Shifts of forest species along an elevational gradient in Southeast France: climate change or stand maturation?




Recent vegetation changes in mountain areas are often explained by climate warming. However, effects of land-use changes, such as recolonization of abandoned pastures by forest, are difficult to separate from those of climate change. Even within forest belts, changes in stand structure due to forest management and stand maturation could confound the climate signal. Here, we evaluate the direction and rate of plant species elevation shifts in mountain forests, considering the role of stand dynamics.


Forests in the plains and mountains of Southeast France.


We compared floristic data from the French National Forest Inventory collected in the 1980s and 1990s. They provided a large-scale (30 985 plots) and representative sample of vegetation between 0 and 2500 m a.s.l. Species response curves along the elevation and exposure gradients were fitted with a logistic regression model. In order to assess the effect of changes in successional stages of the forest stands, we compared plant species shifts in the whole set of stands with those solely in closed stands.


A total of 62 species shifted downward, whereas 113 shifted upward, resulting in a significant upward mean shift of 17.9 m. Upward shifting species were preferentially woody and heliophilous, suggesting a role for forest closure and maturation in the observed changes. Excluding all open forest stages from analyses, the upward trend became weaker (−3.0 m) and was not significant. Forests of the study area have undergone closure and maturation, more strongly at lower altitudes than at higher ones, producing an apparent shift of species.


In the mountain relief of Southeast France, changes in the successional stages of stands appear as the main cause of the apparent upslope movement of forest species. Since a similar trend of forest maturation exists in large areas throughout Europe, forest dynamics should be better taken into account among the causes of vegetation changes before inferring any climate change effect.