Context

Ongoing climate change threatens the health of forests (Allen et al., 2015). The risk of droughts (Anderegg et al., 2012) may offset the fertilizing effects of CO2 (Walker et al., 2021). To adapt our forests to this new context, we need to better qualify the existing genetic diversity and better conserve it in situ. A continent-wide collection of in situ Forest Genetic Resources accessions (http://portal.eufgis.org/), called Genetic Conservation Units (GCUs), is coordinated by the European Forest Genetic Resources Program (EUFORGEN) since 1994. The objective of the European H2020 project FORGENIUS is to better document through in situ measurements, model and remote sensing the resilience of these GCUs to disturbances.

Mission

A post-doctoral position in ecological modelling is available at INRAE – Ecologie des Forêts Méditerranéennes (URFM), Avignon, France.

In FORGENIUS project, 20 genetic conservation units have been selected for ten important temperate European species to understand their vulnerability and resilience facing ongoing climate change. All these stand forests will be characterized using remote-sensing, in situ measurements (forest inventory, leaf area index, soil water capacity) and laboratory measurements for various traits (leaf, growth and hydraulic traits).

The objective of the post-doctoral position is to couple these data along with past climate data within a process-based modeling framework to estimate vulnerability and resilience to different climatic risks of these stands. We will focus on drought and frost perturbations. We will simulate the responses of several key indicators of ecosystem health: wood growth, seed production, defoliation, and mortality risk through carbon starvation and hydraulic failure.

Different models developed by URFM and available in the Capsis platform will be used. URFM has been developing process-based models of forest Functioning: The CASTANEA model (Davi and Cailleret, 2017; Dufrêne et al., 2005) that simulates forest water and carbon balance and tree growth and the SUREAU model (Cochard et al., 2021) that simulates hydraulic processes responsible for tree desiccation and hydraulic failure risk during drought.

First, in a collaboration between INRA, CREAF and INIA simulations done using CASTANEA and Sur-Eau will be compared to simulations carried out with other models: MEDFATE used at CREAF that simulate forest dynamics and fire risk (De Cáceres et al. 2014) and MAIDEN used at INIA more dedicated to simulate ring width increment (Misson et al., 2004). These simulations will be done on a subset of Pinus pinaster GCU covering a drought gradient. This step will allow to assess the uncertainty of the model simulations. This model intercomparison will also improve the different models by adding some useful outputs for GCU resilience estimation. This part of the project could also be an opportunity to collaborate on exchanging species parameter date.

Second, the post doc will further improve CASTANEA and SUR-EAU models by taking advantage of the inter comparison of models, realize coupling between CASTANEA and SUR-EAU and launch the simulation for the 200 GCUs using remote sensing and in situ measurements to parameterize the models. Spatial extrapolation of the results at the entire distribution area of the species and temporal extrapolation to future climatic conditions could be an output of the project.

Skills
– Ecological modelling, ecophysiology, plant hydraulics, functional ecology, forest ecology
– Experience in vegetation remote sensing appreciated
– R language; programming languages such as Java appreciated
– Excellent writing skills in English

Context
The post-doctoral fellow will join a dynamic group of forest ecologist, ecophysiologist and will be supervised by Hendrik Davi and Nicolas Martin, who are currently developing respectively CASTANEA and SUREAU-ECOS model at URFM. A six-month stage in Spain will also be necessary for the model inter-comparison. Funding is currently available for 24 months and will begin the 1st of October 2021.

Contact: hendrik.davi@inrae.fr

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Anderegg, W.R.L., Berry, J.A., Smith, D.D., Sperry, J.S., Anderegg, L.D.L., Field, C.B., 2012. The roles of hydraulic and carbon stress in a widespread climate-induced forest die-off. Proc. Natl. Acad. Sci. 109, 233–237. https://doi.org/10.1073/pnas.1107891109
Cochard, H., Pimont, F., Ruffault, J., Martin-StPaul, N., 2021. SurEau: a mechanistic model of plant water relations under extreme drought. Ann. For. Sci. 78, 55. https://doi.org/10.1007/s13595-021-01067-y
Davi, H., Cailleret, M., 2017. Assessing drought-driven mortality trees with physiological process-based models. Agric. For. Meteorol. 232, 279–290. https://doi.org/10.1016/j.agrformet.2016.08.019
Dufrêne, E., Davi, H., François, C., Maire, G. le, Dantec, V.L., Granier, A., 2005. Modelling carbon and water cycles in a beech forest: Part I: Model description and uncertainty analysis on modelled NEE. Ecol. Model. 185, 407–436. https://doi.org/10.1016/j.ecolmodel.2005.01.004
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