Data from: Environmental controls on canopy foliar N distributions in a neotropical lowland forest

Distributions of foliar nutrients across forest canopies can give insight into their plant functional diversity and improve our understanding of biogeochemical cycling. We used airborne remote sensing and Partial Least Squares Regression (PLSR) to quantify canopy foliar nitrogen (N) across ~164 km2 of wet lowland tropical forest in the Osa Peninsula, Costa Rica. We determined the relative influence of climate and topography on the observed patterns of canopy foliar N using a gradient boosting model (GBM) technique. At a local scale, where climate and substrate where constant, we explored the influence of slope position on canopy N by quantifying canopy N on remnant terraces, their adjacent slopes and knife edged ridges. In addition, we climbed and sampled 540 trees and analyzed foliar N in order to quantify the role of species identity (phylogeny) and environmental factors in predicting canopy N. Observed canopy N heterogeneity reflected environmental factors working at multiple spatial scales. Across the larger landscape, elevation and precipitation had the highest relative influence on predicting canopy foliar N (30 and 24%), followed by soils (15%), site exposure (9%), compound topographic index (8%), substrate (6%), and landscape dissection (6%). Phylogeny explained ~75% of the variation in the filed collected foliar N data, suggesting that phylogeny largely underpins the response to the environmental factors. Taken together, these data suggest that a large fraction of the variance in canopy N across the landscape is proximately driven by species composition, though ultimately this is likely a response to abiotic factors such as climate and topography. Future work should focus on the mechanisms and feedbacks involved, and how shifts in climate may translate to changes in forest function.森林冠层叶片营养元素的分布特征，可为揭示植物功能多样性提供重要视角，并助力我们深化对生物地球化学循环的认知。本研究借助航空遥感技术与偏最小二乘回归（Partial Least Squares Regression, PLSR）模型，对哥斯达黎加奥萨半岛约164平方千米的低地湿润热带森林的冠层叶片氮（N）含量进行了定量测算。本研究采用梯度提升模型（gradient boosting model, GBM）技术，解析了气候与地形因子对冠层叶片氮分布格局的相对影响强度。在气候与基质条件均一的局地尺度上，本研究通过对残余阶地、邻近坡地以及刀刃状山脊的冠层氮含量进行定量分析，探究了坡位对冠层氮含量的影响。此外，本研究还攀爬采集了540株树木的样本，并对其叶片氮含量进行实验室分析，以量化物种属性（系统发育）与环境因子在预测冠层氮含量中的作用。观测到的冠层氮异质性，反映了多空间尺度下环境因子的调控作用。在更大的景观尺度上，海拔与降水对冠层叶片氮含量预测的相对影响占比最高，分别为30%与24%；其次为土壤因子（15%）、立地暴露度（9%）、复合地形指数（8%）、基质类型（6%）与景观切割度（6%）。系统发育解释了野外采集的叶片氮数据中约75%的变异，表明系统发育在很大程度上支撑了植物对环境因子的响应模式。综合来看，本研究数据表明，景观尺度下冠层氮含量的大部分变异直接由物种组成驱动，但从根本上来说，这一过程大概率是对气候、地形等非生物因子的响应。未来的研究应聚焦于其中涉及的作用机制与反馈过程，以及气候变化如何转化为森林功能的改变。