scholarly journals Variabilidad de la eficiencia en el uso del carbono a partir de datos MODIS

2017 ◽  
pp. 1
Author(s):  
M. Cañizares ◽  
A. Moreno ◽  
S. Sánchez-Ruiz ◽  
M.A. Gilabert
Keyword(s):  
Primary Production ◽  
Net Primary Production ◽  
Vegetation Type ◽  
Gross Primary Production ◽  
Annual Average ◽  
Annual Variations ◽  
Carbon Use Efficiency ◽  
Temperature And Precipitation ◽  
Use Efficiency ◽  
Peninsular Spain

<p>Carbon use efficiency (CUE) describes how efficiently plants incorporate the carbon fixed during photosynthesis into biomass gain and can be calculated as the ratio between net primary production (NPP) and gross primary production (GPP). In this work, annual CUE has been obtained from annual GPP and NPP MODIS products for the peninsular Spain study area throughout eight years. CUE is spatially and temporally analyzed in terms of the vegetation type and annual precipitation and annual average air temperature. Results show that dense vegetation areas with moderate to high levels of precipitation present lower CUE values, whereas more arid areas present the highest CUE values. However, the temperature effect on the spatial variation of CUE is not well characterized. On the other hand, inter-annual variations of CUE of different ecosystems are discussed in terms of inter-annual variations of temperature and precipitation. It is shown that CUE exhibited a positive correlation with precipitation and a negative correlation with temperature in most ecosystems. Thus, CUE decreases when the ecosystem conditions change towards aridity.</p>

scholarly journals Global variability of carbon use efficiency in terrestrial ecosystems

2019 ◽  
Author(s):  
Xiaolu Tang ◽  
Nuno Carvalhais ◽  
Catarina Moura ◽  
Bernhard Ahrens ◽  
Sujan Koirala ◽  
...  
Keyword(s):  
Primary Production ◽  
Process Model ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Driving Factors ◽  
Spatial And Temporal Variability ◽  
Carbon Use Efficiency ◽  
Environmental Controls ◽  
C Cycle ◽  
Use Efficiency

Abstract. Vegetation carbon use efficiency (CUE) is a key measure of carbon (C) transfer from the atmosphere to terrestrial biomass, and indirectly reflects how much C is released through autotrophic respiration from the vegetation to the atmosphere. Diagnosing the variability of CUE with climate and other environmental factors is fundamental to understand its driving factors, and to further fill the current gaps in knowledge about the environmental controls on CUE. Thus, to study CUE variability and its driving factors, this study established a global database of site-year CUE based on observations from 188 field measurement sites for five ecosystem types – forest, grass, wetland, crop and tundra. The spatial pattern of CUE was predicted from global climate and soil variables using Random Forest, and compared with estimates from Dynamic Global Vegetation Models (DGVMs) from the TRENDY model ensemble. Globally, we found two prominent CUE gradients in ecosystem types and latitude, that is, CUE varied with ecosystem types, being the highest in wetlands and lowest in grassland, and CUE decreased with latitude with the lowest CUE in tropics, and the highest CUE in higher latitude regions. CUE varied greatly between data-derived CUE and TRENDY-CUE, but also among TRENDY models. Both data-derived and TRENDY-CUE challenged the constant value of 0.5 for CUE, independent of environmental controls. However, given the role of CUE in controlling the spatial and temporal variability of the terrestrial biosphere C cycle, these results emphasize the need to better understand the biotic and abiotic controls on CUE to reduce the uncertainties in prognostic land-process model simulations. Finally, this study proposed a new estimate of net primary production based on CUE and gross primary production, offering another benchmark for net primary production comparison for global carbon modelling.

scholarly journals Forest carbon use efficiency: is respiration a constant fraction of gross primary production?

