Sun-induced fluorescence (SIF) in the far-red region provides a new noninvasive measurement approach that has the potential to quantify dynamic changes in light-use efficiency and gross primary ...production (GPP). However, the mechanistic link between GPP and SIF is not completely understood.
We analyzed the structural and functional factors controlling the emission of SIF at 760 nm (F760) in a Mediterranean grassland manipulated with nutrient addition of nitrogen (N), phosphorous (P) or nitrogen–phosphorous (NP). Using the soil–canopy observation of photosynthesis and energy (SCOPE) model, we investigated how nutrient-induced changes in canopy structure (i.e. changes in plant forms abundance that influence leaf inclination distribution function, LIDF) and functional traits (e.g. N content in dry mass of leaves, N%, Chlorophyll a+b concentration (Cab) and maximum carboxylation capacity (V
cmax)) affected the observed linear relationship between F760 and GPP.
We conclude that the addition of nutrients imposed a change in the abundance of different plant forms and biochemistry of the canopy that controls F760. Changes in canopy structure mainly control the GPP–F760 relationship, with a secondary effect of Cab and V
cmax.
In order to exploit F760 data to model GPP at the global/regional scale, canopy structural variability, biodiversity and functional traits are important factors that have to be considered.
The nitrogen cycle and its effect on carbon uptake in the
terrestrial biosphere is a recent progression in earth system models. As
with any new component of a model, it is important to understand the
...behaviour, strengths, and limitations of the various process
representations. Here we assess and compare five land surface models with
nitrogen cycles that are used as the terrestrial components of some of the
earth system models in CMIP6. The land surface models were run offline with
a common spin-up and forcing protocol. We use a historical control
simulation and two perturbations to assess the model nitrogen-related
performances: a simulation with atmospheric carbon dioxide increased by 200 ppm and one with nitrogen deposition increased by 50 kgN ha−1 yr−1. There is generally greater variability in productivity response
between models to increased nitrogen than to carbon dioxide. Across the five
models the response to carbon dioxide globally was 5 % to 20 % and the
response to nitrogen was 2 % to 24 %. The models are not evenly distributed
within the ensemble range, with two of the models having low productivity
response to nitrogen and another one with low response to elevated atmospheric
carbon dioxide, compared to the other models. In all five models individual
grid cells tend to exhibit bimodality, with either a strong response to
increased nitrogen or atmospheric carbon dioxide but rarely to both to an
equal extent. However, this local effect does not scale to either the
regional or global level. The global and tropical responses are generally
more accurately modelled than boreal, tundra, or other high-latitude areas
compared to observations. These results are due to divergent choices in the
representation of key nitrogen cycle processes. They show the need for more
observational studies to enhance understanding of nitrogen cycle processes,
especially nitrogen-use efficiency and biological nitrogen fixation.
Understanding the impacts of climate extremes on the carbon cycle is important for quantifying the carbon-cycle climate feedback and highly relevant to climate change assessments. Climate extremes ...and fires can have severe regional effects, but a spatially explicit global impact assessment is still lacking. Here, we directly quantify spatiotemporal contiguous extreme anomalies in four global data sets of gross primary production (GPP) over the last 30 years. We find that positive and negative GPP extremes occurring on 7% of the spatiotemporal domain explain 78% of the global interannual variation in GPP and a significant fraction of variation in the net carbon flux. The largest thousand negative GPP extremes during 1982-2011 (4.3% of the data) account for a decrease in photosynthetic carbon uptake of about 3.5 Pg C yr−1, with most events being attributable to water scarcity. The results imply that it is essential to understand the nature and causes of extremes to understand current and future GPP variability.
Including a terrestrial nitrogen (N) cycle in Earth system models has led to substantial attenuation of predicted biosphere-climate feedbacks. However, the magnitude of this attenuation remains ...uncertain. A particularly important but highly uncertain process is biological nitrogen fixation (BNF), which is the largest natural input of N to land ecosystems globally. In order to quantify this uncertainty and estimate likely effects on terrestrial biosphere dynamics, we applied six alternative formulations of BNF spanning the range of process formulations in current state-of-the-art biosphere models within a common framework, the O-CN model: a global map of static BNF rates, two empirical relationships between BNF and other ecosystem variables (net primary productivity and evapotranspiration), two process-oriented formulations based on plant N status, and an optimality-based approach. We examined the resulting differences in model predictions under ambient and elevated atmospheric CO2 and found that the predicted global BNF rates and their spatial distribution for contemporary conditions were broadly comparable, ranging from 108 to 148 Tg N yr-1 (median: 128 Tg N yr-1), despite distinct regional patterns associated with the assumptions of each approach. Notwithstanding, model responses in BNF rates to elevated levels of atmospheric CO2 (+200 ppm) ranged between -4 Tg N yr-1 (-3 %) and 56 Tg N yr-1 (+42 %) (median: 7 Tg N yr-1 (+8 %)). As a consequence, future projections of global ecosystem carbon (C) storage (+281 to +353 Pg C, or +13 to +16 %) as well as N2O emission (-1.6 to +0.5 Tg N yr-1, or -19 to +7 %) differed significantly across the different model formulations. Our results emphasize the importance of better understanding the nature and magnitude of BNF responses to change-induced perturbations, particularly through new empirical perturbation experiments and improved model representation.
