The REFLEX project: Comparing different algorithms and implementations for the inversion of a terrestrial ecosystem model against eddy covariance data

Fox, A. M.; Williams, Mathew; Richardson, Andrew D.; Cameron, David R.; Gove, Jeffrey H.; Quaife, Tristan; Ricciuto, D. M.; Reichstein, Markus; Tomelleri, Enrico; Trudinger, C. M.; Wijk, Mark van

doi:10.1016/j.agrformet.2009.05.002

Cited by 150 publications

(201 citation statements)

References 41 publications

(24 reference statements)

Supporting

Mentioning

198

Contrasting

Order By: Relevance

“…Mobile stored carbon relates only to foliage, and is respired only during periods of bud-burst and leaf-fall. Carbon allocation and canopy phenology are simulated as in the DALEC model Fox et al, 2009). …”

Section: The Föbaar Modelmentioning

confidence: 99%

Using model‐data fusion to interpret past trends, and quantify uncertainties in future projections, of terrestrial ecosystem carbon cycling

Keenan

Davidson

Moffat

et al. 2012

Global Change Biology

Self Cite

171

181

View full text Add to dashboard Cite

Here we assess endogenous and exogenous uncertainties using a model-data fusion framework benchmarked with an artificial neural network (ANN). We used 18 years of eddy-covariance carbon flux data from the Harvard Forest, where ecosystem carbon uptake has doubled over the measurement period, along with 15 ancillary ecological data sets relative to the carbon cycle. We test the ability of combinations of diverse data

show abstract

Section: The Föbaar Modelmentioning

confidence: 99%

Using model‐data fusion to interpret past trends, and quantify uncertainties in future projections, of terrestrial ecosystem carbon cycling

Keenan

Davidson

Moffat

et al. 2012

Global Change Biology

Self Cite

171

181

View full text Add to dashboard Cite

show abstract

“…In the REFLEX project 19 , the atmospheric carbon C a increased by a small amount each year, but we have kept this value constant, although later on we will consider the effect of changing the value of this constant. The other parameters in the ACM, for example soil-plant water potential and foliar nitrogen, can be set to appropriate fixed values for the vegetation in question.…”

Section: A Model Description and Datamentioning

confidence: 99%

“…For our purposes, we express the DALEC EV model equations 19 as a discrete dynamical system in the form of daily maps, specifically:…”

Section: A Model Description and Datamentioning

confidence: 99%

“…We have used realistic data both for parameters and climate data from a European flux site, which was provided for the REFLEX project 19 . The purpose of this project was to compare the strengths and weaknesses of various data assimilation methods for estimating parameters and predicting carbon fluxes using DALEC, based on three years of driver data.…”

Section: A Model Description and Datamentioning

confidence: 99%

See 1 more Smart Citation

A dynamical systems analysis of the data assimilation linked ecosystem carbon (DALEC) models

Chuter

Aston

Skeldon

et al. 2014

Chaos: An Interdisciplinary Journal of Nonlinear Science

View full text Add to dashboard Cite

Changes in our climate and environment make it ever more important to understand the processes involved in Earth systems, such as the carbon cycle. There are many models that attempt to describe and predict the behaviour of carbon stocks and stores but, despite their complexity, significant uncertainties remain. We consider the qualitative behaviour of one of the simplest carbon cycle models, the Data Assimilation Linked Ecosystem Carbon (DALEC) model, which is a simple vegetation model of processes involved in the carbon cycle of forests, and consider in detail the dynamical structure of the model. Our analysis shows that the dynamics of both evergreen and deciduous forests in DALEC are dependent on a few key parameters and it is possible to find a limit point where there is stable sustainable behaviour on one side but unsustainable conditions on the other side. The fact that typical parameter values reside close to this limit point highlights the difficulty of predicting even the correct trend without sufficient data and has implications for the use of data assimilation methods. We show that the DALEC model contains a transition point where, for parameters on one side forests thrive, but on the other they die. Analysing data from two forests we find that they sit near the transition point, and we hypothesize that this is a natural consequence of a tree's need to optimize its resources.Such transition points are important because, in a changing world, we expect parameter values to drift. Drifting across a transition point can have serious consequences and results in "tipping" from one kind of behaviour to another.For example, a shift in the amount of rainfall could induce tipping from a sustainable forest to a forests that dies. The presence of such transition points also has important consequences for prediction. Models often contain many parameters that need to be determined, usually by fitting to data. Different algorithms used to fit models to data typically lead to slightly different values for parameters.Away from transition points for non-chaotic systems, this usually means that there is some small uncertainty in the parameter values that leads to a small uncertainty in prediction. However, near transitions points, small differences in parameter values can lead to very different predictions.

