Coupling of soil carbon and nitrogen dynamics in drylands under climate change

Han, Yaowen; Jia, Yufu; Wang, Guoan; Tan, Qiqi; Liu, Xuejun; Chen, Chongjuan

doi:10.1016/j.catena.2022.106735

Cited by 10 publications

(4 citation statements)

References 41 publications

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“…Hui et al (2021) also found that soil P increased with latitude. This is mainly because the decrease in temperature with increasing altitude would inhibit soil microbial activity, which will weaken the mineralization of organic carbon and ammonia, and eventually lead to the increase of soil nutrients (Han et al, 2023). We observed the soil C:N ratios exhibited a significant negative correlation with elevation and latitude.…”

Section: Discussionmentioning

confidence: 83%

“…This pattern may reflect the slow decomposition rate of organic matter at high altitude, because of low temperatures (Zhai et al, 2019), but could also due to differences in soil type at different elevations. However, other related studies have demonstrated that soil C:N values increased linearly with elevation in tropical forests (He et al, 2016;Hui et al, 2021;Han et al, 2023). Sheng et al (2022) also founded that soil C:N was positively correlated with elevation in paddy soils.…”

Section: Discussionmentioning

confidence: 85%

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Soil C:N:P stoichiometry and its influencing factors in forest ecosystems in southern China

Zeng

et al. 2023

Front. For. Glob. Change

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IntroductionSoil carbon and nutrient contents and their stoichiometric characteristics play a vital role in indicating plant growth and element balance, which can be used to indicate nutrient limitation. However, it has been less studied about their driving factors within forest soils at the regional scale in southern China.MethodsIn this study, soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) were analyzed in the topsoil (0–10 cm) at 345 sampling plots representing different forest types in Guangxi Province.ResultsThe results showed that the mean contents of C, N, and P were 29.80, 2.46, and 0.51 g/kg, respectively, and soil C:N, C:P, and N:P were 13.95, 69.60, and 5.53 respectively. The ratios also showed remarkable correlations with each other. C, N, and P contents and their ratios presented significant differences among different soil and vegetation types. C, N, and P concentrations increased with the increase of elevation and latitude, and decrease with the increase of average annual temperature (MAT). Conversely, C:N showed an opposite trend. C, N, and N:P were also increased with increasing average annual precipitation (MAP). Collectively, soil type, vegetation type, geographical, and climatic factors explained 43.46, 64.02, 68.61, 32.93, 39.64, and 37.87% of the variance in C, N, P, C:N, C:P, and N:P, respectively. For Soil C, both latitude and MAP had strong influences. Soil type was the largest explanation for soil N and P contents. Latitude and longitude were the key factors determining the soil stoichiometric ratios.DiscussionOverall, soil type, geographical and climatic factors were the most vital explanation variables for soil nutrients and their stoichiometric ratios. These results could help improve our understanding of soil stoichiometry within forest ecosystems in southern China.

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Section: Discussionmentioning

confidence: 83%

Section: Discussionmentioning

confidence: 85%

Soil C:N:P stoichiometry and its influencing factors in forest ecosystems in southern China

Zeng

et al. 2023

Front. For. Glob. Change

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“…The physical characteristics of the soil greatly control the supply of N by the soil, due to the considerable influence they have on the moisture content and porosity of the soil, on its biochemical processes and on the activity of microorganisms [8,13]. Soils with higher mineralization rates are generally sandy soils, which are very susceptible to N loss by leaching due to greater aeration and less OM protection.…”

