scholarly journals Relationships between primary production and crop yields in semi-arid and arid irrigated agro-ecosystems

2015 ◽  
Vol XL-7/W3 ◽  
pp. 27-30 ◽  
Author(s):  
H. H. Jaafar ◽  
F. A. Ahmad
Keyword(s):  
Primary Production ◽  
Crop Yield ◽  
Vegetation Index ◽  
Crop Yields ◽  
Gross Primary Production ◽  
Remotely Sensed ◽  
Early Assessment ◽  
Food Shortages ◽  
Semi Arid ◽  
Summer Crop

In semi-arid areas within the MENA region, food security problems are the main problematic imposed. Remote sensing can be a promising too early diagnose food shortages and further prevent the population from famine risks. This study is aimed at examining the possibility of forecasting yield before harvest from remotely sensed MODIS-derived Enhanced Vegetation Index (EVI), Net photosynthesis (net PSN), and Gross Primary Production (GPP) in semi-arid and arid irrigated agro-ecosystems within the conflict affected country of Syria. Relationships between summer yield and remotely sensed indices were derived and analyzed. Simple regression spatially-based models were developed to predict summer crop production. The validation of these models was tested during conflict years. A significant correlation (p<0.05) was found between summer crop yield and EVI, GPP and net PSN. Results indicate the efficiency of remotely sensed-based models in predicting summer yield, mostly for cotton yields and vegetables. Cumulative summer EVI-based model can predict summer crop yield during crisis period, with deviation less than 20% where vegetables are the major yield. This approach prompts to an early assessment of food shortages and lead to a real time management and decision making, especially in periods of crisis such as wars and drought.

scholarly journals Modelling spatial and temporal dynamics of gross primary production in the Sahel from earth-observation-based photosynthetic capacity and quantum efficiency

2017 ◽  
Vol 14 (5) ◽  
pp. 1333-1348 ◽  
Author(s):  
Torbern Tagesson ◽  
Jonas Ardö ◽  
Bernard Cappelaere ◽  
Laurent Kergoat ◽  
Abdulhakim Abdi ◽  
...  
Keyword(s):  
Primary Production ◽  
Quantum Efficiency ◽  
Vegetation Index ◽  
Photosynthetic Capacity ◽  
Gross Primary Production ◽  
Earth Observation ◽  
Arid Ecosystems ◽  
Spatially Explicit ◽  
Equivalent Water Thickness ◽  
Semi Arid

Abstract. It has been shown that vegetation growth in semi-arid regions is important to the global terrestrial CO2 sink, which indicates the strong need for improved understanding and spatially explicit estimates of CO2 uptake (gross primary production; GPP) in semi-arid ecosystems. This study has three aims: (1) to evaluate the MOD17A2H GPP (collection 6) product against GPP based on eddy covariance (EC) for six sites across the Sahel; (2) to characterize relationships between spatial and temporal variability in EC-based photosynthetic capacity (Fopt) and quantum efficiency (α) and vegetation indices based on earth observation (EO) (normalized difference vegetation index (NDVI), renormalized difference vegetation index (RDVI), enhanced vegetation index (EVI) and shortwave infrared water stress index (SIWSI)); and (3) to study the applicability of EO upscaled Fopt and α for GPP modelling purposes. MOD17A2H GPP (collection 6) drastically underestimated GPP, most likely because maximum light use efficiency is set too low for semi-arid ecosystems in the MODIS algorithm. Intra-annual dynamics in Fopt were closely related to SIWSI being sensitive to equivalent water thickness, whereas α was closely related to RDVI being affected by chlorophyll abundance. Spatial and inter-annual dynamics in Fopt and α were closely coupled to NDVI and RDVI, respectively. Modelled GPP based on Fopt and α upscaled using EO-based indices reproduced in situ GPP well for all except a cropped site that was strongly impacted by anthropogenic land use. Upscaled GPP for the Sahel 2001–2014 was 736 ± 39 g C m−2 yr−1. This study indicates the strong applicability of EO as a tool for spatially explicit estimates of GPP, Fopt and α; incorporating EO-based Fopt and α in dynamic global vegetation models could improve estimates of vegetation production and simulations of ecosystem processes and hydro-biochemical cycles.

scholarly journals Can vegetation index track the interannual variation in gross primary production of temperate deciduous forests?