show abstract

“…In recent years, alternative methods for parameter estimation for PBMs have been developed that are based on representing uncertainty about parameter values as probability distributions (Kennedy and O'Hagan 2001;Van Oijen et al 2005b;Fox et al 2009;Ogle 2009;Wang et al 2009). The most generally applicable of these methods is Bayesian calibration (Kennedy and O'Hagan 2001).…”

Section: Cultivar-specific Parameter Estimationmentioning

confidence: 99%

Toward a Bayesian procedure for using process-based models in plant breeding, with application to ideotype design

Oijen

Höglind

2015

Euphytica

View full text Add to dashboard Cite

Process-based grassland models (PBMs) simulate growth and development of vegetation over time. The models tend to have a large number of parameters that represent properties of the plants. To simulate different cultivars of the same species, different parameter values are required. Parameter differences may be interpreted as genetic variation for plant traits. Despite this natural connection between PBMs and plant genetics, there are only few examples of successful use of PBMs in plant breeding. Here we present a new procedure by which PBMs can help design ideotypes, i.e. virtual cultivars that optimally combine properties of existing cultivars. Ideotypes constitute selection targets for breeding. The procedure consists of four steps: (1) Bayesian calibration of model parameters using data from cultivar trials, (2) Estimating genetic variation for parameters from the combination of cultivar-specific calibrated parameter distributions, (3) Identifying parameter combinations that meet breeding objectives, (4) Translating model results to practice, i.e. interpreting parameters in terms of practical selection criteria. We show an application of the procedure to timothy (Phleum pratense L.) as grown in different regions of Norway.Keywords BASGRA Á Cold tolerance Á Genotype-environment interaction Á Plant breeding Á Process-based modelling Á Yield stability Terminology This paper aims to bridge two different plant disciplines, i.e. process-based modelling and breeding, so terms need to be defined. In modelling, we distinguish between plant parameters, which are genotype-specific constants, and output variables, which are plant characteristics that are predicted by the model and that vary between environments. Process-based models (PBMs) are dynamic models that represent physiological and morphological processes in plants, and their interaction with the environment. Simulation is the process of specifying environment and parameter values followed by running the PBM to calculate the output variables. In plant breeding, traits are measurable properties of plants that arise from the interaction between the genotype and its environment (G 9 E). The influence of the environment may be large for some traits (e.g. yield) or small (e.g. flower size). A quantitative trait is a property measured on a Electronic supplementary material The online version of this article

show abstract

The REFLEX project: Comparing different algorithms and implementations for the inversion of a terrestrial ecosystem model against eddy covariance data

Abstract: The NERC and CEH trade marks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner.

Cited by 150 publications

References 41 publications

Using model‐data fusion to interpret past trends, and quantify uncertainties in future projections, of terrestrial ecosystem carbon cycling

Using model‐data fusion to interpret past trends, and quantify uncertainties in future projections, of terrestrial ecosystem carbon cycling

A dynamical systems analysis of the data assimilation linked ecosystem carbon (DALEC) models

Toward a Bayesian procedure for using process-based models in plant breeding, with application to ideotype design

Contact Info

Product

Resources

About