I have been working virtually with the Tsinghua team (Han Wang, Huiying Xu, Shengchao Qiao, Yanghan Ren, Ziqi Zhu, and Colin Prentice) for the last 14 days. We focused particularly on the revision of two papers – Huiying’s paper on the coordination of photosynthetic and hydraulics traits based on the extensive data set we collected in the Gongga Mountains and Shengchao’s paper on the global version of the optimality-based wheat model.
We also made considerable progress on the analysis of the leaf morphological data that we’ve been collecting on our fieldtrips in China over the last 10 years. Leaf morphology is widely used as a way of identifying plant species in regional floras. Traits such as leaf size and the degree of dissection of the leaf margin have also been used as a way of reconstructing past climates, particularly deep-time climates where fossil pollen records are limited but leaf fossils are often preserved. These reconstructions were originally based on simple correlations, for example of temperature against degree of margin dissection. However, the discovery that this relationship varied between continents soon led to the realisation that multiple environmental factors might play a role in determining morphological traits. Our new analyses, based on the analysis of 22 leaf traits for 662 woody species from 92 sites cross China, show that there is a strong element of phylogenetic control of leaf morphological traits — as might be expected since they can be used for identification. Nevertheless, there are variations due to climate and more important variations due to the interaction of phylogeny and climate, indicating that there is some degree of plasticity in morphological traits but that a large part of the observed differences in the abundance of these traits comes from species replacements along environmental gradients. Our analyses suggest that temperature, moisture availability and precipitation seasonality are all important factors controlling the abundance of morphological traits. Moreover, we can demonstrate that although there are distinct syndromes of leaf response to environment in extremely dry or extremely wet condition, there are multiple strategies whereby plants are adapted to less extreme environmental conditions. We are planning to write this work up during my next virtual visit to Tsinghua in July — and then we will be able to see whether these insights into the control on leaf morphological traits can be translated into better predictions of past climates.
During the visit to Tsinghua, we also worked with Yanghan on the controls on leaf respiration, and the relative importance of night-time and daytime conditions on respiration. We are examining the consequences of four alternative optimality hypotheses about leaf respiration, specifically that it occurs at a fixed rate depending on night-time temperature, that it is tied to the maximum rate of Rubisco activity as determined by daytime temperature, that respiration at night is a fixed ratio of daytime photosynthesis, and that respiration at night occurs at a fixed rate relative to daytime assimilation. As with other aspects of the application of optimality theory to modelling plant behaviour, such as timescales of acclimation of photosynthetic parameters, data analysis will reveal which of these hypotheses provides the best description of leaf behaviour. But these analyses are a necessary step for Yanghan’s plans to incorporate optimality-based approaches to the photosynthesis and respiration within the Noah-MP land surface model.
Last but not least, we have been continuing to work with Ziqi on the analysis of changes in vegetation activity on the Tibetan Plateau during recent decades. This has been a great, if somewhat frustrating, lesson on the very large uncertainties in remote-sensing data sets over this region. However, by separating regions that have experienced greening from those that have experience browning, we have been able to show how the vegetation response has been influenced by changes in climate, radiation and hydrological stress over the past three decades. Furthermore, we can show how our “simple” optimality framework that acounts for both carbon and water limitation on plant growth reproduces the observed trends. More work to do here, of course, but then we do have another virtual Tsinghua visit to finalise this.
As ever, my thanks to Wang Han and the rest of the Tsinghua team for this enjoyable and productive visit. We’ll be back in July.
