Assessing the impacts of crop production on climate change: An in-depth analysis of long-term determinants and policy implications.

This research investigates the long-term determinants of carbon emissions in three diverse regions-Europe and Central Asia (ECA), Sub-Saharan Africa (SSA), and the Middle East and North Africa (MENA)-spanning 1990 to 2020. Utilizing advanced econometric models and analyses, including the Regularized Common Correlated Effects Estimator (rCCE), Common Correlated Effects Estimator (CCE), and Mean-Group (MG) approach, the study explores the intricate relationships between carbon emissions, crop production, emissions per agricultural production, energy consumption, renewable energy consumption, per capita GDP, and population. Region-specific nuances are uncovered, highlighting the varying dynamics: ECA exhibits intricate and non-significant relationships, SSA showcases significant effects of population dynamics and green technology adoption, and the MENA region reveals a nuanced interplay between emissions per agricultural production.The findings underscore the universal efficacy of green technology adoption for mitigation. Strategies for mitigating carbon emissions in the agricultural sector require diversified energy transition approaches, emphasizing efficiency enhancements, green technology adoption, and tailored population management strategies based on regional intricacies. Counterfactual simulations indicate the potential efficacy of strategic measures targeting crop production to reduce carbon emissions, while acknowledging the nuanced relationship between economic growth and emissions. Policymakers are urged to recognize the persistence in emission patterns, emphasizing the importance of targeted interventions to transition towards more sustainable trajectories. Overall, the research provides essential insights for crafting effective policies at both regional and global scales to address the complexities of climate change mitigation in the agricultural sector.

Effects of warming on rice production and metabolism process associated with greenhouse gas emissions.

Evaluating the impact of global warming on rice production and greenhouse gas (GHG) emissions is critical for ensuring food security and mitigating the consequences of climate change. Nonetheless, the impacts of warming on crop production, GHG emissions, and microbial mechanisms in the single-cropping rice systems remain unclear. Here, a two-year field experiment was conducted to explore the effects of warming (increased by 2.7-3.0 °C on average) in the rice growing season on crop production and functional microorganisms associated with GHG emissions. Results showed that warming resulted in significant reduction (p < 0.01) in the aboveground biomass and grain yield as well as in grain weight, the number of spikelets per panicle, and the seed-setting rate. However, it caused a significant increase (p < 0.01) in the number of panicles by 15.6 % and 34.9 %, respectively. Furthermore, warming significantly increased (p < 0.01) seasonal methane (CH4) emissions but reduced nitrous oxide (N2O) emissions, particularly in 2022.The relative abundance of genes associated with CH4 metabolism and nitrogen metabolism was increased by 40.7 % and 32.7 %, respectively, in response to warming. Moreover, warming had a positive impact on the abundance of genes related to CH4 production and oxidation processes but did not affect the denitrification processes associated with N2O production. These results showed that warming decreased rice yield and biomass in the single cropping rice system but increased CH4 emissions and global warming potential. Taken together, to address the increasing food demand of a growing population and mitigate the impacts of global warming, it is imperative to duce GHG emissions and enhance crop yields.

Abiotic and biotic factors influencing small-scale corn production along a shade spectrum in arid urban agriculture settings.

Urban agriculture may be an avenue to help alleviate strain on the global production of staple crops like corn (Zea mays), but significant knowledge gaps exist regarding the optimization of staple crop production in urban settings, and especially in arid urban settings where different challenges exist for crop success. We sought to assess abiotic and biotic factors that impact sweet corn production in six arid urban agricultural plots with varying levels of shade stress, a known inhibitor of corn production. Corn successfully reached maturity in 50% of the studied plots (n = 18). Microbial richness and diversity were uniformly high in all plot soils and not indicated as a hinderance to corn production nor correlated with corn success. Multiple corn success metrics were positively correlated with average daytime light intensity (r = 0.74 to 0.84) and soil organic matter (r = 0.77 to 0.89), suggesting that these factors are critical aspects of successful corn production. In plots that did not receive optimal light exposure, exceptional soil health and morning vs afternoon sun exposure offset at least some degree of shade stress in these arid urban environments. Corn success metrics were negatively correlated with soil calcium, magnesium, sodium and sulfate (r = -0.71 to -0.90), suggesting that minimizing or mitigating the buildup of salt constituents in soils is critical for successful corn production. Optimizing staple crop production in arid urban agricultural settings supports food chain stability and social and economic security of local communities. This work suggests abiotic and biotic drivers of corn success which can be utilized for crop optimization in these environments.

