Search

The importance of phosphorus (P) in regulating ecosystem responses to climate change has fostered P-cycle implementation in land surface models, but their CO 2 effects predictions have not been evaluated against measurements. Here, we perform a data-driven model evaluation where simulations of eight widely used P-enabled models were confronted with observations from a long-term free-air CO 2 enrichment experiment in a mature, P-limited Eucalyptus forest. We show that most models predicted the correct sign and magnitude of the CO 2 effect on ecosystem carbon (C) sequestration, but they generally overestimated the effects on plant C uptake and growth. We identify leaf-to-canopy scaling of photosynthesis, plant tissue stoichiometry, plant belowground C allocation, and the subsequent consequences for plant-microbial interaction as key areas in which models of ecosystem C-P interaction can be improved. Together, this data-model intercomparison reveals data-driven insights into the performance and functionality of P-enabled models and adds to the existing evidence that the global CO 2 -driven carbon sink is overestimated by models.

The capacity for terrestrial ecosystems to sequester additional carbon (C) with rising CO 2 concentrations depends on soil nutrient availability 1,2 . Previous evidence suggested that mature forests growing on phosphorus (P)-deprived soils had limited capacity to sequester extra biomass under elevated CO 2 (refs. 3-6 ), but uncertainty about ecosystem P cycling and its CO 2 response represents a crucial bottleneck for mechanistic prediction of the land C sink under climate change 7 . Here, by compiling the first comprehensive P budget for a P-limited mature forest exposed to elevated CO 2 , we show a high likelihood that P captured by soil microorganisms constrains ecosystem P recycling and availability for plant uptake. Trees used P efficiently, but microbial pre-emption of mineralized soil P seemed to limit the capacity of trees for increased P uptake and assimilation under elevated CO 2 and, therefore, their capacity to sequester extra C. Plant strategies to stimulate microbial P cycling and plant P uptake, such as increasing rhizosphere C release to soil, will probably be necessary for P-limited forests to increase C capture into new biomass. Our results identify the key mechanisms by which P availability limits CO 2 fertilization of tree growth and will guide the development of Earth system models to predict future long-term C storage., (© 2024. Crown.)

Elevated atmospheric CO 2 (eCO 2 ) influences the carbon assimilation rate and stomatal conductance of plants, thereby affecting the global cycles of carbon and water. Yet, the detection of these physiological effects of eCO 2 in observational data remains challenging, because natural variations and confounding factors (e.g., warming) can overshadow the eCO 2 effects in observational data of real-world ecosystems. In this study, we aim at developing a method to detect the emergence of the physiological CO 2 effects on various variables related to carbon and water fluxes. We mimic the observational setting in ecosystems using a comprehensive process-based land surface model QUINCY to simulate the leaf-level effects of increasing atmospheric CO 2 concentrations and their century-long propagation through the terrestrial carbon and water cycles across different climate regimes and biomes. We then develop a statistical method based on the signal-to-noise ratio to detect the emergence of the eCO 2 effects. The eCO 2 effect on gross primary productivity (GPP) emerges at relatively low CO 2 increase (∆[CO 2 ] ~ 20 ppm) where the leaf area index is relatively high. Compared to GPP, the eCO 2 effect causing reduced transpiration water flux (normalized to leaf area) emerges only at relatively high CO 2 increase (∆[CO 2 ] >> 40 ppm), due to the high sensitivity to climate variability and thus lower signal-to-noise ratio. In general, the response to eCO 2 is detectable earlier for variables related to the carbon cycle than the water cycle, when plant productivity is not limited by climatic constraints, and stronger in forest-dominated rather than in grass-dominated ecosystems. Our results provide a step toward when and where we expect to detect physiological CO 2 effects in in-situ flux measurements, how to detect them and encourage future efforts to improve the understanding and quantification of these effects in observations of terrestrial carbon and water dynamics., (© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Mesophyll conductance (g m ) limits photosynthesis by restricting CO 2 diffusion between the substomatal cavities and chloroplasts. Although it is known that g m is determined by both leaf anatomical and biochemical traits, their relative contribution across plant functional types (PFTs) is still unclear. We compiled a dataset of g m measurements and concomitant leaf traits in unstressed plants comprising 563 studies and 617 species from all major PFTs. We investigated to what extent g m limits photosynthesis across PFTs, how g m relates to structural, anatomical, biochemical, and physiological leaf properties, and whether these relationships differ among PFTs. We found that g m imposes a significant limitation to photosynthesis in all C 3 PFTs, ranging from 10-30% in most herbaceous annuals to 25-50% in woody evergreens. Anatomical leaf traits explained a significant proportion of the variation in g m (R 2  > 0.3) in all PFTs except annual herbs, in which g m is more strongly related to biochemical factors associated with leaf nitrogen and potassium content. Our results underline the need to elucidate mechanisms underlying the global variability of g m . We emphasise the underestimated potential of g m for improving photosynthesis in crops and identify modifications in leaf biochemistry as the most promising pathway for increasing g m in these species., (© 2022 The Authors. New Phytologist © 2022 New Phytologist Foundation.)

