Bigleaf-An R package for the calculation of physical and physiological ecosystem properties from eddy covariance data

Amazon rainforest adjusts to long-term experimental drought

Drought-induced mortality is expected to cause substantial biomass loss in the Amazon basin. However, rainforest responses to prolonged drought are largely unknown. Here, we demonstrate that an Amazonian rainforest plot subjected to more than two decades of large-scale experimental drought reached eco-hydrological stability. After elevated tree mortality during the first 15 years, ecosystem-level structural changes resulted in the remaining trees no longer experiencing drought stress. The loss of the largest trees led to increasing water availability for the remaining trees, stabilizing biomass in the last 7 years of the experiment. Hydraulic variables linked to physiological stress, such as leaf water potential, sap flow and tissue water content, converged to the values observed in a corresponding non-droughted control forest, indicating hydraulic homeostasis. While it prevented drought-induced collapse, eco-hydrological stabilization resulted in a forest with reduced biomass and carbon accumulation in wood. These findings show how tropical rainforests may be resilient to persistent soil drought.

Dual controls of vapour pressure deficit and soil moisture on photosynthesis in a restored temperate bog

Despite only covering ~3 % of the land mass, peatlands store more carbon (C) per unit area than any other ecosystem. This is due to the discrepancy between C fixed by the plants (Gross primary productivity (GPP)) and decomposition. However, this C is vulnerable to frequent, severe droughts and changes in the peatland microclimate. Plants play a vital role in ecosystem C dynamics under drought by mediating water loss to the atmosphere (surface water vapour conductance) and GPP by the presence/absence of stomatal regulation. This is dependent on soil moisture, air temperature, and vapour pressure deficit (VPD). Although there is ample evidence of the role of VPD on stomatal regulation and GPP, the impact of soil moisture is still debated. We addressed this knowledge gap by investigating the role of bulk surface conductance of water vapour in shifts between climatic (Air temperature (Tair), incoming shortwave radiation (SWR) and VPD) and water limitation of GPP in a peat bog in Canada. A causal analysis process was used to investigate how environmental factors influenced GPP. The results suggested that stomatal regulation in response to increased VPD caused the reduction in GPP in 2016 (~2.5 gC m-2 day-1 as opposed to ~3 gC m-2 day-1 in 2018). In contrast, GPP was limited again in 2019 due to the dry surface. This was driven by the relaxed stomatal regulation adopted by the ecosystem following the initial drought to maximise C assimilation. We found the threshold at which surface water decline limited GPP was at about -8 cm water table depth (82.5 % soil moisture). The causal inference corroborated our findings. The temporal variations of water and energy limitation seen in this study could increasingly restrict GPP due to the projected climate warming.

Key role played by mesophyll conductance in limiting carbon assimilation and transpiration of potato under soil water stress

Introduction

The identification of the physiological processes limiting carbon assimilation under water stress is crucial for improving model predictions and selecting drought-tolerant varieties. However, the influence of soil water availability on photosynthesis-limiting processes is still not fully understood. This study aimed to investigate the origins of photosynthesis limitations on potato (Solanum tuberosum) during a field drought experiment.

Methods

Gas exchange and chlorophyll fluorescence measurements were performed at the leaf level to determine the response of photosynthesis-limiting factors to the decrease in the relative extractable water (REW) in the soil.

Results

Drought induced a two-stage response with first a restriction of CO2 diffusion to chloroplasts induced by stomatal closure and a decrease in mesophyll conductance, followed by a decrease in photosynthetic capacities under severe soil water restrictions. Limitation analysis equations were revisited and showed that mesophyll conductance was the most important constraint on carbon and water exchanges regardless of soil water conditions.

Discussion

We provide a calibration of the response of stomatal and non-stomatal factors to REW to improve the representation of drought effects in models. These results emphasize the need to revisit the partitioning methods to unravel the physiological controls on photosynthesis and stomatal conductance under water stress.

