ORCID Profile
0000-0002-3399-9098
Current Organisation
University of Bristol
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Global Change Biology | Terrestrial Ecology | Ecological Impacts of Climate Change | Other Biological Sciences | Ecological Applications | Carbon Sequestration Science | Climate Change Processes
ANZSRC Socio-Economic Objective (SEO)
Expanding Knowledge in the Environmental Sciences | Mountain and High Country Soils | Ecosystem Adaptation to Climate Change | Climate Change Models | Native Forests |
Related Links
Publications
Comprehensive ecosystem model‐data synthesis using multiple data sets at two temperate forest free‐air CO2 enrichment experiments: Model performance at ambient CO2 concentration
Publisher: American Geophysical Union (AGU)
Date: 05-2014
DOI: 10.1002/2013JG002553
Implementation of an optimal stomatal conductance scheme in the Australian Community Climate Earth Systems Simulator (ACCESS1.3b)
Publisher: Copernicus GmbH
Date: 08-12-2015
Abstract: Abstract. We implement a new stomatal conductance scheme, based on the optimality approach, within the Community Atmosphere Biosphere Land Exchange (CABLEv2.0.1) land surface model. Coupled land–atmosphere simulations are then performed using CABLEv2.0.1 within the Australian Community Climate and Earth Systems Simulator (ACCESSv1.3b) with prescribed sea surface temperatures. As in most land surface models, the default stomatal conductance scheme only accounts for differences in model parameters in relation to the photosynthetic pathway but not in relation to plant functional types. The new scheme allows model parameters to vary by plant functional type, based on a global synthesis of observations of stomatal conductance under different climate regimes over a wide range of species. We show that the new scheme reduces the latent heat flux from the land surface over the boreal forests during the Northern Hemisphere summer by 0.5–1.0 mm day−1. This leads to warmer daily maximum and minimum temperatures by up to 1.0 °C and warmer extreme maximum temperatures by up to 1.5 °C. These changes generally improve the climate model's climatology of warm extremes and improve existing biases by 10–20 %. The bias in minimum temperatures is however degraded but, overall, this is outweighed by the improvement in maximum temperatures as there is a net improvement in the diurnal temperature range in this region. In other regions such as parts of South and North America where ACCESSv1.3b has known large positive biases in both maximum and minimum temperatures (~ 5 to 10 °C), the new scheme degrades this bias by up to 1 °C. We conclude that, although several large biases remain in ACCESSv1.3b for temperature extremes, the improvements in the global climate model over large parts of the boreal forests during the Northern Hemisphere summer which result from the new stomatal scheme, constrained by a global synthesis of experimental data, provide a valuable advance in the long-term development of the ACCESS modelling system.
Applying the Concept of Ecohydrological Equilibrium to Predict Steady State Leaf Area Index
Publisher: American Geophysical Union (AGU)
Date: 08-2018
DOI: 10.1029/2017MS001169
How do groundwater dynamics influence heatwaves in southeast Australia?
Publisher: Elsevier BV
Date: 09-2022
Using models to guide field experiments: a priori predictions for the CO 2 response of a nutrient‐ and water‐limited native Eucalypt woodland
Publisher: Wiley
Date: 09-05-2016
DOI: 10.1111/GCB.13268
Abstract: 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.
Opening Pandora's box: reducing global circulation model uncertainty in Australian simulations of the carbon cycle
Publisher: Copernicus GmbH
Date: 05-05-2023
Abstract: Abstract. Climate projections from global circulation models (GCMs), part of the Coupled Model Intercomparison Project 6 (CMIP6), are often employed to study the impact of future climate on ecosystems. However, especially at regional scales, climate projections display large biases in key forcing variables such as temperature and precipitation. These biases have been identified as a major source of uncertainty in carbon cycle projections, h ering predictive capacity. In this study, we open the proverbial Pandora's box and peer under the lid of strategies to tackle climate model ensemble uncertainty. We employ a dynamic global vegetation model (LPJ-GUESS) and force it with raw output from CMIP6 to assess the uncertainty associated with the choice of climate forcing. We then test different methods to either bias-correct or calculate ensemble averages over the original forcing data to reduce the climate-driven uncertainty in the regional projection of the Australian carbon cycle. We find that all bias correction methods reduce the bias of continental averages of steady-state carbon variables. Bias correction can improve model carbon outputs, but carbon pools are insensitive to the type of bias correction method applied for both in idual GCMs and the arithmetic ensemble average across all corrected models. None of the bias correction methods consistently improve the change in simulated carbon over time compared to the target dataset, highlighting the need to account for temporal properties in correction or ensemble-averaging methods. Multivariate bias correction methods tend to reduce the uncertainty more than univariate approaches, although the overall magnitude is similar. Even after correcting the bias in the meteorological forcing dataset, the simulated vegetation distribution presents different patterns when different GCMs are used to drive LPJ-GUESS. Additionally, we found that both the weighted ensemble-averaging and random forest approach reduce the bias in total ecosystem carbon to almost zero, clearly outperforming the arithmetic ensemble-averaging method. The random forest approach also produces the results closest to the target dataset for the change in the total carbon pool, seasonal carbon fluxes, emphasizing that machine learning approaches are promising tools for future studies. This highlights that, where possible, an arithmetic ensemble average should be avoided. However, potential target datasets that would facilitate the application of machine learning approaches, i.e., that cover both the spatial and temporal domain required to derive a robust informed ensemble average, are sparse for ecosystem variables.
Low sensitivity of gross primary production to elevated CO<sub>2</sub> in a mature eucalypt woodland
Publisher: Copernicus GmbH
Date: 20-01-2020
Abstract: Abstract. 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.
A flux tower dataset tailored for land model evaluation
Publisher: Copernicus GmbH
Date: 03-02-2022
Abstract: Abstract. Eddy covariance flux towers measure the exchange of water, energy, and carbon fluxes between the land and atmosphere. They have become invaluable for theory development and evaluating land models. However, flux tower data as measured (even after site post-processing) are not directly suitable for land surface modelling due to data gaps in model forcing variables, inappropriate gap-filling, formatting, and varying data quality. Here we present a quality-control and data-formatting pipeline for tower data from FLUXNET2015, La Thuile, and OzFlux syntheses and the resultant 170-site globally distributed flux tower dataset specifically designed for use in land modelling. The dataset underpins the second phase of the Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER), an international model intercomparison project encompassing land surface and biosphere models. The dataset is provided in the Assistance for Land-surface Modelling Activities (ALMA) NetCDF format and is CF-NetCDF compliant. For forcing land surface models, the dataset provides fully gap-filled meteorological data that have had periods of low data quality removed. Additional constraints required for land models, such as reference measurement heights, vegetation types, and satellite-based monthly leaf area index estimates, are also included. For model evaluation, the dataset provides estimates of key water, carbon, and energy variables, with the latent and sensible heat fluxes additionally corrected for energy balance closure. The dataset provides a total of 1040 site years covering the period 1992–2018, with in idual sites spanning from 1 to 21 years. The dataset is available at 0.25914/5fdb0902607e1 (Ukkola et al., 2021).
Predicting resilience through the lens of competing adjustments to vegetation function
Publisher: Wiley
Date: 06-07-2022
DOI: 10.1111/PCE.14376
Abstract: There is a pressing need to better understand ecosystem resilience to droughts and heatwaves. Eco‐evolutionary optimization approaches have been proposed as means to build this understanding in land surface models and improve their predictive capability, but competing approaches are yet to be tested together. Here, we coupled approaches that optimize canopy gas exchange and leaf nitrogen investment, respectively, extending both approaches to account for hydraulic impairment. We assessed model predictions using observations from a native Eucalyptus woodland that experienced repeated droughts and heatwaves between 2013 and 2020, whilst exposed to an elevated [CO 2 ] treatment. Our combined approaches improved predictions of transpiration and enhanced the simulated magnitude of the CO 2 fertilization effect on gross primary productivity. The competing approaches also worked consistently along axes of change in soil moisture, leaf area, and [CO 2 ]. Despite predictions of a significant percentage loss of hydraulic conductivity due to embolism (PLC) in 2013, 2014, 2016, and 2017 (99th percentile PLC 45%), simulated hydraulic legacy effects were small and short‐lived (2 months). Our analysis suggests that leaf shedding and/or suppressed foliage growth formed a strategy to mitigate drought risk. Accounting for foliage responses to water availability has the potential to improve model predictions of ecosystem resilience.
Observed and modelled historical trends in the water‐use efficiency of plants and ecosystems
Publisher: Wiley
Date: 06-05-2019
DOI: 10.1111/GCB.14634
Abstract: 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 CO
Annual precipitation explains variability in dryland vegetation greenness globally but not locally
Publisher: Wiley
Date: 22-06-2021
DOI: 10.1111/GCB.15729
Abstract: Dryland vegetation productivity is strongly modulated by water availability. As precipitation patterns and variability are altered by climate change, there is a pressing need to better understand vegetation responses to precipitation variability in these ecologically fragile regions. Here we present a global analysis of dryland sensitivity to annual precipitation variations using long‐term records of normalized difference vegetation index (NDVI). We show that while precipitation explains 66% of spatial gradients in NDVI across dryland regions, precipitation only accounts for % of temporal NDVI variability over most ( %) dryland regions. We observed this weaker temporal relative to spatial relationship between NDVI and precipitation across all global drylands. We confirmed this result using three alternative water availability metrics that account for water loss to evaporation, and growing season and precipitation timing. This suggests that predicting vegetation responses to future rainfall using space‐for‐time substitution will strongly overestimate precipitation control on interannual variability in aboveground growth. We explore multiple mechanisms to explain the discrepancy between spatial and temporal responses and find contributions from multiple factors including local‐scale vegetation characteristics, climate and soil properties. Earth system models (ESMs) from the latest Coupled Model Intercomparison Project overestimate the observed vegetation sensitivity to precipitation variability up to threefold, particularly during dry years. Given projections of increasing meteorological drought, ESMs are likely to overestimate the impacts of future drought on dryland vegetation with observations suggesting that dryland vegetation is more resistant to annual precipitation variations than ESMs project.
Evaluating a land surface model at a water-limited site: implications for land surface contributions to droughts and heatwaves
Publisher: Copernicus GmbH
Date: 28-01-2021
Abstract: Abstract. Land surface models underpin coupled climate model projections of droughts and heatwaves. However, the lack of simultaneous observations of in idual components of evapotranspiration, concurrent with root-zone soil moisture, has limited previous model evaluations. Here, we use a comprehensive set of observations from a water-limited site in southeastern Australia including both evapotranspiration and soil moisture to a depth of 4.5 m to evaluate the Community Atmosphere-Biosphere Land Exchange (CABLE) land surface model. We demonstrate that alternative process representations within CABLE had the capacity to improve simulated evapotranspiration, but not necessarily soil moisture dynamics–highlighting problems of model evaluations against water fluxes alone. Our best simulation was achieved by resolving a soil evaporation bias, using a more realistic initialisation of the groundwater aquifer state and higher vertical soil resolution informed by observed soil properties, and further calibrating soil hydraulic conductivity. Despite these improvements, the role of the empirical soil moisture stress function in influencing the simulated water fluxes remained important: using a site-calibrated function reduced the soil water stress on plants by 36 % during drought and 23 % at other times. These changes in CABLE not only improve the seasonal cycle of evapotranspiration but also affect the latent and sensible heat fluxes during droughts and heatwaves. The range of parameterisations tested led to differences of ∼150 W m−2 in the simulated latent heat flux during a heatwave, implying a strong impact of parameterisations on the capacity for evaporative cooling and feedbacks to the boundary layer (when coupled). Overall, our results highlight the opportunity to advance the capability of land surface models to capture water cycle processes, particularly during meteorological extremes, when sufficient observations of both evapotranspiration fluxes and soil moisture profiles are available.
Biochemical photosynthetic responses to temperature: How do interspecific differences compare with seasonal shifts?
Publisher: Oxford University Press (OUP)
Date: 09-07-2013
Abstract: Plants show flexible acclimation of leaf photosynthesis to temperature that depends both on their prevailing growth environment and the climate where they originated. This acclimation has been shown to involve changes in the temperature responses of the apparent maximum rate of Rubisco carboxylation (Vcmax) and apparent maximum rate of electron transport (Jmax), as well as changes in the ratio of these parameters. We asked whether such changes in photosynthetic biochemistry attributable to climate of origin are similar in nature and magnitude to those attributable to growth environment. To address this question, we measured temperature responses of photosynthesis and chlorophyll fluorescence on six Eucalyptus species from erse geographical and climatic regions growing in a common garden. Measurements were made in three seasons, allowing us to compare interspecific differences with seasonal changes. We found significant interspecific differences in apparent Vcmax and Jmax standardized to 25 °C, but there were no significant differences in the temperature responses of these parameters among species. Comparing data across seasons, we found significant seasonal changes in apparent Vcmax25, but not in Jmax25, causing a change in their ratio (J/V ratio). However, there were no seasonal changes in the temperature response of either parameter. We concluded that the growth environment had a much larger effect on temperature response than climate of origin among this set of species. Mean daytime temperature increased by 15 °C from winter to summer, whereas we estimated that the seasonal change in J/V ratio would cause a change in the optimum temperature (Topt) for gross photosynthesis of 3.6 °C. Use of a general relationship to describe photosynthetic temperature acclimation resulted in a strong underestimation of the Topt for photosynthesis for these species. Our results indicated that variation in photosynthetic temperature responses cannot be captured in one simple relationship with growth temperature. Further comparative research on species groups will be needed to develop a basis for modelling these interspecific differences in plant temperature acclimation.