2007 ◽  
Vol 13 (6) ◽  
pp. 1157-1167 ◽  
Author(s):  
EVAN H. DeLUCIA ◽  
JOHN E. DRAKE ◽  
RICHARD B. THOMAS ◽  
MIQUEL GONZALEZ-MELER
Keyword(s):  
Primary Production ◽  
Gross Primary Production ◽  
Forest Carbon ◽  
Carbon Use Efficiency ◽  
Use Efficiency

scholarly journals P-model v1.0: An optimality-based light use efficiency model for simulating ecosystem gross primary production

2019 ◽  
Author(s):  
Benjamin D. Stocker ◽  
Han Wang ◽  
Nicholas G. Smith ◽  
Sandy P. Harrison ◽  
Trevor F. Keenan ◽  
...  
Keyword(s):  
Primary Production ◽  
Satellite Data ◽  
Vegetation Type ◽  
Meteorological Data ◽  
Gross Primary Production ◽  
Satellite Monitoring ◽  
Light Use Efficiency ◽  
Spatial And Temporal Scales ◽  
Wide Range ◽  
Use Efficiency

Abstract. Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth System Model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a gross primary production (GPP, photosynthesis per unit ground area) model, the P-model, that combines the Farquhar-von Caemmerer-Berry model for C3 photosynthesis with an optimality principle for the carbon assimilation-transpiration trade-off, and predicts a multi-day average light use efficiency (LUE) for any climate and C3 vegetation type. The model is forced here with satellite data for the fraction of absorbed photosynthetically active radiation and site-specific meteorological data and is evaluated against GPP estimates from a globally distributed network of ecosystem flux measurements. Although the P-model requires relatively few inputs and prescribed parameters, the R2 for predicted versus observed GPP based on the full model setup is 0.75 (8-day mean, 131 sites) – better than some state-of-the-art satellite data-driven light use efficiency models. The R2 is reduced to 0.69 when not accounting for the reduction in quantum yield at low temperatures and effects of low soil moisture on LUE. The R2 for the P-model-predicted LUE is 0.37 (means by site) and 0.53 (means by vegetation type). The P-model provides a simple but powerful method for predicting – rather than prescribing – light use efficiency and simulating terrestrial photosythesis across a wide range of conditions. The model is available as an R package (rpmodel).

scholarly journals Net primary productivity, allocation pattern and carbon use efficiency in an apple orchard assessed by integrating eddy covariance, biometric and continuous soil chamber measurements

2013 ◽  
Vol 10 (5) ◽  
pp. 3089-3108 ◽  
Author(s):  
D. Zanotelli ◽  
L. Montagnani ◽  
G. Manca ◽  
M. Tagliavini
Keyword(s):  
Primary Production ◽  
Eddy Covariance ◽  
Gross Primary Production ◽  
Apple Orchard ◽  
Allocation Pattern ◽  
Carbon Use Efficiency ◽  
Standing Biomass ◽  
Measurement Protocol ◽  
Allocation Patterns ◽  
Use Efficiency

Abstract. Carbon use efficiency (CUE), the ratio of net primary production (NPP) over gross primary production (GPP), is a functional parameter that could possibly link the current increasingly accurate global GPP estimates with those of net ecosystem exchange, for which global predictors are still unavailable. Nevertheless, CUE estimates are actually available for only a few ecosystem types, while information regarding agro-ecosystems is scarce, in spite of the simplified spatial structure of these ecosystems that facilitates studies on allocation patterns and temporal growth dynamics. We combined three largely deployed methods, eddy covariance, soil respiration and biometric measurements, to assess monthly values of CUE, NPP and allocation patterns in different plant organs in an apple orchard during a complete year (2010). We applied a measurement protocol optimized for quantifying monthly values of carbon fluxes in this ecosystem type, which allows for a cross check between estimates obtained from different methods. We also attributed NPP components to standing biomass increments, detritus cycle feeding and lateral exports. We found that in the apple orchard, both net ecosystem production and gross primary production on a yearly basis, 380 ± 30 g C m−2 and 1263 ± 189 g C m−2 respectively, were of a magnitude comparable to those of natural forests growing in similar climate conditions. The largest differences with respect to forests are in the allocation pattern and in the fate of produced biomass. The carbon sequestered from the atmosphere was largely allocated to production of fruit: 49% of annual NPP was taken away from the ecosystem through apple production. Organic material (leaves, fine root litter, pruned wood and early fruit falls) contributing to the detritus cycle was 46% of the NPP. Only 5% was attributable to standing biomass increment, while this NPP component is generally the largest in forests. The CUE, with an annual average of 0.71 ± 0.12, was higher than the previously suggested constant values of 0.47–0.50. Low nitrogen investment in fruit, the limited root apparatus, and the optimal growth temperature and nutritional condition observed at the site are suggested to be explanatory variables for the high CUE observed.

