Predictors for digital mapping of forest soil organic carbon stocks in different types of landscape

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F22%3A00126065" target="_blank" >RIV/00216224:14310/22:00126065 - isvavai.cz</a>

Alternative codes found

RIV/60460709:41210/22:89980

Result on the web

<a href="https://www.agriculturejournals.cz/web/swr.htm?type=article&id=4_2022-SWR" target="_blank" >https://www.agriculturejournals.cz/web/swr.htm?type=article&id=4_2022-SWR</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.17221/4/2022-SWR" target="_blank" >10.17221/4/2022-SWR</a>

Result language

angličtina

Original language name

Predictors for digital mapping of forest soil organic carbon stocks in different types of landscape

Original language description

Forest soils have a high potential to store carbon and thus mitigate climate change. The information on spatial distribution of soil organic carbon (SOC) stocks is thus very important. This study aims to analyse the importance of environmental predictors for forest SOC stock prediction at the regional and national scale in the Czech Republic. A big database of forest soil data for more than 7 000 sites was compiled from several surveys. SOC stocks were calculated from SOC content and bulk density for the topsoil mineral layer 0-30 cm. Spatial prediction models were developed separately for individual natural forest areas and for four subsets with different altitude range, using random forest method. The importance of environmental predictors in the models strongly differs between regions and altitudes. At lower altitudes, forest edaphic series and soil classes are strong predictors, while at higher altitudes the predictors related to topography become more important. The importance of soil classes depends on the pedodiversity level and on the difference in SOC stock between the classes. The contribution of forest types as predictors is limited when one (mostly coniferous) type dominates. Better prediction results can be obtained in smaller, but consistent regions, like some natural forest areas.

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

10503 - Water resources

Project

<a href="/en/project/QK1920163" target="_blank" >QK1920163: Development and verification of spatial models of forest soil properties in the Czech Republic</a><br>

Continuities

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

Publication year

2022

Confidentiality

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

Name of the periodical

SOIL AND WATER RESEARCH

ISSN

1801-5395

e-ISSN

—

Volume of the periodical

17

Issue of the periodical within the volume

2

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

11

Pages from-to

69-79

UT code for WoS article

000753949300001

EID of the result in the Scopus database

2-s2.0-85129909085