Does Climate Change Influence Russian Agriculture? Evidence from Panel Data Analysis

Gordeev, Roman V.; Pyzhev, Anton I.; Zander, Evgeniya V.

doi:10.3390/su14020718

Cited by 14 publications

(6 citation statements)

References 46 publications

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“…Severity of climate impact on yield differ by crop, geographical location, and magnitude, as well as the direction of shift in the climatic variables 19 , 20 . Worldwide climate change impacts are uneven, particularly in nations with vast land areas 21 , 22 . Scientific community agrees to some extent that the present trends would be detrimental to the tropical and subtropical areas of Africa, middle east, south, and southeast Asia 23 – 26 , and advantageous to Russia, Ireland 27 , Canada 28 , 29 , and Finland 30 , 31 in the context of cereal yield.…”

Section: Introductionmentioning

confidence: 99%

Impact of recent climate change on corn, rice, and wheat in southeastern USA

Sharma

Kumar²,

Vatta³

et al. 2022

Sci Rep

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Climate change and its impact on agriculture productivity vary among crops and regions. The southeastern United States (SE-US) is agro-ecologically diversified, economically dependent on agriculture, and mostly overlooked by agroclimatic researchers. The objective of this study was to compute the effect of climatic variables; daily maximum temperature (Tmax), daily minimum temperature (Tmin), and rainfall on the yield of major cereal crops i.e., corn (Zea mays L.), rice (Oryza sativa L.), and wheat (Triticum aestivum L.) in SE-US. A fixed-effect model (panel data approach) was used by applying the production function on panel data from 1980 to 2020 from 11 SE-US states. An asymmetrical warming pattern was observed, where nocturnal warming was 105.90%, 106.30%, and 32.14%, higher than the diurnal warming during corn, rice, and wheat growing seasons, respectively. Additionally, a shift in rainfall was noticed ranging from 19.2 to 37.2 mm over different growing seasons. Rainfall significantly reduced wheat yield, while, it had no effect on corn and rice yields. The Tmax and Tmin had no significant effect on wheat yield. A 1 °C rise in Tmax significantly decreased corn (− 34%) and rice (− 8.30%) yield which was offset by a 1 °C increase in Tmin increasing corn (47%) and rice (22.40%) yield. Conclusively, overall temperature change of 1 °C in the SE-US significantly improved corn yield by 13%, rice yield by 14.10%, and had no effect on wheat yield.

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Section: Introductionmentioning

confidence: 99%

Impact of recent climate change on corn, rice, and wheat in southeastern USA

Sharma

Kumar²,

Vatta³

et al. 2022

Sci Rep

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“…Climate change represents a change in the statistical distribution of weather patterns and takes into account an extended period of time. The first measures to combat the phenomenon were initiated in Rio de Janeiro in 1992 with the signing of the United Nations Framework Convention on Climate Change, when 194 countries agreed to take long-term measures to stabilize the concentration of greenhouse gases and prevent dangerous human influence on the climate system [5][6][7][8][9]. Five years later, measures to combat climate change were agreed to in Kyoto, where commitments were signed to reduce greenhouse emissions between 2008 and 2012 [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Climate Change—Between “Myth and Truth” in Romanian Farmers’ Perception

et al. 2022

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The study analyzes the awareness of the effects of climate change on agriculture and the measures that should be implemented in this regard from the farmer’s perspective, taking into account the financial and promotional measures supported by the European Union for farmers. Thus, the study tracks the level of openness of farmers to implementing the measures that European policy makers will take in the coming period. Taking into account the fact that agriculture plays a particularly important economic role, due to the share of agricultural products in Romania’s total exports, particularly in plant production, a quantitative survey was carried out among Romanian farmers, using a questionnaire as an instrument, with a total of 407 respondents. The farmers interviewed undoubtedly recognize that the problems they face are caused by the effects of climate change and are willing to adapt, seek and implement the necessary solutions. The most problematic climatic phenomenon identified by farmers (71.5%) is drought, with negative effects on their activity. At the same time, 54.15% of the respondents believe that the effects of climate change are affecting their business through lower yields. Although the farmers interviewed are willing to implement solutions to combat climate effects, 80.34% of them are not considering revising cropping patterns, giving more importance to market demand than to practices that protect the environment. In conclusion, as long as farmers feel and understand the effects of climate change, it cannot be a myth, especially if they are willing to adapt to these challenges.

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“…The climate in Russia is warming about 2.5 times more intensely than the global average. The softening of winters in Russia could be an important factor in the future development of agriculture [53]. An increase in precipitation and climate warming leads to an increase in soybean yields.…”

Section: Discussionmentioning

confidence: 99%

Multi-Year Cropland Mapping Based on Remote Sensing Data: A Case Study for the Khabarovsk Territory, Russia

Dubrovin,

Verkhoturov,

Stepanov

et al. 2024

Remote Sensing

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Cropland mapping using remote sensing data is the basis for effective crop monitoring, crop rotation control, and the detection of irrational land use. Classification using Normalized Difference Vegetation Index (NDVI) time series from multi-year data requires additional time costs, especially when sentinel data are sparse. Approximation by nonlinear functions was proposed to solve this problem. Time series of weekly NDVI composites were plotted using multispectral Sentinel-2 (Level-2A) images at a resolution of 10 m for sites in Khabarovsk District from April to October in the years 2021 and 2022. Missing values due to the lack of suitable images for analysis were recovered using cubic polynomial, Fourier series, and double sinusoidal function approximation. The classes that were considered included crops, namely, soybean, buckwheat, oat, and perennial grasses, and fallow. The mean absolute percentage error (MAPE) of each class fitting was calculated. It was found that Fourier series fitting showed the highest accuracy, with a mean error of 8.2%. Different classifiers, such as the support vector machine (SVM), random forest (RF), and gradient boosting (GB), were comparatively evaluated. The overall accuracy (OA) for the site pixels during the cross-validation (Fourier series restored) was 67.3%, 87.2%, and 85.9% for the SVM, RF, and GB classifiers, respectively. Thus, it was established that the best result in terms of combined accuracy, performance, and limitations in cropland mapping was achieved by composite construction using Fourier series and machine learning using GB. Similar results should be expected in regions with similar cropland structures and crop phenological cycles, including other regions of the Far East.

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Does Climate Change Influence Russian Agriculture? Evidence from Panel Data Analysis

Cited by 14 publications

References 46 publications

Impact of recent climate change on corn, rice, and wheat in southeastern USA

Impact of recent climate change on corn, rice, and wheat in southeastern USA

Climate Change—Between “Myth and Truth” in Romanian Farmers’ Perception

Multi-Year Cropland Mapping Based on Remote Sensing Data: A Case Study for the Khabarovsk Territory, Russia

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