Modelling mature temperate forest responses to elevated CO2 and changing climatic conditions: insights from the BIFoR FACE experiment

Climate models predict a rise in CO2 levels from around 400 ppm now to 400–1000 ppm by 2100, correlated with more extreme weather events such as droughts, storms and flooding (Intergovernmental Panel on Climate Change, 2021). Although increased CO2 levels have negative effects on ambient temperature, they have a positive impact on plant growth by increasing the photosynthesis rate, known as the CO2 fertilization effect (Chen et al., 2022). However, the potential of adapting crop plants to higher CO2 levels and thereby increase their production has not yet been fully exploited by breeding programs. Toshiyuki Takai and Yusaku Uga, authors of the highlighted publication, met at the International Rice Research Institute (IRRI) during their PhD studies, where they started to discuss the future of rice (Oryza sativa) breeding. Already back then, Takai suggested that breeders could combine larger panicles with more tillers as a next ideotype to increase the rice yield potential. Increasing the sink capacity, which is a product of both spikelet number and seed size, could be a key factor to enhance yield under elevated atmospheric CO2 levels (Ainsworth & Long, 2021). However, high-yielding rice varieties already produce large panicles, so further increases in panicle size are not considered feasible. Instead, Takai et al. addressed panicle number in an attempt to increase sink capacity (Takai et al., 2023). They focused on the quantitative trait locus (QTL) MORE PANICLES 3 (MP3). The Koshihikari allele of MP3 in a near-isogenic line (NIL) in the Takanari genetic background produced 19% more panicles and 12–20% more spikelets (Takai et al., 2014). In the highlighted study, the authors showed that NIL-MP3 produced more tillers than the parental cultivars until the heading stage and had more elongated axillary buds at the axil of the second leaf, suggesting that the increased tiller number was caused by a different elongation rate of axillary buds (Figure 1a). MP3 affects tillering in rice and grain yield under elevated CO2 conditions. (a) Takanari, NIL-MP3 and NIL-fc1 plants grown in pots. (b) Takanari, NIL-MP3 and NIL-fc1 plants grown in a paddy field in the late grain-filling stage. (c) FACE plot with the CO2 emission tubes in an octagonal arrangement. (d) Grain yield of Takanari and NIL-MP3 under ambient and elevated CO2 (FACE) conditions; figure modified from Takai et al. (2023). To clone the causal gene underlying the QTL, the authors used high-resolution mapping on segregating F2 plants and subsequent recombinant F3,4 lines. They found only one predicted open reading frame in the candidate region, TEOSINTE BRANCHED1/FINE CULM 1 (OsTB1/FC1). OsTB1/FC1 is a TCP transcription factor that is a negative regulator of tiller bud outgrowth (Takeda et al., 2003). The authors analyzed the expression pattern of OsTB1/FC1 and detected expression in the axillary buds, but saw no difference in expression level between Takanari and NIL-MP3. However, by collecting transcriptome data of the shoot apical meristem and axillary meristem at various time points and analyzing the expression trajectories, they found that NIL-MP3 reached a more advanced growth stage on the trajectory than Takanari, suggesting that MP3 exerts positive effects on axillary bud growth. MP3 had three polymorphisms in the 5′ UTR, coding sequence (CDS), and 3′ UTR, so the authors tested their importance by identifying different combinations in chromosome segment substitution lines with the Koshihikari background. They found that all three polymorphisms were necessary for the difference in panicle number. Perhaps these polymorphisms lead to an alteration in translational efficiency and protein structure, and thereby cause a moderate increase in panicle number without decreasing the number of spikelets per panicle. Analysis of haplotypes in a rice single-nucleotide polymorphism database showed that the Koshihikari allele accounted for 74% of accessions in temperate japonica subgroups, while the Takanari allele accounted for 50–59% of accessions in indica subgroups. This prompted the authors to introduce the Koshihikari MP3 allele as NILs into two high-yielding indica cultivars, Hokuriku 193 and IR64, which are categorized as Takanari MP3 haplotypes. Phenotyping under field conditions confirmed that the NILs developed a greater number of tillers and a similar number of spikelets per panicle as the parental cultivars. They previously found that the OsTB1/FC1 allele was derived from a loss-of-function allele in the fc1 mutant, which had a 1-bp deletion in the CDS, resulting in a premature stop codon. When the authors compared a NIL with this allele in the Takanari background with the Takanari wild type and the mild NIL-MP3 allele, they found that NIL-fc1 produced more panicles, and overall more spikelets per m2 than Takanari. Nevertheless, the grain yield in Takanari-fc1 was much lower than that in the Takanari wild type because the plants lodged during the grain-filling period, i.e., the stems bent near the ground level, because they were thinner and lighter than wild-type stems (Figure 1a,b). Even though the number of panicles and the number of spikelets per m2 were increased in NIL-MP3, the overall yield was not. The authors hypothesized that this was caused by limited photosynthetic capacity that was not sufficient to fill the spikelets. Therefore, they compared the yield under normal air and free-air CO2 enrichment (FACE) treatments in open paddy fields, in which CO2 is supplied from tubes installed around the experimental plots above the rice canopy (Figure 1c). NIL-MP3 had a higher sink capacity than Takanari in both CO2 conditions, and under higher CO2 conditions, the yield of NIL-MP3 was significantly higher than the yield of Takanari (Figure 1d). In conclusion, the authors propose that mild alleles such as MP3, which moderately increase panicle number, combined with large-sized panicle varieties can be used to create high-yielding varieties adapted to rising CO2 levels. At the National Agriculture and Food Research Organization in Tsukuba, Japan, Uga focuses additionally on the genetic improvement of the root system. His group is studying the effects of pyramiding some QTLs for root traits such as root length, volume, and thickness, and in the future he will analyze the potential of pyramiding above- and belowground QTLs affecting yield and drought resistance.

