FLR-Library reference information system for adaptive forest restoration: cluster analysis of descriptors
Abstract and keywords
Abstract (English):
The lack of uniform terminological and technological approaches to the procedure of adaptive reforestation suggests the justification of the principles of creating a reference information system (FLR-Library), taking into account the specifics of implementing a joint decomposed FLR algorithm to reduce its execution time and rational forecasting of future forest landscape restoration projects. Collected and analyzed more than 120 definitions for more than 30 descriptors, such as "forest", "forest landscapes", "adaptive reforestation", "concepts of adaptive reforestation", "reforestation", "afforestation", "stand", "forest plantation", "forest complex", "forest landscape", "type of forest" and others. Both distinctive features and common points in the definitions of different countries and authors of the same descriptor are found. Technically, an approach to clustering of the most common descriptors is implemented: "forest", "forest landscapes", "reforestation", "afforestation". To do this, for each descriptor, based on the hierarchical clustering module, the combination of a cluster of recalibrated distances was determined and a cluster diagram was constructed based on «variables» (criteria for the descriptors effectiveness) and «observations» (by countries containing a source of information with a descriptor). Common to all sources will be that adaptive reforestation implies adaptation to climate change, but then there are two options for development: 1) planting (sowing) breeds resistant to climate change; 2) import and adaptation of "southern" breeds to northern latitudes. In the future, based on the analysis of descriptors and the principle of decomposition, it is planned to develop an algorithm for the functioning of the FLR system.

Keywords:
restoration of forest landscapes, adaptive reforestation, reference system, terminology, countries by forest area, countries by active forest management, relational data model
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References

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