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Carbon and water cycle dynamics of vegetation are controlled primarily by photosynthesis and stomatal conductance (gs). Our goal is to improve the representation of these key physiological processes within the JULES land surface model, with a particular focus on refining the temperature sensitivity of photosynthesis, impacting modelled carbon, energy and water fluxes. We test (1) an implementation of the Farquhar et al. (1980) photosynthesis scheme and associated plant functional type-dependent photosynthetic temperature response functions, (2) the optimality-based gs scheme from Medlyn et al. (2011) and (3) the Kattge and Knorr (2007) photosynthetic capacity thermal acclimation scheme. New parameters for each model configuration are adopted from recent large observational datasets that synthesise global experimental data. These developments to JULES incorporate current physiological understanding of vegetation behaviour into the model and enable users to derive direct links between model parameters and ongoing measurement campaigns that refine such parameter values. Replacement of the original Collatz et al. (1991) C3 photosynthesis model with the Farquhar scheme results in large changes in GPP for the current day, with ∼ 10 % reduction in seasonal (June–August, JJA, and December–February, DJF) mean GPP in tropical forests and ∼ 20 % increase in the northern high-latitude forests in JJA. The optimality-based gs model decreases the latent heat flux for the present day (∼ 10 %, with an associated increase in sensible heat flux) across regions dominated by needleleaf evergreen forest in the Northern Hemisphere summer. Thermal acclimation of photosynthesis coupled with the Medlyn gs scheme reduced tropical forest GPP by up to 5 % and increased GPP in the high-northern-latitude forests by between 2 % and 5 %. Evaluation of simulated carbon and water fluxes by each model configuration against global data products shows this latter configuration generates improvements in these key areas. Thermal acclimation of photosynthesis coupled with the Medlyn gs scheme improved modelled carbon fluxes in tropical and high-northern-latitude forests in JJA and improved the simulation of evapotranspiration across much of the Northern Hemisphere in JJA. Having established good model performance for the contemporary period, we force this new version of JULES offline with a future climate scenario corresponding to rising atmospheric greenhouse gases (Shared Socioeconomic Pathway (SSP5), Representative Concentration Pathway 8.5 (RCP8.5)). In particular, these calculations allow for understanding of the effects of long-term warming. We find that the impact of thermal acclimation coupled with the optimality-based gs model on simulated fluxes increases latent heat flux (+50 %) by the year 2050 compared to the JULES model configuration without acclimation. This new JULES configuration also projects increased GPP across tropical (+10 %) and northern-latitude regions (+30 %) by 2050. We conclude that thermal acclimation of photosynthesis with the Farquhar photosynthesis scheme and the new optimality-based gs scheme together improve the simulation of carbon and water fluxes for the current day and have a large impact on modelled future carbon cycle dynamics in a warming world.

The importance of phosphorus (P) in plant function and ecosystem biogeochemistry has led to the addition of a P cycle to a range of vegetation models, but the predictions of these P-enabled models have rarely been evaluated with ecosystem-scale data. Here, we confronted eight state-of-the-art, P-enabled models with data from EucFACE, a P-limited Eucalyptus forest subject to long-term Free-Air CO2 Enrichment. We evaluated the capability of the models to capture the observed elevated CO2 responses in this ecosystem. We show that the inclusion of phosphorus-cycle is necessary to more realistically simulate ecosystem function and biogeochemistry, but this enhanced capacity did not directly translate into improved prediction accuracy. Specifically, models diverged in capturing the observed CO2 responses, with simulation accuracy depending upon model assumptions about plant physiology, allocation, plant-soil interactions and soil nutrient processes. Confronting models with experimental responses observed at EucFACE represents a valuable opportunity to improve our understanding of the carbon-phosphorus interaction under rising CO2, and is an important step towards more accurate predictions of the future land carbon sink under climate change.

Climate change, driven by rising atmospheric CO2 concentrations, is well under way, and we are already starting to see significant shifts in the function and distribution of vegetation as a result. Dynamic vegetation models, the main platform used to predict the likely magnitude, rate and nature of these shifts, were originally rooted in theories of successional dynamics following disturbance. A key question for these models is how well they can capture vegetation responses to climatic change, which includes both press and pulse disturbances. Here we develop a general framework for representing climate-driven successional dynamics in vegetation models. The framework is illustrated with a series of case studies from Australia of vegetation responses to the major global change drivers of rising CO2, warming, drought and fire. The Australian environment, intrinsically characterized by high climate variability, has experienced increasingly challenging climate extremes in recent years and thus provides an excellent testbed for predictive models.