Rising CO₂– future ecosystems

Abstract. Predicting the responses of terrestrial ecosystem carbon to future global change strongly relies on our ability to model accurately the underlying processes at a global scale. However, terrestrial biosphere models representing the carbon and nitrogen cycles and their interactions remain subject to large uncertainties, partly because of unknown or poorly constrained parameters. Parameter estimation is a powerful tool that can be used to optimise these parameters by confronting the model with observations. In this paper, we identify sensitive model parameters from a recent version of the ORgainzing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) land surface model that includes the nitrogen cycle. These sensitive parameters include ones involved in parameterisations controlling the impact of the nitrogen cycle on the carbon cycle and, in particular, the limitation of photosynthesis due to leaf nitrogen availability. We optimise these ORCHIDEE parameters against carbon flux data collected on sites from the FLUXNET network. However, optimising against present-day observations does not automatically give us confidence in future projections of the model, given that environmental conditions are likely to shift compared to the present day. Manipulation experiments give us a unique look into how the ecosystem may respond to future environmental changes. One such type of manipulation experiment, the Free Air CO2 Enrichment (FACE) experiment, provides a unique opportunity to assess vegetation response to increasing CO2 by providing data under ambient and elevated CO2 conditions. Therefore, to better capture the ecosystem response to increased CO2, we add the data from two FACE sites to our optimisations, in addition to the FLUXNET data. We use data from both CO2 conditions of FACE, which allows us to gain extra confidence in the model simulations using this set of parameters. We find that we are able to improve the magnitude of modelled productivity. Although we are unable to correct the interannual variability fully, we start to simulate possible progressive nitrogen limitation at one of the sites. Using an idealised simulation experiment based on increasing atmospheric CO2 by 1 % yr−1 over 100 years, we find that optimising against only FLUXNET data tends to imply a large fertilisation effect, whereas optimising against FLUXNET and FACE data (with information about nutrient limitation and acclimation of plants) decreases it significantly.

