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Scots pine transfer effect models for growth and survival in Sweden and Finland
Author(s) -
Mats Berlin,
Torgny Persson,
Gunnar Jansson,
Matti Haapanen,
Seppo Ruotsalainen,
Lars Bärring,
Bengt Andersson Gull
Publication year - 2016
Publication title -
silva fennica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.622
H-Index - 60
eISSN - 2242-4075
pISSN - 0037-5330
DOI - 10.14214/sf.1562
Subject(s) - scots pine , environmental science , software deployment , climate change , physical geography , forestry , geography , pinus <genus> , ecology , biology , computer science , botany , operating system
In this study, we developed models of transfer effects for growth and survival of Scots pine (Pinus sylvestris L.) in Sweden and Finland using a general linear mixed-model approach. For model development, we used 378 provenance and progeny trials with a total of 276 unimproved genetic entries (provenances and stand seed check-lots) distributed over a wide variety of climatic conditions in both countries. In addition, we used 119 progeny trials with 3921 selected genetic entries (open- and control pollinated plus-tree families) for testing model performance. As explanatory variables, both climatic indices derived from high-resolution gridded climate datasets and geographical variables were used. For transfer, latitude (photoperiod) and, for describing the site, temperature sum were found to be main drivers for both survival and growth. In addition, interaction terms (between transfer in latitude and site altitude for survival, and transfer in latitude and temperature sum for growth) entail changed reaction patterns of the models depending on climatic conditions of the growing site. The new models behave in a way that corresponds well to previous studies and recommendations for both countries. The model performance was tested using selected plus-trees from open and control pollinated progeny tests. Results imply that the models are valid for both countries and perform well also for genetically improved material. These models are the first step in developing common deployment recommendations for genetically improved forest regeneration material in both Sweden and Finland.

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