Research status and prospect of ratoon rice in China under mechanically harvested condition.

The proportion and area of ratoon rice planting in China have been substantially increased, due to continuous improvement of rice breeding methods and consecutive innovation of cultivation technology, which has developed into one of rice planting modes with significant production efficiency. Combining the experience in research and practice, from the perspective of crop physiology and ecology, we reviewed the current situation and prospects of high-yielding formation and physiological mechanisms of ratoon rice. We focused on four key aspects: screening and breeding of ratoon rice cultivars and the classification; suitable stubble height for mechanically harvested ratoon rice, as well as water and fertilizer management; dry matter production and allocation in ratoon rice and the relationship with yield formation; regenerative activity and vigor of ratoon rice roots and their relationship with rhizosphere micro-ecological characteristics. As for the extending of mechanized low-cut stubbles ratoon rice technique, we should properly regulate the rhizosphere system, coordinate rhizosphere nutrient supply, germination of axillary buds, and tillering regeneration, to achieve the target of "four-high-one-low", that is high regeneration coefficient, high number of regeneration panicle, high harvest index, high yield, high quality, low-carbon and safe, aiming to improve the sustainability of ratoon rice industry.

Root proliferation adaptation strategy improved maize productivity in the US Great Plains: Insights from crop simulation model under future climate change.

Adaptation measures are essential for reducing the impact of future climate risks on agricultural production systems. The present study focuses on implementing an adaptation strategy to mitigate the impact of future climate change on rainfed maize production in the Eastern Kansas River Basin (EKSRB), an important rainfed maize-producing region in the US Great Plains, which faces potential challenges of future climate risks due to a significant east-to-west aridity gradient. We used a calibrated CERES-Maize crop model to evaluate the impacts of baseline climate conditions (1985-2014), late-term future climate scenarios (under the SSP245 emission pathway and CMIP6 models), and a novel root proliferation adaptation strategy on regional maize yield and rainfall productivity. Changes in the plant root system by increasing the root density could lead to yield benefits, especially under drought conditions. Therefore, we modified the governing equation of soil root growth in the CERES-Maize model to reflect the genetic influence of a maize cultivar to improve root density by proliferation. Under baseline conditions, maize yield values ranged from 6522 to 12,849 kgha-1, with a regional average value of 9270 kgha-1. Projections for the late-term scenario indicate a substantial decline in maize yield (36 % to 50 %) and rainfall productivity (25 % to 42 %). Introducing a hypothetical maize cultivar by employing root proliferation as an adaptation strategy resulted in a 27 % increase in regional maize yield, and a 28 % increase in rainfall productivity compared to the reference cultivar without adaptation. We observed an indication of spatial dependency of maize yield and rainfall productivity on the regional precipitation gradient, with counties towards the east having an implicit advantage over those in the west. These findings offer valuable insights for the US Great Plains maize growers and breeders, guiding strategic decisions to adapt rainfed maize production to the region's impending challenges posed by climate change.

Zeolite application mitigates NH3 and N2O emissions from pig slurry-applied field and improves nitrogen use efficiency in Italian ryegrass-maize crop rotation system for forage production.

