A Static Model of Abiotic Predictors and Forest Ecosystem Receptor Designed Using Dimensionality Reduction and Regression Analysis

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F16%3A00467364" target="_blank" >RIV/86652079:_____/16:00467364 - isvavai.cz</a>

Alternative codes found

RIV/62156489:43410/16:43910894 RIV/47813059:19240/16:N0000201 RIV/61989592:15310/16:33161845

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

A Static Model of Abiotic Predictors and Forest Ecosystem Receptor Designed Using Dimensionality Reduction and Regression Analysis

Original language description

The closeness of dependence level between growth environment (abiotic predictors) and forest ecosystem (receptor) indicatesnaccordance or discrepancy between site and forest state. Our forest ecosystem analysis was focused on static model approximationnbetween abiotic predictors with the closest dependence and properties of the receptor at 11 km grid in the Czech Republic (CentralnEurope). The predictors have been selected from natural abiotic quantities sets of temperatures, precipitation, acid deposition, soilnproperties and relative site insolation. The receptor properties have been selected from remote sensing data, density and volume ofnabove-ground biomass of forest stands according to the forest management plans, and from surface humus chemical properties. Anselection of the most dependent quantities was made by combining factor analysis and cluster analysis. The static modelling of thendependences between selected predictors and receptor properties was conducted by canonical correlation analysis. Average temperature,nannual precipitation, total potential acid deposition, soil base saturation, CEC, total acid elements and site insolation indexnclosely corresponded to NDVI and surface humus base saturation, Corg and acid elements content at 30% of the analysed grid ofnforest soils and it indicated forest state within the confidence interval at 69% of the forest soil grid (rCCA = 0.79; P < 0.00001). Thenforest ecosystem state that corresponds to the selected abiotic predictors was demonstrated in hilly altitudes. The tested procedure isninconvenient for forest state analysis in floodplains and moorlands. Based on approximation deviations, highland and mountain forestsnwere divided into areas with non-optimum or more optimum ecosystem state than as corresponds to the values of the predictors.n

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

EH - Ecology - communities

OECD FORD branch

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Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2016

Confidentiality

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

Name of the periodical

Baltic Forestry

ISSN

1392-1355

e-ISSN

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Volume of the periodical

22

Issue of the periodical within the volume

2

Country of publishing house

LT - LITHUANIA

Number of pages

14

Pages from-to

259-274

UT code for WoS article

000392367900009

EID of the result in the Scopus database

2-s2.0-85008485191