Young Douglas-fir (Pseudotsuga menziesii Mirb. Franco) trees (younger than 10 years-old) are increasingly affected by needle reddening in late winter—early spring. Although some climatic factors have been suggested as potential drivers by empirical observations, no large-scale bioclimatic study has been carried out on this phenomenon. We used the database collected by the French Forest Health Service since 1989 and meteorological data provided by Meteo France downscaled to a resolution of 8 × 8 km to identify and quantify the relationship between climatic anomalies and the occurrence of reddening. By analysing local (site scale) and regional (all reddening sites) anomalies, we found that anomalies in maximum temperature, thermal amplitude, light intensity, air relative humidity, potential evapotranspiration, soil water content and wind speed were more frequent when reddening was observed. The period when these factors deviated the most from the normal was about two months before the reddening observation for all factors except wind speed. The young trees may be affected by a drought episode but show no symptoms yet. Anomalous local wind episodes were observed more frequently in the week before reddening, and would therefore be the trigger for reddening. Prediction of reddening events by computing dynamic standardization and through random forest classification was more accurate at local than regional scale, suggesting an acclimation of the trees to local conditions. Furthermore, the detection of critical thresholds in standardized values of climatic variables for predicting the geographical pattern of reddening seems to lead to more realistic results than the random forest classification. The observed relationships suggest that the physiological mechanism triggering winter reddening involves winter drought and photo-oxidative stress, but not cold deacclimation. Our results build an important basis to define the conditions that could be controlled for during experimental testing of the mechanism of reddening, and identify vulnerable areas for physiological monitoring and mitigation measures to reduce the vulnerability of young trees.
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