Triose phosphates are the principal product of photosynthesis. They are used within the chloroplast for starch synthesis, or translocated to the cytosol where they are used to fuel sucrose synthesis. Use of triose phosphate releases inorganic phosphate, and is under strict metabolic control that matches the supply of triose phosphate from the Calvin-Benson cycle to the demand for carbon by sinks (Heldt & Heldt, 2011; McClain & Sharkey, 2019). However, a low rate of triose phosphate utilization (TPU) can deplete the phosphate pool, restrict ATP synthesis and reduce the availability of ATP to power the Calvin-Benson cycle, thereby limiting photosynthesis (Sharkey, 1985).

Understanding the interactions between atmosphere and vegetation in changing climatic conditions is important so that we can predict the carbon sequestration potential of ecosystems. Helpful tools here are the terrestrial biosphere models (TBMs), since they include detailed ecophysiological process descriptions, e.g. the manifold interactions between the carbon and nitrogen cycles. However, the modelling of the nitrogen cycle poses challenges and having observational constraints on nitrogen cycle is crucial. Current remote sensing products offer estimates of leaf chlorophyll (Cab), that is related to the nitrogen cycle. In this study we want to assess how useful Cab observations are at site scale to constrain a TBM.   In this work we are studying a temperate mixed forest, Borden, located in Canada. We use a TBM QUantifying Interactions between terrestrial Nutrient Cycles, QUINCY, to model this site. From the site we have long-term (20 years) flux tower and LAI (from PAR measurements) observations together with leaf level observations of leaf chlorophyll (Cab), leaf nitrogen, and photochemical parameters of maximum carboxylation rate (Vcmax) and maximum potential electron transport rate (Jmax).    The QUINCY model was predicting too late leaf senescence, which we tuned using the site level data. The amount of leaf nitrogen was originally quite successfully simulated by QUINCY, but the amount of simulated Cab was too low. Matching the simulated Cab values with the observations did not have a pronounced effect on the GPP. Additionally, the development of LAI and Cab were originally fully coupled in QUINCY, whereas the observations showed a delayed development of Cab compared to LAI. When we implemented this decoupling between LAI and Cab, an improvement of simulated GPP compared to the observations was found. Also then the simulated Vcmax and Jmax showed better correspondence to the observations.    Assessment of the long-term behaviour of the model at the site showed that the model was able to capture the drought-induced drawdown of carbon fluxes taking place in 2007. The observations showed an increase in the component fluxes of carbon during the time period, but this was not replicated by the model. The start of season (SOS) and end of season (EOS) were estimated from both the simulated and observed GPP and LAI using a simple threshold method. The model was more successful in capturing the changes in the growing season metrics estimated by LAI than by GPP. The model was predicting too late onset of GPP in many years, but captured largely the interannual variation of SOS in observed GPP.    This study paves the way for work using remotely sensed leaf chlorophyll in evaluation and improvement of the QUINCY model.

Terrestrial biosphere models (TBMs) include the representation of vertical gradients in leaf traits associated with modeling photosynthesis, respiration, and stomatal conductance. However, model assumptions associated with these gradients have not been tested in complex tropical forest canopies. We compared TBM representation of the vertical gradients of key leaf traits with measurements made in a tropical forest in Panama and then quantified the impact of the observed gradients on simulated canopy-scale CO2 and water fluxes. Comparison between observed and TBM trait gradients showed divergence that impacted canopy-scale simulations of water vapor and CO2 exchange. Notably, the ratio between the dark respiration rate and the maximum carboxylation rate was lower near the ground than at the top-of-canopy, leaf-level water-use efficiency was markedly higher at the top-of-canopy, and the decrease in maximum carboxylation rate from the top-of-canopy to the ground was less than TBM assumptions. The representation of the gradients of leaf traits in TBMs is typically derived from measurements made within-individual plants, or, for some traits, assumed constant due to a lack of experimental data. Our work shows that these assumptions are not representative of the trait gradients observed in species-rich, complex tropical forests.