Evidence for widespread thermal acclimation of canopy photosynthesis

Plants acclimate to temperature by adjusting their photosynthetic capacity over weeks to months. However, most evidence for photosynthetic acclimation derives from leaf-scale experiments. Here we address the scarcity of evidence for canopy-scale photosynthetic acclimation by examining the correlation between maximum photosynthetic rates (Amax,2,000) and growth temperature (T air ¯ ) across a range of concurrent temperatures and canopy foliage quantity, using data from >200 eddy covariance sites. We detect widespread thermal acclimation of canopy-scale photosynthesis, demonstrated by enhanced Amax,2,000 under higherT air ¯ , across flux sites with adequate water availability. A 14-day period is identified as the most relevant timescale for acclimation across all sites, with a range of 12-25 days for different plant functional types. The mean apparent thermal acclimation rate across all ecosystems is 0.41 (-0.38-1.04 for 5th-95th percentile range) µmol m-2 s-1 °C-1, with croplands showing the largest acclimation rates and grasslands the lowest. Incorporating an optimality-based prediction of leaf photosynthetic capacities into a biochemical photosynthesis model is shown to improve the representation of thermal acclimation. Our results underscore the critical need for enhanced understanding and modelling of canopy-scale photosynthetic capacity to accurately predict plant responses to warmer growing seasons.

Global convergence in terrestrial gross primary production response to atmospheric vapor pressure deficit

Atmospheric vapor pressure deficit (VPD) increases with climate warming and may limit plant growth. However, gross primary production (GPP) responses to VPD remain a mystery, offering a significant source of uncertainty in the estimation of global terrestrial ecosystems carbon dynamics. In this study, in-situ measurements, satellite-derived data, and Earth System Models (ESMs) simulations were analysed to show that the GPP of most ecosystems has a similar threshold in response to VPD: first increasing and then declining. When VPD exceeds these thresholds, atmospheric drought stress reduces soil moisture and stomatal conductance, thereby decreasing the productivity of terrestrial ecosystems. Current ESMs underscore CO2 fertilization effects but predict significant GPP decline in low-latitude ecosystems when VPD exceeds the thresholds. These results emphasize the impacts of climate warming on VPD and propose limitations to future ecosystems productivity caused by increased atmospheric water demand. Incorporating VPD, soil moisture, and canopy conductance interactions into ESMs enhances the prediction of terrestrial ecosystem responses to climate change.

Cover crop inclusion and residue retention improves soybean production and physiology in drought conditions

Soybean (Glycine max (L.) Merr.) planting has increased in central and western North Dakota despite frequent drought occurrences that limit productivity. Soybean plants need high photosynthetic and transpiration rates to be productive, but they also need high water use efficiency when water is limited. Crop residues and cover crops in crop rotations may improve soybean drought tolerance in northern Great Plains. We aimed to examine how a management practice that included cover crops and residue retention impacts agronomic, ecosystem water and carbon dioxide flux, and canopy-scale physiological attributes of soybeans in the northern Great Plains under drought conditions. The experiment consisted of two soybean fields over two years with business-as-usual (no-cover crops and spring wheat residue removal) and aspirational management (cover crops and spring wheat residue retention) during a drought year. We compared yield; aboveground biomass; green chromatic coordinates, and CO2 and H2O fluxes from eddy covariance, Phenocam images, and ancillary micrometeorological measurements. These measurements were used to derive ecosystem-scale physical, and physiological attributes with the 'big leaf' framework to diagnose underlying processes. Soybean yields were 29 % higher under drought conditions in the field managed in a system that included cover crops and residue retention. This yield increase was associated with a 5 day increase in the green-chromatic-coordinate defined maturity phenophase, increasing agronomic and intrinsic water use efficiency by 27 % and 33 %, respectively, increasing water uptake, and increasing the rubisco-limited photosynthetic capacity (Vcmax25) by 42 %. The inclusion of cover crops and residue retention into a cropping system improved soybean productivity because of differences in water use, phenology timing, and photosynthetic capacity. These results suggest that farmers can improve soybean productivity and yield stability by incorporating cover crops and residue retention into their management suite because these practices to facilitate more aggressive water uptake.

Diagnosing evapotranspiration responses to water deficit across biomes using deep learning

Accounting for water limitation is key to determining vegetation sensitivity to drought. Quantifying water limitation effects on evapotranspiration (ET) is challenged by the heterogeneity of vegetation types, climate zones and vertically along the rooting zone. Here, we train deep neural networks using flux measurements to study ET responses to progressing drought conditions. We determine a water stress factor (fET) that isolates ET reductions from effects of atmospheric aridity and other covarying drivers. We regress fET against the cumulative water deficit, which reveals the control of whole-column moisture availability. We find a variety of ET responses to water stress. Responses range from rapid declines of fET to 10% of its water-unlimited rate at several savannah and grassland sites, to mild fET reductions in most forests, despite substantial water deficits. Most sensitive responses are found at the most arid and warm sites. A combination of regulation of stomatal and hydraulic conductance and access to belowground water reservoirs, whether in groundwater or deep soil moisture, could explain the different behaviors observed across sites. This variety of responses is not captured by a standard land surface model, likely reflecting simplifications in its representation of belowground water storage.