Australia is the driest inhabited continent. Annual rainfall is low and is accompanied by marked inter-annual variability, leading to multi-year droughts. n particular, ​South-East Australia​ ​has recently experienced two of the worst droughts in the historical record (2000–2009 and 2017–2020). Predicting species-level responses to drought at the landscape scale is critical to reducing uncertainty in future terrestrial carbon and water cycle projections. We embedded a stomatal optimisation model in the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model and parameterised the model for 15 canopy-dominant eucalypt tree species across South-Eastern Australia (mean annual precipitation range: 344–1424 mm yr-1). We carried out three experiments: applying CABLE to the recent drought; a theoretical future drier drought (20% reduction in rainfall); and a future drier drought (20% reduction in rainfall) with a doubling of atmospheric carbon dioxide (CO2). The drought's severity was highlighted as at least 25% of their distribution ranges, and 60% of species experienced leaf water potentials beyond the water potential at which 50% of hydraulic conductivity is lost due to embolism. We identified areas of severe hydraulic stress within species’ ranges, but we also pinpointed resilience in species found in predominantly semiarid regions. The importance of the role of CO2 in ameliorating drought stress was consistent across species. Our results represent an important advance in our capacity to forecast the resilience of individual tree species, providing an evidence base for decision-making around the resilience of restoration plantings or net-zero emission strategies.

Rising carbon dioxide (CO2) levels can lead to more carbon sequestration in plant biomass, and forests’ natural ability to store carbonin long-lived woody tissue is of particular interest. However, the extent of CO2-fertilization in trees varies across age, species and the availability of other resources. Woody tissue encompasses more than just the tree’s trunk, and a critical knowledge gap lies in the allocation of carbon to the other woody components like branches and twigs. In addition, the flux of woody carbon from the tree to the forest floor (turnover) is more than events of single tree mortality. These fluxes come in the form of litterfall, breakage of whole branches or complete tree mortality. The goal of this study is to quantify biomass allocation patterns and subsequent turnover rates within the woody carbon pool of two contrasting forest FACE experiments, BIFoR FACE in Staffordshire UK, and EucFACE in Sydney, Australia and answer the following questions: how do these allocation patterns determine the potential for carbon sequestration and how do patterns shift with elevated CO2 concentrations?Terrestrial laser scanning provided the tools to determine canopy structure on a stand scale, and the use of algorithms on the resulting point cloud trees supplied data on the partitioning of biomass among twigs, branches and stems. These results were then used to test general hypotheses about canopy structure and how it changes with elevated CO2. The fluxes from the different wood components were quantified with monthly observations and collections, litter traps to collect the smallest material and transects to make an inventory of larger compartments like branches. The results of these studies will be combined with the canopy structure partitioning fractions to determine if the allocation patterns vary over time and between two contrasting forest types. It is worthwhile to increase our understanding of the dynamics of all woody components within forests and on a global scale beyond single tree mortality to improve the accuracy of predictive carbon budget models.

Climate change is projected to increase the imbalance between the supply (precipitation) and atmospheric demand for water (i.e., increased potential evapotranspiration), stressing plants in water-limited environments. Plants may be able to offset increasing aridity because rising CO2 increases water use efficiency. CO2 fertilization has also been cited as one of the drivers of the widespread “greening” phenomenon. However, attributing the size of this CO2 fertilization effect is complicated, due in part to a lack of long-term vegetation monitoring and interannual- to decadal-scale climate variability. In this study we asked the question of how much CO2 has contributed towards greening. We focused our analysis on a broad aridity gradient spanning eastern Australia's woody ecosystems. Next we analyzed 38 years of satellite remote sensing estimates of vegetation greenness (normalized difference vegetation index, NDVI) to examine the role of CO2 in ameliorating climate change impacts. Multiple statistical techniques were applied to separate the CO2-attributable effects on greening from the changes in water supply and atmospheric aridity. Widespread vegetation greening occurred despite a warming climate, increases in vapor pressure deficit, and repeated record-breaking droughts and heat waves. Between 1982–2019 we found that NDVI increased (median 11.3 %) across 90.5 % of the woody regions. After masking disturbance effects (e.g., fire), we statistically estimated an 11.7 % increase in NDVI attributable to CO2, broadly consistent with a hypothesized theoretical expectation of an 8.6 % increase in water use efficiency due to rising CO2. In contrast to reports of a weakening CO2 fertilization effect, we found no consistent temporal change in the CO2 effect. We conclude rising CO2 has mitigated the effects of increasing aridity, repeated record-breaking droughts, and record-breaking heat waves in eastern Australia. However, we were unable to determine whether trees or grasses were the primary beneficiary of the CO2-induced change in water use efficiency, which has implications for projecting future ecosystem resilience. A more complete understanding of how CO2-induced changes in water use efficiency affect trees and non-tree vegetation is needed.

