Colangelo, MicheleGazol, AntonioCamarero, J. JulioBorghetti, MarcoSánchez Salguero, RaúlMatías Resina, LuisCastellaneta, MariaNola, PaolaRipullone, Francesco2025-06-182025-06-182025-06-10Colangelo, M., Gazol, A., Camarero, J.J., Borghetti, M., Sánchez Salguero, R., Matías Resina, L.,...,Ripullone, F. (2025). Earlywood vessel characteristics are early indicators of drought-induced decline in ring-porous oak species within the Mediterranean Basin. Science of the total enviroment, 980, 179565. https://doi.org/10.1016/j.scitotenv.2025.179565.1879-10260048-9697https://hdl.handle.net/11441/174502Heat and drought stress have triggered forest dieback episodes worldwide, affecting oak forests, particularly in,hotspots of climate change such as the Mediterranean Basin. However, forecasting dieback is not straightforward.,In this study, we used the earlywood anatomy to improve dieback forecasts in five oak species characterized by,different drought sensitivity (i.e. from high to low Quercus robur, Q. cerris, Q. frainetto and Q. canariensis, Q.,humilis, Q. pubescens) across Italy and Spain. We measured radial growth, expressed as basal area increment,(BAI), earlywood hydraulic diameter (Dh) and vessel area of coexisting non-declining (ND) and declining (D),trees in each stand. Then, we calculated the product between the coefficient of variation (CV) of vessel area and a,spatial aggregation index (AI). High CV × AI values indicate regularly spaced vessels with variable area of,vessels, while low values correspond to clustered vessels with similar area. ND trees showed higher BAI values,than D trees from 10 to 40 years before the dieback onset, when ND trees grew 20–50 % more than the D trees.,We observed a decline in the vessel area CV several decades prior to dieback in D trees, with the exception of Q. cerris. The AI showed higher values in ND than in D trees. Consequently, the CV × AI product was consistently,higher in ND than in D trees. The CV × AI divergence between ND and D trees was pronounced in the wettest,sites, specifically for Q. robur and Q. humilis. Time series of CV × AI effectively differentiated trees based on their,vigor. Wood anatomy variables could be used to enhance predictions of vulnerability to drought-induced,dieback. This study can help identify vulnerable trees before the onset of dieback symptoms, serving as a tool,to support the management of forests prone to drought.application/pdf12 p.engAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/Climate changeQuercus XylemVessel áreaVessel distributionEarlywood anatomyinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccesshttps://doi.org/10.1016/j.scitotenv.2025.179565