scholarly journals Estimation of gross primary production of the Amazon-Cerrado transitional forest by remote sensing techniques

2014 ◽  
Vol 29 (1) ◽  
pp. 01-12 ◽  
Author(s):  
Maísa Caldas Souza ◽  
Marcelo Sacardi Biudes ◽  
Victor Hugo de Morais Danelichen ◽  
Nadja Gomes Machado ◽  
Carlo Ralph de Musis ◽  
...  
Keyword(s):  
Primary Production ◽  
Vegetation Type ◽  
Gross Primary Production ◽  
Circulation Model ◽  
Lookup Table ◽  
Sensor Data ◽  
Climatic Data ◽  
Light Use Efficiency ◽  
Transitional Forest ◽  
Use Efficiency

The gross primary production (GPP) of ecosystems is an important variable in the study of global climate change. Generally, the GPP has been estimated by micrometeorological techniques. However, these techniques have a high cost of implantation and maintenance, making the use of orbital sensor data an option to be evaluated. Thus, the objective of this study was to evaluate the potential of the MODIS (Moderate Resolution Imaging Spectroradiometer) MOD17A2 product and the vegetation photosynthesis model (VPM) to predict the GPP of the Amazon-Cerrado transitional forest. The GPP predicted by MOD17A2 (GPP MODIS) and VPM (GPP VPM) were validated with the GPP estimated by eddy covariance (GPP EC). The GPP MODIS, GPP VPM and GPP EC have similar seasonality, with higher values in the wet season and lower in the dry season. However, the VPM performed was better than the MOD17A2 to estimate the GPP, due to use local climatic data for predict the light use efficiency, while the MOD17A2 use a global circulation model and the lookup table of each vegetation type to estimate the light use efficiency.

scholarly journals P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production

2020 ◽  
Vol 13 (3) ◽  
pp. 1545-1581 ◽  
Author(s):  
Benjamin D. Stocker ◽  
Han Wang ◽  
Nicholas G. Smith ◽  
Sandy P. Harrison ◽  
Trevor F. Keenan ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Quantum Yield ◽  
Primary Production ◽  
Vegetation Type ◽  
Meteorological Data ◽  
Gross Primary Production ◽  
Satellite Monitoring ◽  
Light Use Efficiency ◽  
Wide Range ◽  
Use Efficiency

