Selecting Populations for Non-Analogous Climate Conditions Using Universal Response Functions: The Case of Douglas-Fir in Central Europe

• Published in: PloS one 2015-08, Vol.10 (8), p.e0136357-e0136357
• Main Authors: Chakraborty, Debojyoti, Wang, Tongli, Andre, Konrad, Konnert, Monika, Lexer, Manfred J, Matulla, Christoph, Schueler, Silvio
• Format: Article
• Language: English
• Subjects: Acclimatization - physiology; Adaptation; Assisted migration; Biogeography; Cascades; Case studies; Climate Change; Climate change scenarios; Climate models; Climatic conditions; Coastal zone; Ecology; Ecosystem; Ecosystems; Empirical analysis; Europe; Evergreen trees; Forests; Global temperature changes; Life sciences; Models, Biological; Natural resources; North America; Performance prediction; Pinus ponderosa; Plant species; Populations; Precipitation; Precipitation (Meteorology); Precipitation regime; Principal components analysis; Provenance; Pseudotsuga - growth & development; Pseudotsuga - physiology; Pseudotsuga menziesii; Rainfall; Reforestation; Response functions; Soil sciences; Trees; Trees - growth & development; Trees - physiology
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0136357

Identifying populations within tree species potentially adapted to future climatic conditions is an important requirement for reforestation and assisted migration programmes. Such populations can be identified either by empirical response functions based on correlations of quantitative traits with climate variables or by climate envelope models that compare the climate of seed sources and potential growing areas. In the present study, we analyzed the intraspecific variation in climate growth response of Douglas-fir planted within the non-analogous climate conditions of Central and continental Europe. With data from 50 common garden trials, we developed Universal Response Functions (URF) for tree height and mean basal area and compared the growth performance of the selected best performing populations with that of populations identified through a climate envelope approach. Climate variables of the trial location were found to be stronger predictors of growth performance than climate variables of the population origin. Although the precipitation regime of the population sources varied strongly none of the precipitation related climate variables of population origin was found to be significant within the models. Overall, the URFs explained more than 88% of variation in growth performance. Populations identified by the URF models originate from western Cascades and coastal areas of Washington and Oregon and show significantly higher growth performance than populations identified by the climate envelope approach under both current and climate change scenarios. The URFs predict decreasing growth performance at low and middle elevations of the case study area, but increasing growth performance on high elevation sites. Our analysis suggests that population recommendations based on empirical approaches should be preferred and population selections by climate envelope models without considering climatic constrains of growth performance should be carefully appraised before transferring populations to planting locations with novel or dissimilar climate.