The observed global net land carbon sink is captured by current land models. All models agree that atmospheric CO 2 and nitrogen deposition driven gains in carbon stocks are partially offset by climate and land-use and land-cover change (LULCC) losses. However, there is a lack of consensus in the partitioning of the sink between vegetation and soil, where models do not even agree on the direction of change in carbon stocks over the past 60 years. This uncertainty is driven by plant productivity, allocation, and turnover response to atmospheric CO 2 (and to a smaller extent to LULCC), and the response of soil to LULCC (and to a lesser extent climate). Overall, differences in turnover explain ~70% of model spread in both vegetation and soil carbon changes. Further analysis of internal plant and soil (individual pools) cycling is needed to reduce uncertainty in the controlling processes behind the global land carbon sink., (© 2022. The Author(s).)

In 2018, central and northern parts of Europe experienced heat and drought conditions over many months from spring to autumn, strongly affecting both natural ecosystems and crops. Besides their impact on nature and society, events like this can be used to study the impact of climate variations on the terrestrial carbon cycle, which is an important determinant of the future climate trajectory. Here, variations in the regional net ecosystem exchange (NEE) of CO 2 between terrestrial ecosystems and the atmosphere were quantified from measurements of atmospheric CO 2 mole fractions. Over Europe, several observational records have been maintained since at least 1999, giving us the opportunity to assess the 2018 anomaly in the context of at least two decades of variations, including the strong climate anomaly in 2003. In addition to an atmospheric inversion with temporally explicitly estimated anomalies, we use an inversion based on empirical statistical relations between anomalies in the local NEE and anomalies in local climate conditions. For our analysis period 1999-2018, we find that higher-than-usual NEE in hot and dry summers may tend to arise in Central Europe from enhanced ecosystem respiration due to the elevated temperatures, and in Southern Europe from reduced photosynthesis due to the reduced water availability. Despite concerns in the literature, the level of agreement between regression-based NEE anomalies and temporally explicitly estimated anomalies indicates that the atmospheric CO 2 measurements from the relatively dense European station network do provide information about the year-to-year variations of Europe's carbon sources and sinks, at least in summer. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

