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

Abstract

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 distribution patterns of mangrove ecosystems GPP (e.g., the bimodal annual pattern, latitudinal gradients, etc.) demonstrated the regulatory influence of external environmental conditions on GPP estimates. The model ensemble attribution analysis indicated that the fraction of absorbed photosynthetically active radiation exerted the dominant control on GPP estimations, while temperature, salinity, and humidity acted as secondary constraints. The findings of this study provide valuable insights for monitoring, modeling, and managing mangrove ecosystems GPP; and underscore the critical role of mangroves in global carbon sequestration. By quantifying the influences of environmental factors, we enhance our understanding of mangrove carbon cycling estimates, thereby helping sustain of these disproportionately productive ecosystems.

Keywords: Attribution analysis; Environmental factors; Gaussian process regression; Gross primary production; Spatiotemporal variability.