Tree ring ecological signal is consistent with floristic composition and plant indicator values in Mediterranean Fagus sylvatica forests

1. We compared the multivariate patterns of tree ring chronologies with those of ␣oristic composition (and of its associated Ellenberg indicator values – EIVs) across the whole elevation gradient of Fagus sylvatica forests in Central Italy (from 300 to 1900 m a.s.l.). Both data sets were also compared with bioclimatic parameters obtained from reconstructed, site-representative meteorological data. 2. Procrustes analysis showed that the patterns of tree ring chronologies and ␣oristic assemblages were signi␣cantly correlated. The two main bio-climatic belts obtained from tree ring analysis showed signi␣cantly different ␣oristic composition and signi␣cantly different distribution of EIVs. 3. Constrained ordination with meteorological data as covariates showed that in both data sets, most of the variation was explained by mean summer temperature, while precipitation parameters had only minor explanatory power. 4. Ellenberg indicator values for temperature showed a strong correlation with mean summer tem- perature obtained from the meteorological data. EIVs for continentality were weakly correlated with annual temperature range. No correlation emerged between the EIVs for moisture and the precipita- tion parameters. Constrained ordination of the tree ring data set with the ␣oras’ mean EIVs as covariates found that the most explanatory variables were the EIVs for temperature followed by the EIVs for light. This latter ␣nding is probably a consequence of temperature control (via summer drought) on canopy Leaf Area Index. 5. Synthesis. Ecological classi␣cation of beech forest stands through either tree ring chronologies or ␣oristic composition yields very similar results. Both bio-indication methods point to the predomi- nant role of growing-season temperatures in controlling patterns and processes of forest ecosystems across wide elevation gradients. Thus, similarities in tree ring chronologies of the past between sites could be used to infer analogies in past ␣oristic assemblages. Moreover, temperature indicator values obtained from ␣oras show excellent accordance with meteorological data, allowing reliable usage of diachronic ␣oristic data for climate change monitoring at detailed spatial scale.