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Modelling Mediterranean pine stands dynamics: a first functional approach

  • Helluy, M.
  • Prévosto, Bernard
  • Balandier, Philippe
  • Donès, Nicolas
Publication Date
Oct 08, 2018
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The frequency and severity of extreme weather events are increasing as a result of climate change. The effects on Mediterranean forests are expected to include events such as longer summer droughts in the near future. Management strategies are thus needed to increase forest resilience. Models are useful tools to test adaptive management strategies and to study their long-term effects in relation to climatic conditions. As there is a lack of functional models of forest dynamics available for Mediterranean forest stands, our study aims to develop a functional-structural model for Mediterranean pine stands. To achieve this, we adapted the RReShar model (Regeneration and Resources Sharing) to the Mediterranean context. This is an individual-based model describing all vegetation strata dynamics in relation to water and light. Here we will present the part of the model related to the pine canopy dynamics. We studied twelve 50 year-old Pinus halepensis stands located in the South-East of France distributed in different cover treatments (light, medium or dense). We first developed a water balance model using the stand characteristics (LAI values in particular) and soil properties following the methods used in the BILJOU model. Trees of all stands were measured (height, dbh) and spatialized. Cores from 175 trees were extracted and analysed to produce tree ring increments. We then developed a tree-based circumference model, which predicts radial increment first as a function of the Hegyi competition index then by combining the competition index with a water stress index. We also developed models that predict tree height, as well as crown diameter and crown height. Multiple regressions analysis have been used to produce radial increment models using the competition index and the water stress. Our results show that the competition index and water stress are good predictors of trees growth (model fit improves with these two predictors combined). We expect further improvements to the model by linking understorey growth and the tree regeneration dynamics with water stress and transmitted light.

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