High elevation ecosystems are one of the most sensitive to climate change. The analysis of growth and xylem structure of trees from marginal populations, especially the ones growing at the treeline, could provide early-warning signs to better understand species-specific responses to future climate conditions. In this study, we combined classical dendrochronology with wood density and anatomical measurements to investigate the climate sensitivity of Pinus cembra L., a typical European high-elevation tree species distributed in isolated patches in the Carpathians. Samples were collected from the Retezat Mountains, South-Western Romania. We analyzed ring-width (TRW), maximum density (MXD), xylem anatomical traits (cell number per ring (CNo), cell density (CD), conduit area (CA), and cell-wall thickness (CWT)) time series, split into ring sectors and assessed the relationships with monthly and daily climate records over the last century (1901-2015). The analysis showed a strong dependency of TRW on CNo and MXD on CWT. Summer temperature positively correlated with MXD and CWT (monthly correlation (r) were 0.65 and 0.48 respectively) from the early- to late-wood but not TRW (r=0.22). CA positively correlated with water availability (r=0.37) and negatively correlated with temperature (r=-0.39). This study improves our general understanding of the climate-growth relationships of a European high-elevation tree species and the results could be considered for forecasting population dynamics on projected changes in climate.

These files include the data used to analyze: i) time series of tree-ring and xylem anatomical traits of Pinus cembra L. and climate data from the Retezat Mountains, South-Western Romania; ii) the association between TRW, MXD, and xylem traits chronologies; iii) the relationships with monthly and daily climate records over the last century (1901–2015). In particular, we analysed tree-ring width (TRW), maximum density (MXD), xylem anatomical traits [cell number per ring (CNo), cell density (CD), conduit area (CA), and cell wall thickness (CWT)] time series, split into ring sectors and assessed the relationships with monthly and daily climate records (mean temperature, accumulation of precipitation, and scPDSI). Variables are organized in columns and named with the acronyms described in Table 1 and Figures 2-4.