Data from: Vegetation growth responses to climate change: A cross-scale analysis of biological memory and time-lags using tree ring and satellite data

Vegetation growth is affected by past growth rates and climate
variability. However, the impacts of vegetation growth carryover (VGC;
biotic) and lagged climatic effects (LCE; abiotic) on tree stem radial
growth may be decoupled from photosynthetic capacity, as higher
photosynthesis does not always translate into greater growth. To assess
the interaction of tree-species level VGC and LCE with ecosystem-scale
photosynthetic processes, we utilized tree-ring width (TRW) data for three
tree species: Castanopsis eyrei (CE), Castanea henryi (CH, Chinese
chinquapin), and Liquidambar formosana (LF, Chinese sweet gum), along with
satellite-based data on canopy greenness (EVI, enhanced vegetation index),
leaf area index (LAI), and gross primary productivity (GPP). We used
vector autoregressive models, impulse response functions, and forecast
error variance decomposition to analyze the duration, intensity, and
drivers of VGC and of LCE response to precipitation, temperature, and
sunshine duration. The results showed that at the tree-species level, VGC
in TRW was strongest in the first year, with an average 77% reduction in
response intensity by the fourth year. VGC and LCE exhibited
species-specific patterns; compared to CE and CH (diffuse-porous species),
LF (ring-porous species) exhibited stronger VGC but weaker LCE. For
photosynthetic capacity at the ecosystem scale (EVI, LAI, and GPP), VGC
and LCE occurred within 96 days. Our study demonstrates that VGC effects
play a dominant role in vegetation function and productivity, and that
vegetation responses to previous growth states are decoupled from climatic
variability. Additionally, we discovered the possibility for tree-ring
growth to be decoupled from canopy condition. Investigating VGC and LCE of
multiple indicators of vegetation growth at multiple scales has the
potential to improve the accuracy of terrestrial global change models.