Abstract. Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth system model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a GPP (photosynthesis per unit ground area) model, the P-model, that combines the Farquhar–von Caemmerer–Berry model for C3 photosynthesis with an optimality principle for the carbon assimilation–transpiration trade-off, and predicts a multi-day average light use efficiency (LUE) for any climate and C3 vegetation type. The model builds on the theory developed in Prentice et al. (2014) and Wang et al. (2017a) and is extended to include low temperature effects on the intrinsic quantum yield and an empirical soil moisture stress factor. The model is forced with site-level data of the fraction of absorbed photosynthetically active radiation (fAPAR) and meteorological data and is evaluated against GPP estimates from a globally distributed network of ecosystem flux measurements. Although the P-model requires relatively few inputs, the R2 for predicted versus observed GPP based on the full model setup is 0.75 (8 d mean, 126 sites) – similar to comparable satellite-data-driven GPP models but without predefined vegetation-type-specific parameters. The R2 is reduced to 0.70 when not accounting for the reduction in quantum yield at low temperatures and effects of low soil moisture on LUE. The R2 for the P-model-predicted LUE is 0.32 (means by site) and 0.48 (means by vegetation type). Applying this model for global-scale simulations yields a total global GPP of 106–122 Pg C yr−1 (mean of 2001–2011), depending on the fAPAR forcing data. The P-model provides a simple but powerful method for predicting – rather than prescribing – light use efficiency and simulating terrestrial photosynthesis across a wide range of conditions. The model is available as an R package (rpmodel).

scholarly journals Primary production in forests and grasslands of China: contrasting environmental responses of light- and water-use efficiency models

2012 ◽  
Vol 9 (4) ◽  
pp. 4285-4321 ◽  
Author(s):  
H. Wang ◽  
I. C. Prentice ◽  
J. Ni
Keyword(s):  
Primary Production ◽  
Water Use Efficiency ◽  
Water Use ◽  
South China ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Stomatal Closure ◽  
Co2 Response ◽  
Data Set ◽  
Use Efficiency

Abstract. An extensive data set on net primary production (NPP) in China's forests is analysed with two semi-empirical models based on the light use efficiency (LUE) and water use efficiency (WUE) concepts, respectively. Results are shown to be broadly consistent with other data sets (grassland above-ground NPP; globally extrapolated gross primary production, GPP) and published analyses. But although both models describe the data about equally well, they predict notably different responses to [CO2] and temperature. These are illustrated by sensitivity tests in which [CO2] is kept constant or doubled, temperatures are kept constant or increased by 3.5 K, and precipitation is changed by ±10%. Precipitation changes elicit similar responses in both models. The [CO2] response of the WUE model is much larger but is probably an overestimate for dense vegetation as it assumes no increase in runoff; while the [CO2] response of the LUE model is probably too small for sparse vegetation as it assumes no increase in vegetation cover. In the LUE model warming reduces total NPP with the strongest effect in South China, where the growing season cannot be further extended. In the WUE model warming increases total NPP, again with the strongest effect in South China, where abundant water supply precludes stomatal closure. The qualitative differences between the two formulations illustrate potential causes of the large differences (even in sign) in the global NPP response of dynamic global vegetation models to [CO2] and climate change. As it is not clear which response is more realistic, the issue needs to be resolved by observation and experiment.

scholarly journals Net primary productivity, allocation pattern and carbon use efficiency in an apple orchard assessed by integrating eddy-covariance, biometric and continuous soil chamber measurements

2012 ◽  
Vol 9 (10) ◽  
pp. 14091-14143 ◽  
Author(s):  
D. Zanotelli ◽  
L. Montagnani ◽  
G. Manca ◽  
M. Tagliavini
Keyword(s):  
Primary Production ◽  
Eddy Covariance ◽  
Gross Primary Production ◽  
Apple Orchard ◽  
Allocation Pattern ◽  
Carbon Use Efficiency ◽  
Standing Biomass ◽  
Measurement Protocol ◽  
Allocation Patterns ◽  
Use Efficiency

