Exploring the spatio-temporal patterns of global mangrove gross primary production and quantifying the factors affecting its estimation, 1996-2020

Mangrove ecosystems, as an important component of Blue Carbon, play a curial role on global carbon cycling; however, the lack of the global estimates of mangrove ecosystem gross primary production (GPP) and the underlying environmental controls on its estimation remain a gap in knowledge. In this study, we utilized global mangrove eddy covariance data and applied Gaussian Process Regression (GPR) to estimate GPP for global mangrove ecosystems, aiming to elucidate the factors influencing these estimates. The optimal GPR achieved favorable estimation performance through cross-validation (R2 = 0.90, RMSE = 0.92 gC/m2/day, WI = 0.86). Over the study period, the globally annual averaged GPP was 2054.53 +/- 38.51 gC/m2/yr (comparable to that of evergreen broadleaf forests and exceeds the GPP of most other plant function types), amounting to a total of 304.82 +/- 7.71TgC/yr, hotspots exceeding 3000 gC/m2/yr observed near the equator. The analysis revealed a decline in global mangrove GPP during 1996-2020 of -0.89 TgC/yr. Human activities (changes in mangrove cover area) played a relatively consistent role in contributing to this decrease. Conversely, variations in external environmental conditions showed distinct inter-annual differences in their impact. The spatio-temporal

Automated summary

This study estimated the gross primary production (GPP) of global mangrove ecosystems using global mangrove eddy covariance data and Gaussian Process Regression (GPR), and analyzed the factors influencing these estimates. Human activities and variations in external environmental conditions were found to play significant roles in the decline of global mangrove GPP.