Lavergne Aliénor, Voelker Steve, Csank Adam, Graven Heather, de Boer Hugo J, Daux Valérie, Robertson Iain, Dorado-Liñán Isabel, Martínez-Sancho Elisabet, Battipaglia Giovanna, Bloomfield Keith J, Still Christopher J, Meinzer Frederick C, Dawson Todd E, Julio Camarero J, Clisby Rory, Fang Yunting, Menzel Annette, Keen Rachel M, Roden John S, Prentice I Colin
Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot, SL5 7PY, UK.
Department of Physics, Imperial College London, Exhibition Road, London, SW7 2AZ, UK.
New Phytol. 2020 Mar;225(6):2484-2497. doi: 10.1111/nph.16314. Epub 2019 Dec 10.
The ratio of leaf internal (c ) to ambient (c ) partial pressure of CO , defined here as χ, is an index of adjustments in both leaf stomatal conductance and photosynthetic rate to environmental conditions. Measurements and proxies of this ratio can be used to constrain vegetation model uncertainties for predicting terrestrial carbon uptake and water use. We test a theory based on the least-cost optimality hypothesis for modelling historical changes in χ over the 1951-2014 period, across different tree species and environmental conditions, as reconstructed from stable carbon isotopic measurements across a global network of 103 absolutely dated tree-ring chronologies. The theory predicts optimal χ as a function of air temperature, vapour pressure deficit, c and atmospheric pressure. The theoretical model predicts 39% of the variance in χ values across sites and years, but underestimates the intersite variability in the reconstructed χ trends, resulting in only 8% of the variance in χ trends across years explained by the model. Overall, our results support theoretical predictions that variations in χ are tightly regulated by the four environmental drivers. They also suggest that explicitly accounting for the effects of plant-available soil water and other site-specific characteristics might improve the predictions.
叶片内部二氧化碳分压(c)与环境二氧化碳分压(c)的比值,在此定义为χ,是叶片气孔导度和光合速率对环境条件调整的一个指标。该比值的测量值及替代指标可用于限制植被模型在预测陆地碳吸收和水分利用方面的不确定性。我们基于最低成本最优假设检验了一种理论,用于模拟1951 - 2014年期间不同树种和环境条件下χ的历史变化,这些变化是根据全球103个绝对定年的树轮年表网络的稳定碳同位素测量重建的。该理论将最优χ预测为气温、水汽压差、c和大气压力的函数。理论模型预测了不同地点和年份χ值方差的39%,但低估了重建χ趋势中的地点间变异性,导致模型仅解释了χ趋势逐年方差的8%。总体而言,我们的结果支持χ的变化受四个环境驱动因素严格调控的理论预测。它们还表明,明确考虑植物可利用土壤水分和其他特定地点特征的影响可能会改善预测。