Abstract. Carbon use efficiency (CUE) is a functional parameter that could possibly link the current increasingly accurate global estimates of gross primary production with those of net ecosystem exchange, for which global predictors are still unavailable. Nevertheless, CUE estimates are actually available for only a few ecosystem types, while information regarding agro-ecosystems is scarce, in spite of the simplified spatial structure of these ecosystems that facilitates studies on allocation patterns and temporal growth dynamics. We combined three largely deployed methods, eddy covariance, soil respiration and biometric measurements, to assess monthly values of CUE, net primary production (NPP) and allocation patterns in different plant organs in an apple orchard during a complete year (2010). We applied a~measurement protocol optimized for quantifying monthly values of carbon fluxes in this ecosystem type, which allows for a cross-check between estimates obtained from different methods. We also attributed NPP components to standing biomass increments, detritus cycle feeding and lateral exports. We found that in the apple orchard both net ecosystem production and gross primary production on yearly basis, 380 ± 30 g C m−2 and 1263 ± 189 g C m−2 respectively, were of a magnitude comparable to those of natural forests growing in similar climate conditions. The largest differences with respect to forests are in the allocation pattern and in the fate of produced biomass. The carbon sequestered from the atmosphere was largely allocated to production of fruits: 49% of annual NPP was taken away from the ecosystem through apple production. Organic material (leaves, fine root litter, pruned wood and early fruit falls) contributing to the detritus cycle was 46% of the NPP. Only 5% was attributable to standing biomass increment, while this NPP component is generally the largest in forests. The CUE, with an annual average of 0.71 ± 0.09, was higher than the previously suggested constant values of 0.47–0.50. Low nitrogen investment in fruits, the limited root-apparatus, and the optimal growth temperature and nutritional condition observed at the site are suggested to be explanatory variables for the high CUE observed.

scholarly journals Impact of annual and seasonal precipitation and air temperature on gross primary production in Mediterranean ecosystems in Europe

2016 ◽  
Author(s):  
Svenja Bartsch ◽  
Bertrand Guenet ◽  
Christophe Boissard ◽  
Juliette Lathière ◽  
Jean-Yves Peterschmitt ◽  
...  
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Air Temperature ◽  
Seasonal Variations ◽  
Carbon Fixation ◽  
Gross Primary Production ◽  
Mediterranean Ecosystems ◽  
Early Spring ◽  
Annual Variations ◽  
Temperature And Precipitation

Abstract. Mediterranean ecosystems are significant carbon sinks but are also particularly sensitive to climate change but the carbon dynamic in such ecosystem is still not fully understood. An improved understanding of the drivers of the carbon fixation by plants is needed to better predict how such ecosystems will respond to climate change. Here, for the first time, a large dataset collected through the FLUXNET network is used to estimate how the gross primary production (GPP) of different Mediterranean ecosystems was affected by air temperature and precipitation between the years 1996 and 2013. We showed that annual precipitation was not a significant driver of annual GPP. Our results also indicated that seasonal variations of air temperature significantly affected seasonal variations of GPP but without major impact on inter annual variations. Inter-annual variations of GPP seemed largely controlled by the precipitation during early spring (March–April), making this period crucial for the future of Mediterranean ecosystems. Finally, we also observed that the sensitivity of GPP in Mediterranean ecosystems to climate drivers is not ecosystem type dependent.

Energy and nutrients

2019 ◽  
pp. 161-176
Author(s):  
Richard T. Corlett
Keyword(s):  
Primary Production ◽  
Forest Ecology ◽  
Net Primary Production ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
Nitrogen And Phosphorus ◽  
New Information ◽  
Tropical Forest Ecology ◽  
Toxic Concentrations

This chapter deals with the ecology of Tropical East Asia from the perspective of water, energy, and matter flows through ecosystems, particularly forests. Data from the network of eddy flux covariance towers is revealing general patterns in gross primary production, ecosystem respiration, and net ecosystem production, and exchange. There is also new information on the patterns of net primary production and biomass within the region. In contrast, our understanding of the role of soil nutrients in tropical forest ecology still relies mostly on work done in the Neotropics, with just enough data from Asia to suggest that the major patterns may be pantropical. Nitrogen and phosphorus have received most attention regionally, followed by calcium, potassium, and magnesium, and there has been very little study of the role of micronutrients and potentially toxic concentrations of aluminium, manganese, and hydrogen ions. Animal nutrition has also been neglected.

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