Carbon and nitrogen cycling on the Qinghai–Tibetan Plateau

Chen, Huai; Ju, Peijun; Zhu, Qiuan; Xu, Xingliang; Wu, Ning; Gao, Yongheng; Feng, Xiaojuan; Tian, Jianqing; Niu, Shuli; Zhang, Yangjian; Peng, Changhui; Wang, Yanfen

doi:10.1038/s43017-022-00344-2

Cited by 118 publications

(53 citation statements)

References 202 publications

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“…Counties with relatively high average FLCs were mainly distributed in the Horqin rangeland of eastern Inner Mongolia and the center of the Qinghai-Tibetan Plateau. Spatially explicit production-side measures should focus on these hotspots, including optimizing herd structure, constructing artificial rangelands, and increasing livestock mobility. ,, In rangelands that are sensitive to disturbance (e.g., alpine rangelands in the Qinghai-Tibetan Plateau and desert rangelands in Inner Mongolia), even minimal FLCs induced by grazing, combined with climate change and local biotic and abiotic contexts, can significantly threaten plant production, soil carbon and nitrogen stocks, and biodiversity patterns. − …”

Section: Resultsmentioning

confidence: 99%

“…The FLCs in China induced by grazing activities have led to rangeland degradation through reductions in vegetation production and coverage, reductions in soil organic carbon and total nitrogen, and raising trade-offs among multiple ecosystem services. ,, China has set an ambitious goal of eradicating the FLCs in pastoral regions by 2035 to solve the rangeland degradation challenge. To achieve this goal, the Chinese government has introduced a package of environmental policy measures, including the third round of the five-year RECP program, the Guideline on Promoting the Development of Grass-based Livestock Husbandry, and the 14th Five-Year Plan for the Protection and Development of Forestry and Rangeland.…”

Section: Discussionmentioning

confidence: 99%

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Consumption in Non-Pastoral Regions Drove Three-Quarters of Forage–Livestock Conflicts in China

Yang

Liang

Zhou

et al. 2023

Environ. Sci. Technol.

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Forage–livestock conflict (FLC) is a major anthropogenic cause of rangeland degradation. It poses tremendous threats to the environment owing to its adverse impacts on carbon sequestration, water supply and regulation, and biodiversity conservation. Existing policy interventions focus on the in situ FLCs induced by local production activities but overlook the role of consumption activities in driving FLCs. Here, we investigate the spatiotemporal variations in China’s FLCs and the domestic final consumers at the county level by combining remote sensing data and multi-regional input–output model. Results show that during 2005–2015, China’s pastoralism induced an average of 82 million tons of FLCs per year. Domestic final demand was responsible for 85–93% of the FLCs in China. There was spatiotemporal heterogeneity in domestic consumption driving China’s FLCs. In particular, the final demand of non-pastoral regions was responsible for around three-quarters (74–79%) of the total FLCs throughout the decade. The rangeland-based livestock raising, agricultural and sideline product processing, and catering sectors are important demand-side drivers. These findings can support targeted demand-side strategies and interregional cooperation to reduce China’s FLCs, thus mitigating rangeland degradation.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Consumption in Non-Pastoral Regions Drove Three-Quarters of Forage–Livestock Conflicts in China

Yang

Liang

Zhou

et al. 2023

Environ. Sci. Technol.

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“…Soil nutrient content (e.g., total nitrogen (TN), total phosphorus pentoxide (TP 2 O 5 ), soil organic matter (SOM), and others) is a direct expression of soil fertility, which is essential for all biological processes and is an important indicator of soil degradation [ 6 , 7 , 8 , 9 ]. Soil nutrient composition and content determine vegetation growth, composition, and distribution, and soil nutrients and other chemical components affect the structure of soil microbial communities, enzyme activity, and the cycling of elements such as carbon (C), nitrogen (N) and phosphorus (P) in terrestrial ecosystems [ 7 , 10 , 11 ]. Moreover, these effects are more pronounced in alpine regions that are ecologically fragile and sensitive to climate change.…”

Section: Introductionmentioning

confidence: 99%

Vis–NIR Spectroscopy Combined with GAN Data Augmentation for Predicting Soil Nutrients in Degraded Alpine Meadows on the Qinghai–Tibet Plateau

