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| Titel |
Estimation of Mangrove Net Primary Production and Carbon Sequestration service using Light Use Efficiency model in the Sunderban Biosphere region, India |
| VerfasserIn |
Srikanta Sannigrahi, Somnath Sen, Saikat Paul |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250122768
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| Publikation (Nr.) |
 EGU/EGU2016-1884.pdf |
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| Zusammenfassung |
| Net Primary Production (NPP) of mangrove ecosystem and its capacity to sequester carbon
from the atmosphere may be used to quantify the regulatory ecosystem services.
Three major group of parameters has been set up as BioClimatic Parameters (BCP):
(Photosynthetically Active Radiation (PAR), Absorbed PAR (APAR), Fraction of PAR
(FPAR), Photochemical Reflectance Index (PRI), Light Use Efficiency (LUE)),
BioPhysical Parameters (BPP) :(Normalize Difference Vegetation Index (NDVI), scaled
NDVI, Enhanced Vegetation Index (EVI), scaled EVI, Optimised and Modified
Soil Adjusted Vegetation Index (OSAVI, MSAVI), Leaf Area Index (LAI)), and
Environmental Limiting Parameters (ELP) (Temperature Stress (TS), Land Surface Water
Index (LSWI), Normalize Soil Water Index (NSWI), Water Stress Scalar (WS),
Inversed WS (iWS) Land Surface Temperature (LST), scaled LST, Vapor Pressure
Deficit (VPD), scaled VPD, and Soil Water Deficit Index (SWDI)). Several LUE
models namely Carnegie Ames Stanford Approach (CASA), Eddy Covariance
– LUE (EC-LUE), Global Production Efficiency Model (GloPEM), Vegetation
Photosynthesis Model (VPM), MOD NPP model, Temperature and Greenness Model (TG),
Greenness and Radiation model (GR) and MOD17 was adopted in this study to assess
the spatiotemporal nature of carbon fluxes. Above and Below Ground Biomass
(AGB & BGB) was calculated using field based estimation of OSAVI and NDVI.
Microclimatic zonation has been set up to assess the impact of coastal climate on
environmental limiting factors. MODerate Resolution Imaging Spectroradiometer (MODIS)
based yearly Gross Primary Production (GPP) and NPP product MOD17 was also
tested with LUE based results with standard model validation statistics: Root Mean
Square of Error (RMSE), Mean Absolute Error (MEA), Bias, Coefficient of Variation
(CV) and Coefficient of Determination (R2). The performance of CASA NPP was
tested with the ground based NPP with R2 = 0.89 RMSE = 3.28 P = 0.01. Among
the all adopted models, EC-LUE and VPM models has explained the maximum
variances (>80%) in comparison to the other model. Study result has also showed that
the BPP has explained the maximum model variances (>93%) followed by BCP
(>65%) and ELP (>50%). Scaled WS, iWS, LST, VPD, NDVI was performed
better in a minimum ELP condition whereas surface moisture and wetness was
highly correlated with the AGB and NPP (R2 = 0.86 RMSE = 1.83). During this
study period (2000-2013), it was found that there was a significantly declining
trend (R2 = 0.32 P = 0.05) of annual NPP and the maximum decrease was found in
the eastern part where built-up area was mainly accounted for reduction of NPP.
BCP are explained higher variances (>80%) in the optimum climatic condition
exist along the coastal stretches in comparison to the landward extent (>45%). |
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