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Fan Liu ◽  
Chuankuan Wang ◽  
Xingchang Wang
Keyword(s):  
Primary Production ◽  
Vegetation Index ◽  
Near Infrared ◽  
Deciduous Forest ◽  
Gross Primary Production ◽  
Growing Season ◽  
Temperate Deciduous Forest ◽  
Near Infrared Reflectance ◽  
Modis Ndvi ◽  
Temperate Deciduous

Abstract Background Vegetation indices (VIs) by remote sensing are widely used as simple proxies of the gross primary production (GPP) of vegetation, but their performances in capturing the inter-annual variation (IAV) in GPP remain uncertain. Methods We evaluated the performances of various VIs in tracking the IAV in GPP estimated by eddy covariance in a temperate deciduous forest of Northeast China. The VIs assessed included the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), and the near-infrared reflectance of vegetation (NIRv) obtained from tower-radiometers (broadband) and the Moderate Resolution Imaging Spectroradiometer (MODIS), respectively. Results We found that 25%–35% amplitude of the broadband EVI tracked the start of growing season derived by GPP (R2: 0.56–0.60, bias < 4 d), while 45% (or 50%) amplitudes of broadband (or MODIS) NDVI represented the end of growing season estimated by GPP (R2: 0.58–0.67, bias < 3 d). However, all the VIs failed to characterize the summer peaks of GPP. The growing-season integrals but not averaged values of the broadband NDVI, MODIS NIRv and EVI were robust surrogates of the IAV in GPP (R2: 0.40–0.67). Conclusion These findings illustrate that specific VIs are effective only to capture the GPP phenology but not the GPP peak, while the integral VIs have the potential to mirror the IAV in GPP.

scholarly journals Satellites reveal an increase in gross primary production in a greenlandic high arctic fen 1992–2008

2010 ◽  
Vol 7 (1) ◽  
pp. 1101-1129 ◽  
Author(s):  
T. Tagesson ◽  
M. Mastepanov ◽  
M. P. Tamstorf ◽  
L. Eklundh ◽  
P. Schubert ◽  
...  
Keyword(s):  
Primary Production ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Gross Primary Production ◽  
Field Measurements ◽  
High Arctic ◽  
Research Area ◽  
Strong Increase ◽  
Co2 Uptake ◽  
Flux Measurements

Abstract. Arctic wetlands play a key role in the terrestrial carbon cycle. Recent studies have shown a greening trend and indicated an increase in CO2 uptake in boreal and sub- to low-arctic areas. Our aim was to combine satellite-based normalized difference vegetation index (NDVI) with ground-based flux measurements of CO2 to investigate a possible greening trend and potential changes in gross primary production (GPP) between 1992 and 2008 in a high arctic fen area. The study took place in Rylekaerene in the Zackenberg Research Area (74°28' N 20°34' W), located in the National park of North Eastern Greenland. We estimated the light use efficiency (ε) for the dominant vegetation types from field measured fractions of photosynthetic active radiation (FAPAR) and ground-based flux measurements of GPP. Measured FAPAR were correlated to satellite-based NDVI. The FAPAR-NDVI relationship in combination with ε was applied to satellite data to model GPP 1992–2008. The model was evaluated against field measured GPP. The model was a useful tool for up-scaling GPP and all basic requirements for the model were well met, e.g., FAPAR was well correlated to NDVI and modeled GPP was well correlated to field measurements. The studied high arctic fen area has experienced a strong increase in GPP between 1992 and 2008. The area has during this period also experienced a substantial increase in local air temperature. Consequently, the observed greening trend is most likely due to ongoing climatic change possibly in combination with CO2 fertilization, due to increasing atmospheric concentrations of CO2.

scholarly journals A Comparison of OCO-2 SIF, MODIS GPP, and GOSIF Data from Gross Primary Production (GPP) Estimation and Seasonal Cycles in North America

2020 ◽  
Vol 12 (2) ◽  
pp. 258 ◽  
Author(s):  
Ruonan Qiu ◽  
Ge Han ◽  
Xin Ma ◽  
Hao Xu ◽  
Tianqi Shi ◽  
...  
Keyword(s):  
North America ◽  
Primary Production ◽  
Vegetation Type ◽  
Gross Primary Production ◽  
Remotely Sensed ◽  
Seasonal Cycles ◽  
Vegetation Types ◽  
Growth Trend ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Highly Correlated

