Leaf area index (LAI) is a critical biophysical indicator that describes foliage abundance in ecosystems. An accurate and continuous estimation of LAI is therefore desirable to quantify ecosystem status and function (e.g. carbon and water exchange between the land surface and the atmosphere). However, deriving accurate LAI measurements at regular temporal intervals remains challenging, requiring either destructive sampling or manual collection of canopy gap fraction measurements at discrete time intervals. In this study, we present four methods to obtain continuous LAI data, simply derived from above and below canopy measurements of photosynthetically active radiation (PAR) at the Borden Forest Research Station from 1999 to 2018. We compared LAI derived using the four PAR-based methods to independent measurements of LAI from optical methods and the MODIS satellite LAI product. LAI derived from all four PAR-based methods captured the seasonal changes in observed and remotely sensed LAI and showed a close linear correspondence with one another (R² of 0.55 to 0.76 compared to MODIS LAI, and R² of 0.78 to 0.84 compared to LAI-2000 measurements). A PAR-based method using Miller's Integral theorem showed the strongest linear relationship with LAI-2000 measurements (R²=0.84, p<0.001, SE=0.40). In many years MODIS LAI indicated an earlier start of season and earlier end of season than the daily PAR-based LAI datasets showing systematic biases in the MODIS assessment of growing season.

The four PAR-based LAI methods outlined in this study provide an LAI dataset of unprecedented temporal resolution. These methods will allow precise determination of phenological events, improve leaf to canopy scaling in process-based models, and provide valuable insight into dynamic vegetation responses to global climate change.

叶面积指数（LAI）是描述生态系统中叶片丰度的重要生物物理指标。因此，需要对LAI进行准确，连续的估算，以量化生态系统的状态和功能（例如，陆地表面与大气之间的碳和水交换）。然而，以规则的时间间隔得出准确的LAI测量值仍然具有挑战性，需要以不连续的时间间隔进行破坏性采样或手动收集冠层间隙分数测量值。在这项研究中，我们提出了四种获取连续LAI数据的方法，这些方法仅是根据1999年至2018年在博登森林研究站的光合有效辐射（PAR）的冠层的上下测量得出的。我们将使用四种基于PAR的方法得出的LAI与光学方法和MODIS卫星LAI产品的LAI进行了独立测量。从所有四种基于PAR的方法得出的LAI捕获了观测到的和遥感LAI的季节变化，并且彼此之间显示出紧密的线性对应关系（R与MODIS LAI相比，其²为0.55至0.76，而与LAI-2000测量相比，其R ²为0.78至0.84）。使用米勒积分定理的基于PAR的方法与LAI-2000测量显示出最强的线性关系（R ² = 0.84，p <0.001，SE = 0.40）。与基于PAR的日常LAI数据集相比，MODIS LAI在许多年中显示出更早的季节开始和更早的季节结束，这表明MODIS评估生长季节时存在系统性偏差。

本研究概述的四种基于PAR的LAI方法提供了前所未有的时间分辨率的LAI数据集。这些方法将可以精确确定物候事件，在基于过程的模型中改善叶片到树冠的比例，并提供对动态植被对全球气候变化的反应的宝贵见解。