| Title: | Empirical vs. light-use efficiency modelling for estimating carbon fluxes in a mid-succession ecosystem developed on abandoned karst grassland |
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| Authors: | ID Noumonvi, Koffi Dodji (Author)
ID Ferlan, Mitja (Author) |
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| Files: |  PDF - Presentation file, download (3,07 MB)
MD5: B4888CEBDCB1898AD52717FAC36AC5A7
 URL - Source URL, visit https://doi.org/10.1371/journal.pone.0237351
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| Language: | English |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: |  SciVie - Slovenian Forestry Institute
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| Abstract: | 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. |
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| Keywords: | eddy covariance, carbon flux, GPP, NEE, vegetation indices, remote sensing, satellite data, GPP map |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Year of publishing: | 2020 |
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| Number of pages: | 18 str. |
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| Numbering: | e 0237351, iss. 8 |
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| PID: | 20.500.12556/DiRROS-14690  |
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| UDC: | 630*1+630*58 |
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| ISSN on article: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0237351 |
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| COBISS.SI-ID: | 29022723 |
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| Note: | Nasl. iz nasl. zaslona;
Opis vira z dne 21. 9. 2020;
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| Publication date in DiRROS: | 03.01.2022 |
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| Views: | 986 |
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| Downloads: | 630 |
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| Metadata: |    |
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