Towards species-level forecasts of drought-induced tree mortality risk
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-8249
Abstract: 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, & #8203 South-East Australia& #8203 & #8203 has recently experienced two of the worst droughts in the historical record (2000& #8211 and 2017& #8211 ). 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& #8211 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& #8217 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 in idual tree species, providing an evidence base for decision-making around the resilience of restoration plantings or net-zero emission strategies.
A test of an optimal stomatal conductance scheme within the CABLE Land Surface Model
Publisher: Copernicus GmbH
Date: 15-10-2014
Abstract: Abstract. Stomatal conductance (gs) affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model (LSM). In common with many LSMs, CABLE does not differentiate between gs model parameters in relation to plant functional type (PFT), but instead only in relation to photosynthetic pathway. We therefore constrained the key model parameter "g1" which represents a plants water use strategy by PFT based on a global synthesis of stomatal behaviour. As proof of concept, we also demonstrate that the g1 parameter can be estimated using two long-term average (1960–1990) bioclimatic variables: (i) temperature and (ii) an indirect estimate of annual plant water availability. The new stomatal models in conjunction with PFT parameterisations resulted in a large reduction in annual fluxes of transpiration (~ 30% compared to the standard CABLE simulations) across evergreen needleleaf, tundra and C4 grass regions. Differences in other regions of the globe were typically small. Model performance when compared to upscaled data products was not degraded, though the new stomatal conductance scheme did not noticeably change existing model-data biases. We conclude that optimisation theory can yield a simple and tractable approach to predicting stomatal conductance in LSMs.
Acclimation and adaptation components of the temperature dependence of plant photosynthesis at the global scale
Publisher: Wiley
Date: 08-02-2019
DOI: 10.1111/NPH.15668
Abstract: The temperature response of photosynthesis is one of the key factors determining predicted responses to warming in global vegetation models (GVMs). The response may vary geographically, owing to genetic adaptation to climate, and temporally, as a result of acclimation to changes in ambient temperature. Our goal was to develop a robust quantitative global model representing acclimation and adaptation of photosynthetic temperature responses. We quantified and modelled key mechanisms responsible for photosynthetic temperature acclimation and adaptation using a global dataset of photosynthetic CO
Examining the role of environmental memory in the predictability of carbon and water fluxes across Australian ecosystems
Publisher: Copernicus GmbH
Date: 05-04-2022
Abstract: Abstract. The vegetation's response to climate change is a significant source of uncertainty in future terrestrial biosphere model projections. Constraining climate–carbon cycle feedbacks requires improving our understanding of both the immediate and long-term plant physiological responses to climate. In particular, the timescales and strength of memory effects arising from both extreme events (i.e. droughts and heatwaves) and structural lags in the systems (such as delays between rainfall and peak plant water content or between a precipitation deficit and down-regulation of productivity) have largely been overlooked in the development of terrestrial biosphere models. This is despite the knowledge that plant responses to climatic drivers occur across multiple timescales (seconds to decades), with the impact of climate extremes resonating for many years. Using data from 12 eddy covariance sites, covering two rainfall gradients (256 to 1491 mm yr−1) in Australia, in combination with a hierarchical Bayesian model, we characterised the timescales and magnitude of influence of antecedent drivers on daily net ecosystem exchange (NEE) and latent heat flux (λE). By focussing our analysis on a single continent (and predominately on a single genus), we reduced the degrees of variation between each site, providing a novel chance to explore the unique characteristics that might drive the importance of memory. Model fit varied considerably across sites when modelling NEE, with R2 values of between 0.30 and 0.83. λE was considerably more predictable across sites, with R2 values ranging from 0.56 to 0.93. When considered at a continental scale, both fluxes were more predictable when memory effects (expressed as lagged climate predictors) were included in the model. These memory effects accounted for an average of 17 % of the NEE predictability and 15 % for λE. Consistent with prior studies, the importance of environmental memory in predicting fluxes increased as site water availability declined (ρ=-0.73, p .01 for NEE, ρ=-0.67, p .05 for λE). However, these relationships did not necessarily hold when sites were grouped by vegetation type. We also tested a model of k-means clustering plus regression to confirm the suitability of the Bayesian model for modelling these sites. The k-means approach performed similarly to the Bayesian model in terms of model fit, demonstrating the robustness of the Bayesian framework for exploring the role of environmental memory. Our results underline the importance of capturing memory effects in models used to project future responses to climate change, especially in water-limited ecosystems. Finally, we demonstrate a considerable variation in in idual-site predictability, driven to a notable degree by environmental memory, and this should be considered when evaluating model performance across ecosystems.
Supplementary material to "Do land surface models need to include differential plant species responses to drought? Examining model predictions across a latitudinal gradient in Europe"
Publisher: Copernicus GmbH
Date: 06-08-2015
Evaluating CMIP5 Model Agreement for Multiple Drought Metrics
Publisher: American Meteorological Society
Date: 06-2018
Abstract: Global climate models play an important role in quantifying past and projecting future changes in drought. Previous studies have pointed to shortcomings in these models for simulating droughts, but systematic evaluation of their level of agreement has been limited. Here, historical simulations (1950–2004) for 20 models from the latest Coupled Model Intercomparison Project (CMIP5) were analyzed for a variety of drought metrics and thresholds using a standardized drought index. Model agreement was investigated for different types of drought (precipitation, runoff, and soil moisture) and how this varied with drought severity and duration. At the global scale, climate models were shown to agree well on most precipitation drought metrics, but systematically underestimated precipitation drought intensity compared to observations. Conversely, simulated runoff and soil moisture droughts varied significantly across models, particularly for intensity. Differences in precipitation simulations were found to explain model differences in runoff and soil moisture drought metrics over some regions, but predominantly with respect to drought intensity. This suggests it is insufficient to evaluate models for precipitation droughts to increase confidence in model performance for other types of drought. This study shows large but metric-dependent discrepancies in CMIP5 for modeling different types of droughts that relate strongly to the component models (i.e., atmospheric or land surface scheme) used in the coupled modeling systems. Our results point to a need to consider multiple models in drought impact studies to account for high model uncertainties.
Non‐Stationary Lags and Legacies in Ecosystem Flux Response to Antecedent Rainfall
Publisher: American Geophysical Union (AGU)
Date: 05-2023
DOI: 10.1029/2022JG007144
Abstract: Ecosystem function can be affected directly by climate, including by meteorological extremes, and also by sustained lags and legacies on timescales that surpass those of the weather events themselves. However, important gaps remain in our understanding of the influence and timescale of persistence of antecedent climate, known as environmental memory, on terrestrial carbon and water fluxes. Identifying the interactions between the lagged response to climate and the legacies to climate extremes, and whether the influence of memory varies through time, has not been fully explored. Here, we used a novel k ‐means clustering plus regression approach to examine timeseries of the sensitivity of terrestrial fluxes to antecedent precipitation at 65 eddy‐covariance sites across a range of ecosystems. Quantifying the sensitivity to past precipitation and temperature reveals that the role of memory in ecosystem fluxes varies across sites and in time. When memory was accounted for in the model, relative improvement in modeled site flux r 2 compared to an instantaneous model varied between 0% and 57%, with mean of 12%. Our results show that vegetation type was a stronger predictor of memory importance than site aridity, implying a need to understand vegetation resilience conferred by physiological traits and acclimation capacity. The influence of memory varied strongly through time at many sites, with the role of different timescales exhibiting consistent non‐stationarity. Our results demonstrate the importance of accounting for time‐varying vegetation response to antecedent rainfall in land surface models to accurately predict future terrestrial fluxes.
Where does the carbon go? A model–data intercomparison of vegetation carbon allocation and turnover processes at two temperate forest free‐air CO2 enrichment sites
Publisher: Wiley
Date: 21-05-2014
DOI: 10.1111/NPH.12847
Abstract: Elevated atmospheric CO 2 concentration ( eCO 2 ) has the potential to increase vegetation carbon storage if increased net primary production causes increased long‐lived biomass. Model predictions of eCO 2 effects on vegetation carbon storage depend on how allocation and turnover processes are represented. We used data from two temperate forest free‐air CO 2 enrichment ( FACE ) experiments to evaluate representations of allocation and turnover in 11 ecosystem models. Observed eCO 2 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 eCO 2 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.
A test of the 'one-point method' for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis
Publisher: Wiley
Date: 31-12-2016
DOI: 10.1111/NPH.13815
Abstract: Simulations of photosynthesis by terrestrial biosphere models typically need a specification of the maximum carboxylation rate ( V cmax ). Estimating this parameter using A – C i curves (net photosynthesis, A , vs intercellular CO 2 concentration, C i ) is laborious, which limits availability of V cmax data. However, many multispecies field datasets include net photosynthetic rate at saturating irradiance and at ambient atmospheric CO 2 concentration ( A sat ) measurements, from which V cmax can be extracted using a ‘one‐point method’. We used a global dataset of A – C i curves (564 species from 46 field sites, covering a range of plant functional types) to test the validity of an alternative approach to estimate V cmax from A sat via this ‘one‐point method’. If leaf respiration during the day ( R day ) is known exactly, V cmax can be estimated with an r 2 value of 0.98 and a root‐mean‐squared error ( RMSE ) of 8.19 μmol m −2 s −1 . However, R day typically must be estimated. Estimating R day as 1.5% of V cmax, we found that V cmax could be estimated with an r 2 of 0.95 and an RMSE of 17.1 μmol m −2 s −1 . The one‐point method provides a robust means to expand current databases of field‐measured V cmax , giving new potential to improve vegetation models and quantify the environmental drivers of V cmax variation.
Forest water use and water use efficiency at elevated CO2 FACE sites
Publisher: Wiley
Date: 25-03-2013
DOI: 10.1111/GCB.12164
Abstract: 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.
Low phosphorus supply constrains plant responses to elevated CO2: A meta‐analysis
Publisher: Wiley
Date: 31-07-2020
DOI: 10.1111/GCB.15277
Ideas and perspectives: How coupled is the vegetation to the boundary layer?
Publisher: Copernicus GmbH
Date: 17-05-2017
DOI: 10.5194/BG-2017-182
Abstract: Abstract. Understanding the sensitivity of transpiration to stomatal conductance is critical to simulating the water cycle. This sensitivity is a function of the degree of coupling between the vegetation and the atmosphere, and is commonly expressed by the decoupling factor. The level of decoupling assumed by models varies considerably and has previously been shown to be a major cause for model disagreement when simulating changes in transpiration in response to elevated CO2. The degree of coupling also offers us insight into how different vegetation types control transpiration fluxes, fundamental to our understanding of land–atmosphere interactions. To explore this issue, we estimated the decoupling factor from FLUXNET data, finding notable departures from values previously reported in single site studies. Evergreen needleleaf forests appear to be on the whole more decoupled than the literature suggests, whilst evergreen broadleaved forests and shrubs were considerably more coupled than is suggested in the literature or than would be predicted based on leaf size and plant stature. We found that the assumption that grasses would be strongly decoupled (due to vegetation stature) was only true for high precipitation sites. These results were robust to assumptions about aerodynamic conductance and energy balance closure. Thus, these data form a benchmarking metric against which to test model assumptions about coupling. Our results identify a clear need to improve the quantification of the processes involved in scaling from the leaf to the whole ecosystem. Progress could be made with targeted measurement c aigns at flux sites, as well as more site characteristic information across the FLUXNET network.
