scholarly journals Improving Estimation of Gross Primary Production in Dryland Ecosystems by a Model-Data Fusion Approach

2019 ◽  
Vol 11 (3) ◽  
pp. 225 ◽  
Author(s):  
Haibo Wang ◽  
Xin Li ◽  
Mingguo Ma ◽  
Liying Geng
Keyword(s):  
Carbon Cycle ◽  
Arid Region ◽  
Arid Regions ◽  
Meteorological Data ◽  
Gross Primary Production ◽  
Arid Ecosystems ◽  
Desert Ecosystems ◽  
Dryland Ecosystems ◽  
Semi Arid

Accurate and continuous monitoring of the production of arid ecosystems is of great importance for global and regional carbon cycle estimation. However, the magnitude of carbon sequestration in arid regions and its contribution to the global carbon cycle is poorly understood due to the worldwide paucity of measurements of carbon exchange in arid ecosystems. The Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary productivity (GPP) product provides worldwide high-frequency monitoring of terrestrial GPP. While there have been a large number of studies to validate the MODIS GPP product with ground-based measurements over a range of biome types. Few studies have comprehensively validated the performance of MODIS estimates in arid and semi-arid ecosystems, especially for the newly released Collection 6 GPP products, whose resolution have been improved from 1000 m to 500 m. Thus, this study examined the performance of MODIS-derived GPP by compared with eddy covariance (EC)-observed GPP at different timescales for the main ecosystems in arid and semi-arid regions of China. Meanwhile, we also improved the estimation of MODIS GPP by using in situ meteorological forcing data and optimization of biome-specific parameters with the Bayesian approach. Our results revealed that the current MOD17A2H GPP algorithm could, on the whole, capture the broad trends of GPP at eight-day time scales for the most investigated sites. However, GPP was underestimated in some ecosystems in the arid region, especially for the irrigated cropland and forest ecosystems (with R2 = 0.80, RMSE = 2.66 gC/m2/day and R2 = 0.53, RMSE = 2.12 gC/m2/day, respectively). At the eight-day time scale, the slope of the original MOD17A2H GPP relative to the EC-based GPP was only 0.49, which showed significant underestimation compared with tower-based GPP. However, after using in situ meteorological data to optimize the biome-based parameters of MODIS GPP algorithm, the model could explain 91% of the EC-observed GPP of the sites. Our study revealed that the current MODIS GPP model works well after improving the maximum light-use efficiency (εmax or LUEmax), as well as the temperature and water-constrained parameters of the main ecosystems in the arid region. Nevertheless, there are still large uncertainties surrounding GPP modelling in dryland ecosystems, especially for desert ecosystems. Further improvements in GPP simulation in dryland ecosystems are needed in future studies, for example, improvements of remote sensing products and the GPP estimation algorithm, implementation of data-driven methods, or physiology models.

scholarly journals Performance of the Remotely-Derived Products in Monitoring Gross Primary Production across Arid and Semi-Arid Ecosystems in Northwest China

Land ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 288 ◽  
Author(s):  
Qing Gu ◽  
Hui Zheng ◽  
Li Yao ◽  
Min Wang ◽  
Mingguo Ma ◽  
...  
Keyword(s):  
Primary Production ◽  
Large Scale ◽  
Meteorological Data ◽  
Gross Primary Production ◽  
Carbon Fluxes ◽  
Arid Ecosystems ◽  
Model Parameters ◽  
Net Ecosystem Carbon Exchange ◽  
Dryland Ecosystems ◽  
Semi Arid