The Millennium Drought lasted more than a decade and is notable for causing persistent shifts in the relationship between rainfall and runoff in many southeastern Australian catchments. Research to date has successfully characterised where and when shifts occurred and explored relationships with potential drivers, but a convincing physical explanation for observed changes in catchment behaviour is still lacking. Originating from a large multi-disciplinary workshop, this paper presents and evaluates a range of hypothesised process explanations of flow response to the Millennium Drought. The hypotheses consider climatic forcing, vegetation, soil moisture dynamics, groundwater, and anthropogenic influence. The hypotheses are assessed against evidence both temporally (e.g. why was the Millennium Drought different to previous droughts?) and spatially (e.g. why did rainfall–runoff relationships shift in some catchments but not in others?). Thus, the strength of this work is a large-scale assessment of hydrologic changes and potential drivers. Of 24 hypotheses, 3 are considered plausible, 10 are considered inconsistent with evidence, and 11 are in a category in between, whereby they are plausible yet with reservations (e.g. applicable in some catchments but not others). The results point to the unprecedented length of the drought as the primary climatic driver, paired with interrelated groundwater processes, including declines in groundwater storage, altered recharge associated with vadose zone expansion, and reduced connection between subsurface and surface water processes. Other causes include increased evaporative demand and harvesting of runoff by small private dams. Finally, we discuss the need for long-term field monitoring, particularly targeting internal catchment processes and subsurface dynamics. We recommend continued investment in the understanding of hydrological shifts, particularly given their relevance to water planning under climate variability and change.

Predicting ecosystem resilience to droughts and heatwaves requires a predictive capacity that is currently lacking in land-surface models (LSMs). Eco-evolutionary optimisation approaches have the potential to increase predictability, but competing approaches are yet to be probed together in LSMs. Here, we coupled schemes that optimise canopy gas-exchange vs. leaf nitrogen investment, and both approaches were extended to account for hydraulic legacies from water-stress. We assessed model predictions using observations from a South-Eastern Australian woodland exposed to repeated drought between 2013 and 2020, under both ambient and elevated [CO2]. Our simulations were in good agreement with observations of transpiration (r2∼0.7), leaf water potential (±0.1 MPa), and leaf photosynthetic capacities (±5% of the observations). Despite predictions of significant percentage loss of conductivity (PLC) due to water stress in 2013, 2014, 2016, and 2017 (p99 > 45%), hydraulic legacy effects were small and recovered rapidly. Combining the optimisation schemes and hydraulic legacies led to improved model predictions and enhanced the simulated magnitude fertilisation effect on GPP at elevated [CO2], albeit that the impact on the canopy fluxes was small overall. Our simulations suggested that leaf shedding and/or suppressed foliage growth formed an active strategy to mitigate drought risk, with leaves being grown during wet years to replenish carbon stores, whereas LAI dropped in anticipation of severe water stress to prevent high PLC. Accounting for leaf acclimation in response to drought therefore has the potential to improve predictions of ecosystem resilience to drought in water-limited regions.

