Analyzing the occurrence of an invasive aquatic fern in wetland using data-driven and multivariate techniques

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41340%2F17%3A75590" target="_blank" >RIV/60460709:41340/17:75590 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/s11273-017-9530-6" target="_blank" >http://dx.doi.org/10.1007/s11273-017-9530-6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11273-017-9530-6" target="_blank" >10.1007/s11273-017-9530-6</a>

Result language

angličtina

Original language name

Analyzing the occurrence of an invasive aquatic fern in wetland using data-driven and multivariate techniques

Original language description

In the present study, the data-driven (classification trees and support vector machines) and multivariate techniques (principal component analysis and discriminant analysis) were applied to study the habitat preferences of an invasive aquatic fern (Azolla filiculoides) in the Selkeh Wildlife Refuge (a protected area in Anzali wetland, northern Iran). The applied database consisted of measurements from seven different sampling sites in the protected area over the study period 2007 and 2008. The cover percentage of the exotic fern was modelled based on various wetland characteristics. The predictive performances of the both data-driven methods were assessed based on the percentage of Correctly Classified Instances and Cohens kappa statistics. The results of the t test showed that SVMs outperformed the CTs and thus yielded more reliable prediction than the CTs. All data mining and multivariate techniques showed that both physical habitat and water quality variables (in particular some nutrients) might a

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

40106 - Agronomy, plant breeding and plant protection; (Agricultural biotechnology to be 4.4)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2017

Confidentiality

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

Name of the periodical

Wetlands Ecology and Management

ISSN

0923-4861

e-ISSN

—

Volume of the periodical

25

Issue of the periodical within the volume

4

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

16

Pages from-to

485-500

UT code for WoS article

000406288200008

EID of the result in the Scopus database

2-s2.0-85013104340