Supplementary material to "Examining the evidence for sustained transpiration during heat extremes"
Publisher: Copernicus GmbH
Date: 24-09-0100
Supplementary material to "FluxnetLSM R package (v1.0): A community tool for processing FLUXNET data for use in land surface modelling"
Publisher: Copernicus GmbH
Date: 27-03-2017
Towards physiologically meaningful water-use efficiency estimates from eddy covariance data
Publisher: Wiley
Date: 11-10-2018
DOI: 10.1111/GCB.13893
Abstract: Intrinsic water-use efficiency (iWUE) characterizes the physiological control on the simultaneous exchange of water and carbon dioxide in terrestrial ecosystems. Knowledge of iWUE is commonly gained from leaf-level gas exchange measurements, which are inevitably restricted in their spatial and temporal coverage. Flux measurements based on the eddy covariance (EC) technique can overcome these limitations, as they provide continuous and long-term records of carbon and water fluxes at the ecosystem scale. However, vegetation gas exchange parameters derived from EC data are subject to scale-dependent and method-specific uncertainties that compromise their ecophysiological interpretation as well as their comparability among ecosystems and across spatial scales. Here, we use estimates of canopy conductance and gross primary productivity (GPP) derived from EC data to calculate a measure of iWUE (G
FluxnetLSM R package (v1.0): A community tool for processing FLUXNET data for use in land surface modelling
Publisher: Copernicus GmbH
Date: 27-03-2017
DOI: 10.5194/GMD-2017-58
Abstract: Abstract. Flux towers measure ecosystem-scale surface-atmosphere exchanges of energy, carbon dioxide and water vapour. The network of flux towers now encompasses ~ 900 sites, spread across every continent. Consequently, these data have become an essential benchmarking tool for land surface models (LSMs). However, these data as released are not immediately usable for driving, evaluating and benchmarking LSMs. Flux tower data must first be transformed into a LSM-readable file format, a process which involves changing units, screening missing data and varying degrees of additional gap- filling. All of this often leads to an under-utilisation of these data in model benchmarking. To resolve some of these issues, and to help make flux tower measurements more widely used, we present a reproducible, open-source R package that transforms the latest FLUXNET2015 release into community standard NetCDF files that are directly usable by LSMs.
Mechanisms of woody-plant mortality under rising drought, CO2 and vapour pressure deficit
Publisher: Springer Science and Business Media LLC
Date: 29-03-2022
A test of an optimal stomatal conductance scheme within the CABLE land surface model
Publisher: Copernicus GmbH
Date: 24-02-2015
Abstract: Abstract. Stomatal conductance (gs) affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model (LSM). In common with many LSMs, CABLE does not differentiate between gs model parameters in relation to plant functional type (PFT), but instead only in relation to photosynthetic pathway. We constrained the key model parameter "g1", which represents plant water use strategy, by PFT, based on a global synthesis of stomatal behaviour. As proof of concept, we also demonstrate that the g1 parameter can be estimated using two long-term average (1960–1990) bioclimatic variables: (i) temperature and (ii) an indirect estimate of annual plant water availability. The new stomatal model, in conjunction with PFT parameterisations, resulted in a large reduction in annual fluxes of transpiration (~ 30% compared to the standard CABLE simulations) across evergreen needleleaf, tundra and C4 grass regions. Differences in other regions of the globe were typically small. Model performance against upscaled data products was not degraded, but did not noticeably reduce existing model–data biases. We identified assumptions relating to the coupling of the vegetation to the atmosphere and the parameterisation of the minimum stomatal conductance as areas requiring further investigation in both CABLE and potentially other LSMs. We conclude that optimisation theory can yield a simple and tractable approach to predicting stomatal conductance in LSMs.
Robust Future Changes in Meteorological Drought in CMIP6 Projections Despite Uncertainty in Precipitation
Publisher: American Geophysical Union (AGU)
Date: 09-06-2020
DOI: 10.1029/2020GL087820
How do leaf and ecosystem measures of water-use efficiency compare?
Publisher: Wiley
Date: 02-06-2017
DOI: 10.1111/NPH.14626
Abstract: The terrestrial carbon and water cycles are intimately linked: the carbon cycle is driven by photosynthesis, while the water balance is dominated by transpiration, and both fluxes are controlled by plant stomatal conductance. The ratio between these fluxes, the plant water-use efficiency (WUE), is a useful indicator of vegetation function. WUE can be estimated using several techniques, including leaf gas exchange, stable isotope discrimination, and eddy covariance. Here we compare global compilations of data for each of these three techniques. We show that patterns of variation in WUE across plant functional types (PFTs) are not consistent among the three datasets. Key discrepancies include the following: leaf-scale data indicate differences between needleleaf and broadleaf forests, but ecosystem-scale data do not leaf-scale data indicate differences between C
A reporting format for leaf-level gas exchange data and metadata
Publisher: Elsevier BV
Date: 03-2021
Thirty-eight years of CO<sub>2</sub> fertilization has outpaced growing aridity to drive greening of Australian woody ecosystems
Publisher: Copernicus GmbH
Date: 28-01-2022
Abstract: Abstract. 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 impact of alternative trait‐scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax) on global gross primary production
Publisher: Wiley
Date: 23-06-2017
DOI: 10.1111/NPH.14623
Abstract: The maximum photosynthetic carboxylation rate ( V cmax ) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production ( GPP ). Four trait‐scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model ( SDGVM ). Global GPP varied from 108.1 to 128.2 PgC yr −1 , 65% of the range of a recent model intercomparison of global GPP . The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity ( NBP ). All hypotheses produced global GPP that was highly correlated ( r = 0.85–0.91) with three proxies of global GPP . Plant functional type‐based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM . Mismatch between environmental filtering (the most data‐driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes.
Predicting long‐term carbon sequestration in response to CO2 enrichment: How and why do current ecosystem models differ?
Publisher: American Geophysical Union (AGU)
Date: 04-2015
DOI: 10.1002/2014GB004995
Green-up and brown-down: Modelling grassland foliage phenology responses to soil moisture availability
Publisher: Elsevier BV
Date: 2023
Supplementary material to "How representative are FLUXNET measurements of surface fluxes during temperature extremes?"
Publisher: Copernicus GmbH
Date: 20-12-2018
Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts
Publisher: Copernicus GmbH
Date: 13-09-2021
Abstract: Abstract. The co-occurrence of droughts and heatwaves can have significant impacts on many socioeconomic and environmental systems. Groundwater has the potential to moderate the impact of droughts and heatwaves by moistening the soil and enabling vegetation to maintain higher evaporation, thereby cooling the canopy. We use the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, coupled to a groundwater scheme, to examine how groundwater influences ecosystems under conditions of co-occurring droughts and heatwaves. We focus specifically on south-east Australia for the period 2000–2019, when two significant droughts and multiple extreme heatwave events occurred. We found groundwater plays an important role in helping vegetation maintain transpiration, particularly in the first 1–2 years of a multi-year drought. Groundwater impedes gravity-driven drainage and moistens the root zone via capillary rise. These mechanisms reduced forest canopy temperatures by up to 5 ∘C during in idual heatwaves, particularly where the water table depth is shallow. The role of groundwater diminishes as the drought lengthens beyond 2 years and soil water reserves are depleted. Further, the lack of deep roots or stomatal closure caused by high vapour pressure deficit or high temperatures can reduce the additional transpiration induced by groundwater. The capacity of groundwater to moderate both water and heat stress on ecosystems during simultaneous droughts and heatwaves is not represented in most global climate models, suggesting that model projections may overestimate the risk of these events in the future.
Examining the Role of Environmental Memory in the Predictability of Carbon and Water Fluxes Across Australian Ecosystems
Publisher: Copernicus GmbH
Date: 10-2021
DOI: 10.5194/BG-2021-254
Abstract: Abstract. The vegetation’s response to climate change is a significant source of uncertainty in future terrestrial biosphere model projections. Constraining climate-carbon cycle feedbacks requires improving our understanding of direct, as well as long-term, plant physiological responses to climate. In particular, the timescales and strength of memory effects arising from both extreme events (i.e., droughts and heatwaves) and structural lags in the systems have largely been overlooked in the development of models. This is despite the knowledge that plant responses to climatic drivers occur across multiple timescales (seconds to decades), with the impact of climate extremes resonating for many years. Using data from 13 eddy covariance sites, covering two rainfall gradients (256 to 1491 mm yr−1) in Australia, in combination with a hierarchical Bayesian model, we characterised the timescales and magnitude of influence of antecedent drivers on daily net ecosystem exchange (NEE) and latent heat flux (λE). Model fit varied considerably across sites when modelling NEE, with R2 values of between 0.30 and 0.83. Latent heat was considerably more predictable across sites, with R2 values ranging from 0.56 to 0.95. When considered at a continental scale, both fluxes were more predictable when memory effects were included in the model. These memory effects accounted for an average of 17 % of the NEE predictability and 15 % for λE. The importance of environmental memory in predicting fluxes increased as site water availability declined (ρ = −0.72, p 0.01 for NEE, ρ = −0.62, p 0.05 for λE). However, these relationships did not necessarily hold when sites were grouped by vegetation type. We also tested a k-means clustering plus regression model to confirm the suitability of the Bayesian model for modelling these sites. The k-means approach performed similarly to the Bayesian model in terms of model fit, demonstrating the robustness of the Bayesian framework for exploring the role of environmental memory. Our results underline the importance of capturing memory effects in models used to project future responses to climate change, especially in water-limited ecosystems. Finally, we demonstrate a considerable variation in in idual site predictability, driven to a notable degree by environmental memory, and this should be considered when evaluating model performance across ecosystems.
Satellite based estimates underestimate the effect of CO2 fertilization on net primary productivity
Publisher: Springer Science and Business Media LLC
Date: 28-09-2016
DOI: 10.1038/NCLIMATE3105
Gross primary production responses to warming, elevated CO 2, and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland
Publisher: Wiley
Date: 22-03-2017
DOI: 10.1111/GCB.13602
Abstract: Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO
Supplementary material to "A flux tower dataset tailored for land model evaluation"
Publisher: Copernicus GmbH
Date: 28-07-2021
Mesophyll conductance in land surface models: effects on photosynthesis and transpiration
Publisher: Wiley
Date: 10-12-2019
DOI: 10.1111/TPJ.14587
Abstract: The CO
Examining the vulnerability of Australian eucalypts to future drought-induced tree mortality
Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-14527
Abstract: & & 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 CO& sub& & /sub& (increasing water use-efficiency) to provide the first assessment of future drought risk to Australian trees.& &
The fate of carbon in a mature forest under carbon dioxide enrichment
Publisher: Springer Science and Business Media LLC
Date: 08-04-2020
To what extent can rising [CO2] ameliorate plant drought stress?
Publisher: Wiley
Date: 28-07-2021
DOI: 10.1111/NPH.17540
Abstract: Plant responses to elevated atmospheric carbon dioxide (eCO 2 ) have been hypothesized as a key mechanism that may ameliorate the impact of future drought. Yet, despite decades of experiments, the question of whether eCO 2 reduces plant water use, yielding ‘water savings’ that can be used to maintain plant function during periods of water stress, remains unresolved. In this Viewpoint, we identify the experimental challenges and limitations to our understanding of plant responses to drought under eCO 2 . In particular, we argue that future studies need to move beyond exploring whether eCO 2 played ‘a role’ or ‘no role’ in responses to drought, but instead more carefully consider the timescales and conditions that would induce an influence. We also argue that considering emergent differences in soil water content may be an insufficient means of assessing the impact of eCO 2 . We identify eCO 2 impact during severe drought (e.g. to the point of mortality), interactions with future changes in vapour pressure deficit and uncertainty about changes in leaf area as key gaps in our current understanding. New insights into CO 2 × drought interactions are essential to better constrain model theory that governs future climate model projections of land–atmosphere interactions during periods of water stress.
Implementation of an optimal stomatal conductance model in the Australian Community Climate Earth Systems Simulator (ACCESS1.3b)
Publisher: Copernicus GmbH
Date: 03-07-2015
Abstract: Abstract. We implement a new stomatal conductance model, based on the optimality approach, within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. Coupled land-atmosphere simulations are then performed using CABLE within the Australian Community Climate and Earth Systems Simulator (ACCESS) with prescribed sea surface temperatures. As in most land surface models, the default stomatal conductance scheme only accounts for differences in model parameters in relation to the photosynthetic pathway, but not in relation to plant functional types. The new scheme allows model parameters to vary by plant functional type, based on a global synthesis of observations of stomatal conductance under different climate regimes over a wide range of species. We show that the new scheme reduces the latent heat flux from the land surface over the boreal forests during the Northern Hemisphere summer by 0.5 to 1.0 mm day-1. This leads to warmer daily maximum and minimum temperatures by up to 1.0 °C and warmer extreme maximum temperatures by up to 1.5 °C. These changes generally improve the climate model's climatology and improve existing biases by 10–20 %. The change in the surface energy balance also affects net primary productivity and the terrestrial carbon balance. We conclude that the improvements in the global climate model which result from the new stomatal scheme, constrained by a global synthesis of experimental data, provide a valuable advance in the long-term development of the ACCESS modelling system.
Examining the evidence for sustained transpiration during heat extremes
Publisher: Copernicus GmbH
Date: 24-09-2018
DOI: 10.5194/BG-2018-399
Abstract: Abstract. 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 d en, rather than lify, 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 s le 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 d ening of the land-atmosphere lification is thus not included in climate model projections.