Remotely sensed products are of great significance to estimating global gross primary production (GPP), which helps to provide insight into climate change and the carbon cycle. Nowadays, there are three types of emerging remotely sensed products that can be used to estimate GPP, namely, MODIS GPP (Moderate Resolution Imaging Spectroradiometer GPP, MYD17A2H), OCO-2 SIF, and GOSIF. In this study, we evaluated the performances of three products for estimating GPP and compared with GPP of eddy covariance(EC) from the perspectives of a single tower (23 flux towers) and vegetation types (evergreen needleleaf forests, deciduous broadleaf forests, open shrublands, grasslands, closed shrublands, mixed forests, permeland wetlands, and croplands) in North America. The results revealed that sun-induced chlorophyll fluorescence (SIF) data and MODIS GPP data were highly correlated with the GPP of flux towers (GPPEC). GOSIF and OCO-2 SIF products exhibit a higher accuracy in GPP estimation at the a single tower (GOSIF: R2 = 0.13–0.88, p < 0.001; OCO-2 SIF: R2 = 0.11–0.99, p < 0.001; MODIS GPP: R2 = 0.15–0.79, p < 0.001). MODIS GPP demonstrates a high correlation with GPPEC in terms of the vegetation type, but it underestimates the GPP by 1.157 to 3.884 gCm−2day−1 for eight vegetation types. The seasonal cycles of GOSIF and MODIS GPP are consistent with that of GPPEC for most vegetation types, in spite of an evident advanced seasonal cycle for grasslands and evergreen needleleaf forests. Moreover, the results show that the observation mode of OCO-2 has an evident impact on the accuracy of estimating GPP using OCO-2 SIF products. In general, compared with the other two datasets, the GOSIF dataset exhibits the best performance in estimating GPP, regardless of the extraction range. The long time period of MODIS GPP products can help in the monitoring of the growth trend of vegetation and the change trends of GPP.

scholarly journals Isoprene emissions track the seasonal cycle of canopy temperature, not primary production: evidence from remote sensing

2014 ◽  
Vol 11 (13) ◽  
pp. 3437-3451 ◽  
Author(s):  
P. N. Foster ◽  
I. C. Prentice ◽  
C. Morfopoulos ◽  
M. Siddall ◽  
M. van Weele
Keyword(s):  
Primary Production ◽  
Air Temperature ◽  
Seasonal Cycle ◽  
Gross Primary Production ◽  
Canopy Temperature ◽  
Remotely Sensed ◽  
Formaldehyde Concentration ◽  
Isoprene Emission ◽  
The Tropics ◽  
Better Than

Abstract. Isoprene is important in atmospheric chemistry, but its seasonal emission pattern – especially in the tropics, where most isoprene is emitted – is incompletely understood. We set out to discover generalized relationships applicable across many biomes between large-scale isoprene emission and a series of potential predictor variables, including both observed and model-estimated variables related to gross primary production (GPP) and canopy temperature. We used remotely sensed atmospheric concentrations of formaldehyde, an intermediate oxidation product of isoprene, as a proxy for isoprene emission in 22 regions selected to span high to low latitudes, to sample major biomes, and to minimize interference from pyrogenic sources of volatile organic compounds that could interfere with the isoprene signal. Formaldehyde concentrations showed the highest average seasonal correlations with remotely sensed (r = 0.85) and model-estimated (r = 0.80) canopy temperatures. Both variables predicted formaldehyde concentrations better than air temperature (r= 0.56) and a "reference" isoprene model that combines GPP and an exponential function of temperature (r = 0.49), and far better than either remotely sensed green vegetation cover, fPAR (r = 0.25) or model-estimated GPP (r = 0.14). Gross primary production in tropical regions was anti-correlated with formaldehyde concentration (r = −0.30), which peaks during the dry season. Our results were most reliable in the tropics, where formaldehyde observational errors were the least. The tropics are of particular interest because they are the greatest source of isoprene emission as well as the region where previous modelling attempts have been least successful. We conjecture that positive correlations of isoprene emission with GPP and air temperature (as found in temperate forests) may arise simply because both covary with canopy temperature, peaking during the relatively short growing season. The lack of a general correlation between GPP and formaldehyde concentration in the seasonal cycle is consistent with experimental evidence that isoprene emission rates are largely decoupled from photosynthetic rates, and with the likely adaptive significance of isoprene emission in protecting leaves against heat damage and oxidative stress.

