Fig. 4: Machine-learning prediction of global methane oxidation (MOx) rates. | Nature Communications

Fig. 4: Machine-learning prediction of global methane oxidation (MOx) rates.

From: Aerobic oxidation of methane significantly reduces global diffusive methane emissions from shallow marine waters

Fig. 4

a Global map of predicted MOx rates in surface water of near-shore (0–50 m) and outer shelf (50–200 m). The rates were generated by the random regression forest (RRF) method based on the published dataset containing methane, temperature, salinity, and depth (6633 datapoint) in diffusion-driven waters. b Probability distributions of predicted MOx rates in surface water and at depths in the near-shore (0–50 m) and outer shelf (50–200 m). MOx rates at depths were predicted using the depth profiles of methane and other variables from global database. Red dashed lines are the median values, and the green diamonds are the mean values. The lengths of the boxes represent the interquartile range, with whiskers spanning the maximum and minimum excluding outliers.

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