To create a comprehensive view of ecosystem resource use, we integrated parallel resource use efficiency observations into a multiple-resource use efficiency (mRUE) framework using a dynamic factor analysis model. Results from 56 site-years of eddy covariance data and mRUE factors for a site in the US Midwest show temporal dynamics and coherence (using Pearson’s R) among resources are associated with interannual variation in precipitation. Loading factors are derived from mRUE observations and quantify how strongly data are connected to the underlying ecosystem state. Water and light resource use loading factors are coherent at annual timescales (Pearson’s R of 0.86), whereas declining patterns of carbon use efficiency loading factors highlight the ecosystem’s trade-off between carbon uptake and respiration during the growing season. At annual and monthly timescales, influence decreases from ~ 85 to ~ 65% for loading factors for carbon use, while influence of light use loading factors peaks to ~ 60% at growing season timescales. Quantifying variation in ecosystem function provides novel insights into the temporal dynamics of changing importance of multiple resources to ecosystem function.

为了创建生态系统资源利用的全面视图，我们使用动态因素分析模型将并行资源利用效率的观察结果集成到多资源利用效率（mRUE）框架中。来自美国中西部一个站点的56个站点年的涡度协方差数据和mRUE因子的结果表明，资源之间的时间动态和连贯性（使用Pearson's R）与降水的年际变化相关。加载因子来自mRUE观测值，并量化数据与基础生态系统状态的关联程度。水资源和轻水资源利用负荷因子在每年的时间尺度上是一致的（Pearson的R为0.86），而碳利用效率负荷因子的下降模式突显了生态系统在生长季节碳吸收与呼吸之间的权衡。在每年和每月的时间尺度上，碳使用负荷因子的影响从〜85降低至〜65％，而在生长季节时尺度，轻度使用负荷因子的影响则达到〜60％。量化生态系统功能的变化为改变多种资源对生态系统功能的重要性的时间动态提供了新颖的见解。