Emulation of wildland fire spread simulation using deep learning.

Numerical simulation of wildland fire spread is useful to predict the locations that are likely to burn and to support decision in an operational context, notably for crisis situations and long-term planning. For short-term, the computational time of traditional simulators is too high to be tractable over large zones like a country or part of a country, especially for fire danger mapping. This issue is tackled by emulating the area of the burned surface returned after simulation of a fire igniting anywhere in Corsica island and spreading freely during one hour, with a wide range of possible environmental input conditions. A deep neural network with a hybrid architecture is used to account for two types of inputs: the spatial fields describing the surrounding landscape and the remaining scalar inputs. After training on a large simulation dataset, the network shows a satisfactory approximation error on a complementary test dataset with a MAPE of 32.8%. The convolutional part is pre-computed and the emulator is defined as the remaining part of the network, saving significant computational time. On a 32-core machine, the emulator has a speed-up factor of several thousands compared to the simulator and the overall relationship between its inputs and output is consistent with the expected physical behavior of fire spread. This reduction in computational time allows the computation of one-hour burned area map for the whole island of Corsica in less than a minute, opening new application in short-term fire danger mapping.

Revealing the deposition of macrophytes transported offshore: Evidence of their long-distance dispersal and seasonal aggregation to the deep sea.

The role of coastal macrophyte beds as a carbon sink is under debate. Various studies have provided global estimates of the carbon sequestration and stocks of macrophyte beds; however, the final fate of macrophyte debris exported from coastal beds remains uncertain, and must be determined in order to fully clarify the role of coastal vegetation as a carbon sink. Here we conducted bottom-trawl surveys to investigate the extensive and seasonal aggregation of exported macrophytes on the continental shelf and slope seafloor (40-1,800 m). Sunken macrophytes showed a clear seasonal trend with highest biomasses in summer. This was mainly caused by the most collected macrophyte species Sargassum horneri. Furthermore, we used numerical simulations to verify the link between sea-surface hydrographic condition and seafloor distribution of sunken macrophytes. Our results showed that S. horneri accumulated beneath the Kuroshio Extension current, which is the western boundary current of the North Pacific subtropical gyre. Overall, floating macrophytes that became transported offshore by a stable sea-surface current, such as the western boundary current, constitute an organic carbon pathway from coastal waters to the deep sea. Our findings suggest that these buoyant macrophytes can act as a biological pump to enhance oceanic carbon sequestration.