The present study aimed to assess the efficiency of zeolite in mitigating the nitrogen (N) losses through ammonia (NH3) and nitrous oxide (N2O) emissions from pig slurry (PS) applied to Italian ryegrass (IRG)-maize fields under a crop rotation system and the consequent effect on nitrogen use efficiency (NUE) for forage production. PS was applied at rates of 150 and 200 kg N ha-1 for the IRG and maize growing seasons, respectively, with or without zeolite. Soil mineral N content and NH3 and N2O emissions were measured periodically throughout the year-round cultivation of IRG and maize. Forage yield and nutritional composition were also analyzed at the harvest time of each crop. The PS with/without zeolite application effects were interpreted by comparison with those obtained for the negative control (no-N fertilization). Soil ammonium (NH4+) content in the PS-applied plots sharply increased within the first week, then progressively decreased in both the IRG and maize growing seasons. Soil NH4+ contents in the zeolite-amended plots were higher compared to the treatment without zeolite except for the first 1 or 2 weeks after PS application when soil nitrate (NO3-) contents significantly decreased. The increase in soil NH4+ content as affected by zeolite application was more distinct in the maize growing season than in the IRG growing season. NH3 emission was predominant at the early 2 weeks after PS application. Zeolite application reduced the cumulative emission of NH3 from PS by 16.7% and 24.4% and that of N2O by 15.6% and 31.5% in the IRG growing and maize growing seasons, respectively. NUE for dry matter (DM) and total digestible nutrients (TDN) production significantly improved in annual yield basis of the IRG-maize cropping. Zeolite application in PS-applied field may represent effective management in mitigating N losses through odorous NH3 and greenhouse gas (N2O) emissions, thereby improving NUE forage production.

Effects of narrow-wide row planting patterns on canopy photosynthetic characteristics, bending resistance and yield of soybean in maize‒soybean intercropping systems.

With the improvements in mechanization levels, it is difficult for the traditional intercropping planting patterns to meet the needs of mechanization. In the traditional maize‒soybean intercropping, maize has a shading effect on soybean, which leads to a decrease in soybean photosynthetic capacity and stem bend resistance, resulting in severe lodging, which greatly affects soybean yield. In this study, we investigated the effects of three intercropping ratios (four rows of maize and four rows of soybean; four rows of maize and six rows of soybean; six rows of maize and six rows of soybean) and two planting patterns (narrow-wide row planting pattern of 80-50 cm and uniform-ridges planting pattern of 65 cm) on soybean canopy photosynthesis, stem bending resistance, cellulose, hemicellulose, lignin and related enzyme activities. Compared with the uniform-ridge planting pattern, the narrow-wide row planting pattern significantly increased the LAI, PAR, light transmittance and compound yield by 6.06%, 2.49%, 5.68% and 5.95%, respectively. The stem bending resistance and cellulose, hemicellulose, lignin and PAL, TAL and CAD activities were also significantly increased. Compared with those under the uniform-ridge planting pattern, these values increased by 7.74%, 3.04%, 8.42%, 9.76%, 7.39%, 10.54% and 8.73% respectively. Under the three intercropping ratios, the stem bending resistance, cellulose, hemicellulose, lignin content and PAL, TAL, and CAD activities in the M4S6 treatment were significantly greater than those in the M4S4 and M6S6 treatments. Compared with the M4S4 treatment, these variables increased by 12.05%, 11.09%, 21.56%, 11.91%, 18.46%, 16.1%, and 16.84%, respectively, and compared with the M6S6 treatment, they increased by 2.06%, 2.53%, 2.78%, 2.98%, 8.81%, 4.59%, and 4.36%, respectively. The D-M4S6 treatment significantly improved the lodging resistance of soybean and weakened the negative impact of intercropping on soybean yield. Therefore, based on the planting pattern of narrow-wide row maize‒soybean intercropping planting pattern, four rows of maize and six rows of soybean were more effective at improving the lodging resistance of soybean in the semiarid region of western China.

Spatial autocorrelation and driving factors of carbon emission density of crop production in China.

