Сибирский федеральный университет

Тип публикации: статья из журнала

Год издания: 2020

Идентификатор DOI: 10.17516/1997-1370-0691

Ключевые слова: autoregressive distributed lag model, forestry, global climate change, logging season, logging volumes

Аннотация: As a part of global economy, forestry experiences influence of diverse factors and global climate change in particular, which can affect forestry directly or indirectly via changes in qualitative and quantitative assessment of forest growing stocks, and in positive or negative manner. Climate change effects on Russian forestry are still poorly studied and call for more attention in policy-making. One of the direct impacts is shortening of winter logging season duration, which may result in decreasing wood harvests. Using the data on logging volumes in Krasnoyarsk Krai and Irkutsk Oblast and estimated duration of winter logging season on meteorological stations for the retrospective period of 1966-2018, eight ARDL models were evaluated. The modeling results supported the idea of dependence of harvested wood volumes on winter logging season duration across all considered meteorological stations. To reduce negative impacts on logging industry in terms of wood harvest reduction, adaptation activities in forestry are sorely needed. © Siberian Federal University. All rights reserved

Журнал: Journal of Siberian Federal University - Humanities and Social Sciences

Выпуск журнала: Vol. 13, Is. 11

Номера страниц: 1870-1879

ISSN журнала: 19971370

Издатель: Siberian Federal University

• Chugunkova A.V. (Siberian Federal University, Krasnoyarsk, Russian Federation)

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