Predicting species-level responses to drought at the landscape scale is critical to reducing future uncertainty in terrestrial carbon and water cycle projections. We embedded a stomatal optimisation model in the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. We parameterised the model for 15 canopy dominant eucalypt tree species representative of a broad precipitation gradient across South East Australia (mean annual precipitation range: 344–1424 mm yr-1). We conducted three experiments: (i) applying CABLE to the 2017–2019 drought in South East Australia; (ii) a 20% drier drought; and (iii) a 20% drier drought with a doubling of atmospheric carbon dioxide (CO2). We identified several drought hotspots across the ranges of E.viminalis, E.obliqua, E.globulus, E.saligna, and E.grandis. By contrast, CABLE simulated drought resilience in species that are found predominately in semi-arid areas such as E.largiflorens and E.populnea. We identified several key model assumptions (e.g., the degree of stomatal control) and sensitivities (e.g., the role of CO2 in ameliorating drought) that require future research. Our results represent an important step forward in our capacity to forecast the resilience of individual tree species, providing an evidence base for decision-making around the resilience of restoration plantings or strategies associated with achieving net-zero emissions.

Anthropocene impact on atmospheric carbon has led to increased efforts to better understand the carbon cycle in terrestrial vegetation. Forests and their natural ability to assimilate carbon dioxide (CO2) from the air have increasingly been incorporated into climate change mitigation policies. The increase in global CO2 levels has also been shown to cause photosynthetic enhancement, although the extent of this CO2-fertilization effect varies across vegetation type, age, species and the availability of other resources. An important knowledge gap for the projected mitigation function of (future) forests is the currently unknown fate of this additional carbon as a result of the increased photosynthetic activity [1]. Woody biomass is still thought to harbour a substation fraction of the unaccounted for carbon [2] and by including smaller woody compartments to the well-represented stem diameter datasets this research project aims to provide more details to the standing and turned over woody biomass inventories. The branch and twig compartments might detach faster from trees pre-mortality under elevated CO2, increasing the turn-over rate of carbon within forest stands where this has previously gone unnoticed. To determine the choices of trees regarding growth under future CO2 levels observation will be collected in two second-generation Free Air CO2 Enrichment (FACE) facilities: BIFoR FACE, in Staffordshire UK and EucFACE in Sydney Australia. By making stand scale inventories using Terrestrial Laser Scanning (TLS) for standing biomass and line transects along with litter traps for fallen woody tissue, the fluxes of newly grown wood under eCO2 versus wood exposed to long term ambient concentrations can be compared. With additional comparisons between the two facilities, subsequent environmental factors and weather events to follow so that predictive carbon budget models can be improved. The increased CO2 concentrations at these sites reach the levels estimated to be the global ambient in 30-40 years. In the current phase of this research project, the datasets resulting from the first fieldwork campaign and pipelines for array scale TLS analysis and turnover expansion factors are constructed.References[1] Jiang, M., Medlyn, B. E., Drake, J. E., Duursma, R. A., Anderson, I. C., Barton, C. V., ... & Ellsworth, D. S. (2020). The fate of carbon in a mature forest under carbon dioxide enrichment. Nature, 580(7802), 227-231.[2] Walker, A. P., De Kauwe, M. G., Medlyn, B. E., Zaehle, S., Iversen, C. M., Asao, S., ... & Norby, R. J. (2019). Decadal biomass increment in early secondary succession woody ecosystems is increased by CO 2 enrichment. Nature communications, 10(1), 1-13.

The response of mature forest ecosystems to a rising atmospheric carbon dioxide concentration (Ca) is a major uncertainty in projecting the future trajectory of the Earth's climate. Although leaf-level net photosynthesis is typically stimulated by exposure to elevated Ca (eCa), it is unclear how this stimulation translates into carbon cycle responses at the ecosystem scale. Here we estimate a key component of the carbon cycle, the gross primary productivity (GPP), of a mature native eucalypt forest exposed to free-air CO2 enrichment (the EucFACE experiment). In this experiment, light-saturated leaf photosynthesis increased by 19 % in response to a 38 % increase in Ca. We used the process-based forest canopy model, MAESPA, to upscale these leaf-level measurements of photosynthesis with canopy structure to estimate the GPP and its response to eCa. We assessed the direct impact of eCa, as well as the indirect effect of photosynthetic acclimation to eCa and variability among treatment plots using different model scenarios. At the canopy scale, MAESPA estimated a GPP of 1574 g C m−2 yr−1 under ambient conditions across 4 years and a direct increase in the GPP of +11 % in response to eCa. The smaller canopy-scale response simulated by the model, as compared with the leaf-level response, could be attributed to the prevalence of RuBP regeneration limitation of leaf photosynthesis within the canopy. Photosynthetic acclimation reduced this estimated response to 10 %. After taking the baseline variability in the leaf area index across plots in account, we estimated a field GPP response to eCa of 6 % with a 95 % confidence interval (−2 %, 14 %). These findings highlight that the GPP response of mature forests to eCa is likely to be considerably lower than the response of light-saturated leaf photosynthesis. Our results provide an important context for interpreting the eCa responses of other components of the ecosystem carbon cycle.