Mitigating carbon emissions from crop production is essential for addressing global warming. At a macro-level, existing studies have often relied on the calculation of carbon emission intensity of crop production to understand comparable carbon effects between regions. However, this approach obscures the differences in crop planting scale and natural attributes across regions, leaving room for improvement in the methods and scope of analysis. To extend the existing research, we proposed an idea for calculating the carbon emission density of crop production based on planting area. Additionally, we developed an analytical framework for driving factors of carbon emission density of crop production from a spatial interaction perspective. The provincial carbon emission density of crop production in mainland China between 2000 and 2020 was calculated, and spatial econometric models were utilized to investigate the spatial autocorrelation and driving factors. The results indicate that the national average carbon emission density of crop production was 1.462 t/hm2 annually. Over 21 years, the carbon emission density of agricultural materials, rice cultivation, soil management, and straw burning evolved from 0.384 to 0.470 t/hm2, 0.409 to 0.367 t/hm2, 0.171 to 0.169 t/hm2, and 0.317 to 0.448 t/hm2, respectively. The global Moran's index indicated a positive spatial autocorrelation of carbon emission density of crop production and the subdivided carbon sources among provinces. Regarding direct effects, an increase in the proportion of paddy fields in cropland composition and irrigation efficiency would significantly promote the carbon emission density, while factors such as cropland area, multiple cropping, agricultural personnel numbers, departmental proportion, and disaster degree would decrease the local carbon emission density. Certain factors, such as cropland area and agricultural disasters, had a spatial spillover effect on carbon emission density between provinces. The study suggests harnessing key drivers and spatial spillover effects to achieve regional low-carbon crop production.

The emergence of pesticide-free crop production systems in Europe.

Pesticide risk reduction is a priority in European agricultural policies, but how to reach these targets remains an open question. Against this background, a novel approach for transforming pest management practices is currently gaining momentum in Europe: pesticide-free, non-organic production systems. These involve the non-use of pesticides in parts of crop rotations or entire crop rotations but do not comply with other organic farming regulations. Here we present insights into the first real-world examples of such systems, in Switzerland and Germany. In both countries, pesticide-free production was initiated jointly by farmers and downstream actors some years ago. This was followed by the launch of public support schemes in 2023. We discuss the functioning and impacts of these examples, as well as farmers' adoption behaviour. Compared with organic production, the reviewed pesticide-free production schemes are more flexible and have lower adoption hurdles for farmers, as well as lower yield losses. These characteristics facilitate the large-scale adoption of pesticide-free production systems. Moreover, pesticide-free can become a clear-cut and simple production standard. Pesticide-free production can thus be a disruptive approach to create a tangible 'third way' between conventional and organic production. However, there are various adoption barriers and pesticide-free production would not currently be profitable without support in most cases.

Nanowonders in agriculture: Unveiling the potential of nanoparticles to boost crop resilience to salinity stress.

Soil salinization significantly affects crop production by reducing crop quality and decreasing yields. Climate change can intensify salinity-related challenges, making the task of achieving global food security more complex. To address the problem of elevated salinity stress in crops, nanoparticles (NPs) have emerged as a promising solution. NPs, characterized by their small size and extensive surface area, exhibit remarkable functionality and reactivity. Various types of NPs, including metal and metal oxide NPs, carbon-based NPs, polymer-based NPs, and modified NPs, have displayed potential for mitigating salinity stress in plants. However, the effectiveness of NPs application in alleviating plant stress is dependent upon multiple factors, such as NPs size, exposure duration, plant species, particle composition, and prevailing environmental conditions. Moreover, alterations to NPs surfaces through functionalization and coating also play a role in influencing plant tolerance to salinity stress. NPs can influence cellular processes by impacting signal transduction and gene expression. They counteract reactive oxygen species (ROS), regulate the water balance, enhance photosynthesis and nutrient uptake and promote plant growth and yield. The objective of this review is to discuss the positive impacts of diverse NPs on alleviating salinity stress within plants. The intricate mechanisms through which NPs accomplish this mitigation are also discussed. Furthermore, this review addresses existing research gaps, recent breakthroughs, and prospective avenues for utilizing NPs to combat salinity stress.

Managing fragmented croplands for environmental and economic benefits in China.

Cropland fragmentation contributes to low productivity and high abandonment risk. Using spatial statistics on a detailed land use map, we show that 10% of Chinese croplands have no potential to be consolidated for large-scale farming (>10 ha) owing to spatial constraints. These fragmented croplands contribute only 8% of total crop production while using 15% of nitrogen fertilizers, leading to 12% of fertilizer loss in China. Optimizing the cropping structure of fragmented croplands to meet animal food demand in China can increase animal food supply by 19%, equivalent to increasing cropland proportionally. This crop-switching approach would lead to a 10% and 101% reduction in nitrogen and greenhouse gas emissions, respectively, resulting in a net benefit of US$ 7 billion yr-1. If these fragmented croplands were relocated to generate large-scale farming units, livestock, vegetable and fruit production would be increased by 8%, 3% and 14%, respectively, and reactive nitrogen and greenhouse gas emissions would be reduced by 16% and 5%, respectively, resulting in a net benefit of US$ 44 billion yr-1. Both solutions could be used to achieve synergies between food security, economic benefits and environmental protection through increased agricultural productivity, without expanding the overall cropland area.

