Intrinsic vegetation memory as a proxy of engineering resilience may be an oversimplification.


Vegetation memory describes the effect of antecedent environmental and ecosystem states on ecosystem state in the present and has been used as an important proxy for ecosystem recovery rates potentially a key component of vegetation resilience, at a global scale. We tested the components and drivers of vegetation memory in dryland regions using state-of-the-art climate reanalysis data and geo-statistical downscaling methods which have hitherto been used sparsely in ecology and certainly not at global scales. Furthermore, we refined statistical models and model selection to identify vegetation-memory characteristics across global dryland regions. We showed 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 novel, downscaled 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. Our findings demonstrate novel observations of vegetation memory patterns across dryland regions such as regional differences of processes forming vegetation memory capabilities. Consequently, this study provides a helpful stepping stone for refining and combining already existing methodology which could, in turn, generate important knowledge of ecosystem functioning and resilience particularly of interest for policy makers and land-use managers. Currently, we are working to establish the link between vegetation memory and plant function to bolster usability of this framework by non-biologists.

Jun 25, 2020 11:00 — 12:00
Online Conference
Erik Kusch
Erik Kusch
Senior Engineer & Statistical Consultant

In my research, I focus on statistical approaches to understanding complex processes and patterns in biology using a variety of data banks.