Climate warming negatively affects plant water-use efficiency in a seasonal hydroperiod wetland

Climate warming has substantial influences on plant water-use efficiency (PWUE), which is defined as the ratio of plant CO2 uptake to water loss and is central to the cycles of carbon and water in ecosystems. However, it remains uncertain how does climate warming affect PWUE in wetland ecosystems, especially those with seasonally alternating water availability during the growing season. In this study, we used a continuous 10-year (2011-2020) eddy covariance (EC) dataset from a seasonal hydroperiod wetland coupled with a 15-year (2003-2017) satellite-based dataset (called PML-V2) and an in situ warming experiment to examine the climate warming impacts on wetland PWUE. The 10-year EC observational results revealed that rising temperatures had significant negative impacts on the interannual variations in wetland PWUE, and increased transpiration (Et) rather than changes in gross primary productivity (GPP) dominated these negative impacts. Furthermore, the 15-year satellite-based evidence confirmed that, in the study region, climate warming had significant negative consequences for the interannual variations in wetland PWUE by enhancing wetland Et. Lastly, at the leaf-scale, the light response curves of leaf photosynthesis, leaf Et, and leaf-scale PWUE indicated that wetland plants need to consume more water during the photosynthesis process under warmer conditions. These findings provide a fresh perspective on how climate warming influences carbon and water cycles in wetland ecosystems.

Leaf-level coordination principles propagate to the ecosystem scale

Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories - the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis - are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

Oil palm (Elaeis guineensis) plantation on tropical peatland in South East Asia: Photosynthetic response to soil drainage level for mitigation of soil carbon emissions

While existing moratoria in Indonesia and Malaysia should preclude continued large-scale expansion of palm oil production into new areas of South-East Asian tropical peatland, existing plantations in the region remain a globally significant source of atmospheric carbon due to drainage driven decomposition of peatland soils. Previous studies have made clear the direct link between drainage depth and peat carbon decomposition and significant reductions in the emission rate of CO₂ can be made by raising water tables nearer to the soil surface. However, the impact of such changes on palm fruit yield is not well understood and will be a critical consideration for plantation managers. Here we take advantage of very high frequency, long-term monitoring of canopy-scale carbon exchange at a mature oil palm plantation in Malaysian Borneo to investigate the relationship between drainage level and photosynthetic uptake and consider the confounding effects of light quality and atmospheric vapour pressure deficit. Canopy modelling from our dataset demonstrated that palms were exerting significantly greater stomatal control at deeper water table depths (WTD) and the optimum WTD for photosynthesis was found to be between 0.3 and 0.4 m below the soil surface. Raising WTD to this level, from the industry typical drainage level of 0.6 m, could increase photosynthetic uptake by 3.6 % and reduce soil surface emission of CO₂ by 11 %. Our study site further showed that despite being poorly drained compared to other planting blocks at the same plantation, monthly fruit bunch yield was, on average, 14 % greater. While these results are encouraging, and at least suggest that raising WTD closer to the soil surface to reduce emissions is unlikely to produce significant yield penalties, our results are limited to a single study site and more work is urgently needed to confirm these results at other plantations.

The use of R in photosynthesis research

R is one of the most commonly used analytical tools in the plant sciences. To identify key trends in general reported R use and patterns in photosynthesis research, we explored the frequency of R use in 2966 articles published in the 377 journals with 'photosynthesis' in the title from 2010 to 2019 using the Web of Science search. Solutions provided by each R package cited in the articles or online sources was recorded and classified. The percentage of research articles reporting R use increased linearly from 3.6% in 2010 to 12.5% in 2019. The three main categories of R package solutions were 'general statistical calculations and graph packages' (G); 'photosynthesis special-purpose packages' (S); and 'genetic and evolutionary packages' (E). The top five R packages cited were nlme (G), lme4 (G), multcomp (G), plantecophys (S), and ape (E). The increasing popularity of R use in photosynthesis research is due to its user-friendly and abundant open-source codes online for handling specific issues, particularly in fitting photosynthesis models. These findings are limited by the number of articles and online sources, but they reveal a significant increase in usage in photosynthesis research over the past decade and have a bright prospect in the future.