Climate change is projected to increase the imbalance between the supply (precipitation) and atmospheric demand for water (i.e. increased potential evapotranspiration), stressing plants in water-limited environments. Plants may be able to offset increasing aridity because rising CO2 increases water-use-efficiency. CO2 fertilization has also been cited as one of the drivers of the widespread ‘greening’ phenomenon. However, attributing the size of this CO2 fertilization effect is complicated, due in part to a lack of long-term vegetation monitoring and interannual to decadal-scale climate variability. In this study we asked the question, how much has CO2 contributed towards greening? We focused our analysis on a broad aridity gradient spanning eastern Australia’s woody ecosystems. Next we analysed 38-years of satellite remote sensing estimates of vegetation greenness (normalized difference vegetation index, NDVI) to examine the role of CO2 in ameliorating climate change impacts. Multiple statistical techniques were applied to separate the CO2-attributable effects on greening from the changes in water supply and atmospheric aridity. Widespread vegetation greening occurred despite a warming climate, increases in vapor pressure deficit, and repeated record-breaking droughts and heatwaves. Between 1982–2019 we found that NDVI increased (median 11.3 %) across 90.5 % of the woody regions. After masking disturbance effects (e.g. fire), we statistically estimated an 11.7 % increase in NDVI attributable to CO2, broadly consistent with a hypothesized theoretical expectation of an 8.6 % increase in water-use-efficiency due to rising CO2. In contrast to reports of a weakening CO2 fertilization effect, we found no consistent temporal change in the CO2 effect. We conclude rising CO2 has mitigated the effects of increasing aridity, repeated record-breaking droughts, and record-breaking heat waves in eastern Australia. However, we were unable to determine whether trees or grasses were the primary beneficiary of the CO2 induced change in water-use-efficiency, which has implications for projecting future ecosystem resilience. A more complete understanding of how CO2 induced changes in water-use-efficiency affect trees and non-tree vegetation is needed.

Boreal regions are undergoing rapid climate change but our understanding of the long-term consequences for forest processes is hampered by limited knowledge of how trees acclimate to rising atmospheric CO2 concentrations and temperature. This study used the detailed canopy flux model MAESTRA to simulate the effects of elevated CO2 (eCO2) and warming on net photosynthesis (An) and transpiration (E) of mature boreal Norway spruce, investigating how these effects are influenced by the observed acclimation of photosynthetic capacity, respiration, stomatal behavior, and phenology. Without any type of acclimation, eCO2 increased shoot and crown An during the non-frost growing season by 23-44%, while warming only had a minor effect (±2%). Photosynthetic downregulation greatly decreased the positive effect under eCO2. Under warming, both stomatal and phenological acclimation had substantial effects on An but in opposite directions. Transpiration at shoot and crown level was greatly decreased (23-50%) by eCO2 and increased by warming (27-42%) in the absence of acclimation. However, both these effects were largely cancelled by stomatal acclimation. Effects of eCO2 on An were generally smaller at entire crown compared to shoot level, as a result of photosynthetic stimulation being smaller in shaded canopy positions. In addition, upregulation of respiration in eCO2 had a considerably larger negative effect on An at crown compared to shoot level. Overall, tree physiological acclimation generally acted to dampen non-acclimated responses. We conclude that photosynthetic and respiratory acclimation greatly reduce the positive effect of eCO2 on tree CO2 assimilation, while stomatal and phenological acclimation are crucial for annual water consumption under warming. These results highlight the critical need to account for acclimation in models.

Australia is the driest inhabited continent. Annual rainfall is low and is accompanied by marked inter-annual variability, leading to multi-year droughts. Climate change is expected to alter the frequency, magnitude, and intensity of future droughts, with potentially major environmental and socio-economic consequences for Australia. However, Australian vegetation is well adapted to extended dry periods, thus, the likelihood of drought-induced mortality in the future depends both on the severity of future drought events and inherent vegetation resilience. Here, we used the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, coupled with a stomatal optimisation scheme, to examine the projected impact of future drought for 24 Eucalyptus species. We forced CABLE with future climate from four global climate models (MIROC, ECHAM, CCCMA, and CSIRO) dynamically downscaled by three regional climate models. We separated the impact of climate change (e.g. increasing VPD, precipitation variability) from rising CO2 (increasing water use-efficiency) to provide the first assessment of future drought risk to Australian trees.

