Common Scots pine deployment recommendations for Sweden and Finland
For the past decade, Sweden and Finland have been collaborating on research and development of a joint system for deployment recommendations of Scots pine. Recently, transfer effect models based on tailored climate variables and covering both countries were developed. However, to provide deployment recommendations for Swedish and Finnish improved plant material a common framework for standardizing seed orchard traits and combining them into a compound measure of performance must be developed. Together with deployment zone limits, this measure of performance can then be used to rank and select plants from seed orchards at an arbitrarily selected regeneration site.
This report describes how all key traits needed to predict seed orchard performance in growth and survival at a regeneration site in Sweden or Finland are defined and calculated. This includes e.g. the amount of external pollen contamination, how to calculate a standardized origin of the trees in the seed orchard and how that affects its reaction patterns. A key task has been to categorize the seed orchards, standardize the estimates of genetic gain and the effect of different management regimes. The report also shows how growth and survival are combined to predict areal production over a rotation and ranking of the seed orchards.
In addition, a framework for assigning valid deployment zones for each seed orchard has been developed. This includes both biological and administrative limitations that partly differ between the two countries.
In summary, this report is primarily a technical description which together with the scientific background constitutes the new joint Swedish-Finnish deployment recommendations for Scots pine. The next step is to implement this framework in a web-based decision support tool (Planter’s Guide) across both countries and in both languages.
The Planter’s Guide tool is planned for operational release in the autumn of 2019.
This project has received funding from the European Union's Horizon 2020 Programme for Research & Innovation under grant agreement No 773383.
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