In Europe, three widespread extreme summer drought and heat (DH) events have occurred in 2003, 2010 and 2018. These events were comparable in magnitude but varied in their geographical distribution and biomes affected. In this study, we perform a comparative analysis of the impact of the DH events on ecosystem CO 2 fluxes over Europe based on an ensemble of 11 dynamic global vegetation models (DGVMs), and the observation-based FLUXCOM product. We find that all DH events were associated with decreases in net ecosystem productivity (NEP), but the gross summer flux anomalies differ between DGVMs and FLUXCOM. At the annual scale, FLUXCOM and DGVMs indicate close to neutral or above-average land CO 2 uptake in DH2003 and DH2018, due to increased productivity in spring and reduced respiration in autumn and winter compensating for less photosynthetic uptake in summer. Most DGVMs estimate lower gross primary production (GPP) sensitivity to soil moisture during extreme summers than FLUXCOM. Finally, we show that the different impacts of the DH events at continental-scale GPP are in part related to differences in vegetation composition of the regions affected and to regional compensating or offsetting effects from climate anomalies beyond the DH centres. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Phosphorus (P) is an essential macro-nutrient required for plant metabolism and growth. Low P availability could potentially limit plant responses to elevated carbon dioxide (eCO 2 ), but consensus has yet to be reached on the extent of this limitation. Here, based on data from experiments that manipulated both CO 2 and P for young individuals of woody and non-woody species, we present a meta-analysis of P limitation impacts on plant growth, physiological, and morphological response to eCO 2 . We show that low P availability attenuated plant photosynthetic response to eCO 2 by approximately one-quarter, leading to a reduced, but still positive photosynthetic response to eCO 2 compared to those under high P availability. Furthermore, low P limited plant aboveground, belowground, and total biomass responses to eCO 2 , by 14.7%, 14.3%, and 12.4%, respectively, equivalent to an approximate halving of the eCO 2 responses observed under high P availability. In comparison, low P availability did not significantly alter the eCO 2 -induced changes in plant tissue nutrient concentration, suggesting tissue nutrient flexibility is an important mechanism allowing biomass response to eCO 2 under low P availability. Low P significantly reduced the eCO 2 -induced increase in leaf area by 14.3%, mirroring the aboveground biomass response, but low P did not affect the eCO 2 -induced increase in root length. Woody plants exhibited stronger attenuation effect of low P on aboveground biomass response to eCO 2 than non-woody plants, while plants with different mycorrhizal associations showed similar responses to low P and eCO 2 interaction. This meta-analysis highlights crucial data gaps in capturing plant responses to eCO 2 and low P availability. Field-based experiments with longer-term exposure of both CO 2 and P manipulations are critically needed to provide ecosystem-scale understanding. Taken together, our results provide a quantitative baseline to constrain model-based hypotheses of plant responses to eCO 2 under P limitation, thereby improving projections of future global change impacts., (© 2020 John Wiley & Sons Ltd.)

Understanding changes in terrestrial carbon balance is important to improve our knowledge of the regional carbon cycle and climate change. However, evaluating regional changes in the terrestrial carbon balance is challenging due to the lack of surface flux measurements. This study reveals that the terrestrial carbon uptake over the Republic of Korea has been enhanced from 1999 to 2017 by analyzing long-term atmospheric CO 2 concentration measurements at the Anmyeondo Station (36.53°N, 126.32°E) located in the western coast. The influence of terrestrial carbon flux on atmospheric CO 2 concentrations (ΔCO 2 ) is estimated from the difference of CO 2 concentrations that were influenced by the land sector (through easterly winds) and the Yellow Sea sector (through westerly winds). We find a significant trend in ΔCO 2 of -4.75 ppm per decade (p < .05) during the vegetation growing season (May through October), suggesting that the regional terrestrial carbon uptake has increased relative to the surrounding ocean areas. Combined analysis with satellite measured normalized difference vegetation index and gross primary production shows that the enhanced carbon uptake is associated with significant nationwide increases in vegetation and its production. Process-based terrestrial model and inverse model simulations estimate that regional terrestrial carbon uptake increases by up to 18.9 and 8.0 Tg C for the study period, accounting for 13.4% and 5.7% of the average annual domestic carbon emissions, respectively. Atmospheric chemical transport model simulations indicate that the enhanced terrestrial carbon sink is the primary reason for the observed ΔCO 2 trend rather than anthropogenic emissions and atmospheric circulation changes. Our results highlight the fact that atmospheric CO 2 measurements could open up the possibility of detecting regional changes in the terrestrial carbon cycle even where anthropogenic emissions are not negligible., (© 2020 John Wiley & Sons Ltd.)