Does growing atmospheric CO2 explain increasing carbon sink in a boreal coniferous forest?

The terrestrial net ecosystem productivity (NEP) has increased during the past three decades, but the mechanisms responsible are still unclear. We analyzed 17 years (2001-2017) of eddy-covariance measurements of NEP, evapotranspiration (ET) and light and water use efficiency from a boreal coniferous forest in Southern Finland for trends and inter-annual variability (IAV). The forest was a mean annual carbon sink (252 [ ± 42] gC m-2a-1 ), and NEP increased at rate +6.4-7.0 gC m-2a-1 (or ca. +2.5% a-1 ) during the period. This was attributed to the increasing gross-primary productivity GPP and occurred without detectable change in ET. The start of annual carbon uptake period was advanced by 0.7 d a-1 , and increase in GPP and NEP outside the main growing season contributed ca. one-third and one-fourth of the annual trend, respectively. Meteorological factors were responsible for the IAV of fluxes but did not explain the long-term trends. The growing season GPP trend was strongest in ample light during the peak growing season. Using a multi-layer ecosystem model, we showed that direct CO2 fertilization effect diminishes when moving from leaf to ecosystem, and only 30-40% of the observed ecosystem GPP increase could be attributed to CO2 . The increasing trend in leaf-area index (LAI), stimulated by forest thinning in 2002, was the main driver of the enhanced GPP and NEP of the mid-rotation managed forest. It also compensated for the decrease of mean leaf stomatal conductance with increasing CO2 and LAI, explaining the apparent proportionality between observed GPP and CO2 trends. The results emphasize that attributing trends to their physical and physiological drivers is challenged by strong IAV, and uncertainty of LAI and species composition changes due to the dynamic flux footprint. The results enlighten the underlying mechanisms responsible for the increasing terrestrial carbon uptake in the boreal zone.

Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production

Sun-induced fluorescence in the far-red region (SIF) is increasingly used as a remote and proximal-sensing tool capable of tracking vegetation gross primary production (GPP). However, the use of SIF to probe changes in GPP is challenged during extreme climatic events, such as heatwaves. Here, we examined how the 2018 European heatwave (HW) affected the GPP-SIF relationship in evergreen broadleaved trees with a relatively invariant canopy structure. To do so, we combined canopy-scale SIF measurements, GPP estimated from an eddy covariance tower, and active pulse amplitude modulation fluorescence. The HW caused an inversion of the photosynthesis-fluorescence relationship at both the canopy and leaf scales. The highly nonlinear relationship was strongly shaped by nonphotochemical quenching (NPQ), that is, a dissipation mechanism to protect from the adverse effects of high light intensity. During the extreme heat stress, plants experienced a saturation of NPQ, causing a change in the allocation of energy dissipation pathways towards SIF. Our results show the complex modulation of the NPQ-SIF-GPP relationship at an extreme level of heat stress, which is not completely represented in state-of-the-art coupled radiative transfer and photosynthesis models.

The three major axes of terrestrial ecosystem function

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.

Seasonal trends in photosynthesis and leaf traits in scarlet oak

Understanding seasonal variation in photosynthesis is important for understanding and modeling plant productivity. Here, we used shotgun sampling to examine physiological, structural and spectral leaf traits of upper canopy, sun-exposed leaves in Quercus coccinea Münchh (scarlet oak) across the growing season in order to understand seasonal trends, explore the mechanisms underpinning physiological change and investigate the impact of extrapolating measurements from a single date to the whole season. We tested the hypothesis that photosynthetic rates and capacities would peak at the summer solstice, i.e., at the time of peak photoperiod. Contrary to expectations, our results reveal a late-season peak in both photosynthetic capacity and rate before the expected sharp decrease at the start of senescence. This late-season maximum occurred after the higher summer temperatures and vapor pressure deficit and was correlated with the recovery of leaf water content and increased stomatal conductance. We modeled photosynthesis at the top of the canopy and found that the simulated results closely tracked the maximum carboxylation capacity of Rubisco. For both photosynthetic capacity and modeled top-of-canopy photosynthesis, the maximum value was therefore not observed at the summer solstice. Rather, in each case, the measurements at and around the solstice were close to the overall seasonal mean, with values later in the season leading to deviations from the mean by up to 41 and 52%, respectively. Overall, we found that the expected Gaussian pattern of photosynthesis was not observed. We conclude that an understanding of species- and environment-specific changes in photosynthesis across the season is essential for correct estimation of seasonal photosynthetic capacity.

