Several forest tree species (e.g. beech) have undergone clear browning during the peak heat and drought wave of the summer 2018, while other tree species (e.g. oak) have not. In addition, the browning effects have been more dramatic in specific regions of Switzerland or under specific topographic or ecological site conditions than under others. Here, we have started to analyze the degree of browning/greening using remote sensing time series, and we are analyzing the climatic, topographic and other drivers behind these effects, as it is not clearly understood, what factors led to browning or greening across larger spatial scales.
The first step consists of an RS-based analyses of spatial patterns, while the second step consists in analyzing the drivers that best explain these spatial patterns. The results are planned to be written up in an ISI paper, and will be prepared as digested input to a website on the summer 2018 drought at WSL.
1) RS-based analyses: We analyzed the spectral data and indices from Sentinel-2 and Landsat time series of past years (e.g. 2016/2017) during the summer season and compared the results with data from 2018. Different time windows and reference periods to 2018 will be tested (+/- already done). From indices (e.g. NDWI) anomalies from 2018 to reference periods are calculated in order to visualize browning and greening across Switzerland. The analysis is set up such that it can be computed for any region in Europe. In coordination with the statistical analyses, specific RS-based analyses are continued in order to optimally support the analyses of drivers and the spatial mapping of results.
2) Statistical analyses: We evaluate to what degree different drivers combine to explain the found patterns in the RS-based analyses. We analyze time series data on climate and soil moisture predictors, but also topographic (elevation, aspect, slope, topographic position), or stand structural (crown and tree size, forest structure, distance to forest edges, species composition) effects. Preliminary results indicate that a fair proportion of the spatial variation in the deviation in greenness from the long-term trend can be explained by an optimized combination of such predictors.
The results from these analyses are written up as an ISI publication, an SZF article is additionally envisioned. All results and dynamic animations are prepared for a WSL website on the summer drought 2018.