Jiang

Zhao

Ding

et al. 2023

Sensors

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Soil nutrients play vital roles in vegetation growth and are a key indicator of land degradation. Accurate, rapid, and non-destructive measurement of the soil nutrient content is important for ecological conservation, degradation monitoring, and precision farming. Currently, visible and near-infrared (Vis–NIR) spectroscopy allows for rapid and non-destructive monitoring of soil nutrients. However, the performance of Vis–NIR inversion models is extremely dependent on the number of samples. Limited samples may lead to low prediction accuracy of the models. Therefore, modeling and prediction based on a small sample size remain a challenge. This study proposes a method for the simultaneous augmentation of soil spectral and nutrient data (total nitrogen (TN), soil organic matter (SOM), total potassium oxide (TK2O), and total phosphorus pentoxide (TP2O5)) using a generative adversarial network (GAN). The sample augmentation range and the level of accuracy improvement were also analyzed. First, 42 soil samples were collected from the pika disturbance area on the QTP. The collected soils were measured in the laboratory for Vis–NIR and TN, SOM, TK2O, and TP2O5 data. A GAN was then used to augment the soil spectral and nutrient data simultaneously. Finally, the effect of adding different numbers of generative samples to the training set on the predictive performance of a convolutional neural network (CNN) was analyzed and compared with another data augmentation method (extended multiplicative signal augmentation, EMSA). The results showed that a GAN can generate data very similar to real data and with better diversity. A total of 15, 30, 60, 120, and 240 generative samples (GAN and EMSA) were randomly selected from 300 generative samples to be included in the real data to train the CNN model. The model performance first improved and then deteriorated, and the GAN was more effective than EMSA. Further shortening the interval for adding GAN data revealed that the optimal ranges were 30–40, 50–60, 30–35, and 25–35 for TK2O, TN, TP2O5, and SOM, respectively, and the validation set accuracy was maximized in these ranges. Therefore, the above method can compensate to some extent for insufficient samples in the hyperspectral prediction of soil nutrients, and can quickly and accurately estimate the content of soil TK2O, TN, TP2O5, and SOM.

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“…The alpine grasslands on the Qinghai-Tibetan Plateau, which cover roughly 40% of China’s grassland area, serve as an essential ecological barrier and carbon sink ( Chen et al, 2022 ; Wang Y. et al, 2022 ). However, due to human disturbances and climate changes, degradation of alpine grasslands is widespread and has accelerated in the past decades, resulting in a significant loss of biodiversity and soil C stocks ( Bardgett et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Linking between soil properties, bacterial communities, enzyme activities, and soil organic carbon mineralization under ecological restoration in an alpine degraded grassland

et al. 2023

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Soil organic carbon (SOC) mineralization is affected by ecological restoration and plays an important role in the soil C cycle. However, the mechanism of ecological restoration on SOC mineralization remains unclear. Here, we collected soils from the degraded grassland that have undergone 14 years of ecological restoration by planting shrubs with Salix cupularis alone (SA) and, planting shrubs with Salix cupularis plus planting mixed grasses (SG), with the extremely degraded grassland underwent natural restoration as control (CK). We aimed to investigate the effect of ecological restoration on SOC mineralization at different soil depths, and to address the relative importance of biotic and abiotic drivers of SOC mineralization. Our results documented the statistically significant impacts of restoration mode and its interaction with soil depth on SOC mineralization. Compared with CK, the SA and SG increased the cumulative SOC mineralization but decreased C mineralization efficiency at the 0–20 and 20–40 cm soil depths. Random Forest analyses showed that soil depth, microbial biomass C (MBC), hot-water extractable organic C (HWEOC), and bacterial community composition were important indicators that predicted SOC mineralization. Structural equal modeling indicated that MBC, SOC, and C-cycling enzymes had positive effects on SOC mineralization. Bacterial community composition regulated SOC mineralization via controlling microbial biomass production and C-cycling enzyme activities. Overall, our study provides insights into soil biotic and abiotic factors in association with SOC mineralization, and contributes to understanding the effect and mechanism of ecological restoration on SOC mineralization in a degraded grassland in an alpine region.

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Carbon and nitrogen cycling on the Qinghai–Tibetan Plateau

Cited by 118 publications

References 202 publications

Consumption in Non-Pastoral Regions Drove Three-Quarters of Forage–Livestock Conflicts in China

Consumption in Non-Pastoral Regions Drove Three-Quarters of Forage–Livestock Conflicts in China

Vis–NIR Spectroscopy Combined with GAN Data Augmentation for Predicting Soil Nutrients in Degraded Alpine Meadows on the Qinghai–Tibet Plateau

Linking between soil properties, bacterial communities, enzyme activities, and soil organic carbon mineralization under ecological restoration in an alpine degraded grassland

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