Partitioning Light and Water Use Efficiencies (LUE, WUE) between cover tree (Cocos nucifera L.) and grass under-storey, using eddy covariance, LAI-2000 and Net Primary Productivity (NPP)
Net Primary Productivity (NPP) is a key driver of ecosystem C balance. Its seasonal and annual variations can be measured directly at the stand level. However, estimating NPP on larger areas would require indirect methods such as: (i) process models, e.g. e-models based on the fraction of intercepted PAR (fIPAR) and on the light use efficiency (LUE = NPP/IPAR), or else models based on the water-use-efficiency (WUE = NPP/E, where E = evapo-transpiration); (ii) remote sensing, to estimate fIPAR (from the Normalized Difference Vegetation Index: NDVI) or else E (from the energy balance closure). However, two main impediments may interfere with such estimations of NPP: first, LUE and/or WUE may vary in time, and second, remote sensing may be unable to distinguish between the layers of the stands, which sounds critical for agroforestry systems. In a 20-year-old coconut grove from Vanuatu (South Pacific), we monitored NPP, E, LUE and WUE separately for the coconut layer (subscript "c"; LAI = 3; canopy cover around 75%) and for the under-storey composed of grasses (subscript "g"; LAI = 2.7). Light interception by the coconuts (IPARc) was estimated by optical indirect techniques (LAI-2000). Evapotranspiration of the whole stand (subscript "s"), Es, was measured directly by eddy-covariance, and the contribution of the coconuts was assessed by sapflow (Tc). Light interception and evapotranspiration from the under-storey (IPARg and Eg) was estimated from the difference. We reported elsewhere that NPPc represented 75% of NPPs (amounting to 32 tDM ha-1 year-1), Tc represented 68% of Es (amounting to 950 mm year-1) and IPARc amounted to 73% of incident PAR. This partitioning results were very close to the rule-of-thumb evaluation, based on the simple observation of the canopy closeness (0.75%). We found here that WUEs (mean annual value = 3.7 gDM kgH2O -1) was mainly driven by the coconuts (4.0), and to a lesser extent by the understorey (2.4). WUEs had high seasonal variations, between 2 and 6, being dependent mainly on Es rather than on NPPs. LUEs (mean annual value = 0.29 gDM molPARinc. -1) appeared to be similar for coconuts and for the understorey. LUEs also had high seasonal variations, between 0.18 and 0.52, which was mainly explained by seasonal variations of incident PAR rather than by variations of NPP. The large seasonality observed for LUE and WUE could be modelled empirically (0.82 < R2 < 0.95), which appears to be useful for running large scale process-models on similar plantations.
| Main Authors: | , , , , , , , , , , , |
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| Format: | conference_item biblioteca |
| Language: | eng |
| Published: |
CATIE
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| Subjects: | F08 - Systèmes et modes de culture, U10 - Informatique, mathématiques et statistiques, F60 - Physiologie et biochimie végétale, |
| Online Access: | http://agritrop.cirad.fr/540941/ |
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| Summary: | Net Primary Productivity (NPP) is a key driver of ecosystem C balance. Its seasonal and annual variations can be measured directly at the stand level. However, estimating NPP on larger areas would require indirect methods such as: (i) process models, e.g. e-models based on the fraction of intercepted PAR (fIPAR) and on the light use efficiency (LUE = NPP/IPAR), or else models based on the water-use-efficiency (WUE = NPP/E, where E = evapo-transpiration); (ii) remote sensing, to estimate fIPAR (from the Normalized Difference Vegetation Index: NDVI) or else E (from the energy balance closure). However, two main impediments may interfere with such estimations of NPP: first, LUE and/or WUE may vary in time, and second, remote sensing may be unable to distinguish between the layers of the stands, which sounds critical for agroforestry systems. In a 20-year-old coconut grove from Vanuatu (South Pacific), we monitored NPP, E, LUE and WUE separately for the coconut layer (subscript "c"; LAI = 3; canopy cover around 75%) and for the under-storey composed of grasses (subscript "g"; LAI = 2.7). Light interception by the coconuts (IPARc) was estimated by optical indirect techniques (LAI-2000). Evapotranspiration of the whole stand (subscript "s"), Es, was measured directly by eddy-covariance, and the contribution of the coconuts was assessed by sapflow (Tc). Light interception and evapotranspiration from the under-storey (IPARg and Eg) was estimated from the difference. We reported elsewhere that NPPc represented 75% of NPPs (amounting to 32 tDM ha-1 year-1), Tc represented 68% of Es (amounting to 950 mm year-1) and IPARc amounted to 73% of incident PAR. This partitioning results were very close to the rule-of-thumb evaluation, based on the simple observation of the canopy closeness (0.75%). We found here that WUEs (mean annual value = 3.7 gDM kgH2O -1) was mainly driven by the coconuts (4.0), and to a lesser extent by the understorey (2.4). WUEs had high seasonal variations, between 2 and 6, being dependent mainly on Es rather than on NPPs. LUEs (mean annual value = 0.29 gDM molPARinc. -1) appeared to be similar for coconuts and for the understorey. LUEs also had high seasonal variations, between 0.18 and 0.52, which was mainly explained by seasonal variations of incident PAR rather than by variations of NPP. The large seasonality observed for LUE and WUE could be modelled empirically (0.82 < R2 < 0.95), which appears to be useful for running large scale process-models on similar plantations. |
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