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- Chiwara, P., et al.
(författare)
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Estimating terrestrial gross primary productivity in water limited ecosystems across Africa using the Southampton Carbon Flux (SCARF) model
- 2018
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Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697. ; 630, s. 1472-1483
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Tidskriftsartikel (refereegranskat)abstract
- The amount of carbon uptake by vegetation is an important component to understand the functioning of ecosystem processes and their response/feedback to climate. Recently, a new diagnostic model called the Southampton Carbon Flux (SCARF) Model driven by remote sensing data was developed to predict terrestrial gross primary productivity (GPP) and successfully applied in temperate regions. The model is based on the concept of quantum yield of plants and improves on the previous diagnostic models by (i) using the fraction of photosynthetic active radiation absorbed by the photosynthetic pigment (FAPARps) and (ii) using direct quantum yield by classifying the vegetation into C3 or C4 classes. In this paper, we calibrated and applied the model to evaluate GPP across various ecosystems in Africa. The performance of the model was evaluated using data from seven eddy covariance flux tower sites. Overall, the modelled GPP values showed good correlation (R > 0.59, p < 0.0001) with estimated flux tower GPP at most sites (except at a tropical rainforest site, R = 0.38, p = 0.02) in terms of their seasonality and absolute values. Mean daily GPP across the investigated period varied significantly across sites depending on the vegetation types from a minimum of 0.44 g C m−2 day−1 at the semi-arid and sub-humid savanna grassland sites to a maximum of 9.86 g C m−2 day−1 at the woodland and tropical rain forest sites. Generally, strong correlation is observed in savanna woodlands and grasslands where vegetation follows a prescribed seasonal cycle as determined by changes in canopy chlorophyll content and leaf area index. Finally, the mean annual GPP value for Africa predicted by the model was 35.25 Pg C yr−1. The good performance of the SCARF model in water-limited ecosystems across Africa extends its potential for global application.
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| 2. |
- Chiwara, P, et al.
(författare)
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Evaluating the Potential of Southampton Carbon Flux Model (SCARF) for Monitoring Terrestrial Gross Primary Productivity Across African Ecosystems
- 2016
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Ingår i: AGU Fall Meeting Abstracts.
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Konferensbidrag (refereegranskat)abstract
- Accurate knowledge about the amount and dynamics of terrestrial gross primary productivity is an important component for understanding of ecosystem functioning and processes. Recently a new diagnostic model, Southampton Carbon Flux (SCARF), was developed to predict terrestrial gross primary productivity at regional to global scale based on a chlorophyll index derived from MERIS data. The model aims at mitigating some shortcomings in traditional light-use-efficiency based models by (i) using the fraction of photosynthetic active radiation absorbed only by the photosynthetic components of the canopy (FAPARps) and (ii) using the intrinsic quantum yields of C3 and C4 photosynthesis thereby reducing errors from land cover misclassification. Initial evaluation of the model in northern higher latitude ecosystems shows good agreement with in situ measurements. The current study calibrated and validated the model for a diversity of vegetation types across Africa in order to test its performance over a water limiting environment. The validation was based on GPP measurements from seven eddy flux towers across Africa. Sensitivity and uncertainty analyses were also performed to determine the importance of key biophysical and meteorological input parameters.Overall, modelled GPP values show good agreement with in situ measured GPP at most sites except tropical rainforest site. Mean daily GPP varied significantly across sites depending on the vegetation types and climate; from a minimum of -0.12 gC m2 day-1 for the semi-arid savannah to a maximum of 7.30 gC m2 day-1 for tropical rain forest ecosystems at Ankasa (Ghana). The model results have modest to very strong positive agreement with observed GPP at most sites (R2 values ranging from 0.60 for Skukuza in South Africa) and 0.85 for Mongu in Zambia) except tropical rain forest ecosystem (R2=0.34). Overall, the model has a stronger across-site coefficient of determination (R2=0.78) than MOD17 GPP product (R2=0.68). PAR and VPD are the parameters that propagate much variation in model output at most sites especially in semi-arid and sub-humid ecosystems. The results demonstrate that the SCARF model can improve prediction of GPP across a wide range of African ecosystems..Key words: GPP, climate change, diagnostic model, photosynthetic quantum yield, C3/C4 photosynthesis
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