PhD studentship on ecological modelling (M/F): simulation of long-term forest growth and transpiration in a global land surface model informed by tree rings

Job title:

PhD studentship on ecological modelling (M/F): simulation of long-term forest growth and transpiration in a global land surface model informed by tree rings

Company:

Job description

Offer DescriptionThe workplace will be the LSCE ( ), a world-class institute on climate change research and Earth System modelling located on the plateau of Saclay, near Paris. It employs over 320 researchers from more than 30 different nationalities and diverse scientific disciplines. The student will be part of the MOSAIC (Modelling of Continental Surfaces and Interfaces) team in the LSCE and will be enrolled in the Doctoral School of Environmental Sciences of Île-de-France (SEIF) at the University of Paris-Saclay. This is a PhD program by Research and it benefits from a very dynamic research environment and world-class modelling infrastructure.

• Scientific background :

Gradual anthropogenic warming and parallel changes in the major global biogeochemical cycles are slowly pushing forest ecosystems into novel growing conditions, with uncertain consequences for ecosystem dynamics and climate. Short-term forest responses to warming, drought and increased atmospheric CO2 and nitrogen deposition are relatively well understood and skilfully simulated by process models. However, process-based understanding and confidence on model projections of carbon and water cycles weaken towards longer time scales and to the future, mainly because long-term observations of key processes by which long-lived trees die or adapt to the new growing conditions are lacking. In particular, long-term belowground forest responses are shrouded in mystery. Even more easily observable aboveground forest growth trends, such as the so-called tree-ring divergence from warming at cool northern latitudes or the apparent absence of sustained CO2 fertilisation of growth widely predicted by ecosystem models are difficult to explain with current field observations and experiments.The utilisation of tree-ring width, combined with their carbon (δ13C) and oxygen (δ18O) stable isotope composition, is increasingly recognized as a method to address the lack of direct observations on century-scale alterations in plant physiology and growth with global change. This approach can be combined with readily available short-term satellite and eddy-covariance observations of forest growth and carbon and water fluxes over the past few decades to provide a consistent long-term benchmark for land surface models, a resource that is just beginning to be exploited. The ERC-funded project CATES is pioneering the field by developing a new cross-disciplinary framework to constrain climate projections by jointly improving the simulation of forest growth and water use efficiency (WUE; the ratio of photosynthesis to transpiration) at long time scales (decades to century) using novel observational standards for historical growth and physiology derived from tree-ring data.

• Objective of the thesis :

The thesis is part of the CATES project and its aim is to combine multiple tree-ring data (ring width, and carbon and oxygen stable isotopes) and eddy-covariance observations from a network of supersites to improve the simulation of carbon and water fluxes in the ORCHIDEE land surface model at local scale. The work will contribute to the overarching scientific goal of CATES of reducing uncertainties in the simulation of the feedbacks of altered tree growth and physiology on the Earth system.

• Requirements :
• Master degree (M2 in France).
• Demonstrated interest in Biogeosciences and numerical modelling.
• Analytical and scientifically-minded thinking.
• Computing, programming and English writing skills.

• Approach :

The process by which observations of a system are incorporated into a numerical model of that system is called data assimilation. In this project, a formal Bayesian Data assimilation (DA) scheme will be used to optimally combine process-based information from the ORCHIDEE land surface model with site-level tree-ring and flux observations. This DA framework has routinely been applied to eddy covariance observations. The scientific challenge is to apply it to multiple types of tree-ring data (ring width and stable isotopes) in combination with traditional short-term data streams to validate, and where needed to improve, the capability of ORCHIDEE to simulate the effects of global change on transpiration and biomass production from interannual to century-long time scales. Most of the tree-ring data are already available, but the candidate will help with the collection and measurement at key sites.

• Expected results :

The data assimilation process should result in a calibrated model that is able to realistically simulate short-term forest responses to climate extremes (e.g., drought, warming) and long-term changes in water use efficiency over the 20th century for different forest types.RequirementsResearch Field Environmental science Education Level Master Degree or equivalentResearch Field Biological sciences Education Level Master Degree or equivalentResearch Field Geosciences Education Level Master Degree or equivalentLanguages FRENCH Level BasicResearch Field Environmental science Years of Research Experience NoneResearch Field Biological sciences Years of Research Experience NoneResearch Field Geosciences Years of Research Experience NoneAdditional InformationWebsite for additional job detailsWork Location(s)Number of offers available 1 Company/Institute Laboratoire des Sciences du Climat et de l’Environnement Country France City GIF SUR YVETTE GeofieldWhere to apply WebsiteContact CityGIF SUR YVETTE WebsiteSTATUS: EXPIRED

Expected salary

Location

Gif-sur-Yvette, Essonne

Job date

Thu, 25 Apr 2024 01:31:29 GMT

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