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The world's fifth largest producer of common wheat (Triticum aestivum L.), France, has been affected since the mid-1990s by climate change, which is disruptive to the cereal industry, with yields already stagnating, partly due to an increase in hot days and droughts. This article examines the evolution of the bioclimatic potential of this cereal in 2070 and 2100 for 7 sites representative of French cereal growing. The phenoclimatic approach used for this study consists of simulating the plant cycle and calculating the occurrence of climatic hazards on the sensitive phases of the cycle from data extracted from the regional climate model ALADIN-Climat of Météo-France. The results alleviate some of the expected concerns about the sustainability of soft wheat, but also highlight the appearance of new hazards, particularly due to a change in the length of the phenological periods. This research illustrates the need for prospective impact studies in climatology, using a systemic and multidisciplinary approach (geography, climatology, agronomy, pedology) to rationally consider the adaptation of agrosystems to climate change.

Low sandy coasts are small and constrained spaces very sensitive to coastal hazards. The settlement of human activities next to the coastline sets up at-risk territories. The identification of territories exposed to coastal erosion is one of the objectives of the French national strategy for integrated coastal management initiated by the French Ministry of Ecology. This national strategy relies on the network of regional coastal observatories. This paper proposes a common geomatics approach of two of these regional observatories aimed at spatializing a new coastal erosion risk indicator. The partnership between the "Réseau d’observation du littoral de Normandie et des Hauts-de-France" and the "Observatoire régional des risques côtiers en Pays de la Loire", aims at applying this indicator along the sandy coasts of western Manche and northern Vendée, France. The indicator is composed of the combination of 3 variables into spatial units (“boxes”): (i) the historical shoreline change, (ii) the distance between the shoreline and the buildings, roads and campsites located in the 100-m coastal strip and (iii) the presence/absence of coastal protections. The computation of the indicator for each stake, at the scale of the territories, allows the ranking of the erosion risk territories