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 (G1, “stomatal slope”) at the ecosystem level at six sites comprising tropical, Mediterranean, temperate, and boreal forests. We assess the following six mechanisms potentially causing discrepancies between leaf and ecosystem‐level estimates of G1: (i) non‐transpirational water fluxes; (ii) aerodynamic conductance; (iii) meteorological deviations between measurement height and canopy surface; (iv) energy balance non‐closure; (v) uncertainties in net ecosystem exchange partitioning; and (vi) physiological within‐canopy gradients. Our results demonstrate that an unclosed energy balance caused the largest uncertainties, in particular if it was associated with erroneous latent heat flux estimates. The effect of aerodynamic conductance on G1 was sufficiently captured with a simple representation. G1 was found to be less sensitive to meteorological deviations between canopy surface and measurement height and, given that data are appropriately filtered, to non‐transpirational water fluxes. Uncertainties in the derived GPP and physiological within‐canopy gradients and their implications for parameter estimates at leaf and ecosystem level are discussed. Our results highlight the importance of adequately considering the sources of uncertainty outlined here when EC‐derived water‐use efficiency is interpreted in an ecophysiological context.
The intrinsic water‐use efficiency (iWUE) metric G1 inferred from eddy covariance measurements is affected by confounding physical and methodological factors (1–6) to a different extent. Meteorological deviations between measurement height and canopy surface (4), the NEE‐partitioning approach (5) and possible physiological within‐canopy gradients (6) are generally less critical for the accurate estimation of intrinsic WUE at the ecosystem level than non‐transpirational water fluxes (1), aerodynamic resistance (2) or the energy balance non‐closure (3).
Nitrogen is an essential element controlling ecosystem carbon (C) productivity and its response to climate change and atmospheric CO.sub.2 increase. This study presents the evaluation - focussing on ...gross primary production (GPP) - of a new version of the ORCHIDEE model that gathers the representation of the nitrogen cycle and of its interactions with the carbon cycle from the OCN model and the most recent developments from the ORCHIDEE trunk version.
Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across ...many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate–carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate–carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1 % per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to anthropogenic activity over the 21st century and beyond. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set up and run the simulations. Particular attention is paid to boundary conditions, input data, and requested output diagnostics. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design.
The first generation of forest free‐air CO₂ enrichment (FACE) experiments has successfully provided deeper understanding about how forests respond to an increasing CO₂ concentration in the ...atmosphere. Located in aggrading stands in the temperate zone, they have provided a strong foundation for testing critical assumptions in terrestrial biosphere models that are being used to project future interactions between forest productivity and the atmosphere, despite the limited inference space of these experiments with regards to the range of global ecosystems. Now, a new generation of FACE experiments in mature forests in different biomes and over a wide range of climate space and biodiversity will significantly expand the inference space. These new experiments are: EucFACE in a mature Eucalyptus stand on highly weathered soil in subtropical Australia; AmazonFACE in a highly diverse, primary rainforest in Brazil; BIFoR‐FACE in a 150‐yr‐old deciduous woodland stand in central England; and SwedFACE proposed in a hemiboreal, Pinus sylvestris stand in Sweden. We now have a unique opportunity to initiate a model–data interaction as an integral part of experimental design and to address a set of cross‐site science questions on topics including responses of mature forests; interactions with temperature, water stress, and phosphorus limitation; and the influence of biodiversity.
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.
We analysed the responses of 11 ecosystem models to elevated atmospheric CO₂ (eCO₂) at two temperate forest ecosystems (Duke and Oak Ridge National Laboratory (ORNL) Free‐Air CO₂ Enrichment (FACE) ...experiments) to test alternative representations of carbon (C)–nitrogen (N) cycle processes. We decomposed the model responses into component processes affecting the response to eCO₂ and confronted these with observations from the FACE experiments. Most of the models reproduced the observed initial enhancement of net primary production (NPP) at both sites, but none was able to simulate both the sustained 10‐yr enhancement at Duke and the declining response at ORNL: models generally showed signs of progressive N limitation as a result of lower than observed plant N uptake. Nonetheless, many models showed qualitative agreement with observed component processes. The results suggest that improved representation of above‐ground–below‐ground interactions and better constraints on plant stoichiometry are important for a predictive understanding of eCO₂ effects. Improved accuracy of soil organic matter inventories is pivotal to reduce uncertainty in the observed C–N budgets. The two FACE experiments are insufficient to fully constrain terrestrial responses to eCO₂, given the complexity of factors leading to the observed diverging trends, and the consequential inability of the models to explain these trends. Nevertheless, the ecosystem models were able to capture important features of the experiments, lending some support to their projections.
PDF
