Two Post-Doctoral research positions.

Climate Change, Forest diversity and Changes of productivity in the Alps: an
analysis of tree growth and mortality responses.

Laboratory: Cemagref – Grenoble (France). Mountain Ecosystem Research Unit

Description:
These two positions are part of the EU FP7 project BACCARA (Biodiversity And
Climate Change: A Risk Analysis). The goal of this project is to evaluate
risks of European forest biodiversity and productivity loss under climate
change focussing on forest trees and associated species (mainly insects and
pathogens). In this project our team focuses on the relations between
climate, tree demography, tree functional diversity and productivity in the
Alps. We participate both to the observational/experimental and to the
modelling effort in this project.
        The objective of these post-doc projects are to assess the risk of 
change
in productivity and mortality due to climate changes in mountain forests.
More specifically the goal is to rate the risks of dysfunction (loss of
forest cover) and loss of productivity due to the effects of climate change
in forest of different functional and phylogenetic compositions. The project
will be organised around the diversity-stability paradigm. Adapted to our
context, this paradigm states that more diverse communities should
experience less risks of dysfunction and loss of productivity due to climate
change. Functional diversity will be analysed based on traits related to
climate stress tolerance (for instance a low tolerance of water stress), but
we will also consider traits related to competitive ability (for instance
shade tolerance).  We consider that tree-tree interactions are keys to
understand the response of forest communities to global change. Our approach
will be based both on a retrospective analysis of National Forest Inventory
(NFI) data covering a 50 years period and the development of an individual
based model of growth and mortality. The model will be used to forecast
future change in tree growth and mortality based on climate scenarios. We
will make use of recent advance in Hierarchical Bayesian statistic to
analyse this large data set. We have developed non manipulative methods to
analyse tree growth and mortality response to tree-tree interaction and to
climate effects. These growth and mortality model will be used to forecast
changes of stand productivity and mortality of virtual communities of
varying functional composition. 
        These two post-doctoral fellowships are proposed in the Mountain 
Ecosystem
Research Unit, Cemagref Grenoble.  The unit studies mountain forest and
grassland ecosystems of the Alps, to develop basis for their sound and
sustainable management. We develop a multifunctional approach of forest
ecosystem services with special focus on forest diversity and protection
efficiency against natural hazards. The work of the team is based on Samsara
a simulation model in the simulation software Capsis, which used to train
forest managers.

Education: Required qualifications include a PhD degree in the fields of
ecology, forestry, environmental science or related field. Preference will
be given to candidates who have experience in R statistical software,
modelling, or Hierarchical Bayesian statistics.

Conditions:
Work will be located in Cemagref in Saint-Martin-d’Hères near Grenoble.
Gross salary will be of 2200 €/month. 
Duration of  appointment 19 months for one position and 14 months for the
second position. To start as soon as possible . 

Contact:
Applicants should send a cover letter summarizing their research background,
suitability and interest in the position, a CV including a publication list,
and contact information for two referees (everything as one PDF document) no
later than 18 June 2010 by e-mail using the keyword "Post-doc position" to
Dr. Georges Kunstler & Dr. Benoît Courbaud (georges.kunst...@cemagref.fr,
benoit.courb...@cemagref.fr), Research Unit Mountain Ecosystems, Cemagref de
Grenoble, 2, rue de la Papeterie - BP 76, F-38402 Saint-Martin-d'Hères cedex
(France), Tel : +33 4 76 76 27 61.

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