Atmospheric carbon dioxide enrichment (eCO 2 ) can enhance plant carbon uptake and growth 1-5 , thereby providing an important negative feedback to climate change by slowing the rate of increase of the atmospheric CO 2 concentration 6 . Although evidence gathered from young aggrading forests has generally indicated a strong CO 2 fertilization effect on biomass growth 3-5 , it is unclear whether mature forests respond to eCO 2 in a similar way. In mature trees and forest stands 7-10 , photosynthetic uptake has been found to increase under eCO 2 without any apparent accompanying growth response, leaving the fate of additional carbon fixed under eCO 2 unclear 4,5,7-11 . Here using data from the first ecosystem-scale Free-Air CO 2 Enrichment (FACE) experiment in a mature forest, we constructed a comprehensive ecosystem carbon budget to track the fate of carbon as the forest responded to four years of eCO 2 exposure. We show that, although the eCO 2 treatment of +150 parts per million (+38 per cent) above ambient levels induced a 12 per cent (+247 grams of carbon per square metre per year) increase in carbon uptake through gross primary production, this additional carbon uptake did not lead to increased carbon sequestration at the ecosystem level. Instead, the majority of the extra carbon was emitted back into the atmosphere via several respiratory fluxes, with increased soil respiration alone accounting for half of the total uptake surplus. Our results call into question the predominant thinking that the capacity of forests to act as carbon sinks will be generally enhanced under eCO 2 , and challenge the efficacy of climate mitigation strategies that rely on ubiquitous CO 2 fertilization as a driver of increased carbon sinks in global forests.

Mesophyll conductance (g m ) is known to affect plant photosynthesis. However, g m is rarely explicitly considered in land surface models (LSMs), with the consequence that its role in ecosystem and large-scale carbon and water fluxes is poorly understood. In particular, the different magnitudes of g m across plant functional types (PFTs) are expected to cause spatially divergent vegetation responses to elevated CO 2 concentrations. Here, an extensive literature compilation of g m across major vegetation types is used to parameterize an empirical model of g m in the LSM JSBACH and to adjust photosynthetic parameters based on simulated A n  - C i curves. We demonstrate that an explicit representation of g m changes the response of photosynthesis to environmental factors, which cannot be entirely compensated by adjusting photosynthetic parameters. These altered responses lead to changes in the photosynthetic sensitivity to atmospheric CO 2 concentrations which depend both on the magnitude of g m and the climatic conditions, particularly temperature. We then conducted simulations under ambient and elevated (ambient + 200 μmol/mol) CO 2 concentrations for contrasting ecosystems and for historical and anticipated future climate conditions (representative concentration pathways; RCPs) globally. The g m -explicit simulations using the RCP8.5 scenario resulted in significantly higher increases in gross primary productivity (GPP) in high latitudes (+10% to + 25%), intermediate increases in temperate regions (+5% to + 15%), and slightly lower to moderately higher responses in tropical regions (-2% to +5%), which summed up to moderate GPP increases globally. Similar patterns were found for transpiration, but with a lower magnitude. Our results suggest that the effect of an explicit representation of g m is most important for simulated carbon and water fluxes in the boreal zone, where a cold climate coincides with evergreen vegetation., (© 2019 The Authors Global Change Biology Published by John Wiley & Sons Ltd.)

Increasing atmospheric CO 2 stimulates photosynthesis which can increase net primary production (NPP), but at longer timescales may not necessarily increase plant biomass. Here we analyse the four decade-long CO 2 -enrichment experiments in woody ecosystems that measured total NPP and biomass. CO 2 enrichment increased biomass increment by 1.05 ± 0.26 kg C m -2 over a full decade, a 29.1 ± 11.7% stimulation of biomass gain in these early-secondary-succession temperate ecosystems. This response is predictable by combining the CO 2 response of NPP (0.16 ± 0.03 kg C m -2  y -1 ) and the CO 2 -independent, linear slope between biomass increment and cumulative NPP (0.55 ± 0.17). An ensemble of terrestrial ecosystem models fail to predict both terms correctly. Allocation to wood was a driver of across-site, and across-model, response variability and together with CO 2 -independence of biomass retention highlights the value of understanding drivers of wood allocation under ambient conditions to correctly interpret and predict CO 2 responses.

