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Naslov:Empirical vs. light-use efficiency modelling for estimating carbon fluxes in a mid-succession ecosystem developed on abandoned karst grassland
Avtorji:ID Noumonvi, Koffi Dodji (Avtor)
ID Ferlan, Mitja (Avtor)
Datoteke:.pdf PDF - Predstavitvena datoteka, prenos (3,07 MB)
MD5: B4888CEBDCB1898AD52717FAC36AC5A7
 
URL URL - Izvorni URL, za dostop obiščite https://doi.org/10.1371/journal.pone.0237351
 
Jezik:Angleški jezik
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:Logo SciVie - Gozdarski inštitut Slovenije
Povzetek:Karst systems represent an important carbon sink worldwide. However, several phenomena such as the CO2 degassing and the exchange of cave air return a considerable amount of CO2 to the atmosphere. It is therefore of paramount importance to understand the contribution of the ecosystem to the carbon budget of karst areas. In this study conducted in a mid-succession ecosystem developed on abandoned karst grassland, two types of model were assessed, estimating the gross primary production (GPP) or the net ecosystem exchange (NEE) based on seven years of eddy covariance data (2013%2019): (1) a quadratic vegetation index-based empirical model with five alternative vegetation indices as proxies of GPP and NEE, and (2) the vegetation photosynthesis model (VPM) which is a light use efficiency model to estimate only GPP. The Enhanced Vegetation Index (EVI) was the best proxy for NEE whereas SAVI performed very similarly to EVI in the case of GPP in the empirical model setting. The empirical model performed better than the VPM model which tended to underestimate GPP. Therefore, for this ecosystem, we suggest the use of the empirical model provided that the quadratic relationship observed persists. However, the VPM model would be a good alternative under a changing climate, as it is rooted in the understanding of the photosynthesis process, if the scalars it involves could be improved to better estimate GPP.
Ključne besede:eddy covariance, carbon flux, GPP, NEE, vegetation indices, remote sensing, satellite data, GPP map
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Leto izida:2020
Št. strani:18 str.
Številčenje:e 0237351, iss. 8
PID:20.500.12556/DiRROS-14690 Novo okno
UDK:630*1+630*58
ISSN pri članku:1932-6203
DOI:10.1371/journal.pone.0237351 Novo okno
COBISS.SI-ID:29022723 Novo okno
Opomba:Nasl. iz nasl. zaslona; Opis vira z dne 21. 9. 2020;
Datum objave v DiRROS:03.01.2022
Število ogledov:988
Število prenosov:630
Metapodatki:XML DC-XML DC-RDF
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Gradivo je del revije

Naslov:PloS one
Založnik:Public Library of Science
ISSN:1932-6203
COBISS.SI-ID:2005896 Novo okno

Gradivo je financirano iz projekta

Financer:EC - European Commission
Program financ.:H2020
Številka projekta:774234
Naslov:Development of Integrated Web-Based Land Decision Support System Aiming Towards the Implementation of Policies for Agriculture and Environment
Akronim:LANDSUPPORT

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:Z4-8217
Naslov:Identifikacija drevesnega koreninskega sistema in spremljanje zadrževanja vode v tleh z označevalnimi poizkusi

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:P4-0107
Naslov:Gozdna biologija, ekologija in tehnologija

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:03.01.2022

Sekundarni jezik

Jezik:Ni določen
Ključne besede:mikrometeorološke metode, metoda kovariance vrtincev, tok ogljika, GPP, NEE, modeliranje, vegetacijski indeksi, daljinsko zaznavanje


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