Imaging canopy temperature: shedding (thermal) light on ecosystem processes

Canopy temperature T_can is a key driver of plant function that emerges as a result of interacting biotic and abiotic processes and properties. However, understanding controls on T_can and forecasting canopy responses to weather extremes and climate change are difficult due to sparse measurements of T_can at appropriate spatial and temporal scales. Burgeoning observations of T_can from thermal cameras enable evaluation of energy budget theory and better understanding of how environmental controls, leaf traits and canopy structure influence temperature patterns. The canopy scale is relevant for connecting to remote sensing and testing biosphere model predictions. We anticipate that future breakthroughs in understanding of ecosystem responses to climate change will result from multiscale observations of T_can across a range of ecosystems.

Social hierarchy reveals thermoregulatory trade-offs in response to repeated stressors

Coping with stressors can require substantial energetic investment, and when resources are limited, such investment can preclude simultaneous expenditure on other biological processes. Among endotherms, energetic demands of thermoregulation can also be immense, yet our understanding of whether a stress response is sufficient to induce changes in thermoregulatory investment is limited. Using the black-capped chickadee as a model species, we tested a hypothesis that stress-induced changes in surface temperature (Ts), a well-documented phenomenon across vertebrates, stem from trade-offs between thermoregulation and stress responsiveness. Because social subordination is known to constrain access to resources in this species, we predicted that Ts and dry heat loss of social subordinates, but not social dominants, would fall under stress exposure at low ambient temperatures (Ta), and rise under stress exposure at high Ta, thus permitting a reduction in total energetic expenditure toward thermoregulation. To test our predictions, we exposed four social groups of chickadees to repeated stressors and control conditions across a Ta gradient (n=30 days/treatment/group), whilst remotely monitoring social interactions and Ts Supporting our hypothesis, we show that: (1) social subordinates (n=12), who fed less than social dominants and alone experienced stress-induced mass-loss, displayed significantly larger changes in Ts following stress exposure than social dominants (n=8), and (2) stress-induced changes in Ts significantly increased heat conservation at low Ta and heat dissipation at high Ta among social subordinates alone. These results suggest that chickadees adjust their thermoregulatory strategies during stress exposure when resources are limited by ecologically relevant processes.

Evaluation of particulate matter (PM10) emissions and its chemical characteristics during rotary harrowing operations at different forward speeds and levelling bar heights

Particulate matter (PM) is an air pollutant which poses a considerable risk to human health. The agricultural sector is responsible of the 15% of the total anthropogenic emissions of PM₁₀ (PM fraction with aerodynamic diameter below 10 μm) and soil preparation activities have been recognized as one of the main drivers of this contribution. The emission factors (EF) proposed by European environmental agency (EEA) for tilling operations are based on very few studies, none of which has been made in Italy. Moreover, few studies have considered the influence of operative parameters on PM₁₀ emissions during tilling. The aim of this work was to assess PM₁₀ emission and dispersion during rotary harrowing and to understand how operative parameters, such as forward speed and implement choice may affect PM release. A further objective was to assess the near field dispersion of PM₁₀ to address exposure risks. Emission factors (EFs) were determined during two different trials (T1 and T2). During T1, the effect of tractor speeds (0.6, 1.1 and 1.7 m s^-1) on PM₁₀ emissions was investigated, while in T2 a comparative essay was made to study the influence of levelling bar height on emissions. The average ground level downwind concentrations of PM₁₀ during harrowing operation was estimated through dispersion modelling. The observed PM₁₀ EFs for rotary harrowing were 8.9 ± 2.0 mg m^-2 and 9.5 ± 2.5 mg m^-2 on T1 and T2, respectively. The heavy metal content of soil-generated PM₁₀ was also assessed. In the generated PM, the elemental concentrations were higher than ones in soil. As, Cd and Ni concentration levels, determined in PM₁₀ near to the tractor path, were also high, being several times higher than the annual average regulatory threshold levels in ambient air, as defined by the European regulation.

