School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing, China.
Qinghai Provincial Key Laboratory of Plateau Climate Change and Corresponding Ecological and Environmental Effects, Qinghai University of Science and Technology, Xining, China.
Glob Chang Biol. 2024 Aug;30(8):e17479. doi: 10.1111/gcb.17479.
Terrestrial gross primary productivity (GPP) is the largest carbon flux in the global carbon cycle and plays a crucial role in terrestrial carbon sequestration. However, historical and future global GPP estimates still vary markedly. In this study, we reduced uncertainties in global GPP estimates by employing an innovative emergent constraint method on remote sensing-based GPP datasets (RS-GPP), using ground-based estimates of GPP from flux towers as the observational constraint. Using this approach, the global GPP in 2001-2014 was estimated to be 126.8 ± 6.4 PgC year, compared to the original RS-GPP ensemble mean of 120.9 ± 10.6 PgC year, which reduced the uncertainty range by 39.6%. Independent space- and time-based (different latitudinal zones, different vegetation types, and individual year) constraints further confirmed the robustness of the global GPP estimate. Building on these insights, we extended our constraints to project global GPP estimates in 2081-2100 under various Shared Socioeconomic Pathway (SSP) scenarios: SSP126 (140.6 ± 9.3 PgC year), SSP245 (153.5 ± 13.4 PgC year), SSP370 (170.7 ± 16.9 PgC year), and SSP585 (194.1 ± 23.2 PgC year). These findings have important implications for understanding and projecting climate change, helping to develop more effective climate policies and carbon reduction strategies.
陆地总初级生产力 (GPP) 是全球碳循环中最大的碳通量，对陆地碳封存起着至关重要的作用。然而，历史和未来的全球 GPP 估计仍然存在显著差异。在这项研究中，我们通过将通量塔的 GPP 地面观测值作为观测约束，应用一种创新的遥感 GPP 数据集 (RS-GPP) 新兴约束方法，减少了全球 GPP 估计的不确定性。使用这种方法，我们估计 2001-2014 年全球 GPP 为 126.8 ± 6.4 PgC 年，而原始 RS-GPP 集合平均值为 120.9 ± 10.6 PgC 年，不确定性范围缩小了 39.6%。独立的空间和时间约束（不同的纬度带、不同的植被类型和个别年份）进一步证实了全球 GPP 估计的稳健性。在此基础上，我们将约束条件扩展到各种共享社会经济路径 (SSP) 情景下，以预测 2081-2100 年的全球 GPP 估计值：SSP126（140.6 ± 9.3 PgC 年）、SSP245（153.5 ± 13.4 PgC 年）、SSP370（170.7 ± 16.9 PgC 年）和 SSP585（194.1 ± 23.2 PgC 年）。这些发现对于理解和预测气候变化具有重要意义，有助于制定更有效的气候政策和碳减排战略。