Dataset of the suitability of major food crops in Africa under climate change.

Understanding the extent and adapting to the impacts of climate change in the agriculture sector in Africa requires robust data on which technical and policy decisions can be based. However, there are no publicly available comprehensive data of which crops are suitable where under current and projected climate conditions for impact assessments and targeted adaptation planning. We developed a dataset on crop suitability of 23 major food crops (eight cereals, six legumes & pulses, six root & tuber crops, and three in banana-related family) for rainfed agriculture in Africa in terms of area and produced quantity. This dataset is based on the EcoCrop model parameterized with temperature, precipitation and soil data and is available for the historical period and until mid-century. The scenarios used for future projections are SSP1:RCP2.6, SSP3:RCP7.0 and SSP5:RCP8.5. The dataset provides a quantitative assessment of the impacts of climate change on crop production potential and can enable applications and linkages of crop impact studies to other socioeconomic aspects, thereby facilitating more comprehensive understanding of climate change impacts and assessment of options for building resilience.

Plant Biostimulant as an Environmentally Friendly Alternative to Modern Agriculture.

Ensuring the safety of crop production presents a significant challenge to humanity. Pesticides and fertilizers are commonly used to eliminate external interference and provide nutrients, enabling crops to sustain growth and defense. However, the addition of chemical substances does not meet the environmental standards required for agricultural production. Recently, natural sources such as biostimulants have been found to help plants with growth and defense. The development of biostimulants provides new solutions for agricultural product safety and has become a widely utilized tool in agricultural. The review summarizes the classification of biostimulants, including humic-based biostimulant, protein-based biostimulant, oligosaccharide-based biostimulant, metabolites-based biostimulants, inorganic substance, and microbial inoculant. This review attempts to summarize suitable alternative technology that can address the problems and analyze the current state of biostimulants, summarizes the research mechanisms, and anticipates future technological developments and market trends, which provides comprehensive information for researchers to develop biostimulants.

Nano-enabled agrochemicals: mitigating heavy metal toxicity and enhancing crop adaptability for sustainable crop production.

The primary factors that restrict agricultural productivity and jeopardize human and food safety are heavy metals (HMs), including arsenic, cadmium, lead, and aluminum, which adversely impact crop yields and quality. Plants, in their adaptability, proactively engage in a multitude of intricate processes to counteract the impacts of HM toxicity. These processes orchestrate profound transformations at biomolecular levels, showing the plant's ability to adapt and thrive in adversity. In the past few decades, HM stress tolerance in crops has been successfully addressed through a combination of traditional breeding techniques, cutting-edge genetic engineering methods, and the strategic implementation of marker-dependent breeding approaches. Given the remarkable progress achieved in this domain, it has become imperative to adopt integrated methods that mitigate potential risks and impacts arising from environmental contamination on yields, which is crucial as we endeavor to forge ahead with the establishment of enduring agricultural systems. In this manner, nanotechnology has emerged as a viable field in agricultural sciences. The potential applications are extensive, encompassing the regulation of environmental stressors like toxic metals, improving the efficiency of nutrient consumption and alleviating climate change effects. Integrating nanotechnology and nanomaterials in agrochemicals has successfully mitigated the drawbacks associated with traditional agrochemicals, including challenges like organic solvent pollution, susceptibility to photolysis, and restricted bioavailability. Numerous studies clearly show the immense potential of nanomaterials and nanofertilizers in tackling the acute crisis of HM toxicity in crop production. This review seeks to delve into using NPs as agrochemicals to effectively mitigate HM toxicity and enhance crop resilience, thereby fostering an environmentally friendly and economically viable approach toward sustainable agricultural advancement in the foreseeable future.

