Application of GIS to Empirical Windthrow Risk Model in Mountain Forested Landscapes

KREJČÍ, Lukáš, Jaromír KOLEJKA, Vít VOŽENÍLEK a Ivo MACHAR. Application of GIS to Empirical Windthrow Risk Model in Mountain Forested Landscapes. Forests. Basel: MDPI AG, 2018, roč. 9, č. 2, s. nestránkováno, 18 s. ISSN 1999-4907. Dostupné z: https://dx.doi.org/10.3390/f9020096.

Základní údaje

Originální název

Application of GIS to Empirical Windthrow Risk Model in Mountain Forested Landscapes

Název česky

Využití GIS pro empirický model rizika polomů horských lesních krajin

Autoři

KREJČÍ, Lukáš (203 Česká republika), Jaromír KOLEJKA (203 Česká republika, garant, domácí), Vít VOŽENÍLEK (203 Česká republika) a Ivo MACHAR (203 Česká republika)

Vydání

Forests, Basel, MDPI AG, 2018, 1999-4907

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Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10508 Physical geography

Stát vydavatele

Švýcarsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 2.116

Kód RIV

RIV/00216224:14410/18:00103630

Organizační jednotka

Pedagogická fakulta

DOI

http://dx.doi.org/10.3390/f9020096

UT WoS

000427520600049

Klíčová slova česky

empirické modelování; narušení lesa; monokulury smrku ztepilého, model rizika; prostorová analýza; polom

Klíčová slova anglicky

empirical modelling; forest disturbance; Norway spruce dominated forests; risk model; spatial analysis; windthrow

Štítky

Forest, geoinformatics - geodatabase, GIS, models, mountains, windthrows

Příznaky

Mezinárodní význam, Recenzováno

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Anotace

V originále

Norway spruce dominates mountain forests in Europe. Natural variations in the mountainous coniferous forests are strongly influenced by all the main components of forest and landscape dynamics: species diversity, the structure of forest stands, nutrient cycling, carbon storage, and other ecosystem services. This paper deals with an empirical windthrow risk model based on the integration of logistic regression into GIS to assess forest vulnerability to wind-disturbance in the mountain spruce forests of Šumava National Park (Czech Republic). It is an area where forest management has been the focus of international discussions by conservationists, forest managers, and stakeholders. The authors developed the empirical windthrow risk model, which involves designing an optimized data structure containing dependent and independent variables entering logistic regression. The results from the model, visualized in the form of map outputs, outline the probability of risk to forest stands from wind in the examined territory of the national park. Such an application of the empirical windthrow risk model could be used as a decision support tool for the mountain spruce forests in a study area. Future development of these models could be useful for other protected European mountain forests dominated by Norway spruce.

Česky

Norway spruce dominates mountain forests in Europe. Natural variations in the mountainous coniferous forests are strongly influenced by all the main components of forest and landscape dynamics: species diversity, the structure of forest stands, nutrient cycling, carbon storage, and other ecosystem services. This paper deals with an empirical windthrow risk model based on the integration of logistic regression into GIS to assess forest vulnerability to wind-disturbance in the mountain spruce forests of Šumava National Park (Czech Republic). It is an area where forest management has been the focus of international discussions by conservationists, forest managers, and stakeholders. The authors developed the empirical windthrow risk model, which involves designing an optimized data structure containing dependent and independent variables entering logistic regression. The results from the model, visualized in the form of map outputs, outline the probability of risk to forest stands from wind in the examined territory of the national park. Such an application of the empirical windthrow risk model could be used as a decision support tool for the mountain spruce forests in a study area. Future development of these models could be useful for other protected European mountain forests dominated by Norway spruce.