Central-European vegetation types and their optima along successional gradient

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F20%3A43901303" target="_blank" >RIV/60076658:12310/20:43901303 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985939:_____/20:00539975 RIV/00216224:14310/20:00117754

Výsledek na webu

<a href="http://www.preslia.cz/P204Tichy.pdf" target="_blank" >http://www.preslia.cz/P204Tichy.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.23855/preslia.2020.341" target="_blank" >10.23855/preslia.2020.341</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Central-European vegetation types and their optima along successional gradient

Popis výsledku v původním jazyce

Although the identification of plant communities is the basic language of communication, studies that focus on the classification of vegetation in successional series are rather rare, mainly because it is difficult to identify different types of vegetation. Thanks to formalized algorithms of machine learning, we were able to assign some of vegetation plots stored in a Database of Successional Series (DaSS) to alliances in the vegetation classification system. Of the samples in DaSS 67.4% were classified into 96 vegetation alliances. Classification of the seral stages was then used to predict optima and intervals of occurrence of 33 main types of vegetation in the first 70 years from the onset of succession. In accordance with general expectations, main types of vegetation were arranged at the time-scale from ruderal and segetal vegetation, across grasslands to shrubby and forest vegetation. Successional optima of particular units of vegetation can be used to roughly predict the successional changes at human-disturbed sites in central Europe.

Název v anglickém jazyce

Central-European vegetation types and their optima along successional gradient

Popis výsledku anglicky

Although the identification of plant communities is the basic language of communication, studies that focus on the classification of vegetation in successional series are rather rare, mainly because it is difficult to identify different types of vegetation. Thanks to formalized algorithms of machine learning, we were able to assign some of vegetation plots stored in a Database of Successional Series (DaSS) to alliances in the vegetation classification system. Of the samples in DaSS 67.4% were classified into 96 vegetation alliances. Classification of the seral stages was then used to predict optima and intervals of occurrence of 33 main types of vegetation in the first 70 years from the onset of succession. In accordance with general expectations, main types of vegetation were arranged at the time-scale from ruderal and segetal vegetation, across grasslands to shrubby and forest vegetation. Successional optima of particular units of vegetation can be used to roughly predict the successional changes at human-disturbed sites in central Europe.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10618 - Ecology

Projekt

<a href="/cs/project/GA20-06065S" target="_blank" >GA20-06065S: Sukcese vegetace na širokých geografických škálách: Uzrál čas pro meta-analýzy</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název periodika

Preslia : časopis České botanické společnosti

ISSN

0032-7786

e-ISSN

—

Svazek periodika

92

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

12

Strana od-do

341-352

Kód UT WoS článku

000600545400001

EID výsledku v databázi Scopus

2-s2.0-85098693850