scholarly journals Effects of nitrogen and phosphorus fertilizer on crop yields in a field pea-spring wheat-potato rotation system with calcareous soil in semi-arid environments

2016 ◽  
Vol 14 (2) ◽  
pp. e1101 ◽  
Author(s):  
Chang-An Liu ◽  
Sen Zhang ◽  
Shuai Hua ◽  
Xin Rao
Keyword(s):  
Crop Yield ◽  
Spring Wheat ◽  
Calcareous Soil ◽  
Crop Yields ◽  
Potato Crop ◽  
Field Pea ◽  
Arid Environments ◽  
Annual Average ◽  
N Treatment ◽  
Semi Arid

The object of the present study was to investigate the yield-affecting mechanisms influenced by N and P applications in rainfed areas with calcareous soil. The experimental treatments were as follows: NF (no fertilizer), N (nitrogen), P (phosphorus), and NP (nitrogen plus phosphorus) in a field pea-spring wheat-potato cropping system. This study was conducted over six years (2003-2008) on China’s semi-arid Loess Plateau. The fertilizer treatments were found to decrease the soil water content more than the NF treatment in each of the growing seasons. The annual average yields of the field pea crops during the entire experimental period were 635, 677, 858, and 1117 kg/ha for the NF, N, P, and NP treatments, respectively. The annual average yields were 673, 547, 966, and 1056 kg/ha for the spring wheat crops for the NF, N, P, and NP treatments, respectively. Also, the annual average yields were 1476, 2120, 1480, and 2424 kg/ha for the potato crops for the NF, N, P, and NP treatments, respectively. In the second cycle of the three-year rotation, the pea and spring wheat yields in the P treatment were 1.2 and 2.8 times higher than that in the N treatment, respectively. Meanwhile, the potato crop yield in the N treatment was 3.1 times higher than that in the P treatment. In conclusion, the P fertilizer was found to increase the yields of the field pea and wheat crops, and the N fertilizer increased the potato crop yield in rainfed areas with calcareous soil.

scholarly journals Eddy covariance carbon flux in a scrub in the Mexican highland

2020 ◽  
Author(s):  
Aurelio Guevara-Escobar ◽  
Enrique González-Sosa ◽  
Mónica Cervantes-Jiménez ◽  
Humberto Suzán-Azpiri ◽  
Mónica Elisa Queijeiro-Bolaños ◽  
...  
Keyword(s):  
Primary Production ◽  
Eddy Covariance ◽  
Vegetation Index ◽  
Carbon Sink ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
Net Ecosystem Exchange ◽  
R Package ◽  
Dark Cycle ◽  
Remote Sensors

Abstract. Vegetation fixes C in its biomass through photosynthesis or might release it into the atmosphere through respiration. Measurements of these fluxes would help us understand ecosystem functioning. The eddy covariance technique (EC) is widely used to measure the net ecosystem exchange of C (NEE) which is the balance between gross primary production (GPP) and ecosystem respiration (Reco). Orbital satellites such as MODIS can also provide estimates of GPP. In this study, we measured NEE with the EC in a scrub at Bernal in Mexico, and then partitioned into gross primary production (GPP-EC) and Reco using the recent R package Reddyproc. Measurements of GPP-EC were related to the estimates from the MODIS satellite provided in product MOD17A2H, which contains data of the gross primary productivity (GPP-MODIS). The Bernal site was a carbon sink despite it was an overgrazed site, the average NEE during fifteen months of 2017 and 2018 was −0.78 g C m−2 d−1 and the flux was negative in all measured months. The GPP-MODIS underestimated the ground data when representing the relation with a Theil-Sen regression: GPP-EC = 1.866 + 1.861 GPP-MODIS; an ordinary less squares regression had similar coefficients and the R2 was 0.6. Although cacti (CAM), legume shrubs (C3) and herbs (C3) had a similar vegetation index, the nighttime flux was characterized by positive NEE suggesting that the photosynthetic dark-cycle flux of cacti was lower than Reco. The discrepancy among the GPP flux estimates stresses the need to understand the limitations of EC and remote sensors, while incorporating complementary monitoring and modelling schemes of nighttime Reco, particularly in the presence of species with different photosynthetic cycles.

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