Interannual variations in the large-scale net ecosystem exchange (NEE) of CO 2 between the terrestrial biosphere and the atmosphere were estimated for 1957-2017 from sustained measurements of atmospheric CO 2 mixing ratios. As the observations are sparse in the early decades, available records were combined into a 'quasi-homogeneous' dataset based on similarity in their signals, to minimize spurious variations from beginning or ending data records. During El Niño events, CO 2 is anomalously released from the tropical band, and a few months later also in the northern extratropical band. This behaviour can approximately be represented by a linear relationship of the NEE anomalies and local air temperature anomalies, with sensitivity coefficients depending on geographical location and season. The apparent climate sensitivity of global total NEE against variations in pan-tropically averaged annual air temperature slowly changed over time during the 1957-2017 period, first increasing (though less strongly than in previous studies) but then decreasing again. However, only part of this change can be attributed to actual changes in local physiological or ecosystem processes, the rest probably arising from shifts in the geographical area of dominating temperature variations.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'., (© 2018 The Authors.)

Sun-induced fluorescence (SIF) in the far-red region provides a new noninvasive measurement approach that has the potential to quantify dynamic changes in light-use efficiency and gross primary production (GPP). However, the mechanistic link between GPP and SIF is not completely understood. We analyzed the structural and functional factors controlling the emission of SIF at 760 nm (F 760 ) in a Mediterranean grassland manipulated with nutrient addition of nitrogen (N), phosphorous (P) or nitrogen-phosphorous (NP). Using the soil-canopy observation of photosynthesis and energy (SCOPE) model, we investigated how nutrient-induced changes in canopy structure (i.e. changes in plant forms abundance that influence leaf inclination distribution function, LIDF) and functional traits (e.g. N content in dry mass of leaves, N%, Chlorophyll a+b concentration (Cab) and maximum carboxylation capacity (V cmax )) affected the observed linear relationship between F 760 and GPP. We conclude that the addition of nutrients imposed a change in the abundance of different plant forms and biochemistry of the canopy that controls F 760 . Changes in canopy structure mainly control the GPP-F 760 relationship, with a secondary effect of Cab and V cmax . In order to exploit F 760 data to model GPP at the global/regional scale, canopy structural variability, biodiversity and functional traits are important factors that have to be considered., (© 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.)

Ecosystem water-use efficiency (WUE) is an important metric linking the global land carbon and water cycles. Eddy covariance-based estimates of WUE in temperate/boreal forests have recently been found to show a strong and unexpected increase over the 1992-2010 period, which has been attributed to the effects of rising atmospheric CO 2 concentrations on plant physiology. To test this hypothesis, we forced the observed trend in the process-based land surface model JSBACH by increasing the sensitivity of stomatal conductance (g s ) to atmospheric CO 2 concentration. We compared the simulated continental discharge, evapotranspiration (ET), and the seasonal CO 2 exchange with observations across the extratropical northern hemisphere. The increased simulated WUE led to substantial changes in surface hydrology at the continental scale, including a significant decrease in ET and a significant increase in continental runoff, both of which are inconsistent with large-scale observations. The simulated seasonal amplitude of atmospheric CO 2 decreased over time, in contrast to the observed upward trend across ground-based measurement sites. Our results provide strong indications that the recent, large-scale WUE trend is considerably smaller than that estimated for these forest ecosystems. They emphasize the decreasing CO 2 sensitivity of WUE with increasing scale, which affects the physiological interpretation of changes in ecosystem WUE., (© 2016 Max Planck Institute for Biogeochemistry New Phytologist © 2016 New Phytologist Trust.)

