叶氮浓度（Leaf Nitrogen Concentration, LN）、叶磷浓度（Leaf Phosphorus Concentration, LP）、叶片含水量（Leaf Water Content, LWC）、气孔面积（Stomatal Area, SA）、气孔密度（Stomatal Density, SD）以及最大气孔导度（Maximum Stomatal Conductance, gmax）。