As an important component to quantify the carbon budget, accurate evaluation of terrestrial gross primary production (GPP) is crucial for large-scale applications, especially in dryland ecosystems. Based on the in situ data from six flux sites in northwestern China from 2014 to 2016, this study compares seasonal and interannual dynamics of carbon fluxes between these arid and semi-arid ecosystems and the atmosphere. Meanwhile, the reliability of multiple remotely-derived GPP products in representative drylands was examined, including the Breathing Earth System Simulator (BESS), the Moderate Resolution Imaging Spectroradiometer (MODIS) and data derived from the OCO-2 solar-induced chlorophyll fluorescence (GOSIF). The results indicated that the carbon fluxes had clear seasonal patterns, with all ecosystems functioning as carbon sinks. The maize cropland had the highest GPP with 1183 g C m−2 y−1. Although the net ecosystem carbon exchange (NEE) in the Tamarix spp. ecosystem was the smallest among these flux sites, it reached 208 g C m−2 y−1. Furthermore, distinct advantages of GOSIF GPP (with R2 = 0.85–0.98, and RMSE = 0.87–2.66 g C m−2 d−1) were found with good performance. However, large underestimations in three GPP products existed during the growing seasons, except in grassland ecosystems. The main reasons can be ascribed to the uncertainties in the key model parameters, including the underestimated light use efficiency of the MODIS GPP, the same coarse land cover product for the BESS and MODIS GPP, the coarse gridded meteorological data, and distribution of C3 and C4 plants. Therefore, it still requires more work to accurately quantify the GPP across these dryland ecosystems.

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.

Effects of Genotype and Rainfall on Forage Oats in a Semi-arid Region

1977 ◽  
Vol 13 (3) ◽  
pp. 217-223 ◽  
Author(s):  
A. Hadjichristodoulou
Keyword(s):  
Arid Region ◽  
Selection Criteria ◽  
Crude Protein ◽  
Dry Matter ◽  
Arid Regions ◽  
Correlation Coefficients ◽  
Annual Rainfall ◽  
Varietal Response ◽  
Semi Arid Region ◽  
Semi Arid

SUMMARYThere were significant differences in dry matter yield among five forage oat varieties tested at ten environments during 1970–75. The correlation coefficients between annual rainfall and DM yield varied with variety from 0·69 to 0·88, late varieties tending to give higher yields. Lateness, and high varietal response to annual rainfall and improved environmental conditions, can be used as selection criteria in semi-arid regions. Late varieties had higher DM and lower crude protein contents, and forage produced under lower rainfall conditions tended to have more DM and crude protein.

scholarly journals Deriving seasonal dynamics in ecosystem properties of semi-arid savanna grasslands from in situ-based hyperspectral reflectance

2015 ◽  
Vol 12 (15) ◽  
pp. 4621-4635 ◽  
Author(s):  
T. Tagesson ◽  
R. Fensholt ◽  
S. Huber ◽  
S. Horion ◽  
I. Guiro ◽  
...  
Keyword(s):  
Seasonal Dynamics ◽  
Near Infrared ◽  
Spectral Characteristics ◽  
Arid Ecosystems ◽  
Hyperspectral Reflectance ◽  
Data Set ◽  
Ecosystem Properties ◽  
Shortwave Infrared ◽  
Semi Arid

Abstract. This paper investigates how hyperspectral reflectance (between 350 and 1800 nm) can be used to infer ecosystem properties for a semi-arid savanna grassland in West Africa using a unique in situ-based multi-angular data set of hemispherical conical reflectance factor (HCRF) measurements. Relationships between seasonal dynamics in hyperspectral HCRF and ecosystem properties (biomass, gross primary productivity (GPP), light use efficiency (LUE), and fraction of photosynthetically active radiation absorbed by vegetation (FAPAR)) were analysed. HCRF data (ρ) were used to study the relationship between normalised difference spectral indices (NDSIs) and the measured ecosystem properties. Finally, the effects of variable sun sensor viewing geometry on different NDSI wavelength combinations were analysed. The wavelengths with the strongest correlation to seasonal dynamics in ecosystem properties were shortwave infrared (biomass), the peak absorption band for chlorophyll a and b (at 682 nm) (GPP), the oxygen A band at 761 nm used for estimating chlorophyll fluorescence (GPP and LUE), and blue wavelengths (ρ412) (FAPAR). The NDSI with the strongest correlation to (i) biomass combined red-edge HCRF (ρ705) with green HCRF (ρ587), (ii) GPP combined wavelengths at the peak of green reflection (ρ518, ρ556), (iii) LUE combined red (ρ688) with blue HCRF (ρ436), and (iv) FAPAR combined blue (ρ399) and near-infrared (ρ1295) wavelengths. NDSIs combining near infrared and shortwave infrared were strongly affected by solar zenith angles and sensor viewing geometry, as were many combinations of visible wavelengths. This study provides analyses based upon novel multi-angular hyperspectral data for validation of Earth-observation-based properties of semi-arid ecosystems, as well as insights for designing spectral characteristics of future sensors for ecosystem monitoring.