The terrestrial biosphere plays a critical role in mitigating climate change by absorbing anthropogenic CO2 emissions through photosynthesis. The rate of photosynthesis is determined jointly by environmental variables and the intrinsic photosynthetic capacity of plants (i.e. maximum carboxylation rate; ). A lack of an effective means to derive spatially and temporally explicit has long hampered efforts towards estimating global photosynthesis accurately. Recent work suggests that leaf chlorophyll content (Chlleaf ) is strongly related to , since Chlleaf and are both correlated with photosynthetic nitrogen content. We used medium resolution satellite images to derive spatially and temporally explicit Chlleaf , which we then used to parameterize within a terrestrial biosphere model. Modelled photosynthesis estimates were evaluated against measured photosynthesis at 124 eddy covariance sites. The inclusion of Chlleaf in a terrestrial biosphere model improved the spatial and temporal variability of photosynthesis estimates, reducing biases at eddy covariance sites by 8% on average, with the largest improvements occurring for croplands (21% bias reduction) and deciduous forests (15% bias reduction). At the global scale, the inclusion of Chlleaf reduced terrestrial photosynthesis estimates by 9 PgC/year and improved the correlations with a reconstructed solar-induced fluorescence product and a gridded photosynthesis product upscaled from tower measurements. We found positive impacts of Chlleaf on modelled photosynthesis for deciduous forests, croplands, grasslands, savannas and wetlands, but mixed impacts for shrublands and evergreen broadleaf forests and negative impacts for evergreen needleleaf forests and mixed forests. Our results highlight the potential of Chlleaf to reduce the uncertainty of global photosynthesis but identify challenges for incorporating Chlleaf in future terrestrial biosphere models.

Abstract. Terrestrial biosphere models (TBMs) are invaluable tools for studying plant–atmosphere interactions at multiple spatial and temporal scales, as well as how global change impacts ecosystems. Yet, TBM projections suffer from large uncertainties that limit their usefulness. Forest structure drives a significant part of TBM uncertainty as it regulates key processes such as the transfer of carbon, energy, and water between the land and the atmosphere, but it remains challenging to observe and reliably represent. The poor representation of forest structure in TBMs might actually result in simulations that reproduce observed land fluxes but fail to capture carbon pools, forest composition, and demography. Recent advances in terrestrial laser scanning (TLS) offer new opportunities to capture the three-dimensional structure of the ecosystem and to transfer this information to TBMs in order to increase their accuracy. In this study, we quantified the impacts of prescribing initial conditions (tree size distribution), constraining key model parameters with observations, as well as imposing structural observations of individual trees (namely tree height, leaf area, woody biomass, and crown area) derived from TLS on the state-of-the-art Ecosystem Demography model (ED2.2) of a temperate forest site (Wytham Woods, UK). We assessed the relative contributions of initial conditions, model structure, and parameters to the overall output uncertainty by running ensemble simulations with multiple model configurations. We show that forest demography and ecosystem functions as modelled by ED2.2 are sensitive to the imposed initial state, the model parameters, and the choice of key model processes. In particular, we show that: Parameter uncertainty drove the overall model uncertainty, with a mean contribution of 63 % to the overall variance of simulated gross primary production. Model uncertainty in the gross primary production was reduced fourfold when both TLS and trait data were integrated into the model configuration. Land fluxes and ecosystem composition could be simultaneously and accurately simulated with physically realistic parameters when appropriate constraints were applied to critical parameters and processes. We conclude that integrating TLS data can inform TBMs of the most adequate model structure, constrain critical parameters, and prescribe representative initial conditions. Our study also confirms the need for simultaneous observations of plant traits, structure, and state variables if we seek to improve the robustness of TBMs and reduce their overall uncertainties.