Section: Influence Of Soil Physical Propertiesmentioning

confidence: 99%

Digitization of Crop Nitrogen Modelling: A Review

et al. 2023

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Applying the correct dose of nitrogen (N) fertilizer to crops is extremely important. The current predictive models of yield and soil–crop dynamics during the crop growing season currently combine information about soil, climate, crops, and agricultural practices to predict the N needs of plants and optimize its application. Recent advances in remote sensing technology have also contributed to digital modelling of crop N requirements. These sensors provide detailed data, allowing for real-time adjustments in order to increase nutrient application accuracy. Combining these with other tools such as geographic information systems, data analysis, and their integration in modelling with experimental approaches in techniques such as machine learning (ML) and artificial intelligence, it is possible to develop digital twins for complex agricultural systems. Creating digital twins from the physical field can simulate the impact of different events and actions. In this article, we review the state-of-the-art of modelling N needs by crops, starting by exploring N dynamics in the soil−plant system; we demonstrate different classical approaches to modelling these dynamics so as to predict the needs and to define the optimal fertilization doses of this nutrient. Therefore, this article reviews the currently available information from Google Scholar and ScienceDirect, using relevant studies on N dynamics in agricultural systems, different modelling approaches used to simulate crop growth and N dynamics, and the application of digital tools and technologies for modelling proposed crops. The cited articles were selected following the exclusion criteria, resulting in a total of 66 articles. Finally, we present digital tools and technologies that increase the accuracy of model estimates and improve the simulation and presentation of estimated results to the manager in order to facilitate decision-making processes.

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“…The community drivers of WM, MWD, and TP drive stoichiometric balance through positive indirect effects on the enzyme N:P ratio. The increase in MWD improves the soil physical structure and reduces N loss, which has a positive indirect effect on the enzyme N:P ratio [55]. However, the increase in MWD at low nutrient levels makes soil microorganisms more inclined to utilize SOC, which has a negative indirect effect on the enzyme N:P ratio [56].…”

Section: Ecological Stoichiometry Guides Land Use Patterns In the Yrdmentioning

confidence: 99%

Effects of Three Long-Term Land Use Patterns on Soil Degradation in the Yellow River Delta: Evidence from Ecological Stoichiometry

Kong,

Zhu,

Ming

et al. 2023

Agronomy

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The irrational land use patterns in the Yellow River Delta (YRD) have resulted in an imbalance in ecological stoichiometry, leading to secondary salinization and soil degradation. However, there is limited knowledge about the long-term response of soil and enzyme stoichiometry to land use. This hampers our ability to optimize land use in the YRD to alleviate nutrient limitation and thus promote ecological stoichiometric balance. We investigated the stoichiometry of soil and enzyme carbon (C), nitrogen (N), and phosphorus (P) in three land use patterns (Alfalfa artificial grassland, AG; wheat–maize rotation field, WM; native grassland, PC) established for 19 years in the YRD. The results showed that the soil stoichiometry of the three land uses in the YRD was lower than the world and Chinese averages, indicating lower C and N levels. Nutrient limitations of soil microorganisms were C and P due to an enzyme C:N ratio greater than 1:1 and vector angle greater than 45°. The three land use patterns have different advantages in alleviating nutrient limitations in the YRD. AG promotes soil macroaggregate formation, reduces soil salt content, improves nutrient availability, and mitigates N limitation. This makes AG more conducive to improving the poor soil structure, high soil salinity, and stoichiometric imbalance in the YRD to mitigate local soil degradation and be suitable for long-term continuous cultivation. WM is beneficial for increasing soil total C content due to straw return. However, WM does not reduce soil salinity. WM is more suitable for intercropping or crop rotation to improve soil C content in the YRD. Although PC can alleviate soil microbial C limitation due to its significantly lower vector length than AG and WM, the low nutrient levels hindered its ability to alleviate local soil nutrient limitation. In conclusion, our study provides a theoretical basis for rational land use in the YRD to mitigate soil degradation.

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Coupling of soil carbon and nitrogen dynamics in drylands under climate change

Cited by 10 publications

References 41 publications

Soil C:N:P stoichiometry and its influencing factors in forest ecosystems in southern China

Soil C:N:P stoichiometry and its influencing factors in forest ecosystems in southern China

Digitization of Crop Nitrogen Modelling: A Review

Effects of Three Long-Term Land Use Patterns on Soil Degradation in the Yellow River Delta: Evidence from Ecological Stoichiometry

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