Large interannual variations in the measured growth rate of atmospheric carbon dioxide (CO 2 ) originate primarily from fluctuations in carbon uptake by land ecosystems. It remains uncertain, however, to what extent temperature and water availability control the carbon balance of land ecosystems across spatial and temporal scales. Here we use empirical models based on eddy covariance data and process-based models to investigate the effect of changes in temperature and water availability on gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) at local and global scales. We find that water availability is the dominant driver of the local interannual variability in GPP and TER. To a lesser extent this is true also for NEE at the local scale, but when integrated globally, temporal NEE variability is mostly driven by temperature fluctuations. We suggest that this apparent paradox can be explained by two compensatory water effects. Temporal water-driven GPP and TER variations compensate locally, dampening water-driven NEE variability. Spatial water availability anomalies also compensate, leaving a dominant temperature signal in the year-to-year fluctuations of the land carbon sink. These findings help to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance. Our study indicates that spatial climate covariation drives the global carbon cycle response.

The response of terrestrial ecosystems to rising atmospheric CO2 concentration (Ca ), particularly under nutrient-limited conditions, is a major uncertainty in Earth System models. The Eucalyptus Free-Air CO2 Enrichment (EucFACE) experiment, recently established in a nutrient- and water-limited woodland presents a unique opportunity to address this uncertainty, but can best do so if key model uncertainties have been identified in advance. We applied seven vegetation models, which have previously been comprehensively assessed against earlier forest FACE experiments, to simulate a priori possible outcomes from EucFACE. Our goals were to provide quantitative projections against which to evaluate data as they are collected, and to identify key measurements that should be made in the experiment to allow discrimination among alternative model assumptions in a postexperiment model intercomparison. Simulated responses of annual net primary productivity (NPP) to elevated Ca ranged from 0.5 to 25% across models. The simulated reduction of NPP during a low-rainfall year also varied widely, from 24 to 70%. Key processes where assumptions caused disagreement among models included nutrient limitations to growth; feedbacks to nutrient uptake; autotrophic respiration; and the impact of low soil moisture availability on plant processes. Knowledge of the causes of variation among models is now guiding data collection in the experiment, with the expectation that the experimental data can optimally inform future model improvements., (© 2016 John Wiley & Sons Ltd.)

Atmospheric monitoring of high northern latitudes (above 40°N) has shown an enhanced seasonal cycle of carbon dioxide (CO2) since the 1960s, but the underlying mechanisms are not yet fully understood. The much stronger increase in high latitudes relative to low ones suggests that northern ecosystems are experiencing large changes in vegetation and carbon cycle dynamics. We found that the latitudinal gradient of the increasing CO2 amplitude is mainly driven by positive trends in photosynthetic carbon uptake caused by recent climate change and mediated by changing vegetation cover in northern ecosystems. Our results underscore the importance of climate-vegetation-carbon cycle feedbacks at high latitudes; moreover, they indicate that in recent decades, photosynthetic carbon uptake has reacted much more strongly to warming than have carbon release processes., (Copyright © 2016, American Association for the Advancement of Science.)

The first generation of forest free-air CO2 enrichment (FACE) experiments has successfully provided deeper understanding about how forests respond to an increasing CO2 concentration in the atmosphere. Located in aggrading stands in the temperate zone, they have provided a strong foundation for testing critical assumptions in terrestrial biosphere models that are being used to project future interactions between forest productivity and the atmosphere, despite the limited inference space of these experiments with regards to the range of global ecosystems. Now, a new generation of FACE experiments in mature forests in different biomes and over a wide range of climate space and biodiversity will significantly expand the inference space. These new experiments are: EucFACE in a mature Eucalyptus stand on highly weathered soil in subtropical Australia; AmazonFACE in a highly diverse, primary rainforest in Brazil; BIFoR-FACE in a 150-yr-old deciduous woodland stand in central England; and SwedFACE proposed in a hemiboreal, Pinus sylvestris stand in Sweden. We now have a unique opportunity to initiate a model-data interaction as an integral part of experimental design and to address a set of cross-site science questions on topics including responses of mature forests; interactions with temperature, water stress, and phosphorus limitation; and the influence of biodiversity., (© UT-Battelle, LLC New Phytologist © 2015 New Phytologist Trust.)