Droughts have been implicated as the driver behind recent vegetation die-off across a variety of hydroclimates and are projected to drive greater mortality under future climate change. Predicting ecosystem resilience to future drought requires a predictive capacity, which is currently lacking in state-of-the-art land surface models (LSMs) that rely on simplified empirical relationships to represent the impacts of water stress on vegetation. Novel approaches that optimise stomatal conductance with respect to plant photosynthetic and hydraulic functions have been shown to reduce the biases of LSM gas exchange predictions during drought. These approaches also offer a pathway to further develop mechanistic optimality theory, e.g. pertaining to leaf drought deciduousness. But on what timescale(s) does vegetation function adjust to maximise resource investment? We explore the following timescales of optimality within a simple LSM: (i) instantaneous (regulating canopy gas exchange); (ii) monthly (regulating the investment of nitrogen in photosynthetic capacity); and (iii) seasonal to annual (water stress legacies on plant hydraulics). We use observations from a temperate woodland in South-Eastern Australia to test which optimisation timescales and processes are best supported and whether competing timescales can operate together, both under well-watered conditions and during a severe multi-year drought, and from the leaf-scale to the ecosystem-scale. The insights gained help us characterize how adjoined allocation processes, like leaf biomass adjustment, relate to leaf carbon uptake and plant water status through time (e.g. leaves can be shed to mitigate drought stress or built from structural storage pools when water is not limiting), therefore conferring additional resilience.

Nearly 2/3 of the annual global evapotranspiration (ET) over land arises from the vegetation. Yet, coupled-climate models only attribute between 22% – 58% of the annual terrestrial ET to plants. In coupled-climate models, the exchange of carbon and water between the terrestrial biosphere and the atmosphere is simulated by land-surface models (LSMs). Within those LSMs, stomatal conductance (gs) models allow plants to regulate their transpiration and carbon uptake, but most are empirically linked to climate, soil moisture availabilty, and CO2. Therefore, how and which gs schemes are implemented within LSMs is a key source of model uncertainty. This uncertainty has led to considerable investment in theory development in the recent years; multiple alternative hypotheses of optimal leaf-level regulation of gas exchange have been proposed as solutions to reduce existing model biases. However, a systematic inter-model evaluation is lacking (i.e. inter-model comparison within a single framework is needed to understand how different mechanistic assumptions across these new gs models affect plant behaviour). Here, we asked how, and under what conditions, nine novel optimal gs models differ from one another. The models were trained to match under average conditions before being subjected to: (i) a dry-down, (ii) high vapour pressure deficit, and (iii) elevated CO2. These experiments allowed us to identify the models’ specific responses and sensitivities. To further assess whether the models’ responses were realistic, we tested them against photosynthetic and hydraulic field data measured along mesic-xeric gradients in Europe and Australia. Finally, we evaluated model performance versus model complexity and the amount of information taken in by each model, which enables us to make recommendations regarding the use of stomatal conductance schemes in global climate models.

Predicting the seasonal dynamics of ecosystem carbon fluxes is challenging in broadleaved evergreen forests because of their moderate climates and subtle changes in canopy phenology. We assessed the climatic and biotic drivers of the seasonality of net ecosystem–atmosphere CO2 exchange (NEE) of a eucalyptus-dominated forest near Sydney, Australia, using the eddy covariance method. The climate is characterised by a mean annual precipitation of 800 mm and a mean annual temperature of 18 ∘C, hot summers and mild winters, with highly variable precipitation. In the 4-year study, the ecosystem was a sink each year (−225 g C m−2 yr−1 on average, with a standard deviation of 108 g C m−2 yr−1); inter-annual variations were not related to meteorological conditions. Daily net C uptake was always detected during the cooler, drier winter months (June through August), while net C loss occurred during the warmer, wetter summer months (December through February). Gross primary productivity (GPP) seasonality was low, despite longer days with higher light intensity in summer, because vapour pressure deficit (D) and air temperature (Ta) restricted surface conductance during summer while winter temperatures were still high enough to support photosynthesis. Maximum GPP during ideal environmental conditions was significantly correlated with remotely sensed enhanced vegetation index (EVI; r2 = 0.46) and with canopy leaf area index (LAI; r2 = 0.29), which increased rapidly after mid-summer rainfall events. Ecosystem respiration (ER) was highest during summer in wet soils and lowest during winter months. ER had larger seasonal amplitude compared to GPP, and therefore drove the seasonal variation of NEE. Because summer carbon uptake may become increasingly limited by atmospheric demand and high temperature, and because ecosystem respiration could be enhanced by rising temperatures, our results suggest the potential for large-scale seasonal shifts in NEE in sclerophyll vegetation under climate change.