Impact of the representation of stomatal conductance on model projections of heatwave intensity
Publisher: Springer Science and Business Media LLC
Date: 21-03-2016
DOI: 10.1038/SREP23418
Abstract: Stomatal conductance links plant water use and carbon uptake and is a critical process for the land surface component of climate models. However, stomatal conductance schemes commonly assume that all vegetation with the same photosynthetic pathway use identical plant water use strategies whereas observations indicate otherwise. Here, we implement a new stomatal scheme derived from optimal stomatal theory and constrained by a recent global synthesis of stomatal conductance measurements from 314 species, across 56 field sites. Using this new stomatal scheme, within a global climate model, subtantially increases the intensity of future heatwaves across Northern Eurasia. This indicates that our climate model has previously been under-predicting heatwave intensity. Our results have widespread implications for other climate models, many of which do not account for differences in stomatal water-use across different plant functional types and hence, are also likely under projecting heatwave intensity in the future.
Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network
Publisher: Wiley
Date: 22-03-2022
DOI: 10.1111/GCB.16141
Abstract: In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20 th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO 2 sink to a net CO 2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under‐represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long‐term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.
Interannual variability of ecosystem iso/anisohydry is regulated by environmental dryness
Publisher: Wiley
Date: 03-12-2020
DOI: 10.1111/NPH.17040
Abstract: Plants are characterized by the iso/anisohydry continuum depending on how they regulate leaf water potential (Ψ L ). However, how iso/anisohydry changes over time in response to year‐to‐year variations in environmental dryness and how such responses vary across different regions remains poorly characterized. We investigated how dryness, represented by aridity index, affects the interannual variability of ecosystem iso/anisohydry at the regional scale, estimated using satellite microwave vegetation optical depth (VOD) observations. This ecosystem‐level analysis was further complemented with published field observations of species‐level Ψ L . We found different behaviors in the directionality and sensitivity of isohydricity (σ) with respect to the interannual variation of dryness in different ecosystems. These behaviors can largely be differentiated by the average dryness of the ecosystem itself: in mesic ecosystems, σ decreases in drier years with a higher sensitivity to dryness in xeric ecosystems, σ increases in drier years with a lower sensitivity to dryness. These results were supported by the species‐level synthesis. Our study suggests that how plants adjust their water use across years – as revealed by their interannual variability in isohydricity – depends on the dryness of plants’ living environment. This finding advances our understanding of plant responses to drought at regional scales.
The Nonradiative Effect Dominates Local Surface Temperature Change Caused by Afforestation in China
Publisher: American Meteorological Society
Date: 15-07-2019
Abstract: China is several decades into large-scale afforestation programs to help address significant ecological and environmental degradation, with further afforestation planned for the future. However, the biophysical impact of afforestation on local surface temperature remains poorly understood, particularly in midlatitude regions where the importance of the radiative effect driven by albedo and the nonradiative effect driven by energy partitioning is uncertain. To examine this issue, we investigated the local impact of afforestation by comparing adjacent forest and open land pixels using satellite observations between 2001 and 2012. We attributed local surface temperature change between adjacent forest and open land to radiative and nonradiative effects over China based on the Intrinsic Biophysical Mechanism (IBM) method. Our results reveal that forest causes warming of 0.23°C (±0.21°C) through the radiative effect and cooling of −0.74°C (±0.50°C) through the nonradiative effect on local surface temperature compared with open land. The nonradiative effect explains about 79% (±16%) of local surface temperature change between adjacent forest and open land. The contribution of the nonradiative effect varies with forest and open land types. The largest cooling is achieved by replacing grasslands or rain-fed croplands with evergreen tree types. Conversely, converting irrigated croplands to deciduous broadleaf forest leads to warming. This provides new guidance on afforestation strategies, including how these should be informed by local conditions to avoid lifying climate-related warming.
Identifying areas at risk of drought‐induced tree mortality across South‐Eastern Australia
Publisher: Wiley
Date: 19-08-2020
DOI: 10.1111/GCB.15215
Towards species‐level forecasts of drought‐induced tree mortality risk
Publisher: Wiley
Date: 22-04-2022
DOI: 10.1111/NPH.18129
Abstract: 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 conducted three experiments: applying CABLE to the 2017–2019 drought a 20% drier drought and a 20% drier drought with a doubling of atmospheric carbon dioxide (CO 2 ). The severity of the drought was highlighted as for at least 25% of their distribution ranges, 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 areas. The importance of the role of CO 2 in ameliorating drought stress was consistent across species. Our results represent an important advance in our capacity to forecast the resilience of in idual tree species, providing an evidence base for decision‐making around the resilience of restoration plantings or net‐zero emission strategies.
Model–data synthesis for the next generation of forest free‐air CO 2 enrichment (FACE ) experiments
Publisher: Wiley
Date: 06-08-2015
DOI: 10.1111/NPH.13593
Abstract: The first generation of forest free‐air CO 2 enrichment ( FACE ) experiments has successfully provided deeper understanding about how forests respond to an increasing CO 2 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 bio ersity will significantly expand the inference space. These new experiments are: Euc FACE in a mature Eucalyptus stand on highly weathered soil in subtropical Australia Amazon FACE in a highly erse, primary rainforest in Brazil BIF oR‐ FACE in a 150‐yr‐old deciduous woodland stand in central England and Swed FACE 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 bio ersity.
Reconciling historical changes in the hydrological cycle over land
Publisher: Springer Science and Business Media LLC
Date: 14-03-2022
DOI: 10.1038/S41612-022-00240-Y
Abstract: The sixth Intergovernmental Panel on Climate Change (IPCC) assessment report confirms that global warming drives widespread changes in the global terrestrial hydrological cycle, and that changes are regionally erse. However, reported trends and changes in the hydrological cycle suffer from significant inconsistencies. This is associated with the lack of a rigorous observationally-based assessment of simultaneous trends in the different components of the hydrological cycle. Here, we reconcile these different estimates of historical changes by simultaneously analysing trends in all the major components of the hydrological cycle, coupled with vegetation greenness for the period 1980–2012. We use observationally constrained, conserving estimates of the closure of the hydrological cycle, combined with a data assimilation approach and observationally-driven uncertainty estimates. We find robust changes in the hydrological cycle across more than 50% of the land area, with evapotranspiration (ET) changing the most and precipitation ( P ) the least. We find many instances of unambiguous trends in ET and runoff ( Q ) without robust trends in P , a result broadly consistent with a “wet gets wetter, but dry does not get drier”. These findings provide important opportunities for water resources management and climate risk assessment over a significant fraction of the land surface where hydrological trends have previously been uncertain.
Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe
Publisher: Copernicus GmbH
Date: 21-12-2015
Abstract: Abstract. Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSM and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.
Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts
Publisher: Copernicus GmbH
Date: 06-05-2021
DOI: 10.5194/ESD-2021-31
Abstract: Abstract. The co-occurrence of droughts and heatwaves can have significant impacts on many socioeconomic and environmental systems. Groundwater has the potential to moderate the impact of droughts and heatwaves by moistening the soil and enabling vegetation to maintain higher evaporation, thereby cooling the canopy. We use the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, coupled to a groundwater scheme, to examine how groundwater influences ecosystems under conditions of co-occurring droughts and heatwaves. We focus specifically on South East Australia for the period 2000–2019 when two significant droughts and multiple extreme heatwave events occurred. We found groundwater plays an important role in helping vegetation maintain transpiration, particularly in the first 1–2 years of a multi-year drought. Groundwater impedes gravity-driven drainage and moistens the root zone via capillary rise. These mechanisms reduced forest canopy temperatures by up to 5 °C during in idual heatwaves, particularly where the water table depth is shallow. The role of groundwater diminishes as the drought lengthens beyond 2 years and soil water reserves are depleted. Further, the lack of deep roots or stomatal closure caused by high vapour pressure deficit or high temperatures can reduce the additional transpiration induced by groundwater. The capacity of groundwater to moderate both water and heat stress on ecosystems during simultaneous droughts and heatwaves is not represented in most global climate models, suggesting model projections may overestimate the risk of these events in the future.
FluxnetLSM R package (v1.0): a community tool for processing FLUXNET data for use in land surface modelling
Publisher: Copernicus GmbH
Date: 12-09-2017
Abstract: Abstract. Flux towers measure ecosystem-scale surface–atmosphere exchanges of energy, carbon dioxide and water vapour. The network of flux towers now encompasses ∼ 900 sites, spread across every continent. Consequently, these data have become an essential benchmarking tool for land surface models (LSMs). However, these data as released are not immediately usable for driving, evaluating and benchmarking LSMs. Flux tower data must first be transformed into a LSM-readable file format, a process which involves changing units, screening missing data and varying degrees of additional gap-filling. All of this often leads to an under-utilisation of these data in model benchmarking. To resolve some of these issues, and to help make flux tower measurements more widely used, we present a reproducible, open-source R package that transforms the FLUXNET2015 and La Thuile data releases into community standard NetCDF files that are directly usable by LSMs. We note that these data would also be useful for any other user or community seeking to independently quality control, gap-fill or use the FLUXNET data.
Examining the sensitivity of the terrestrial carbon cycle to the expression of El Niño
Publisher: Copernicus GmbH
Date: 20-08-2020
DOI: 10.5194/BG-2020-299
Abstract: Abstract. The El Niño‐Southern Oscillation (ENSO) influences the global climate and the variability in the terrestrial carbon cycle on interannual timescales. Two different expressions of El Niño have recently been identified: (i) Central–Pacific (CP) and (ii) Eastern–Pacific (EP). Both types of El Nino are characterised by above average sea surface temperature anomalies in the respective locations. Studies exploring the impact of these expressions of El Niño on the carbon cycle have identified changes in the litude of the concentration of interannual atmospheric carbon dioxide (CO2) variability, as well as different lags in terrestrial CO2 release to the atmosphere following increased tropical near surface air temperature. We employ the dynamic global vegetation model LPJ–GUESS within a synthetic experimental framework to examine the sensitivity and potential long term impacts of these two expressions of El Niño on the terrestrial carbon cycle. We manipulated the occurrence of CP and EP events in two climate reanalysis datasets during the later half of the 20th and early 21st century by replacing all EP with CP and separately all CP with EP El Niño events. We found that the different expressions of El Niño affect interannual variability in the terrestrial carbon cycle. However, the effect on longer timescales was negligible for both climate reanalysis datasets. We conclude that capturing any future trends in the relative frequency of CP and EP El Niño events may not be critical for robust simulations of the terrestrial carbon cycle.
Towards species-level forecasts of drought-induced tree mortality risk
Publisher: Copernicus GmbH
Date: 27-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-2419
Abstract: & & 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& #8211 mm yr& sup& -1& /sup& ). We conducted three experiments: (i) applying CABLE to the 2017& #8211 drought in South East Australia (ii) a 20% drier drought and (iii) a 20% drier drought with a doubling of atmospheric carbon dioxide (CO& sub& & /sub& ). We identified several drought hotspots across the ranges of & em& E.viminalis& /em& , & em& E.obliqua& /em& , & em& E.globulus& /em& , & em& E.saligna,& /em& and & em& E.grandis& /em& . By contrast, CABLE simulated drought resilience in species that are found predominately in semi-arid areas such as & em& E.largiflorens& /em& and & em& E.populnea& /em& . We identified several key model assumptions (& em& e& /em& .& em& g& /em& ., the degree of stomatal control) and sensitivities (& em& e& /em& .& em& g& /em& ., the role of CO& sub& & /sub& in ameliorating drought) that require future research. Our results represent an important step forward in our capacity to forecast the resilience of in idual tree species, providing an evidence base for decision-making around the resilience of restoration plantings or strategies associated with achieving net-zero emissions.& &
Examining the evidence for decoupling between photosynthesis and transpiration during heat extremes
Publisher: Copernicus GmbH
Date: 26-02-2019
Abstract: Abstract. 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 d en, rather than lify, 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 3 days leading up to a temperature extreme, defined as including a daily maximum temperature ∘C (similar to the widely used TXx metric), and (ii) heatwaves, defined as 3 or more consecutive days above 35 ∘C. When focusing on (i), we found some evidence of reduced photosynthesis and sustained or increased latent heat fluxes at 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 the vapour pressure deficit. Outside of Australia, the Tier-1 FLUXNET2015 database provided limited scope to tackle this issue as it does not s le 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 tower 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 d ening of the land–atmosphere lification is thus not included in climate model projections.
Red light shines a path forward on leaf minimum conductance
Publisher: Wiley
Date: 29-10-2021
DOI: 10.1111/NPH.17794
Abstract: This article is a Commentary on Márquez et al . (2022), 233 : 156–168 .
Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO2
Publisher: Wiley
Date: 21-10-2020
DOI: 10.1111/NPH.16866
Abstract: Atmospheric carbon dioxide concentration ([CO 2 ]) is increasing, which increases leaf‐scale photosynthesis and intrinsic water‐use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO 2 ] increase and thus climate change. However, ecosystem CO 2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO 2 ]‐driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO 2 ] (iCO 2 ) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre‐industrial times. Established theory, supported by experiments, indicates that iCO 2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO 2 responses are high in comparison to experiments and predictions from theory. Plant mortality and soil carbon iCO 2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO 2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.
Modelling evapotranspiration during precipitation deficits: identifying critical processes in a land surface model
Publisher: Copernicus GmbH
Date: 21-06-2016
DOI: 10.5194/HESS-20-2403-2016
Abstract: Abstract. Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leaf area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.
