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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14410%2F18%3A00103630" target="_blank" >RIV/00216224:14410/18:00103630 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989592:15310/18:73592431

Výsledek na webu

<a href="https://www.mdpi.com/1999-4907/9/2/96" target="_blank" >https://www.mdpi.com/1999-4907/9/2/96</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/f9020096" target="_blank" >10.3390/f9020096</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10508 - Physical geography

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Forests

ISSN

1999-4907

e-ISSN

1999-4907

Svazek periodika

9

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

18

Strana od-do

—

Kód UT WoS článku

000427520600049

EID výsledku v databázi Scopus

2-s2.0-85057062611