Coherency and Time Lags between NDVI/EVI and Climate in Forest of the European Temperate Zone

Identifying the climate-induced variability in the condition of vegetation is particularly important in the context of recent climate change and plants’ impact on the mitigation of climate change. Here we present the coherence and time lags in the spectral response of individual forest types in the European temperate zone to the influencing meteorological factors in the period 2002–2022. Vegetation condition in broadleaved and coniferous forest was measured with monthly anomalies of two spectral indices – normalised difference vegetation index (NDVI) and enhanced vegetation index (EVI). As meteorological elements we used monthly anomalies of temperature (T), precipitation (P), vapour pressure deficit (VPD), evapotranspiration (ETo), and the teleconnection indices North Atlantic Oscillation (NAO) and North Sea Caspian Pattern (NCP). Periodicity in the time series was assessed using the wavelet transform, but no significant intra- or interannual cycles were detected in both vegetation (NDVI/EVI) and meteorological variables. In turn, coherence between NDVI/EVI and meteorological elements was described using the methods of wavelet coherence and Pearson’s linear correlation with time lag. In the European temperate zone analysed in this study, NAO produces strong coherence in a circa 1-year band and a weaker coherence in a circa 3-year band. The strongest relationships occur between condition of the forest vegetation and T and ETo – there is a significant cohesion with the 8–16-month (ca. 1-year) and 20–32-month (ca. 2-year) bands. Aa the results obtained for NDVI and EVI are not entirely consistent, we additionally coupled NDVI and EVI with the data on the amount of dead trees removed within sanitation felling in the shorter period 2015–2022, in order to determine which satellite-borne index represents better the actual condition of vegetation in forests of the European temperate zone. NDVI is a good predictor of the forest vegetation, substantially better than EVI. Spatially, NDVI gives more pixels with negative slope of the trend in spectral index values, while EVI seems to overestimate the number of positive slopes. The bigger number of negative slopes in the trend in NDVI seems to be in agreement with increasing volume of dead trees in the analysed 2015–2022 period.