The temperature dependence of the reaction kinetics of the Rubisco enzyme implies that, at the level of a chloroplast, the response of photosynthesis to rising atmospheric CO2 concentration (Ca ) will increase with increasing air temperature. Vegetation models incorporating this interaction predict that the response of net primary productivity (NPP) to elevated CO2 (eCa ) will increase with rising temperature and will be substantially larger in warm tropical forests than in cold boreal forests. We tested these model predictions against evidence from eCa experiments by carrying out two meta-analyses. Firstly, we tested for an interaction effect on growth responses in factorial eCa  × temperature experiments. This analysis showed a positive, but nonsignificant interaction effect (95% CI for above-ground biomass response = -0.8, 18.0%) between eCa and temperature. Secondly, we tested field-based eCa experiments on woody plants across the globe for a relationship between the eCa effect on plant biomass and mean annual temperature (MAT). This second analysis showed a positive but nonsignificant correlation between the eCa response and MAT. The magnitude of the interactions between CO2 and temperature found in both meta-analyses were consistent with model predictions, even though both analyses gave nonsignificant results. Thus, we conclude that it is not possible to distinguish between the competing hypotheses of no interaction vs. an interaction based on Rubisco kinetics from the available experimental database. Experiments in a wider range of temperature zones are required. Until such experimental data are available, model predictions should aim to incorporate uncertainty about this interaction., (© 2015 John Wiley & Sons Ltd.)

The growth rate of atmospheric carbon dioxide (CO2) concentrations since industrialization is characterized by large interannual variability, mostly resulting from variability in CO2 uptake by terrestrial ecosystems (typically termed carbon sink). However, the contributions of regional ecosystems to that variability are not well known. Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, we show that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions. Whereas the mean sink is dominated by highly productive lands (mainly tropical forests), the trend and interannual variability of the sink are dominated by semi-arid ecosystems whose carbon balance is strongly associated with circulation-driven variations in both precipitation and temperature., (Copyright © 2015, American Association for the Advancement of Science.)

Elevated atmospheric CO2 concentration (eCO2) has the potential to increase vegetation carbon storage if increased net primary production causes increased long-lived biomass. Model predictions of eCO2 effects on vegetation carbon storage depend on how allocation and turnover processes are represented. We used data from two temperate forest free-air CO2 enrichment (FACE) experiments to evaluate representations of allocation and turnover in 11 ecosystem models. Observed eCO2 effects on allocation were dynamic. Allocation schemes based on functional relationships among biomass fractions that vary with resource availability were best able to capture the general features of the observations. Allocation schemes based on constant fractions or resource limitations performed less well, with some models having unintended outcomes. Few models represent turnover processes mechanistically and there was wide variation in predictions of tissue lifespan. Consequently, models did not perform well at predicting eCO2 effects on vegetation carbon storage. Our recommendations to reduce uncertainty include: use of allocation schemes constrained by biomass fractions; careful testing of allocation schemes; and synthesis of allocation and turnover data in terms of model parameters. Data from intensively studied ecosystem manipulation experiments are invaluable for constraining models and we recommend that such experiments should attempt to fully quantify carbon, water and nutrient budgets., (© 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.)

We analysed the responses of 11 ecosystem models to elevated atmospheric [CO2 ] (eCO2 ) at two temperate forest ecosystems (Duke and Oak Ridge National Laboratory (ORNL) Free-Air CO2 Enrichment (FACE) experiments) to test alternative representations of carbon (C)-nitrogen (N) cycle processes. We decomposed the model responses into component processes affecting the response to eCO2 and confronted these with observations from the FACE experiments. Most of the models reproduced the observed initial enhancement of net primary production (NPP) at both sites, but none was able to simulate both the sustained 10-yr enhancement at Duke and the declining response at ORNL: models generally showed signs of progressive N limitation as a result of lower than observed plant N uptake. Nonetheless, many models showed qualitative agreement with observed component processes. The results suggest that improved representation of above-ground-below-ground interactions and better constraints on plant stoichiometry are important for a predictive understanding of eCO2 effects. Improved accuracy of soil organic matter inventories is pivotal to reduce uncertainty in the observed C-N budgets. The two FACE experiments are insufficient to fully constrain terrestrial responses to eCO2 , given the complexity of factors leading to the observed diverging trends, and the consequential inability of the models to explain these trends. Nevertheless, the ecosystem models were able to capture important features of the experiments, lending some support to their projections., (© 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.)