The response of mature forest ecosystems to rising atmospheric carbon dioxide concentration (Ca) is a major uncertainty in projecting the future trajectory of the Earth’s climate. Although leaf-level net photosynthesis is typically stimulated by exposure to elevated Ca (eCa), it is unclear how this stimulation translates into carbon cycle responses at whole-ecosystem scale. Here we estimate a key component of the carbon cycle, the gross primary productivity (GPP), of a mature native Eucalypt forest exposed to Free Air CO2 Enrichment (the EucFACE experiment). In this experiment, light-saturated leaf photosynthesis increased by 19 % in response to a 38 % increase in Ca. We used the process-based forest canopy model, MAESPA, to upscale these leaf-level measurements of photosynthesis with canopy structure to estimate Gross Primary Production (GPP) and its response to eCa. We assessed the direct impact of eCa, as well as the indirect effect of photosynthetic acclimation to eCa and variability among treatment plots via different model scenarios. At the canopy scale, MAESPA estimated a GPP of 1574 g C m−2 yr−1 under ambient conditions across four years and a direct increase in GPP of +11 % in response to eCa. The smaller canopy-scale response simulated by the model, as compared to the leaf-level response, could be attributed to the prevalence of RuBP-regeneration limitation of leaf photosynthesis within the canopy. Photosynthetic acclimation reduced this estimated response to 10 %. Considering variability in leaf area index across plots, we estimated a mean GPP response to eCa of 6 % with a 95 % CI of (−2 %, 14 %). These findings highlight that the GPP response of mature forests to eCa is likely to be considerably lower than the response of light-saturated leaf photosynthesis. Our results provide an important context for interpreting eCa responses of other components of the ecosystem carbon cycle.

Recent experimental evidence suggests that during heat extremes, wooded ecosystems may decouple photosynthesis and transpiration: reducing photosynthesis to near zero but increasing transpiration into the boundary layer. This feedback may act to dampen, rather than amplify, heat extremes in wooded ecosystems. We examined eddy-covariance databases (OzFlux and FLUXNET2015) to identify whether there was field-based evidence to support these experimental findings. We focused on two types of heat extremes: (i) the three days leading up to a temperature extreme, defined as including a daily maximum temperature > 37 °C (similar to the widely used TXx metric) and (ii) heatwaves, defined as three or more consecutive days above 35 °C. When focussing on (i), we found some evidence of reduced photosynthesis and sustained or increased latent heat fluxes in seven Australian evergreen wooded flux sites. However, when considering the role of vapour pressure deficit and focusing on (ii), we were unable to conclusively disentangle the decoupling between photosynthesis and latent heat flux from the effect of increasing vapour pressure deficit. Outside of Australia, the Tier-1 FLUXNET2015 database provided limited scope to tackle this issue as it does not sample sufficient high temperature events with which to probe the physiological response of trees to extreme heat. Thus, further work is required to determine whether this photosynthetic decoupling occurs widely, ideally by matching experimental species with those found at eddy-covariance towers sites. Such measurements would allow this decoupling mechanism to be probed experimentally and at the ecosystem scale. Transpiration during heatwaves remains a key issue to resolve, as no land surface model includes a decoupling mechanism, and any potential dampening of the land-atmosphere amplification is thus not included in climate model projections.

