Vegetation memory has been used as an important proxy for ecosystem recovery rates, potentially a key component of vegetation resilience. In particular, strong vegetation memory effects have been identified in dryland regions coinciding with decreased vegetation sensitivity towards climatological drivers. A recent approach by Ogle et al. distinguishes intrinsic and extrinsic vegetation memory components. Here, we aim to test the components and drivers of vegetation memory in dryland regions using state-of-the-art climate reanalysis data and refined approaches to identify vegetation memory characteristics. This has led to novel insights into spatial patterns of vegetation memory characteristics across four distinct predominantly dryland regions (Southwestern Europe, Contiguous United States, the Caatinga, and Australia).
We show that (1) dryland regions are characterised by strong vegetation memory (intrinsic and extrinsic), (2) it is possible to distinguish intrinsic and extrinsic vegetation memory to a hitherto unachieved degree using climate reanalysis data sets, (3) the link between intrinsic vegetation memory and resilience may be an oversimplification, and (4) dryland vegetation does not react to bioclimatic forcing in the same way across the Earth.
- Data Preparation
a) Rasterising and cropping GIMMs NDVI data (9x9km, 1982-2015, monthly)
b) Rasterising, cropping, and kriging Era5 data from 30x30km to 9x9km (1981-2015, monthly)
c) Rasterising plant functional trait (PFT) data from TRY and BIEN
d) Rasterising Life History Trait (LHT) data from COMPADRE - Analyses
a) Identifying vegetation memory effects using Principal Component Regression within each study region
b) Linking vegetation memory effects with PFT and LHT patterns within each study region
- Alistair Seddon (University of Bergen)
- Richard Davy (Nansen Environmental and Remote Sensing Center)
- Fast-Track Initiative (Bjerknes Center)