Evaluation of the CABLEv2.3.4 Land Surface Model Coupled to NU‐WRFv3.9.1.1 in Simulating Temperature and Precipitation Means and Extremes Over CORDEX AustralAsia Within a WRF Physics Ensemble
Publisher: American Geophysical Union (AGU)
Date: 12-2019
DOI: 10.1029/2019MS001845
Evaluation of 30 urban land surface models in the Urban‐PLUMBER project: Phase 1 results
Publisher: Wiley
Date: 25-10-2023
DOI: 10.1002/QJ.4589
Incorporating non-stomatal limitation improves the performance of leaf and canopy models at high vapour pressure deficit
Publisher: Oxford University Press (OUP)
Date: 14-10-2019
Abstract: Vapour pressure deficit (D) is projected to increase in the future as temperatures rise. In response to increased D, stomatal conductance (gs) and photosynthesis (A) are reduced, which may result in significant reductions in terrestrial carbon, water, and energy fluxes. It is thus important for gas exchange models to capture the observed responses of gs and A with increasing D. We tested a series of coupled A-gs models against leaf gas exchange measurements from the Cumberland Plain Woodland (Australia), where D regularly exceeds 2 kPa and can reach 8 kPa in summer. Two commonly used A-gs models (Leuning 1995 and Medlyn et al. 2011) were not able to capture the observed decrease in A and gs with increasing D at the leaf scale. To explain this decrease in A and gs, two alternative hypotheses were tested: hydraulic limitation (i.e., plants reduce gs and/or A due to insufficient water supply) and non-stomatal limitation (i.e., downregulation of photosynthetic capacity). We found that the model that incorporated a non-stomatal limitation captured the observations with high fidelity and required the fewest number of parameters. While the model incorporating hydraulic limitation captured the observed A and gs, it did so via a physical mechanism that is incorrect. We then incorporated a non-stomatal limitation into the stand model, MAESPA, to examine its impact on canopy transpiration and gross primary production. Accounting for a non-stomatal limitation reduced the predicted transpiration by ~19%, improving the correspondence with sap flow measurements, and gross primary production by ~14%. Given the projected global increases in D associated with future warming, these findings suggest that models may need to incorporate non-stomatal limitation to accurately simulate A and gs in the future with high D. Further data on non-stomatal limitation at high D should be a priority, in order to determine the generality of our results and develop a widely applicable model.
Ideas and perspectives: How coupled is the vegetation to the boundary layer?
Publisher: Copernicus GmbH
Date: 09-10-2017
Abstract: Abstract. Understanding the sensitivity of transpiration to stomatal conductance is critical to simulating the water cycle. This sensitivity is a function of the degree of coupling between the vegetation and the atmosphere and is commonly expressed by the decoupling factor. The degree of coupling assumed by models varies considerably and has previously been shown to be a major cause of model disagreement when simulating changes in transpiration in response to elevated CO2. The degree of coupling also offers us insight into how different vegetation types control transpiration fluxes, which is fundamental to our understanding of land–atmosphere interactions. To explore this issue, we combined an extensive literature summary from 41 studies with estimates of the decoupling coefficient estimated from FLUXNET data. We found some notable departures from the values previously reported in single-site studies. There was large variability in estimated decoupling coefficients (range 0.05–0.51) for evergreen needleleaf forests. This is a result that was broadly supported by our literature review but contrasts with the early literature which suggests that evergreen needleleaf forests are generally well coupled. Estimates from FLUXNET indicated that evergreen broadleaved forests were the most tightly coupled, differing from our literature review and instead suggesting that it was evergreen needleleaf forests. We also found that the assumption that grasses would be strongly decoupled (due to vegetation stature) was only true for high precipitation sites. These results were robust to assumptions about aerodynamic conductance and, to a lesser extent, energy balance closure. Thus, these data form a benchmarking metric against which to test model assumptions about coupling. Our results identify a clear need to improve the quantification of the processes involved in scaling from the leaf to the whole ecosystem. Progress could be made with targeted measurement c aigns at flux sites and greater site characteristic information across the FLUXNET network.
Trees tolerate an extreme heatwave via sustained transpirational cooling and increased leaf thermal tolerance
Publisher: Wiley
Date: 02-02-2018
DOI: 10.1111/GCB.14037
Abstract: Heatwaves are likely to increase in frequency and intensity with climate change, which may impair tree function and forest C uptake. However, we have little information regarding the impact of extreme heatwaves on the physiological performance of large trees in the field. Here, we grew Eucalyptus parramattensis trees for 1 year with experimental warming (+3°C) in a field setting, until they were greater than 6 m tall. We withheld irrigation for 1 month to dry the surface soils and then implemented an extreme heatwave treatment of 4 consecutive days with air temperatures exceeding 43°C, while monitoring whole-canopy exchange of CO
Predicting resilience through the lens of competing adjustments to vegetation function
Publisher: Copernicus GmbH
Date: 27-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-4244
Abstract: & & 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 [CO& sub& & /sub& ]. Our simulations were in good agreement with observations of transpiration (& em& r& sup& & /sup& & /em& & #8764 .7), leaf water potential (& #177 .1 MPa), and leaf photosynthetic capacities (& #177 % of the observations). Despite predictions of significant percentage loss of conductivity (PLC) due to water stress in 2013, 2014, 2016, and 2017 (& em& & sub& & /sub& & /em& & 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 [CO& sub& & /sub& ], 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.& &
Robust future changes in meteorological drought in CMIP6 projections despite uncertainty in precipitation
Publisher: Wiley
Date: 08-03-2020
Robust Future Changes in Meteorological Drought in CMIP6 Projections Despite Uncertainty in Precipitation
Publisher: Copernicus GmbH
Date: 03-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-1889
Abstract: & & Understanding how climate change affects droughts guides adaptation planning in agriculture, water security, and ecosystem management. Earlier climate projections have highlighted high uncertainty in future drought projections, hindering effective planning. We use the latest CMIP6 projections and find more robust projections of meteorological drought compared to mean precipitation. We find coherent projected changes in seasonal drought duration and frequency (robust over & % of the global land area), despite a lack of agreement across models in projected changes in mean precipitation (24% of the land area). Future drought changes are larger and more consistent in CMIP6 compared to CMIP5. We find regionalised increases and decreases in drought duration and frequency that are driven by changes in both precipitation mean and variability. Conversely, drought intensity increases over most regions but is not simulated well historically by the climate models. These more robust projections of meteorological drought in CMIP6 provide clearer direction for water resource planning and the identification of agricultural and natural ecosystems at risk.& &
Inferring the effects of sink strength on plant carbon balance processes from experimental measurements
Publisher: Copernicus GmbH
Date: 03-07-2018
Abstract: Abstract. 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.
Does predictability of fluxes vary between FLUXNET sites?
Publisher: Copernicus GmbH
Date: 25-07-2018
Abstract: Abstract. The FLUXNET dataset contains eddy covariance measurements from across the globe and represents an invaluable estimate of the fluxes of energy, water, and carbon between the land surface and the atmosphere. While there is an expectation that the broad range of site characteristics in FLUXNET result in a ersity of flux behaviour, there has been little exploration of how predictable site behaviour is across the network. Here, 155 datasets with 30 min temporal resolution from the Tier 1 of FLUXNET 2015 were analysed in a first attempt to assess in idual site predictability. We defined site uniqueness as the disparity in performance between multiple empirical models trained globally and locally for each site and used this along with the mean performance as measures of predictability. We then tested how strongly uniqueness was determined by various site characteristics, including climatology, vegetation type, and data quality. The strongest determinant of predictability appeared to be that drier sites tended to be more unique. We found very few other clear predictors of uniqueness across different sites, in particular little evidence that flux behaviour was well discretised by vegetation type. Data length and quality also appeared to have little impact on uniqueness. While this result might relate to our definition of uniqueness, we argue that our approach provides a useful basis for site selection in LSM evaluation, and we invite critique and development of the methodology.
Using Machine Learning to Reveal the Relationships Between Plant Functional Traits and Flux Regimes at Eddy-Covariance Towers
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-10049
Abstract: The current-generation of land surface models (LSMs) are powerful tools used in predictions of the future global climate and carbon cycle. Many of these LSMs are parametrised using plant functional types (PFTs), often of a coarse nature with only relatively few possible groups. In turn, extensive use of eddy-covariance data is utilised when calibrating these LSMs, with the model PFT matched to the classification reported by the site owners. Importantly, the PFT group is one of the few site characteristics that is consistently supplied across FLUXNET sites. However, there are issues with this method of LSM calibration. It is well-known that many PFT classification schemes cannot be predicted from climate, and that traits may vary more within species or sites than between them. Here we present our results assessing the suitability of PFTs for capturing site flux regimes using a suite of machine learning techniques. We explore natural groupings of sites based on the measurements used for LSM calibration and identify potential site characteristics and traits that might allow these natural groupings to be predicted. Our results identify driving characteristics of site flux regime differences, and can be used to direct LSM development and highlight priority locations for future eddy-covariance flux towers.
Does predictability of fluxes vary between FLUXNET sites?
Publisher: Copernicus GmbH
Date: 20-04-2018
DOI: 10.5194/BG-2018-179
Abstract: Abstract. The FLUXNET dataset contains eddy covariance measurements from across the globe, and represents an invaluable estimate of the fluxes of energy, water and carbon between the land surface and the atmosphere. While there is an expectation that the broad range of site characteristics in FLUXNET result in a ersity of flux behaviour, there has been little exploration of how predictable site behaviour is across the network. Aside from intrinsic interest in this fundamental question, understanding site predictability would be useful for land surface model (LSM) evaluation in setting a priori expectations of model performance. It would also provide a clear rationale for selecting particular FLUXNET sites for model development, evaluation and benchmarking. Here, 155 datasets with 30 minute temporal resolution from the Tier 1 of FLUXNET2015 were analysed in a first attempt to assess in idual site predictability. Predictability was defined using the disparity between the ability to simulate fluxes at a site given specific knowledge of the site, and the ability to simulate fluxes given general land surface specifications. We then examined predictability using performance metrics including RMSE, correlation, and probability density overlap, and defined site uniqueness as the disparity between multiple empirical models trained globally and locally for each site. A number of hypotheses potentially explaining site predictability were then tested, including climatology, data quality and site characteristics. We found very few clear predictors of uniqueness across different sites including little evidence that flux behaviour is well discretised by vegetation types. While this result might relate to our definition of uniqueness, we argue that our approach is sound and provides a useful basis for site selection in LSM evaluation.
Can we model forest demography globally? Benchmarking of state-of-the-art Demographic DGVMs
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-14120
Abstract: Forests in Dynamic Global Vegetation Models (DGVMs) have historically been simulated as area-averaged plant functional types in each gridcell instead of representing communities of trees of different sizes and ages (demography). Just as the behaviour of a tree differs according to its ontogeny, so the behaviour of forests is known to differ depending on their demography. Accurately simulating demography is therefore key in order to address questions on afforestation and management strategies, as well as assessments of resilience of forests to disturbances such as drought and fire or ersity changes after a disturbance. Ultimately, demography determines the overall forest biomass in natural forests and is a key arbiter of growth and mortality rates. DGVMs are now able to simulate size and age structure of the trees in forests.& However, these models have so far not been benchmarked alongside each other.We evaluate 6 DGVMs (BiomeE, CABLE-POP, FATES, LPJ-GUESS, JULES-RED, ORCHIDEE) against observations on regrowth dynamics as well as natural forests at boreal, temperate and tropical sites. We examine whether the models capture observed regrowth dynamics after disturbance, well-known stand size structure and well-established processes such as self-thinning. We outline the planned route forward towards a standardised international benchmarking framework for demographic DGVMs.
