Lancaster Environment Centre, Lancaster, UK.
School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA.
Glob Chang Biol. 2017 Aug;23(8):3092-3106. doi: 10.1111/gcb.13602. Epub 2017 Mar 22.
Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO (eCO ) and warming requires accurate quantification of gross primary production (GPP), the largest flux of C in the global C cycle. We evaluated 6 years (2007-2012) of flux-derived GPP data from the Prairie Heating and CO Enrichment (PHACE) experiment, situated in a grassland in Wyoming, USA. The GPP data were used to calibrate a light response model whose basic formulation has been successfully used in a variety of ecosystems. The model was extended by modeling maximum photosynthetic rate (A ) and light-use efficiency (Q) as functions of soil water, air temperature, vapor pressure deficit, vegetation greenness, and nitrogen at current and antecedent (past) timescales. The model fits the observed GPP well (R = 0.79), which was confirmed by other model performance checks that compared different variants of the model (e.g. with and without antecedent effects). Stimulation of cumulative 6-year GPP by warming (29%, P = 0.02) and eCO (26%, P = 0.07) was primarily driven by enhanced C uptake during spring (129%, P = 0.001) and fall (124%, P = 0.001), respectively, which was consistent across years. Antecedent air temperature (Tair ) and vapor pressure deficit (VPD ) effects on A (over the past 3-4 days and 1-3 days, respectively) were the most significant predictors of temporal variability in GPP among most treatments. The importance of VPD suggests that atmospheric drought is important for predicting GPP under current and future climate; we highlight the need for experimental studies to identify the mechanisms underlying such antecedent effects. Finally, posterior estimates of cumulative GPP under control and eCO treatments were tested as a benchmark against 12 terrestrial biosphere models (TBMs). The narrow uncertainties of these data-driven GPP estimates suggest that they could be useful semi-independent data streams for validating TBMs.
确定未来 CO 升高和变暖气候下陆地生物圈是碳源还是碳汇，需要准确量化全球碳循环中最大的碳通量——总初级生产力（GPP）。我们评估了位于美国怀俄明州草原加热和 CO 富集（PHACE）实验的 6 年（2007-2012 年）通量衍生 GPP 数据。该 GPP 数据用于校准光响应模型，该模型的基本公式已成功应用于各种生态系统。通过将最大光合速率（A）和光利用效率（Q）建模为当前和前一时段（过去）土壤水、空气温度、蒸气压亏缺、植被绿色度和氮的函数，对模型进行了扩展。该模型很好地拟合了观测到的 GPP（R ² = 0.79），这通过比较模型的不同变体（例如，是否存在前效）等其他模型性能检查得到了验证。变暖（29%，P = 0.02）和 eCO（26%，P = 0.07）刺激 6 年累积 GPP 的增加主要是由于春季（129%，P = 0.001）和秋季（124%，P = 0.001）分别增强了碳吸收，这种情况在各年中是一致的。过去 3-4 天和 1-3 天内，空气温度（Tair）和蒸气压亏缺（VPD）对 A 的前效（分别）是大多数处理中 GPP 时间变化的最显著预测因子。VPD 的重要性表明，大气干旱对于预测当前和未来气候下的 GPP 很重要；我们强调需要进行实验研究以确定这种前效的机制。最后，根据 12 个陆地生物圈模型（TBM），对对照和 eCO 处理下的累积 GPP 的后验估计值进行了测试，作为基准。这些数据驱动的 GPP 估计值的狭窄不确定性表明，它们可能是验证 TBM 的有用半独立数据流。
