Circadian resonance, whereby a plant's endogenous rhythms are tuned to match environmental cues, has been repeatedly shown to be adaptive, although the underlying mechanisms remain elusive. Concomitantly, the adaptive value of nocturnal transpiration in C3 plants remains unknown because it occurs without carbon assimilation. These seemingly unrelated processes are interconnected because circadian regulation drives temporal patterns in nocturnal stomatal conductance, with maximum values occurring immediately before dawn for many species. We grew individuals of six Eucalyptus camaldulensis genotypes in naturally lit glasshouses and measured sunset, predawn and midday leaf gas exchange and whole-plant biomass production. We tested whether sunrise anticipation by the circadian clock and subsequent increases in genotype predawn stomatal conductance led to rapid stomatal opening upon illumination, ultimately affecting genotype differences in carbon assimilation and growth. We observed faster stomatal responses to light inputs at sunrise in genotypes with higher predawn stomatal conductance. Moreover, early morning and midday stomatal conductance and carbon assimilation, leaf area and total plant biomass were all positively correlated with predawn stomatal conductance across genotypes. Our results lead to the novel hypothesis that genotypic variation in the circadian-regulated capacity to anticipate sunrise could be an important factor underlying intraspecific variation in tree growth.

Climate change threatens the ability of agriculture and forestry to meet growing global demands for food, fibre and wood products. Information gathered from genotype-by-environment interactions (G × E), which demonstrate intraspecific variation in phenotypic plasticity (the ability of a genotype to alter its phenotype in response to environmental change), may prove important for bolstering agricultural and forest productivity under climate change. Nonetheless, very few studies have explicitly quantified genotype plasticity-productivity relationships in agriculture or forestry. Here, we conceptualize the importance of intraspecific variation in agricultural and forest species plasticity, and discuss the physiological and genetic factors contributing to intraspecific variation in phenotypic plasticity. Our discussion highlights the need for an integrated understanding of the mechanisms of G × E, more extensive assessments of genotypic responses to climate change under field conditions, and explicit testing of genotype plasticity-productivity relationships. Ultimately, further investigation of intraspecific variation in phenotypic plasticity in agriculture and forestry may prove important for identifying genotypes capable of increasing or sustaining productivity under more extreme climatic conditions.

The role of the circadian clock in controlling the metabolism of entire trees has seldom been considered. We tested whether the clock influences nocturnal whole-tree water use. Whole-tree chambers allowed the control of environmental variables (temperature, relative humidity). Night-time stomatal conductance (gs ) and sap flow (Q) were monitored in 6- to 8-m-tall Eucalyptus globulus trees during nights when environmental variables were kept constant, and also when conditions varied with time. Artificial neural networks were used to quantify the relative importance of circadian regulation of gs and Q. Under a constant environment, gs and Q declined from 0 to 6 h after dusk, but increased from 6 to 12 h after dusk. While the initial decline could be attributed to multiple processes, the subsequent increase is most consistent with circadian regulation of gs and Q. We conclude that endogenous regulation of gs is an important driver of night-time Q under natural environmental variability. The proportion of nocturnal Q variation associated with circadian regulation (23-56%) was comparable to that attributed to vapor pressure deficit variation (25-58%). This study contributes to our understanding of the linkages between molecular and cellular processes related to circadian regulation, and whole-tree processes related to ecosystem gas exchange in the field.

Globe-LFMC is an extensive global database of live fuel moisture content (LFMC) measured from 1,383 sampling sites in 11 countries: Argentina, Australia, China, France, Italy, Senegal, Spain, South Africa, Tunisia, United Kingdom and the United States of America. The database contains 161,717 individual records based on in situ destructive samples used to measure LFMC, representing the amount of water in plant leaves per unit of dry matter. The primary goal of the database is to calibrate and validate remote sensing algorithms used to predict LFMC. However, this database is also relevant for the calibration and validation of dynamic global vegetation models, eco-physiological models of plant water stress as well as understanding the physiological drivers of spatiotemporal variation in LFMC at local, regional and global scales. Globe-LFMC should be useful for studying LFMC trends in response to environmental change and LFMC influence on wildfire occurrence, wildfire behavior, and overall vegetation health.

Globe-LFMC 2.0, an updated version of Globe-LFMC, is a comprehensive dataset of over 280,000 Live Fuel Moisture Content (LFMC) measurements. These measurements were gathered through field campaigns conducted in 15 countries spanning 47 years. In contrast to its prior version, Globe-LFMC 2.0 incorporates over 120,000 additional data entries, introduces more than 800 new sampling sites, and comprises LFMC values obtained from samples collected until the calendar year 2023. Each entry within the dataset provides essential information, including date, geographical coordinates, plant species, functional type, and, where available, topographical details. Moreover, the dataset encompasses insights into the sampling and weighing procedures, as well as information about land cover type and meteorological conditions at the time and location of each sampling event. Globe-LFMC 2.0 can facilitate advanced LFMC research, supporting studies on wildfire behaviour, physiological traits, ecological dynamics, and land surface modelling, whether remote sensing-based or otherwise. This dataset represents a valuable resource for researchers exploring the diverse LFMC aspects, contributing to the broader field of environmental and ecological research.