Regulation of wheat growth by soil multifunctionality and metagenomic-based microbial functional profiles under mulching treatments.

Soil microbial functional genes play key roles in biogeochemical processes that are closely related to crop development. However, the regulation of crop growth by the composition and potential interactions of metagenomic-based functional genes is poorly understood. Therefore, in a long-term mulching experiment, the regulation of wheat growth by soil multifunctionality, microbial functional profiles driven by soil properties and microbial activity was studied. Soil properties and microbial activity were significantly separated into distinct mulching treatments, and were significantly declined by plastic film mulching treatment, similar to soil multifunctionality. Only carbon (C) and phosphorus (P) cycling gene compositions were divided significantly into distinct mulching treatments to varying degrees. Similarly, intra- and inter-connected sub-networks associated with C and P cycling genes were more complex and stable than the sub-networks containing nitrogen cycling genes. Despite core functional genes being located in the middle of each network, they were rarely observed in the metagenomic assembly genomes. Subsequently, the dominant soil properties and microbial activity had greater effects on C cycling gene composition and network, which played essential roles in wheat growth regulation. Overall, wheat yield and biomass were affected differently by straw and plastic film mulching treatments, and were mainly regulated by C cycling gene network and soil multifunctionality, respectively. The results of the present study provide novel insights into wheat growth regulation by soil microbial functional profiles, with potential implications for sustainable crop production in mulching conservation agroecosystems.

Analysing spatio-temporal drought characteristics and copula-based return period in Indian Gangetic Basin (1901-2021).

Uncertainty and uneven distribution of monsoonal rainfall and its consequences on crop production is a matter of serious concern in India, specifically, in the Indo-Gangetic plain region. In this study, drought patterns were investigated through standardised precipitation index (SPI) of varying timescales, using the India Meteorological Department (IMD) precipitation data (1901-2021). We analysed the spatio-temporal pattern of different drought characteristics (frequency, duration, severity, intensity) of the Indian Gangetic basin using run theory. The bivariate copula method has been incorporated to combine two drought properties (severity and duration). Copula integrates multivariate distribution and considers the dependency rate among the variables. The five most widely used copulas from various copula families, elliptical (normal, t-copula) and Archimedean (Clayton, Gumbel, Frank), were estimated for modelling, and the best fit copula was selected. The study revealed that seasonal drought is more frequent and intense in the Upper and Middle Gangetic Plain, whereas annual drought is quite scattered in nature. It is worthy to mention that downward drought trends were observed in this agricultural belts significantly after 1965; specifically, in the Upper, Middle, and Trans Gangetic Plain regions. With increasing drought duration and severity, the drought return period raised, but the frequency decreased gradually. Most of the droughts characterised by less duration and severity occurred with a return period below 10 years for the whole region. The major 100 + years return period droughts were to be found after 1960 and their frequencies were significantly higher after 2000. The most recent remarkable droughts with more than 100 years of return occurred during 2008-2011 and 2016-2018 in the Upper and Middle Gangetic plains, whereas in the Lower Gangetic plain, a hundred-year return period drought was occurred during 2010-2013. This study provides agroclimatic-zones-wise significant information of drought characteristics and its nature of occurrence in the Indian Ganga Basin. The results enhance the understanding of drought management and formulation of adaptive strategies to mitigate the adverse impact of droughts.

Degradation of atrazine, glyphosate, and 2,4-D in soils collected from two contrasting crop rotations in Southwest Chaco, Argentina.

Argentina stands as one of the leading consumers of herbicides. In a laboratory incubation experiment, the persistence and production of degradation metabolites of Atrazine, 2,4-D, and Glyphosate were investigated in a loamy clay soil under two contrasting agricultural practices: continuous soybean cultivation (T1) and intensified rotations with grasses and legumes (T2). The soils were collected from a long-term no-till trial replicating the influence of the meteorological conditions in the productive region. The soil was enriched with diluted concentrations of 6.71, 9.95, and 24 mg a.i./kg-1 of soil for the respective herbicides, equivalent to annual doses commonly used in the productive region. Samples were taken at intervals of 0, 0.5, 1, 2, 4, 6, 8, 16, 32, and 64 days, and analysis was conducted using high-resolution liquid chromatography UPLC MS/MS. An optimal fit to the first-order kinetic model was observed for each herbicide in both rotations, resulting in relatively short half-lives. Intensified crop sequences favored the production of biotic degradation metabolites. The impact of the high frequency of soybean cultivation revealed a trend of soil acidification and a reduced biological contribution to attenuation processes in soil contamination.