The purpose of this study was to evaluate 10 process-based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux-tower-based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO2 sensitivity of NPP is compared to the results from four Free-Air CO2 Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein et al. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 ± 15 Pg C yr(-1) ) than JU11 (118 ± 6 Pg C yr(-1) ). In response to rising atmospheric CO2 concentration, modeled NPP increases on average by 16% (5-20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO2 than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr(-1) is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr(-1) ). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980-2009. Both model-to-model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is -3.0 ± 1.5 Pg C yr(-1) °C(-1) , within the uncertainty of what derived from RLS (-3.9 ± 1.1 Pg C yr(-1) °C(-1) ). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO2 and climate, the agreement between modeled and observation-based GPP and NBP can be fortuitous. Carbon-nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models., (© 2013 Blackwell Publishing Ltd.)

Predicted responses of transpiration to elevated atmospheric CO2 concentration (eCO2 ) are highly variable amongst process-based models. To better understand and constrain this variability amongst models, we conducted an intercomparison of 11 ecosystem models applied to data from two forest free-air CO2 enrichment (FACE) experiments at Duke University and Oak Ridge National Laboratory. We analysed model structures to identify the key underlying assumptions causing differences in model predictions of transpiration and canopy water use efficiency. We then compared the models against data to identify model assumptions that are incorrect or are large sources of uncertainty. We found that model-to-model and model-to-observations differences resulted from four key sets of assumptions, namely (i) the nature of the stomatal response to elevated CO2 (coupling between photosynthesis and stomata was supported by the data); (ii) the roles of the leaf and atmospheric boundary layer (models which assumed multiple conductance terms in series predicted more decoupled fluxes than observed at the broadleaf site); (iii) the treatment of canopy interception (large intermodel variability, 2-15%); and (iv) the impact of soil moisture stress (process uncertainty in how models limit carbon and water fluxes during moisture stress). Overall, model predictions of the CO2 effect on WUE were reasonable (intermodel μ = approximately 28% ± 10%) compared to the observations (μ = approximately 30% ± 13%) at the well-coupled coniferous site (Duke), but poor (intermodel μ = approximately 24% ± 6%; observations μ = approximately 38% ± 7%) at the broadleaf site (Oak Ridge). The study yields a framework for analysing and interpreting model predictions of transpiration responses to eCO2 , and highlights key improvements to these types of models., (© 2013 Blackwell Publishing Ltd.)

The significant worldwide increase in observed river runoff has been tentatively attributed to the stomatal "antitranspirant" response of plants to rising atmospheric CO(2) [Gedney N, Cox PM, Betts RA, Boucher O, Huntingford C, Stott PA (2006) Nature 439: 835-838]. However, CO(2) also is a plant fertilizer. When allowing for the increase in foliage area that results from increasing atmospheric CO(2) levels in a global vegetation model, we find a decrease in global runoff from 1901 to 1999. This finding highlights the importance of vegetation structure feedback on the water balance of the land surface. Therefore, the elevated atmospheric CO(2) concentration does not explain the estimated increase in global runoff over the last century. In contrast, we find that changes in mean climate, as well as its variability, do contribute to the global runoff increase. Using historic land-use data, we show that land-use change plays an additional important role in controlling regional runoff values, particularly in the tropics. Land-use change has been strongest in tropical regions, and its contribution is substantially larger than that of climate change. On average, land-use change has increased global runoff by 0.08 mm/year(2) and accounts for approximately 50% of the reconstructed global runoff trend over the last century. Therefore, we emphasize the importance of land-cover change in forecasting future freshwater availability and climate.