Abstract. Land surface models are excellent tools for studying how climate change and land use affect surface hydrology. However, in order to assess the impacts of Earth processes on river flows, simulated changes in runoff need to be routed through the landscape. In this technical note, we describe the integration of the Ecosystem Demography (ED2) model with a hydrological routing scheme. The purpose of the study was to create a tool capable of incorporating to hydrological predictions the terrestrial ecosystem responses to climate, carbon dioxide, and land-use change, as simulated with terrestrial biosphere models. The resulting ED2+R model calculates the lateral routing of surface and subsurface runoff resulting from the terrestrial biosphere models' vertical water balance in order to determine spatiotemporal patterns of river flows within the simulated region. We evaluated the ED2+R model in the Tapajós, a 476 674 km2 river basin in the southeastern Amazon, Brazil. The results showed that the integration of ED2 with the lateral routing scheme results in an adequate representation (Nash–Sutcliffe efficiency up to 0.76, Kling–Gupta efficiency up to 0.86, Pearson's R up to 0.88, and volume ratio up to 1.06) of daily to decadal river flow dynamics in the Tapajós. These results are a consistent step forward with respect to the no river representation common among terrestrial biosphere models, such as the initial version of ED2.

The purpose of this study was to obtain basic information on acclimation capacity of photosynthesis in Siebold's beech seedlings to increasing light intensity under future elevated CO2 conditions. We monitored leaf photosynthetic traits of these seedlings in changing light conditions (before removal of shade trees, the year after removal of shade trees and after acclimation to open conditions) in a 10-year free air CO2 enrichment experiment in northern Japan. Elevated CO2 did not affect photosynthetic traits such as leaf mass per area, nitrogen content and biochemical photosynthetic capacity of chloroplasts (i.e. maximum rate of carboxylation and maximum rate of electron transport) before removal of the shade trees and after acclimation to open conditions; in fact, a higher net photosynthetic rate was maintained under elevated CO2 . However, in the year after removal of the shade trees, there was no increase in photosynthesis rate under elevated CO2 conditions. This was not due to photoinhibition. In ambient CO2 conditions, leaf mass per area and nitrogen content were higher in the year after removal of shade trees than before, whereas there was no increase under elevated CO2 conditions. These results indicate that elevated CO2 delays the acclimation of photosynthetic traits of Siebold's beech seedlings to increasing light intensity.

Relationships between behavioral and physiological performance under elevated CO₂ in marine fishes

Abstract. Almost 95 % of all terrestrial plant species form symbioses with mycorrhizal fungi that mediate plant–soil interactions: mycorrhizae facilitate plant nitrogen (N) acquisition and are, therefore, vital for plant growth, but they also build a pathway for plant-assimilated carbon (C) into the rhizosphere. Therefore, mycorrhizae likely play an important role in shaping the response of ecosystems to environmental changes such as rising atmospheric carbon dioxide (CO2) concentrations, which can increase plant N demand and the transfer of plant C assimilation to the soil. While the importance of mycorrhizal fungi is widely recognised, they are rarely represented in current terrestrial biosphere models (TBMs) explicitly. Here, we present a novel, dynamic plant–mycorrhiza–soil model as part of the QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) TBM. This new model is based on mycorrhizal functional types that either actively mine soil organic matter (SOM) for N or enhance soil microbial activity through increased transfer of labile C into the rhizosphere, thereby (passively) priming SOM decomposition. Using the Duke Free-Air CO2 Enrichment (FACE) experiment, we show that mycorrhizal fungi can have important effects on projected SOM turnover and plant nutrition under ambient as well as elevated-CO2 treatments. Specifically, we find that including enhanced active mining of SOM for N in the model allows one to more closely match the observations with respect to observed decadal responses of plant growth, plant N acquisition and soil C dynamics to elevated CO2, whereas a simple enhancement of SOM turnover by increased below-ground C transfer of mycorrhizae is unable to replicate the observed responses. We provide an extensive parameter uncertainty study to investigate the robustness of our findings with respect to model parameters that cannot readily be constrained by observations. Our study points to the importance of implementing mycorrhizal functionalities in TBMs as well as to further observational needs to better constrain mycorrhizal models and to close the existing major knowledge gaps in actual mycorrhizal functioning.

The role of Aspergillus flavus in modulating the physiological adjustments of sunflower to elevated CO2 and temperature

Effects of the nitrification inhibitor nitrapyrin on N2O emissions under elevated CO2 and rising temperature in a wheat cropping system

Trade-offs between water-use related traits, yield components and mineral nutrition of wheat under Free-Air CO2 Enrichment (FACE)