Global production patterns: Understanding the relationship between greenhouse gas emissions, agriculture greening and climate variability.

Climate change due to increased greenhouse gas emissions (GHG) in the atmosphere has been consistently observed since the mid-20th century. The profound influence of global climate change on greenhouse gas (GHG) emissions, encompassing carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), has established a vital feedback loop that contributes to further climate change. This intricate relationship necessitates a comprehensive understanding of the underlying feedback mechanisms. By examining the interactions between global climate change, soil, and GHG emissions, we can elucidate the complexities of CO2, CH4, and N2O dynamics and their implications. In this study, we evaluate the global climate change relationship with GHG globally in 246 countries. We find a robust positive association between climate and GHG emissions. By 2100, GHG emissions will increase in all G7 countries and China while decreasing in the United Kingdom based on current economic growth policies, resulting in a net global increase, suggesting that climate-driven increase in GHG and climate variations impact crop production loss due to soil impacts and not provide climate adaptation. The study highlights the diverse strategies employed by G7 countries in reducing GHG emissions, with France leveraging nuclear power, Germany focusing on renewables, and Italy targeting its industrial and transportation sectors. The UK and Japan are making significant progress in emission reduction through renewable energy, while the US and Canada face challenges due to their industrial activities and reliance on fossil fuels.

Comprehensive analysis of spatiotemporal variability of rainfall-based extremes and their implications on agriculture in the Upper Ganga Command Area.

The agricultural sector in India primarily relies on monsoon rains, making it necessary for agricultural water managers to study variations in water availability by analyzing rainfall patterns. This information is critical for deciding cropping patterns and irrigation approaches, managing water resources, and improving crop water productivity. The long-term spatiotemporal variability over the command area, India Meteorological Department (IMD) based selection of thresholds for extremes indices, and thorough analysis of the consequences of extreme on agriculture make the study unique. These aspects collectively enhance the perception of the climate-agriculture relationship, which is essential for promoting agriculture resilience under changing rainfall patterns. This type of research is very limited in the literature. Therefore, the present study focuses on comprehensively analyzing the spatiotemporal variability of rainfall and extreme precipitation indices and their implications on agriculture. The study is carried out in the Upper Ganga Command Area (UGCA), India's oldest irrigation canal system, by using long-term (1901-2021) high-resolution (0.25 × 0.25°) daily rainfall gridded data obtained from IMD, Pune. Eight different extreme rainfall indices are used to assess spatiotemporal variations. The Mann-Whitney-Pettitt test identified 1970 as a significant change point. Rainfall trends and extreme indices for pre- and post-1970 periods were examined using the non-parametric modified Mann-Kendall test. The results show significant increases in rainfall trends for the annual, monsoon, and kharif seasons from 1901 to 1970, but significant decreases were observed during 1971-2021. This difference resulted in a noticeable decrease in average precipitation in the latter period, approximately 62 mm less than in 1901-1970. Similarly, extreme precipitation indices, including the number of rainy days (NxRainy), consecutive dry days (CWD), simple daily intensity index (SDII), and total precipitation (PRCPTOT), exhibited increasing trends in 1901-1970, but they showed significant decreasing trends in 1971-2021. In addition, there is a strong positive correlation between these indices and total precipitation. The study also found that geographical factors influence these trends, with all indices, except SDII, strongly correlated with latitude and elevation, but not with longitude. The implications of these negative rainfall and extreme rainfall trends were further analyzed, and the results indicate a significant impact on the cropping patterns in the study area. The present research findings will be beneficial for regional water resource managers and policymakers in better understanding the existing trends in rainfall distribution over the UGCA.