A REVIEW OF METHODS FOR MODELING TREE RESPONSE TO CLIMATE CHANGE USING PROVENANCES TRIALS DATA
A. V. Lebedev
Russian State Agrarian University - Moscow Timiryazev Agricultural Academy, Moscow, Russian Federation
Keywords: transfer distance, transfer function, response function, genetic effects, phenotypic plasticity, species adaptation, climate-smart forestry
Abstract
Climate warming in recent decades has had a strong impact on tree populations, which will either adapt to new conditions or their mortality rate increases. The results of provenance tests can serve as a reliable basis for studying the response of trees to environmental change. Since the early 1990s, modeling of phenotypic traits of populations from climatic factors (seed origin and testing sites) and the use of such models in forestry practice have been developed in foreign countries. The objective of this review is to consider the main approaches to modeling tree responses to climate change based on provenance test data and discuss their application to climate-smart forestry. Individual transfer and reaction functions and more complex models (generalized transfer function and universal transfer and reaction functions) are useful tools for solving problems related to forecasting the response of tree populations (growth, productivity and survival) to climate change and assessing their adaptive potential, developing recommendations for seed transfer (including assisted migration) and climate-smart forest seed zoning, safing and increasing the resource and ecological potential of future forests. The results of historical and current provenance tests in conditions of rapid climate warming have special scientific and practical value. The development of reliable models for forecasting the response of forest-forming tree species populations to changing environmental conditions is possible in the presence of representative data on their phenotypic variability. This requires the formation of databases combining the results of provenance tests data.
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