Towards vulnerability minimization of grassland soil organic matter using metamodels

Vulnerability is the degree to which a human or environmental system is likely to experience harm due to a perturbation or a stress. This paper aims at proposing a generic quantitative method for climate change vulnerability assessment and to illustrate it on the particular case of the steady-state soil organic matter (SOM) of grassland thanks to PaSim, a mechanistic biochemical model. Based on literature review, we first present a model of concepts related to climate change vulnerability, and then we give our numerical method for vulnerability assessment. We documented all the different steps of our approach (from building of the initial design of experiments, to assessment of vulnerability with adaptation, through generating response surfaces and searching for vulnerability minima with different optimization methods). This study showed that steady-state SOM content will globally increase in future and that their vulnerability will decrease (due to higher increase of average values compared to the increased variability). Moreover, the analysis of the found vulnerability minima suggests both a reduction of vulnerability of SOM of adapted system and an increase of the gain by adaptation.