Evaluating a land surface model at a water-limited site: implications for land surface contributions to droughts and heatwaves
Publisher: Copernicus GmbH
Date: 03-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-4083
Abstract: & & Land surface models underpin coupled climate model projections of droughts and heatwaves. However, the lack of simultaneous observations of in idual components of evapotranspiration, concurrent with root-zone soil moisture, has limited previous model evaluations. Here, we use a comprehensive set of observations from a water-limited site in southeastern Australia including both evapotranspiration and soil moisture to a depth of 4.5 m to evaluate the Community Atmosphere-Biosphere Land Exchange (CABLE) land surface model. We demonstrate that alternative process representations within CABLE had the capacity to improve simulated evapotranspiration, but not necessarily soil moisture dynamics - highlighting problems of model evaluations against water fluxes alone. Our best simulation was achieved by resolving a soil evaporation bias a more realistic initialisation of the groundwater aquifer state higher vertical soil resolution informed by observed soil properties and further calibrating soil hydraulic conductivity. Despite these improvements, the role of the empirical soil moisture stress function in influencing the simulated water fluxes remained important: using a site calibrated function reduced the soil water stress on plants by 36 % during drought and 23 % at other times. These changes in CABLE not only improve the seasonal cycle of evapotranspiration, but also affect the latent and sensible heat fluxes during droughts and heatwaves. The range of parameterisations tested led to differences of ~150 W m& sup& -2& /sup& in the simulated latent heat flux during a heatwave, implying a strong impact of parameterisations on the capacity for evaporative cooling and feedbacks to the boundary layer (when coupled). Overall, our results highlight the opportunity to advance the capability of land surface models to capture water cycle processes, particularly during meteorological extremes, when sufficient observations of both evapotranspiration fluxes and soil moisture profiles are available.& &
Biogeochemistry: Carbon dioxide and water use in forests
Publisher: Springer Science and Business Media LLC
Date: 07-2013
DOI: 10.1038/NATURE12411
Anthropogenic climate change has driven over 5 million km2 of drylands towards desertification
Publisher: Springer Science and Business Media LLC
Date: 31-07-2020
DOI: 10.1038/S41467-020-17710-7
Abstract: Drylands cover 41% of the earth’s land surface and include 45% of the world’s agricultural land. These regions are among the most vulnerable ecosystems to anthropogenic climate and land use change and are under threat of desertification. Understanding the roles of anthropogenic climate change, which includes the CO 2 fertilization effect, and land use in driving desertification is essential for effective policy responses but remains poorly quantified with methodological differences resulting in large variations in attribution. Here, we perform the first observation-based attribution study of desertification that accounts for climate change, climate variability, CO 2 fertilization as well as both the gradual and rapid ecosystem changes caused by land use. We found that, between 1982 and 2015, 6% of the world’s drylands underwent desertification driven by unsustainable land use practices compounded by anthropogenic climate change. Despite an average global greening, anthropogenic climate change has degraded 12.6% (5.43 million km 2 ) of drylands, contributing to desertification and affecting 213 million people, 93% of who live in developing economies.
Using ecosystem experiments to improve vegetation models
Publisher: Springer Science and Business Media LLC
Date: 21-05-2015
DOI: 10.1038/NCLIMATE2621
Examining the sensitivity of the terrestrial carbon cycle to the expression of El Niño
Publisher: Copernicus GmbH
Date: 25-03-2021
Abstract: Abstract. The El Niño‐-Southern Oscillation (ENSO) influences the global climate and the variability in the terrestrial carbon cycle on interannual timescales. Two different expressions of El Niño have recently been identified: (i) central Pacific (CP) and (ii) eastern Pacific (EP). Both types of El Niño are characterised by above-average sea surface temperature anomalies at the respective locations. Studies exploring the impact of these expressions of El Niño on the carbon cycle have identified changes in the litude of the concentration of interannual atmospheric carbon dioxide (CO2) variability following increased tropical near-surface air temperature and decreased precipitation. We employ the dynamic global vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator) within a synthetic experimental framework to examine the sensitivity and potential long-term impacts of these two expressions of El Niño on the terrestrial carbon cycle. We manipulated the occurrence of CP and EP events in two climate reanalysis datasets during the latter half of the 20th and early 21st century by replacing all EP with CP and separately all CP with EP El Niño events. We found that the different expressions of El Niño affect interannual variability in the terrestrial carbon cycle. However, the effect on longer timescales was small for both climate reanalysis datasets. We conclude that capturing any future trends in the relative frequency of CP and EP El Niño events may not be critical for robust simulations of the terrestrial carbon cycle.
Xylem embolism refilling and resilience against drought‐induced mortality in woody plants: processes and trade‐offs
Publisher: Wiley
Date: 10-03-2018
Decadal biomass increment in early secondary succession woody ecosystems is increased by CO2 enrichment
Publisher: Springer Science and Business Media LLC
Date: 14-02-2019
DOI: 10.1038/S41467-019-08348-1
Abstract: 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.
The multi-assumption architecture and testbed (MAAT v1.0): R code for generating ensembles with dynamic model structure and analysis of epistemic uncertainty from multiple sources
Publisher: Copernicus GmbH
Date: 10-08-2018
Abstract: Abstract. 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 post hoc, incompletely, informally, or is ignored. In this model description paper we present the multi-assumption architecture and testbed (MAAT v1.0) designed to formally and completely analyse process-representation-based epistemic uncertainty. MAAT is a modular modelling code that can simply and efficiently vary model structure (process representation), allowing for the generation and running of large model ensembles that vary in process representation, parameters, parameter values, and environmental conditions during a single execution of the code. MAAT v1.0 approaches epistemic uncertainty through sensitivity analysis, assigning variability in model output to processes (process representation and parameters) or to in idual parameters. In this model description paper we describe MAAT and, by using a simple groundwater model ex le, 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. In the Appendix we describe the photosynthesis model and the unification of multiple representations of photosynthetic processes. The numerical solution to leaf-scale photosynthesis is verified and ex les 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 specific system model employed. Therefore MAAT provides a tool for the development of novel or toy models in many domains, i.e. not only photosynthesis, facilitating rapid informal and formal comparison of alternative modelling approaches.
Improvement of modelling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements
Publisher: Copernicus GmbH
Date: 24-09-2020
DOI: 10.5194/GMD-2020-273
Abstract: Abstract. Drought is predicted to increase in the future due to climate change, bringing with it a myriad of impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance, in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local/regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales, and evaluated ten different representations of stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high latitudes/cold region sites, while LE was best simulated in temperate and high latitude/cold sites. Errors not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savannah and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14, and the soil depth from 3m to 10.8m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation, when the onset of stress was delayed, and when roots extended deeper into the soil. For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and made the simulation worse. Further evaluation into the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress.
Evaluating a land surface model at a water-limited site: implications for land surface contributions to droughts and heatwaves
Publisher: Copernicus GmbH
Date: 10-07-2020
Abstract: Abstract. Land surface models underpin coupled climate model projections of droughts and heatwaves. However, the lack of simultaneous observations of in idual components of evapotranspiration, concurrent with root-zone soil moisture, has limited previous model evaluations. Here, we use a comprehensive set of observations from a water-limited site in southeastern Australia including both evapotranspiration and soil moisture to 4.5 m depth to evaluate the Community Atmosphere-Biosphere Land Exchange (CABLE) land surface model. We demonstrated that alternative process representations within CABLE had the capacity to improve simulated evapotranspiration, but not necessarily soil moisture dynamics – highlighting problems of model evaluations against water fluxes alone. Our best simulation was achieved by resolving a soil evaporation bias a more realistic initialisation of the groundwater aquifer state higher vertical soil resolution informed by observed soil properties and further calibrating soil hydraulic conductivity. Despite these improvements, the role of the empirical soil moisture stress function in simulated water fluxes remained important: using a site calibrated function reduced the median level of water stress by 36 % during drought and 23 % at other times. These changes in CABLE not only improve the seasonal cycle of evapotranspiration, but also affect the latent and sensible heat fluxes during droughts and heatwaves. Alternative parameterisations led to differences of ~ 150 W m−2 in the simulated latent heat flux during a heatwave, implying a strong impact of parameterisations on the capacity for evaporative cooling and feedbacks to the boundary layer (when coupled). Overall, our results highlight the opportunity to advance the capability of land surface models to capture water cycle processes, particularly during meteorological extremes, when sufficient observations of both evapotranspiration fluxes and soil moisture profiles are available.
Supplementary material to "Does predictability of fluxes vary between FLUXNET sites?"
Publisher: Copernicus GmbH
Date: 20-04-2018
Opening Pandora's box: How to constrain regional projections of the carbon cycle
Publisher: Copernicus GmbH
Date: 18-07-2022
DOI: 10.5194/EGUSPHERE-2022-623
Abstract: Abstract. Climate projections from global circulation models (GCMs) part of the Coupled Model Intercomparison Project 6 (CMIP6) are often employed to study the impact of future climate on ecosystems. However, especially at regional scales, climate projections display large biases in key forcing variables such as temperature and precipitation, which h er predictive capacity. In this study we examine different methods to constrain regional projections of the carbon cycle in Australia. We employ a dynamic global vegetation model (LPJ-GUESS) and force it with raw output from CMIP6 to assess the uncertainty associated with the choice of climate forcing. We then test different methods to either bias correct or calculate ensemble averages over the original forcing data to constrain the uncertainty in the regional projection of the Australian carbon cycle. We find that all bias correction methods reduce the bias of continental averages of steady-state carbon variables. Carbon pools are insensitive to the type of bias correction method applied for both in idual GCMs and the arithmetic ensemble average across all corrected models. None of the bias correction methods consistently improve the change in carbon over time, highlighting the need to account for temporal properties in correction or ensemble averaging methods. Some bias correction methods reduce the ensemble uncertainty more than others. The vegetation distribution can depend on the bias correction method used. We further find that both the weighted ensemble averaging and random forest approach reduce the bias in total ecosystem carbon to almost zero, clearly outperforming the arithmetic ensemble averaging method. The random forest approach also produces the results closest to the target dataset for the change in the total carbon pool, seasonal carbon fluxes, emphasizing that machine learning approaches are promising tools for future studies.
Limited Evidence of Cumulative Effects From Recurrent Droughts in Vegetation Responses to Australia's Millennium Drought
Publisher: American Geophysical Union (AGU)
Date: 05-2023
DOI: 10.1029/2022JG006818
Abstract: Drought‐induced vegetation declines have been reported across the globe and may have widespread implications for ecosystem composition, structure, and functions. Thus, it is critical to maximizing our understanding of how vegetation has responded to recent drought extremes. To date, most drought assessments emphasized the importance of drought intensity for vegetation responses. However, drought timing, duration, and repeat exposure all may be important aspects of ecosystem response with the potential for non‐linear effects. Cumulative effects are one such phenomenon, representing the additional decline due to repeated exposure to drought, and indicating gradual loss of ecosystem resistance. This study quantifies the frequency and magnitude of cumulative effects among Australian ecosystems as they responded to the Millennium Drought. Three distinct biophysical variables derived from satellite remote sensing were analyzed, including fraction of photosynthetically absorbed radiation, photosynthetic vegetation cover, and canopy density derived from passive microwave data. Cumulative effects were detected in only 8%–20% of the fire‐free landscape exposed to repeat or long‐duration drought, and could be a statistical artifact. In those limited cases, they approximately doubled drought impacts on leaf abundance, canopy cover, and vegetation density. Cultivated lands and grasslands were the most susceptible to cumulative effects, losing resistance to recurrent droughts, but could be false discovery. Despite being relatively infrequent in forests and savannas, cumulative effects caused larger additional declines in these ecosystems. Overall, our study demonstrates that repeated exposure appears to have limited influence on the magnitude of drought impacts on canopy structure affecting only a few areas.
Desiccation time during drought is highly predictable across species of Eucalyptus from contrasting climates
Publisher: Wiley
Date: 08-08-2019
DOI: 10.1111/NPH.16042
Abstract: Catastrophic failure of the water transport pathway in trees is a principal mechanism of mortality during extreme drought. To be able to predict the probability of mortality at an in idual and landscape scale we need knowledge of the time for plants to reach critical levels of hydraulic failure. We grew plants of eight species of Eucalyptus originating from contrasting climates before allowing a subset to dehydrate. We tested whether a trait-based model of time to plant desiccation t
Do land surface models need to include differential plant species responses to drought? Examining model predictions across a latitudinal gradient in Europe
Publisher: Copernicus GmbH
Date: 06-08-2015
DOI: 10.5194/BGD-12-12349-2015
Abstract: Abstract. Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models, realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSM and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the northernmost sites, and low drought sensitivity at the southernmost sites, was necessary to accurately model responses during drought. Our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.
How representative are FLUXNET measurements of surface fluxes during temperature extremes?
Publisher: Copernicus GmbH
Date: 20-12-2018
DOI: 10.5194/BG-2018-502
Abstract: Abstract. In response to a warming climate, temperature extremes are changing in many regions of the world. Therefore, understanding how the fluxes of sensible heat, latent heat and net ecosystem exchange respond and contribute to these changes is important. We examined 216 sites from the open access Tier 1 FLUXNET2015 and Free-Fair-Use La Thuile datasets, focussing only on observed (non-gap filled) data periods. We examined the availability of sensible heat, latent heat and net ecosystem exchange observations coincident in time with measured temperature for all temperatures, and separately for the upper and lower tail of the temperature distribution and expressed this availability as a measurement ratio. We showed that the measurement ratios for both sensible and latent heat fluxes are generally lower (0.79 and 0.73 respectively) than for temperature, and the measurement ratio of net ecosystem exchange measurements are appreciably lower (0.42). However, sites do exist with a high proportion of measured sensible and latent heat fluxes, mostly over the United States, Europe and Australia. Few sites have a high proportion of measured fluxes at the lower tail of the temperature distribution over very cold regions (e.g. Alaska, Russia) and at the upper tail in many warm regions (e.g. Central America and the majority of the Mediterranean region), and many of the world’s coldest and hottest regions are not represented in the freely available FLUXNET data at all (e.g. India, the Gulf States, Greenland and Antarctica). However, some sites do provide measured fluxes at extreme temperatures suggesting an opportunity for the FLUXNET community to share strategies to increase measurement availability at the tails of the temperature distribution. We also highlight a wide discrepancy between the measurement ratios across FLUXNET sites that is not related to the actual temperature or rainfall regimes at the site, which we cannot explain. Our analysis provides guidance to help select eddy covariance sites for researchers interested in exploring responses to temperature extremes.
Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements
Publisher: Copernicus GmbH
Date: 03-06-2021
Abstract: Abstract. Drought is predicted to increase in the future due to climate change, bringing with it myriad impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local and regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales and evaluated 10 different representations of soil moisture stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high-latitude (cold-region) sites, while LE was best simulated in temperate and high-latitude (cold) sites. Errors that were not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savanna and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14 and the soil depth from 3.0 to 10.8 m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation (the “soil14_psi” experiments), when the critical threshold value for inducing soil moisture stress was reduced (“soil14_p0”), and when plants were able to access soil moisture in deeper soil layers (“soil14_dr*2”). For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and increased model biases but improved the simulated seasonal cycle and brought the monthly variance closer to the measured variance of LE. Further evaluation of the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES or as a general way to improve land surface carbon and water fluxes in other models. In addition, using soil matric potential presents the opportunity to include plant functional type-specific parameters to further improve modeled fluxes.
Assessing the representation of the Australian carbon cycle in global vegetation models
Publisher: Copernicus GmbH
Date: 15-03-2021
DOI: 10.5194/BG-2021-66
Abstract: Abstract. Australia plays an important role in the global terrestrial carbon cycle on inter-annual timescales. While the Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations of net biome production (NBP) and the carbon stored in vegetation between 1901 to 2018 from 13 DGVMs (TRENDY v8 ensemble). We focused our analysis on both Australia's short-term (inter-annual) and long-term (decadal to centennial) terrestrial carbon dynamics. The TRENDY models simulated differing magnitudes of NBP on inter-annual timescales, and these differences contributed to carbon accumulation in the vegetation on decadal to centennial timescales (−4.7–9.5 PgC). We compared the TRENDY ensemble to several satellite-derived datasets and showed that the spread in the models' simulated carbon storage resulted from varying changes in carbon residence time rather than differences in net carbon uptake. Differences in simulated long-term accumulated NBP between models were mostly due to model responses to land-use change. The DGVMs also simulated different sensitivities to atmospheric carbon dioxide (CO2) concentration, although notably, the models with nutrient cycles did not simulate the smallest NBP response to CO2. Our results suggest that a change in the climate forcing did not have a large impact on the carbon cycle on long timescales. However, the inter-annual variability in precipitation drives the year-to-year variability in NBP. We analysed the impact of key modes of climate variability, including the El Nino Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on NBP. While the DGVMs agreed on sign of the response of NBP to El Nino and La Nina, and to positive and negative IOD events, the magnitude of inter-annual variability in NBP differed strongly between models. In addition, we identified differences in the timing of simulated phenology and fire dynamics associated with differences in simulated rescribed vegetation composition and process representation. Model disagreement in simulated vegetation carbon, phenology and apparent carbon residence time, indicates the models have different types of vegetation cover across Australia (whether prescribed or emergent). Our study highlights the need to evaluate parameter assumptions and the key processes that drive vegetation dynamics, such as phenology, mortality and fire, in an Australian context to reduce uncertainty across models.
Supplementary material to "Evaluating a land surface model at a water-limited site: implications for land surface contributions to droughts and heatwaves"
Publisher: Copernicus GmbH
Date: 10-07-2020
Assessing the potential for crop albedo enhancement in reducing heatwave frequency, duration, and intensity under future climate change
Publisher: Elsevier BV
Date: 03-2022
Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand?
Publisher: Wiley
Date: 18-03-2020
DOI: 10.1111/GCB.15024
How representative are FLUXNET measurements of surface fluxes during temperature extremes?
Publisher: Copernicus GmbH
Date: 30-04-2019
Abstract: Abstract. In response to a warming climate, temperature extremes are changing in many regions of the world. Therefore, understanding how the fluxes of sensible heat, latent heat and net ecosystem exchange respond and contribute to these changes is important. We examined 216 sites from the open access Tier 1 FLUXNET2015 and free fair-use La Thuile data sets, focussing only on observed (non-gap-filled) data periods. We examined the availability of sensible heat, latent heat and net ecosystem exchange observations coincident in time with measured temperature for all temperatures, and separately for the upper and lower tail of the temperature distribution, and expressed this availability as a measurement ratio. We showed that the measurement ratios for both sensible and latent heat fluxes are generally lower (0.79 and 0.73 respectively) than for temperature measurements, and the measurement ratio of net ecosystem exchange measurements are appreciably lower (0.42). However, sites do exist with a high proportion of measured sensible and latent heat fluxes, mostly over the United States, Europe and Australia. Few sites have a high proportion of measured fluxes at the lower tail of the temperature distribution over very cold regions (e.g. Alaska, Russia) or at the upper tail in many warm regions (e.g. Central America and the majority of the Mediterranean region), and many of the world's coldest and hottest regions are not represented in the freely available FLUXNET data at all (e.g. India, the Gulf States, Greenland and Antarctica). However, some sites do provide measured fluxes at extreme temperatures, suggesting an opportunity for the FLUXNET community to share strategies to increase measurement availability at the tails of the temperature distribution. We also highlight a wide discrepancy between the measurement ratios across FLUXNET sites that is not related to the actual temperature or rainfall regimes at the site, which we cannot explain. Our analysis provides guidance to help select eddy covariance sites for researchers interested in understanding and/or modelling responses to temperature extremes.
Supplementary material to "Low sensitivity of gross primary production to elevated CO<sub>2</sub> in a mature Eucalypt woodland"
Publisher: Copernicus GmbH
Date: 31-07-2019
Patterns of post‐drought recovery are strongly influenced by drought duration, frequency, post‐drought wetness, and bioclimatic setting
Publisher: Wiley
Date: 18-07-2021
DOI: 10.1111/GCB.15788
Abstract: Understanding vegetation recovery after drought is critical for projecting vegetation dynamics in future climates. From 1997 to 2009, Australia experienced a long‐lasting drought known as the Millennium Drought (MD), which led to widespread reductions in vegetation productivity. However, vegetation recovery post‐drought and its determinants remain unclear. This study leverages remote sensing products from different sources—fraction of absorbed photosynthetically active radiation (FPAR), based on optical data, and canopy density, derived from microwave data—and random forest algorithms to assess drought recovery over Australian natural vegetation during a 20‐year period centered on the MD. Post‐drought recovery was prevalent across the continent, with 6 out of 10 drought events seeing full recovery within about 6 months. Canopy density was slower to recover than leaf area seen in FPAR. The probability of full recovery was most strongly controlled by drought return interval, post‐drought hydrological condition, and drought length. Full recovery was seldom observed when drought events occurred at intervals of 3 months or less, and moderately dry (standardized water balance anomaly [SWBA] within [−1, −0.76]) post‐drought conditions resulted in less complete recovery than wet (SWBA 0.3) post‐drought conditions. Press droughts, which are long term but not extreme, delayed recovery more than pulse droughts (short term but extreme) and led to a higher frequency of persistent decline. Following press droughts, the frequency of persistent decline differed little among biome types but peaked in semi‐arid regions across aridity levels. Forests and savanna required the longest recovery times for press drought, while grasslands were the slowest to recover for pulse drought. This study provides quantitative thresholds that could be used to improve the modeling of ecosystem dynamics post‐drought.
One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models
Publisher: American Geophysical Union (AGU)
Date: 04-2022
DOI: 10.1029/2021MS002761
Abstract: Stomatal conductance schemes that optimize with respect to photosynthetic and hydraulic functions have been proposed to address biases in land‐surface model (LSM) simulations during drought. However, systematic evaluations of both optimality‐based and alternative empirical formulations for coupling carbon and water fluxes are lacking. Here, we embed 12 empirical and optimization approaches within a LSM framework. We use theoretical model experiments to explore parameter identifiability and understand how model behaviors differ in response to abiotic changes. We also evaluate the models against leaf‐level observations of gas‐exchange and hydraulic variables, from xeric to wet forest/woody species spanning a mean annual precipitation range of 361–3,286 mm yr −1 . We find that models differ in how easily parameterized they are, due to: (a) poorly constrained optimality criteria (i.e., resulting in multiple solutions), (b) low influence parameters, (c) sensitivities to environmental drivers. In both the idealized experiments and compared to observations, sensitivities to variability in environmental drivers do not agree among models. Marked differences arise in sensitivities to soil moisture (soil water potential) and vapor pressure deficit. For ex le, stomatal closure rates at high vapor pressure deficit range between −45% and +70% of those observed. Although over half the new generation of stomatal schemes perform to a similar standard compared to observations of leaf‐gas exchange, two models do so through large biases in simulated leaf water potential (up to 11 MPa). Our results provide guidance for LSM development, by highlighting key areas in need for additional experimentation and theory, and by constraining currently viable stomatal hypotheses.
New developments in the effort to model ecosystems under water stress
Publisher: Wiley
Date: 25-08-2016
DOI: 10.1111/NPH.14082
Challenging terrestrial biosphere models with data from the long‐term multifactor Prairie Heating and CO 2 Enrichment experiment
Publisher: Wiley
Date: 06-03-2017
DOI: 10.1111/GCB.13643
Abstract: Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single-factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO
Supplementary material to "Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts"
Publisher: Copernicus GmbH
Date: 06-05-2021
Supplementary material to "Modelling evapotranspiration during precipitation deficits: identifying critical processes in a land surface model"
Publisher: Copernicus GmbH
Date: 21-10-2015
Convergence in phosphorus constraints to photosynthesis in forests around the world
Publisher: Springer Science and Business Media LLC
Date: 25-08-2022
DOI: 10.1038/S41467-022-32545-0
Abstract: Tropical forests take up more carbon (C) from the atmosphere per annum by photosynthesis than any other type of vegetation. Phosphorus (P) limitations to C uptake are paramount for tropical and subtropical forests around the globe. Yet the generality of photosynthesis-P relationships underlying these limitations are in question, and hence are not represented well in terrestrial biosphere models. Here we demonstrate the dependence of photosynthesis and underlying processes on both leaf N and P concentrations. The regulation of photosynthetic capacity by P was similar across four continents. Implementing P constraints in the ORCHIDEE-CNP model, gross photosynthesis was reduced by 36% across the tropics and subtropics relative to traditional N constraints and unlimiting leaf P. Our results provide a quantitative relationship for the P dependence for photosynthesis for the front-end of global terrestrial C models that is consistent with canopy leaf measurements.
A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas
Publisher: Copernicus GmbH
Date: 03-06-2016
Abstract: Abstract. The savanna ecosystem is one of the most dominant and complex terrestrial biomes, deriving from a distinct vegetative surface comprised of co-dominant tree and grass populations. While these two vegetation types co-exist functionally, demographically they are not static but are dynamically changing in response to environmental forces such as annual fire events and rainfall variability. Modelling savanna environments with the current generation of terrestrial biosphere models (TBMs) has presented many problems, particularly describing fire frequency and intensity, phenology, leaf biochemistry of C3 and C4 photosynthesis vegetation, and root-water uptake. In order to better understand why TBMs perform so poorly in savannas, we conducted a model inter-comparison of six TBMs and assessed their performance at simulating latent energy (LE) and gross primary productivity (GPP) for five savanna sites along a rainfall gradient in northern Australia. Performance in predicting LE and GPP was measured using an empirical benchmarking system, which ranks models by their ability to utilise meteorological driving information to predict the fluxes. On average, the TBMs performed as well as a multi-linear regression of the fluxes against solar radiation, temperature and vapour pressure deficit but were outperformed by a more complicated nonlinear response model that also included the leaf area index (LAI). This identified that the TBMs are not fully utilising their input information effectively in determining savanna LE and GPP and highlights that savanna dynamics cannot be calibrated into models and that there are problems in underlying model processes. We identified key weaknesses in a model's ability to simulate savanna fluxes and their seasonal variation, related to the representation of vegetation by the models and root-water uptake. We underline these weaknesses in terms of three critical areas for development. First, prescribed tree-rooting depths must be deep enough, enabling the extraction of deep soil-water stores to maintain photosynthesis and transpiration during the dry season. Second, models must treat grasses as a co-dominant interface for water and carbon exchange rather than a secondary one to trees. Third, models need a dynamic representation of LAI that encompasses the dynamic phenology of savanna vegetation and its response to rainfall interannual variability. We believe that this study is the first to assess how well TBMs simulate savanna ecosystems and that these results will be used to improve the representation of savannas ecosystems in future global climate model studies.
Thirty-eight years of CO<sub>2</sub> fertilization have outpaced growing aridity to drive greening of Australian woody ecosystems
Publisher: Copernicus GmbH
Date: 23-08-2021
DOI: 10.5194/BG-2021-218
Abstract: Abstract. 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.
