The implementation of adaptation strategies of agriculture and forestry to climate change is conditioned by the knowledge of the impacts of climate change on the vegetation cycle and of the associated uncertainties. Using the same generic Land Surface Model (LSM) to simulate the response of various vegetation types is more straightforward than using several specialized crop and forestry models, as model implementation differences are difficult to assess. The objective of this study is to investigate the potential of a LSM to address this issue. Using the SURFEX (“Surface Externalisée”) modeling platform, we produced and analyzed 150-yr (1950–2100) simulations of the biomass of four vegetation types (rainfed straw cereals, rainfed grasslands, broadleaf and needleleaf forests) and of the soil water content associated to each of these vegetation types over France. Statistical methods were used to quantify the impact of climate change on simulated phenological dates. The duration of soil moisture stress periods increases everywhere in France, especially for grasslands with, on average, an increase of 9 days per year in near-future (NF) conditions and 36 days per year in distant-future (DF) conditions. For all the vegetation types, leaf onset and the annual maximum LAI occur earlier. For straw cereals in the Languedoc-Provence-Corsica area, NF leaf onset occurs 18 days earlier and 37 days earlier in DF conditions, on average. On the other hand, local discrepancies are simulated for the senescence period (e.g. earlier in western and southern France for broadleaf forests, slightly later in mountainous areas of eastern France) for both NF and DF. Changes in phenological dates are more uncertain in DF than in NF conditions in relation to differences in climate models, especially for forests. Finally, it is shown that while changes in leaf onset are mainly driven by air temperature, longer soil moisture stress periods trigger earlier leaf senescence over most of France. This shows that developing in situ soil moisture networks could help monitoring the long-term impacts of climate change.
Laanaia, N., Carrer, D., Calvet, J. C., & Pagé, C. (2016). How will climate change affect the vegetation cycle over France? A generic modeling approach. Climate Risk Management, 13, 31–42. https://doi.org/10.1016/j.crm.2016.06.001