Vegetation-specific model parameters are not required for estimating gross primary production
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43410%2F14%3A00229827" target="_blank" >RIV/62156489:43410/14:00229827 - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/67179843:_____/14:00432456
Výsledek na webu
<a href="http://dx.doi.org/10.1016/j.ecolmodel.2014.08.017" target="_blank" >http://dx.doi.org/10.1016/j.ecolmodel.2014.08.017</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ecolmodel.2014.08.017" target="_blank" >10.1016/j.ecolmodel.2014.08.017</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Vegetation-specific model parameters are not required for estimating gross primary production
Popis výsledku v původním jazyce
Models of gross primary production (GPP) based on remote sensing measurements are currently parameterized with vegetation-specific parameter sets and therefore require accurate information on the distribution of vegetation to drive them. Can this parameterization scheme be replaced with a vegetation-invariant set of parameters that can maintain or increase model applicability by reducing errors introduced from the uncertainty of land cover classification? Based on the measurements of ecosystem carbon fluxes from 168 globally distributed sites in a range of vegetation types, we examined the predictive capacity of seven light use efficiency (LUE) models. Two model experiments were conducted: (i) a constant set of parameters for various vegetation types and (ii) vegetation-specific parameters. The results showed no significant differences in model performance in simulating GPP while using both set of parameters. These results indicate that a universal of set of parameters, which is indepe
Název v anglickém jazyce
Vegetation-specific model parameters are not required for estimating gross primary production
Popis výsledku anglicky
Models of gross primary production (GPP) based on remote sensing measurements are currently parameterized with vegetation-specific parameter sets and therefore require accurate information on the distribution of vegetation to drive them. Can this parameterization scheme be replaced with a vegetation-invariant set of parameters that can maintain or increase model applicability by reducing errors introduced from the uncertainty of land cover classification? Based on the measurements of ecosystem carbon fluxes from 168 globally distributed sites in a range of vegetation types, we examined the predictive capacity of seven light use efficiency (LUE) models. Two model experiments were conducted: (i) a constant set of parameters for various vegetation types and (ii) vegetation-specific parameters. The results showed no significant differences in model performance in simulating GPP while using both set of parameters. These results indicate that a universal of set of parameters, which is indepe
Klasifikace
Druh
J<sub>x</sub> - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
CEP obor
EH - Ekologie – společenstva
OECD FORD obor
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Návaznosti výsledku
Projekt
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Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2014
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Ecological Modelling
ISSN
0304-3800
e-ISSN
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Svazek periodika
292
Číslo periodika v rámci svazku
24 November 2014
Stát vydavatele periodika
NL - Nizozemsko
Počet stran výsledku
10
Strana od-do
1-10
Kód UT WoS článku
343845400001
EID výsledku v databázi Scopus
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