Please use this identifier to cite or link to this item:
Type of publication: research article
Type of publication (PDB): Straipsnis Clarivate Analytics Web of Science / Article in Clarivate Analytics Web of Science (S1)
Field of Science: Miškotyra / Forestry (A004)
Author(s): Kuliešis, Andrius;Kasperavičius, Albertas;Kulbokas, Gintaras;Kuliešis, Andrius A;Pivoriūnas, Aidas;Aleinikovas, Marius;Šilinskas, Benas;Škėma, Mindaugas;Beniušienė, Lina
Title: Using continuous forest inventory data for control of wood production and use in large areas: a case study in Lithuania
Is part of: Forests. Basel : MDPI AG, 2020, vol. 11, iss. 10
Extent: p. 1-19
Date: 2020
Keywords: Forest areas;Growing stock volume;Gross annual increment;Natural losses;Standwise forest inventorytand density
Abstract: Background and Objectives: Significant progress in developing European national forest inventory (NFI) systems could ensure accurate evaluations of gross annual increment (GAI) and its components by employing direct measurements. However, the use of NFI data is insufficient for increasing the efficiency of forest management and the use of wood, as well as for meeting sustainable forestry needs. Specification of forest characteristics, such as GAI and its components, identification of the main factors that impact forest growth, accumulation of wood, and natural losses are among the key elements promoting the productivity of forest stands and possibilities of rational use of wood in large forest areas. The aims of this research were (a) to validate the quality of forest statistics provided by a standwise forest inventory (SFI) and (b) to reveal the potential benefits of rational wood use at the country level through the analysis of forest management results, which are based on GAI, including its components derived from the NFI. Materials and Methods: SFI and NFI data from 1998–2017 were collected from 5600 permanent sample plots and used to evaluate the main forest characteristics. Potential wood use was estimated based on the assumption that 50–70% of the total GAI is accumulated for final forest use. Results: Mean growing stock volume (GSV) is underestimated by 7–14% on average in the course of SFI. Therefore, continuous monitoring of the yield changes in forest stands, detection of factors negatively affecting yield and its accumulation, and regulation of these processes by silviculture measures could increase potential forest use in Lithuania. Conclusions: Implementation of sample-based NFI resulted in an improvement of forest characteristics and led to an increase in GSV and GAI. Continuously gathered data on GAI and its components are a prerequisite for efficient forest management and control of the use [...]
Affiliation(s): Kauno miškų ir aplinkos inžinerijos kolegija
Lietuvos agrarinių ir miškų mokslų centro filialas Miškų institutas
Miškų ir ekologijos fakultetas
Privačių miškų savininkų asociacija
Valstybinė miškų tarnyba
Vytauto Didžiojo universitetas
Appears in Collections:1. Straipsniai / Articles
Universiteto mokslo publikacijos / University Research Publications

Files in This Item:
marc.xml9.58 kBXMLView/Open

MARC21 XML metadata

Show full item record
Export via OAI-PMH Interface in XML Formats
Export to Other Non-XML Formats

CORE Recommender

Citations 5

checked on Apr 24, 2021

Page view(s)

checked on May 1, 2021


checked on May 1, 2021

Google ScholarTM



This item is licensed under a Creative Commons License Creative Commons