Modelling evapotranspiration during precipitation deficits: identifying critical processes in a land surface model
Publisher: Copernicus GmbH
Date: 21-10-2015
DOI: 10.5194/HESSD-12-10789-2015
Abstract: Abstract. Surface fluxes from land surface models (LSM) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat flux simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual time scales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux are explored by employing alternative representations of hydrology, leaf area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance are shown to be highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions but remaining biases point to future research needs. Our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.
Plant profit maximization improves predictions of European forest responses to drought
Publisher: Wiley
Date: 27-01-2020
DOI: 10.1111/NPH.16376
Abstract: Knowledge of how water stress impacts the carbon and water cycles is a key uncertainty in terrestrial biosphere models. We tested a new profit maximization model, where photosynthetic uptake of CO
Supplementary material to "Improvement of modelling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements"
Publisher: Copernicus GmbH
Date: 24-09-2020
Evaluating the Contribution of Land-Atmosphere Coupling to Heat Extremes in CMIP5 Models
Publisher: American Geophysical Union (AGU)
Date: 05-09-2018
DOI: 10.1029/2018GL079102
Exploring the role of lags and legacies in the productivity of Australian ecosystems
Publisher: Copernicus GmbH
Date: 03-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-3684
Abstract: & & The vegetation& #8217 s response to climate change is a major source of uncertainty in terrestrial biosphere model (TBM) projections. Constraining carbon cycle feedbacks to climate change requires improving our understanding of both the direct plant physiological responses to global change, as well as the role of legacy effects (e.g. reductions in plant growth, damage to the plant& #8217 s hydraulic transport system), that drive multi-timescale feedbacks. In particular, the role of these legacy effects - both the timescale and strength of the memory effect - have been largely overlooked in the development of model hypotheses. This is despite the knowledge that plant responses to climatic drivers occur across multiple time scales (seconds to decades), with the impact of climate extremes (e.g. drought) resonating for many years. Using data from 13 eddy covariance sites, covering two rainfall gradients in Australia, in combination with a hierarchical Bayesian model, we characterised the timescales of influence of antecedent drivers on fluxes of net carbon exchange and evapotranspiration. Using our data assimilation approach we were able to partition the influence of ecological memory into both biological and environmental components. Overall, we found that the importance of ecological memory to antecedent conditions increased as water availability declines. Our results therefore underline the importance of capturing legacy effects in TBMs used to project responses in water limited ecosystems.& &
Evaluation of 11 terrestrial carbon–nitrogen cycle models against observations from two temperate F ree‐A ir CO 2 E nrichment studies
Publisher: Wiley
Date: 28-01-2014
DOI: 10.1111/NPH.12697
Abstract: We analysed the responses of 11 ecosystem models to elevated atmospheric [ CO 2 ] (e CO 2 ) at two temperate forest ecosystems ( D uke and Oak Ridge National Laboratory ( ORNL ) F ree‐ A ir CO 2 E nrichment ( 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 e CO 2 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 D uke 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 e CO 2 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 eCO 2 , given the complexity of factors leading to the observed erging 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.
When things get MESI: The Manipulation Experiments Synthesis Initiative—A coordinated effort to synthesize terrestrial global change experiments
Publisher: Wiley
Date: 16-01-2023
DOI: 10.1111/GCB.16585
Abstract: Responses of the terrestrial biosphere to rapidly changing environmental conditions are a major source of uncertainty in climate projections. In an effort to reduce this uncertainty, a wide range of global change experiments have been conducted that mimic future conditions in terrestrial ecosystems, manipulating CO 2 , temperature, and nutrient and water availability. Syntheses of results across experiments provide a more general sense of ecosystem responses to global change, and help to discern the influence of background conditions such as climate and vegetation type in determining global change responses. Several independent syntheses of published data have yielded distinct databases for specific objectives. Such parallel, uncoordinated initiatives carry the risk of producing redundant data collection efforts and have led to contrasting outcomes without clarifying the underlying reason for ergence. These problems could be avoided by creating a publicly available, updatable, curated database. Here, we report on a global effort to collect and curate 57,089 treatment responses across 3644 manipulation experiments at 1145 sites, simulating elevated CO 2 , warming, nutrient addition, and precipitation changes. In the resulting Manipulation Experiments Synthesis Initiative (MESI) database, effects of experimental global change drivers on carbon and nutrient cycles are included, as well as ancillary data such as background climate, vegetation type, treatment magnitude, duration, and, unique to our database, measured soil properties. Our analysis of the database indicates that most experiments are short term (one or few growing seasons), conducted in the USA, Europe, or China, and that the most abundantly reported variable is aboveground biomass. We provide the most comprehensive multifactor global change database to date, enabling the research community to tackle open research questions, vital to global policymaking. The MESI database, freely accessible at 0.5281/zenodo.7153253 , opens new avenues for model evaluation and synthesis‐based understanding of how global change affects terrestrial biomes. We welcome contributions to the database on GitHub.
The quasi-equilibrium framework revisited: analyzing long-term CO<sub>2</sub> enrichment responses in plant–soil models
Publisher: Copernicus GmbH
Date: 28-05-2019
Abstract: Abstract. Elevated carbon dioxide (CO2) can increase plant growth, but the magnitude of this CO2 fertilization effect is modified by soil nutrient availability. Predicting how nutrient availability affects plant responses to elevated CO2 is a key consideration for ecosystem models, and many modeling groups have moved to, or are moving towards, incorporating nutrient limitation in their models. The choice of assumptions to represent nutrient cycling processes has a major impact on model predictions, but it can be difficult to attribute outcomes to specific assumptions in complex ecosystem simulation models. Here we revisit the quasi-equilibrium analytical framework introduced by Comins and McMurtrie (1993) and explore the consequences of specific model assumptions for ecosystem net primary productivity (NPP). We review the literature applying this framework to plant–soil models and then analyze the effect of several new assumptions on predicted plant responses to elevated CO2. Examination of alternative assumptions for plant nitrogen uptake showed that a linear function of the mineral nitrogen pool or a linear function of the mineral nitrogen pool with an additional saturating function of root biomass yield similar CO2 responses at longer timescales ( years), suggesting that the added complexity may not be needed when these are the timescales of interest. In contrast, a saturating function of the mineral nitrogen pool with linear dependency on root biomass yields no soil nutrient feedback on the very-long-term ( years), near-equilibrium timescale, meaning that one should expect the model to predict a full CO2 fertilization effect on production. Secondly, we show that incorporating a priming effect on slow soil organic matter decomposition attenuates the nutrient feedback effect on production, leading to a strong medium-term (5–50 years) CO2 response. Models incorporating this priming effect should thus predict a strong and persistent CO2 fertilization effect over time. Thirdly, we demonstrate that using a “potential NPP” approach to represent nutrient limitation of growth yields a relatively small CO2 fertilization effect across all timescales. Overall, our results highlight the fact that the quasi-equilibrium analytical framework is effective for evaluating both the consequences and mechanisms through which different model assumptions affect predictions. To help constrain predictions of the future terrestrial carbon sink, we recommend the use of this framework to analyze likely outcomes of new model assumptions before introducing them to complex model structures.
Low sensitivity of gross primary production to elevated CO<sub>2</sub> in a mature Eucalypt woodland
Publisher: Copernicus GmbH
Date: 31-07-2019
DOI: 10.5194/BG-2019-272
Abstract: Abstract. 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.
Retraction Note: A constraint on historic growth in global photosynthesis due to increasing CO2
Publisher: Springer Science and Business Media LLC
Date: 30-05-2022
Amazon forest response to CO2 fertilization dependent on plant phosphorus acquisition
Publisher: Springer Science and Business Media LLC
Date: 05-08-2019
Effects of mesophyll conductance on vegetation responses to elevated CO2 concentrations in a land surface model
Publisher: Wiley
Date: 23-03-2019
DOI: 10.1111/GCB.14604
Land surface models systematically overestimate the intensity, duration and magnitude of seasonal-scale evaporative droughts
Publisher: IOP Publishing
Date: 10-2016
A flux tower dataset tailored for land model evaluation
Publisher: Copernicus GmbH
Date: 28-07-2021
Abstract: Abstract. Eddy covariance flux towers measure the exchange of water, energy and carbon fluxes between the land and atmosphere. They have become invaluable for theory development and evaluating land models. However, flux tower data as measured (even after site post-processing) are not directly suitable for land surface modelling due to data gaps in model forcing variables, inappropriate gap-filling, formatting and varying data quality. Here we present a quality-control and data-formatting pipeline for tower data from FLUXNET2015, La Thuile and OzFlux syntheses and the resultant 170-site globally distributed flux tower dataset specifically designed for use in land modelling. The dataset underpins the second phase of the PLUMBER land surface model benchmarking evaluation project, an international model intercomparison project encompassing 20 land surface and biosphere models. The dataset is provided in the Assistance for Land-surface Modelling Activities (ALMA) NetCDF format and is CF-NetCDF compliant. For forcing land surface models, the dataset provides fully gap-filled meteorological data that has had periods of low data quality removed. Additional constraints required for land models, such as reference measurement heights, vegetation types and satellite-based monthly leaf area index estimates, are also included. For model evaluation, the dataset provides estimates of key water, carbon and energy variables, with the latent and sensible heat fluxes additionally corrected for energy balance closure. The dataset provides a total of 1040 site years covering the period 1992–2018, with in idual sites spanning from 1 to 21 years. The dataset is available at 0.25914/5fdb0902607e1 (Ukkola et al., 2021).
Challenges and opportunities in land surface modelling of savanna ecosystems
Publisher: Copernicus GmbH
Date: 24-10-2017
Abstract: Abstract. The savanna complex is a highly erse global biome that occurs within the seasonally dry tropical to sub-tropical equatorial latitudes and are structurally and functionally distinct from grasslands and forests. Savannas are open-canopy environments that encompass a broad demographic continuum, often characterised by a changing dominance between C3-tree and C4-grass vegetation, where frequent environmental disturbances such as fire modulates the balance between ephemeral and perennial life forms. Climate change is projected to result in significant changes to the savanna floristic structure, with increases to woody biomass expected through CO2 fertilisation in mesic savannas and increased tree mortality expected through increased rainfall interannual variability in xeric savannas. The complex interaction between vegetation and climate that occurs in savannas has traditionally challenged terrestrial biosphere models (TBMs), which aim to simulate the interaction between the atmosphere and the land surface to predict responses of vegetation to changing in environmental forcing. In this review, we examine whether TBMs are able to adequately represent savanna fluxes and what implications potential deficiencies may have for climate change projection scenarios that rely on these models. We start by highlighting the defining characteristic traits and behaviours of savannas, how these differ across continents and how this information is (or is not) represented in the structural framework of many TBMs. We highlight three dynamic processes that we believe directly affect the water use and productivity of the savanna system: phenology, root-water access and fire dynamics. Following this, we discuss how these processes are represented in many current-generation TBMs and whether they are suitable for simulating savanna fluxes.Finally, we give an overview of how eddy-covariance observations in combination with other data sources can be used in model benchmarking and intercomparison frameworks to diagnose the performance of TBMs in this environment and formulate road maps for future development. Our investigation reveals that many TBMs systematically misrepresent phenology, the effects of fire and root-water access (if they are considered at all) and that these should be critical areas for future development. Furthermore, such processes must not be static (i.e. prescribed behaviour) but be capable of responding to the changing environmental conditions in order to emulate the dynamic behaviour of savannas. Without such developments, however, TBMs will have limited predictive capability in making the critical projections needed to understand how savannas will respond to future global change.
RETRACTED ARTICLE: A constraint on historic growth in global photosynthesis due to increasing CO2
Publisher: Springer Science and Business Media LLC
Date: 08-12-2021
DOI: 10.1038/S41586-021-04096-9
Abstract: The global terrestrial carbon sink is increasing
Supplementary material to "Examining the Role of Environmental Memory in the Predictability of Carbon and Water Fluxes Across Australian Ecosystems"
Publisher: Copernicus GmbH
Date: 10-2021
Drought Impacts on Australian Vegetation During the Millennium Drought Measured With Multisource Spaceborne Remote Sensing
Publisher: American Geophysical Union (AGU)
Date: 02-2020
DOI: 10.1029/2019JG005145
The optimal stomatal response to atmospheric CO2 concentration: Alternative solutions, alternative interpretations
Publisher: Elsevier BV
Date: 12-2013
Related Organisations
University College London
Location: United Kingdom of Great Britain and Northern Ireland
University Of Bristol
Location: United Kingdom of Great Britain and Northern Ireland
Related Funding Activities
Discovery Projects - Grant ID: DP220100915
Start Date: 06-2022
End Date: 06-2025
Amount: $416,597.00
Funder: Australian Research Council
View Funded ActivityDiscovery Projects - Grant ID: DP190101823
Start Date: 05-2019
End Date: 09-2023
Amount: $430,000.00
Funder: Australian Research Council
View Funded Activity