Exceptional climatic events from 2003 to 2005 (scorching heat and drought) affected the whole of the vegetation in the French Mediterranean region and in particular the Scots pine (Pinus sylvestris L.), one of the most important forest tree species in this area. To understand its response to these extreme conditions, we investigated its radial growth, branch length growth, architectural development and reproduction for the period 1995-2005, and linked these variables to climatic parameters. We used four plots situated in southeastern France and presenting different levels of site quality and potential forest productivity. The results show that: (1) the climatic episode 2003-2005 was highly detrimental to the growth (bole and branches), crown development, and cone production but favored the production of male flowers; (2) these variables depend on climatic factors of both the current and previous years; (3) the 2003 scorching heat impact was strong but was mainly apparent from 2004; it was part of a 6-year-long unfavorable cycle beginning in 2000, characterized by high minimum and maximum temperatures and very dry springs; (4) in spite of a significant effect of site quality, the Scots pine's response to extreme climatic conditions was homogeneous in the French Mediterranean area; and (5) the stress induced by poor site conditions generally resulted in the same consequences for tree growth, architecture, and reproduction as in unfavorable climatic conditions.

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A so-called fuzzy linear regression is used in dendroecology to model empirically tree growth as a function of a bioclimatic index representing the water stress, i.e., the ratio of actual evapotranspiration to potential evapotranspiration. The response function predicts tree growth as (fuzzy) intervals, narrow in the domain where the bioclimatic index is most limiting and becoming progressively larger elsewhere. The method is tested with a population of Pinus pinea L. from the Provence region in France. It is shown that fuzzy linear regression gives results comparable with those obtained using a linear response function. The interval of credibility given by the fuzzy regression suggests that more precise expected growth is obtained for high water stress, which is typical of Mediterranean climate. Fuzzy linear regression can be also a method to test different hypotheses on several potential predictors when any further experimental approach is quite impossible as it is for trees in their natural environment. To sum up, fuzzy regression could be a first step before the construction of a kind of growth simulator adapted to different environments of a given species. In environmental sciences, the fuzzy response function thus appears to be an approach between the mechanistic and the statistical descriptive approaches.Résumé : Une régression dite linéaire floue est utilisée en dendroécologie pour modéliser empiriquement la croissance des arbres en fonction d'un indice bioclimatique représentant le stress hydrique, c'est-à-dire, le ratio de l'évapotranspiration réelle par rapport à l'évapotranspiration potentielle. La fonction prédit la croissance des arbres par intervalles (flous) qui sont étroits dans la région où l'indice bioclimatique est le plus limitatif et s'élargissent progressivement dans les autres régions. La méthode est testée avec une population de Pinus pinea L. de la région provençale de France. Il est démontré que la régression linéaire floue donne des résultats comparables à ceux obtenus avec une fonction à réponse linéaire. L'intervalle de crédibilité donné par la régression floue suggère une croissance plus precise attendue lors d'un stress hydrique élevé, typique du climat méditerranéen. La régression linéaire floue peut aussi servir à tester différentes hypothèses au sujet de prédicteurs potentiels lorsque toute approche expérimentale additionnelle est impossible, comme dans le cas des arbres dans leur environnement naturel. En conclusion, la régression floue pourrait constituer une première étape avant la construction d'une sorte de « simulateur de croissance » adapté aux différents milieux occupés par une espèce donnée. En sciences environnementales, la fonction de réponse floue semble donc être une approche qui se situe entre l'approche déterministe et l'approche des statistiques descriptives. Boreux et al. 1260