scholarly journals Are smallholder farmers’ perceptions of climate variability supported by climatological evidence? Case study of a semi-arid region in South Africa

2020 ◽  
Vol 12 (5) ◽  
pp. 571-585 ◽  
Author(s):  
Maropene Tebello Rapholo ◽  
Lawrence Diko Makia
Keyword(s):  
South Africa ◽  
Climate Variability ◽  
Arid Region ◽  
Smallholder Farmers ◽  
Linear Trend ◽  
Meteorological Data ◽  
Sub Saharan Africa ◽  
Content Type ◽  
Semi Arid Region ◽  
Semi Arid

Purpose Literature contends that not much is known about smallholder farmers’ perceptions of climate variability and the impacts thereof on agricultural practices in Sub-Saharan Africa and South Africa in particular. The purpose of this study is to examine the perceptions of smallholder farmers from Botlokwa (a semi-arid region in South Africa) on climate variability in relation to climatological evidence. Design/methodology/approach The study area is in proximity to a meteorological station and comprises mainly rural farmers, involved in rain-fed subsistence agriculture. Focus group discussions and closed-ended questionnaires covering demographics and perceptions were administered to 125 purposely sampled farmers. To assess farmers’ perceptions of climate variability, their responses were compared with linear trend and variability of historical temperature and rainfall data (1985-2015). Descriptive statistics were used to provide insights into respondents’ perceptions. Findings About 64% of the farmers perceived climate variability that was consistent with the meteorological data, whereas 36% either held contrary observations or were unable to discern. Age, level of education, farming experience and accessibility to information influenced the likelihood of farmers to correctly perceive climate variability. No significant differences in perception based on gender were observed. This study concludes that coping and adaption strategies of over one-third of the farmers could be negatively impacted by wrong perceptions of climate variability. Originality/value This study highlights discrepancies in perceptions among farmers with similar demographic characteristics. To guarantee sustainability of the sector, intervention by government and other key stakeholders to address underlying factors responsible for observed discrepancies is recommended.

Carbon cycle responses of semi-arid ecosystems to positive asymmetry in rainfall

2016 ◽  
Vol 23 (2) ◽  
pp. 793-800 ◽  
Author(s):  
Vanessa Haverd ◽  
Anders Ahlström ◽  
Benjamin Smith ◽  
Josep G. Canadell
Keyword(s):  
Carbon Cycle ◽  
Arid Ecosystems ◽  
Semi Arid

scholarly journals Global comparison of 20 reference evapotranspiration equations in a semi-arid region of Iran

2018 ◽  
Vol 50 (1) ◽  
pp. 282-300 ◽  
Author(s):  
Hadi Farzanpour ◽  
Jalal Shiri ◽  
Ali Ashraf Sadraddini ◽  
Slavisa Trajkovic
Keyword(s):  
Arid Region ◽  
Reference Evapotranspiration ◽  
Meteorological Data ◽  
Irrigation Scheduling ◽  
Climatic Conditions ◽  
Accurate Estimation ◽  
Management Scenarios ◽  
Global Comparison ◽  
Semi Arid Region ◽  
Semi Arid

Abstract Accurate estimation of reference evapotranspiration (ETo) is a major task in hydrology, water resources management, irrigation scheduling and determining crop water requirement. There are many empirical equations suggested by numerous references in literature for calculating ETo using meteorological data. Some such equations have been developed for specific climatic conditions while some have been applied universally. The potential for usage of these equations depends on the availability of necessary meteorological parameters for calculating ETo in different climate conditions. The focus of the present study was a global cross-comparison of 20 ETo estimation equations using daily meteorological records of 10 weather stations (covering a period of 12 years) in a semi-arid region of Iran. Two data management scenarios, namely local and cross-station scenarios, were adopted for calibrating the applied equations against the standard FAO56-PM model. The obtained results revealed that the cross-station calibration might be a good alternative for local calibration of the ETo models when proper similar stations are used for feeding the calibration matrix.

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