The Added Value of Different Data Types for Calibrating and Testing a Hydrologic Model in a Small Catchment

This study investigated the added value of different data for calibrating a runoff model for small basins. The analysis was performed in the 66 ha Hydrological Open Air Laboratory, in Austria. An Hydrologiska Byråns Vattenbalansavdelning (HBV) type, spatially lumped hydrologic model was parameterized following two approaches. First, the model was calibrated using only runoff data. Second, a step-by-step approach was followed, where the modules of the model (snow, soil moisture, and runoff generation) were calibrated using measurements of runoff and model state variables and output fluxes. These measurements comprised laser-based measurements of precipitation, satellite and camera observations of snow, ultrasonic measurements of snow depth, eddy covariance measurements of evapotranspiration, time domain transmissometry-based soil moisture measurements, time-lapse photography of overland flow, and groundwater level measurements by piezometers. The two model parameterizations were evaluated on annual, seasonal, and daily time scales, in terms of how well they simulated snow, soil moisture, evapotranspiration, overland flow, storage change in the saturated zone, and runoff. Using the proposed step-by-step approach, the relative runoff volume errors in the calibration and validation periods were 0.00 and -0.01, the monthly Pearson correlation coefficients were 0.92 and 0.82, and the daily logarithmic Nash Sutcliffe efficiencies were 0.59 and 0.18, respectively. By using different sources of data besides runoff, the overall process consistency improved, compared to the case when only runoff was used for calibration. Soil moisture and evapotranspiration observations had the largest influence on simulated runoff, while the parameterization of the snow and runoff generation modules had a smaller influence.

Non-stomatal processes reduce gross primary productivity in temperate forest ecosystems during severe edaphic drought

Severe drought events are known to cause important reductions of gross primary productivity (GPP) in forest ecosystems. However, it is still unclear whether this reduction originates from stomatal closure (Stomatal Origin Limitation) and/or non-stomatal limitations (Non-SOL). In this study, we investigated the impact of edaphic drought in 2018 on GPP and its origin (SOL, NSOL) using a dataset of 10 European forest ecosystem flux towers. In all stations where GPP reductions were observed during the drought, these were largely explained by declines in the maximum apparent canopy scale carboxylation rate V_CMAX,APP (NSOL) when the soil relative extractable water content dropped below around 0.4. Concurrently, we found that the stomatal slope parameter (G₁, related to SOL) of the Medlyn et al. unified optimization model linking vegetation conductance and GPP remained relatively constant. These results strengthen the increasing evidence that NSOL should be included in stomatal conductance/photosynthesis models to faithfully simulate both GPP and water fluxes in forest ecosystems during severe drought. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Observed and modelled historical trends in the water-use efficiency of plants and ecosystems

Plant water-use efficiency (WUE, the carbon gained through photosynthesis per unit of water lost through transpiration) is a tracer of the plant physiological controls on the exchange of water and carbon dioxide between terrestrial ecosystems and the atmosphere. At the leaf level, rising CO₂ concentrations tend to increase carbon uptake (in the absence of other limitations) and to reduce stomatal conductance, both effects leading to an increase in leaf WUE. At the ecosystem level, indirect effects (e.g. increased leaf area index, soil water savings) may amplify or dampen the direct effect of CO₂ . Thus, the extent to which changes in leaf WUE translate to changes at the ecosystem scale remains unclear. The differences in the magnitude of increase in leaf versus ecosystem WUE as reported by several studies are much larger than would be expected with current understanding of tree physiology and scaling, indicating unresolved issues. Moreover, current vegetation models produce inconsistent and often unrealistic magnitudes and patterns of variability in leaf and ecosystem WUE, calling for a better assessment of the underlying approaches. Here, we review the causes of variations in observed and modelled historical trends in WUE over the continuum of scales from leaf to ecosystem, including methodological issues, with the aim of elucidating the reasons for discrepancies observed within and across spatial scales. We emphasize that even though physiological responses to changing environmental drivers should be interpreted differently depending on the observational scale, there are large uncertainties in each data set which are often underestimated. Assumptions made by the vegetation models about the main processes influencing WUE strongly impact the modelled historical trends. We provide recommendations for improving long-term observation-based estimates of WUE that will better inform the representation of WUE in vegetation models.