Computer models are ubiquitous tools used to represent systems across many scientific and engineering domains. For any given system, many computer models exist, each built on different assumptions and demonstrating variability in the ways in which these systems can be represented. This variability is known as epistemic uncertainty, i.e. uncertainty in our knowledge of how these systems operate. Two primary sources of epistemic uncertainty are: 1) uncertain parameter values, and 2) uncertain mathematical representations of the processes that comprise the system. Many formal methods exist to analyse parameter-based epistemic uncertainty, while process-representation based epistemic uncertainty is often analysed informally and incompletely, or is ignored. In this model description paper we present the Multi-Assumption Architecture and Testbed (MAAT v1.0) designed to formally and more completely analyse process-representation based epistemic uncertainty. MAAT is a modular modelling code that can simply and efficiently vary model structure (process representation) during runtime, allowing the generation of large ensembles that vary in process representation, as well as in parameters, parameter values, and environmental conditions. MAAT v1.0 approaches epistemic uncertainty through sensitivity anlaysis, assigning variability in model output to processes (process representation and parameters) or to individual parameters. In this model description paper we describe MAAT and by using a simple groundwater model example, verify that the sensitivity analysis algorithms have been correctly implemented. The main system model currently coded in MAAT is a unified, leaf-scale enzyme kinetic model of C3 photosynthesis. We describe the photosynthesis model and the unification of multiple representations of photosynthetic processes. The numerical solution to leaf-scale photosynthesis is verified and examples of process variability in temperature response functions are provided. For rapid application to new systems, the MAAT algorithms for efficient variation of model structure and sensitivity analysis are agnostic of the specifc system model employed. Therefore MAAT provides a tool for development of novel or "toy" models in many domains, i.e. not only photosynthesis, facilitating rapid informal and formal comparison of alternative modelling approaches.

The lack of correlation between photosynthesis and plant growth under sink-limited conditions is a long-standing puzzle in plant ecophysiology that currently severely compromises our models of vegetation responses to global change. To address this puzzle, we applied data assimilation to an experiment in which the sink strength of Eucalyptus tereticornis seedlings was manipulated by restricting root volume. Our goals were to infer which processes were affected by sink limitation and to attribute the overall reduction in growth observed in the experiment to the effects on various carbon (C) component processes. Our analysis was able to infer that, in addition to a reduction in photosynthetic rates, sink limitation reduced the rate of utilization of nonstructural carbohydrate (NSC), enhanced respiratory losses, modified C allocation and increased foliage turnover. Each of these effects was found to have a significant impact on final plant biomass accumulation. We also found that inclusion of an NSC storage pool was necessary to capture seedling growth over time, particularly for sink-limited seedlings. Our approach of applying data assimilation to infer C balance processes in a manipulative experiment enabled us to extract new information on the timing, magnitude and direction of the internal C fluxes from an existing dataset. We suggest that this approach could, if used more widely, be an invaluable tool to develop appropriate representations of sink-limited growth in terrestrial biosphere models.

Predicting the seasonal dynamics of ecosystem carbon fluxes is challenging in broadleaved evergreen forests because of their moderate climates and subtle changes in canopy phenology. We assessed the climatic and biotic drivers of the seasonality of net ecosystem-atmosphere CO2 exchange (NEE) of a eucalyptus-dominated forest near Sydney, Australia, using the eddy covariance method. The climate is characterized by a mean annual precipitation of 800 mm and a mean annual temperature of 18 °C, hot summers and mild winters, with highly variable precipitation. In the three-year study, the ecosystem was a small sink in 2014 (54 g C m−2 y−1), a stronger sink in 2015 (183 g C m−2 y−1) and even stronger sink in 2016 (337 g C m−2 y−1), but these variations were not related to precipitation. Daily net C uptake was always detected during the cooler, drier winter months (June through August), while net C loss occurred during the warmer, wetter summer months (December through February). Gross primary productivity (GPP) seasonality was low, despite longer days with higher light intensity in summer, because vapour pressure deficit (D) and air temperature (Ta) restricted surface conductance during summer while winter temperatures were still high enough to support photosynthesis. Maximum GPP during ideal environmental conditions was correlated with canopy leaf area index (LAI) (r2 = 0.24), which increased rapidly after mid-summer rainfall events. Ecosystem respiration (ER) was highest during summer in wet soils and lowest during winter months. ER had larger seasonal amplitude compared to GPP, and therefore drove the seasonal variation of NEE. Because summer carbon uptake may become increasingly limited by atmospheric drought and high temperature, and ecosystem respiration could be enhanced by rising temperature, our results suggest the potential for large-scale seasonal shifts in NEE in sclerophyll vegetation under climate change.