Continuous Parameterization of Leaf Area Index and Phenological Phases Within Deciduous Forests Based on Temperature Measurements

Abstract

The Leaf-Area-Index (LAI) is commonly used to characterize the plant canopy and is a fundamental indication of plant vitality and photosynthetic activity. The forest health status is not only vital for economical reasons, but also has a significant impact on global carbon sequestration. The LAI has a highly dynamic character among deciduous forests and is prone to significant seasonal fluctuations. Accurate continuous LAI measurements do provide valuable information on growth characteristics, but they require considerable measurement effort. In this study, we tested a novel method that would allow for continuous low-effort LAI parameterizations. For our study we used temperature measurements from 2011 to 2019 obtained at two meteorological stations: Station one is an open land station, station two is located inside a forest stand characterized by European beech (measurements were undertaken as part of the ICP Forests program), both are located in Klausen Leopoldsdorf (Austria). We chose the difference in daily maximum temperature between the two sites for our LAI parametrization (LAIpar) since the forest canopy has a significant impact on local radiation conditions. We were able to identify phenological events such as leaf unfolding, the end of leaf growth, and the beginning and end of defoliation by examining at the average course of the year for LAIpar. The resultant LAIpar values were compared to annual values derived from hemispheric photographs taken near the stand temperature sensor. For the years 2011–2017, we found a strong correlation of 0.93 between LAI measures and LAIpar, which dropped to 0.69 after adding the year 2018 and 0.32 after adding 2019. We further compared the phenological events obtained from LAIpar to phenological observations. The impact of forests on their site climate, according to our findings, can be utilized to identify phenological and growth characteristics. The proposed method, however, is not a replacement for conventional LAI measurements.

Assessment of spongy moth infestation impacts on forest productivity and carbon loss using the Sentinel-2 satellite remote sensing and eddy covariance flux data

“…Remotely sensed LAI measurements have been widely used to observe the intensity and extent of defoliation in deciduous and mixed forests (De Beurs and Townsend 2008 ). LAI measurements also provide direct quantification of leaf properties, photosynthetic activity, C uptake (Jarlan et al 2008 ; Boussetta et al 2013 ; Alton 2016 ; Brown et al 2020 ) and often used to estimate vegetation biomass utilizing remote sensing-based models (Zolles et al 2021 ). Our study results showed that the mean LAI values for deciduous forests decreased by about 25% in 2021 as compared to the pre-infestation LAI values in 2020, and by about 22% as compared to the post-infestation LAI values in 2022.…”