A comparison of moderate and high spatial resolution satellite data for modeling gross primary production and transpiration of native prairie, alfalfa, and winter wheat

Celis, Jorge; Xiao, Xiangming; Wagle, Pradeep; Basara, Jeffrey; McCarthy, Heather; Souza, Lara

doi:10.1016/j.agrformet.2023.109797

Cited by 5 publications

(3 citation statements)

References 105 publications

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“…Winter wheat, one of the main food crops in China, with the largest traditional planting area [ 1 ], is highly sensitive to weather conditions [ 2 ]; its year-round growth cycle makes it particularly vulnerable to climate change. As winter wheat is affected substantially by varying climates and management practices, it is important to predict its responses to variable climates [ 3 ]. It is well known that winter wheat is dormant in winter but very active in spring and summer.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Spatial-Temporal Distribution Characteristics of Climate and Its Impact on Winter Wheat Production in Shanxi Province, China, 1964–2018

Wang,

Guo,

Feng

et al. 2024

Plants

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The possible influence of global climate changes on agricultural production is becoming increasingly significant, necessitating greater attention to improving agricultural production in response to temperature rises and precipitation variability. As one of the main winter wheat-producing areas in China, the temporal and spatial distribution characteristics of precipitation, accumulated temperature, and actual yield and climatic yield of winter wheat during the growing period in Shanxi Province were analysed in detail. With the utilisation of daily meteorological data collected from 12 meteorological stations in Shanxi Province in 1964–2018, our study analysed the change in winter wheat yield with climate change using GIS combined with wavelet analysis. The results show the following: (1) Accumulated temperature and precipitation are the two most important limiting factors among the main physical factors that impact yield. Based on the analysis of the ArcGIS geographical detector, the correlation between the actual yield of winter wheat and the precipitation during the growth period was the highest, reaching 0.469, and the meteorological yield and accumulated temperature during this period also reached its peak value of 0.376. (2) The regions with more suitable precipitation and accumulated temperature during the growth period of winter wheat in the study area had relatively high actual winter wheat yields. Overall, the average actual yield of the entire region showed a significant increasing trend over time, with an upward trend of 47.827 kg ha−1 yr−1. (3) The variation coefficient of winter wheat climatic yield was relatively stable in 2008–2018. In particular, there were many years of continuous reduction in winter wheat yields prior to 2006. Thereafter, the impact of climate change on winter wheat yields became smaller. This study expands our understanding of the complex interactions between climate variables and crop yield but also provides practical recommendations for enhancing agricultural practices in this region

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Section: Introductionmentioning

confidence: 99%

Analysis of the Spatial-Temporal Distribution Characteristics of Climate and Its Impact on Winter Wheat Production in Shanxi Province, China, 1964–2018

Wang,

Guo,

Feng

et al. 2024

Plants

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“…Evapotranspiration (ET) and photosynthesis are coupled processes that mediate water, carbon, and energy fluxes between terrestrial ecosystems and atmosphere, which are important components of energy-water balances and global biogeochemical cycling [1][2][3]. In the context of climate change, observations of ecosystem water and carbon exchange, in order to deeply understand the trade-off between ET and the amount of terrestrial carbon assimilated, are currently one of the hottest issues in ecological hydrology research [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…In the present study, we summarized nearly six years of consecutive measurement data of NEE, ET, and environmental factors such as air temperature (T a ), soil temperature (T s ), relative humidity (RH), wind speed (W s ), precipitation (P), soil water content (SWC), VPD, photosynthetically active radiation (PAR), and net radiation (R n ), covering the period from September 2004 to June 2010, which included six winter wheat seasons. The main objectives were to: (1) analyze seasonal and interannual variations in GPP, NEE, ET, and WUE in a winter wheat ecosystem (with a single crop from September to the next June, observed at a 2 m height, denoted as WWE), and an agroforest ecosystem (with both cropland and apple orchard, observed at a 32 m height, denoted as AFE); (2) to explore the applicability of sinusoidal function in the simulation of interannual ET; and (3) to quantify the correlation between environmental factors and the GPP, NEE, and WUE of the two different agroecosystems using the Pearson correlation.…”

Section: Introductionmentioning

confidence: 99%

Dynamics of Carbon and Water Fluxes over Cropland and Agroforest Ecosystems on the Southern Chinese Loess Plateau

Han,

Fang,

Bai

et al. 2024

Forests

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Studies on the spatiotemporal dynamics in ecosystem carbon and water exchanges are essential in predicting the effects of climate change on regional carbon and energy budgets. Using the eddy covariance technique, carbon and water fluxes were observed in a typical winter wheat ecosystem (WWE) and an agroforest ecosystem (AFE) in the southern Loess Plateau from 2004 to 2010. The seasonal and inter-annual variability in gross primary productivity (GPP), net ecosystem exchange (NEE), evapotranspiration (ET), and water use efficiency (WUE) were examined and the main influencing factors were identified using the Pearson correlation. The results indicate that the seasonal GPP and NEE showed a bimodal distribution in WWE, while this was unimodal in AFE. The sinusoidal function did well in the characterization of seasonal ET dynamics for both ecosystems, with the determination coefficients being 0.85 and 0.94, respectively. In WWE and AFE, the annual mean GPP were 724.33 and 723.08 g C m−2 a−1, respectively, and the corresponding ET were 392.22 and 410.02 mm a−1. However, the difference in NEE between the two ecosystems was obvious, NEE were −446.28 and −549.08 g C m−2 a−1, respectively, showing a stronger carbon sink in AFE. There were strong coupling relationships between the GPP and ET of both ecosystems; the overall slopes were 1.71 and 1.69, respectively. The seasonal trend of WUE was bimodal in WWE, with peak values of 3.94 and 3.65 g C kg−1 H2O, occurring in November and April, respectively. However, the monthly WUE in AFE had one single peak of 4.07 g C kg−1 H2O in January. Photosynthetically active radiation (PAR) and soil temperature (Ts) were most positively correlated with GPP, net radiation (Rn) and Ts were the major factors influencing ET, while vapor pressure deficit (VPD) and soil water content (SWC) were the major influencing factors for WUE. These results provide observational support for regional carbon neutrality simulations.

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A Review of Yield Forecasting Techniques and Their Impact on Sustainable Agriculture

Celis,

Xiao,

Wagle

et al. 2024

Greening of Industry Networks Studies

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A comparison of moderate and high spatial resolution satellite data for modeling gross primary production and transpiration of native prairie, alfalfa, and winter wheat

Cited by 5 publications

References 105 publications

Analysis of the Spatial-Temporal Distribution Characteristics of Climate and Its Impact on Winter Wheat Production in Shanxi Province, China, 1964–2018

Analysis of the Spatial-Temporal Distribution Characteristics of Climate and Its Impact on Winter Wheat Production in Shanxi Province, China, 1964–2018

Dynamics of Carbon and Water Fluxes over Cropland and Agroforest Ecosystems on the Southern Chinese Loess Plateau

A Review of Yield Forecasting Techniques and Their Impact on Sustainable Agriculture

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