Soil carbon and nitrogen storage in recently restored and mature native Scirpus marshes in the Yangtze Estuary, China: Implications for restoration

Chen, Wei; Ge, Zheng–Ming; Fei, Bei-Li; Zhang, Chao; Liu, Quan‐Xing; Zhang, Liquan

doi:10.1016/j.ecoleng.2017.04.027

Cited by 22 publications

(8 citation statements)

References 38 publications

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“…Some studies confirmed that vegetation restoration and belowground biomass had a close relationship with SOC 48 , and played a critical role in improving SOC stock in a degraded salt land 47 . Chen et al confirmed that soil carbon accumulation was strongly driven by the establishment of vegetation 49 . As a salt-tolerate plant, alfalfa has high biomass and root activity, which is the main reason why artificial alfalfa grassland has high carbon content and stock compared to arable land and forest land in the saline-alkali reclamation region.…”

Section: Discussionmentioning

confidence: 96%

Variation of soil organic carbon and physical properties in relation to land uses in the Yellow River Delta, China

Jiao

et al. 2020

Sci Rep

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Soil physical properties and soil organic carbon (SOC) are considered as important factors of soil quality. Arable land, grassland, and forest land coexist in the saline-alkali reclamation area of the Yellow River Delta (YRD), China. Such different land uses strongly influence the services of ecosystem to induce soil degradation and carbon loss. The objective of this study is to evaluate the variation of soil texture, aggregates stability, and soil carbon affected by land uses. For each land use unit, we collected soil samples from five replicated plots from “S” shape soil profiles to the depth of 50 cm (0–5, 5–10, 10–20, 20–30, and 30–50 cm). The results showed that the grassland had the lowest overall sand content of 39.98–59.34% in the top 50 cm soil profile. The content of soil aggregates > 0.25 mm (R0.25), mean weight diameter and geometric mean diameter were significantly higher in grassland than those of the arable and forest land. R0.25, aggregate stability in arable land in the top 30 cm were higher than that of forest land, but lower in the soil profile below 20 cm, likely due to different root distribution and agricultural practices. The carbon management index (CMI) was considered as the most effective indicator of soil quality. The overall SOC content and CMI in arable land were almost the lowest among three land use types. In combination with SOC, CMI and soil physical properties, we argued that alfalfa grassland had the advantage to promote soil quality compared with arable land and forest land. This result shed light on the variations of soil properties influenced by land uses and the importance to conduct proper land use for the long-term sustainability of the saline-alkali reclamation region.

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Section: Discussionmentioning

confidence: 96%

Variation of soil organic carbon and physical properties in relation to land uses in the Yellow River Delta, China

Jiao

et al. 2020

Sci Rep

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“…This quantification could act as an economic mechanism for restoration, particularly when carbon incentives are in place. Given that positive interactions can alter plant productivity, plants may sequester more carbon through growth and given the heightened sediment-trapping abilities of closely planted species, higher planting densities can be related to higher sediment organic carbon levels (e.g., Chen et al, 2017). Facilitation in the form of predator reintroduction could also positively benefit blue carbon stocks (Atwood et al, 2015), which further emphasizes the importance of holistic, community-scale restoration designs for both ecosystem services (e.g., carbon sequestration) and community development.…”

Section: Avenues For Further Investigationmentioning

confidence: 99%

Harnessing Positive Species Interactions to Enhance Coastal Wetland Restoration

Renzi

Silliman

2019

Front. Ecol. Evol.

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Coastal wetlands are among the most productive ecosystems in the world. They generate critical services for humans including shoreline protection, carbon storage, pollution mitigation, and fisheries production. Restoration of coastal wetlands has historically been viewed as a secondary conservation strategy, but recently-given the continued loss of wetlands worldwide-many non-governmental and governmental organizations have elevated habitat restoration to be a primary method for wetland conservation. The long-held paradigm in coastal wetland restoration has been to restore target habitats by reducing physical stressors and avoiding competition among outplants, such as mangrove saplings or Spartina plugs. Recent ecological research, however, reveals that positive species interactions, such as facilitation, are critical to wetland recovery after disturbance. Here, we review the scientific evidence for the importance of positive species interactions in the recovery of salt-marsh and mangrove ecosystems and assess the extent to which they have been integrated into restoration studies. We found that only a small proportion of studies of marsh and mangrove restoration examined the effects of positive species interactions, despite the important role they play in the regrowth of coastal wetlands. We outline how positive species interactions can be systematically incorporated into future restoration work and discuss how this incorporation can help the reestablishment of coastal wetland biota through: (1) trophic facilitation, (2) stress reduction, and (3) associational defenses. The absence of positive interactions in restoration designs may partially explain the significant disparities between the functioning of natural and restored coastal plant ecosystems.

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“…For this study area, soil organic carbon mapping has not been studied, but the study of soil carbon storage and distribution characteristics will appear in previous studies [104]. For the spatial distribution of soil organic carbon (SOC), the main manifestation is the higher soil organic carbon content in the oasis region, a phenomenon that does not exclude the influence of human activities on SOC [105], while vegetation growth and withering processes and animal activities also contribute to this phenomenon [106]. The SOC content was lower in relatively wet and relatively dry environments, around water bodies and in desert areas, which is consistent with the results of [107].…”

Section: Comparison Of Spatial Prediction Modelsmentioning

confidence: 99%

Digital Mapping of Soil Organic Carbon Using Sentinel Series Data: A Case Study of the Ebinur Lake Watershed in Xinjiang

Ding

Liu

et al. 2021

Remote Sensing

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As an important evaluation index of soil quality, soil organic carbon (SOC) plays an important role in soil health, ecological security, soil material cycle and global climate cycle. The use of multi-source remote sensing on soil organic carbon distribution has a certain auxiliary effect on the study of soil organic carbon storage and the regional ecological cycle. However, the study on SOC distribution in Ebinur Lake Basin in arid and semi-arid regions is limited to the mapping of measured data, and the soil mapping of SOC using remote sensing data needs to be studied. Whether different machine learning methods can improve prediction accuracy in mapping process is less studied in arid areas. Based on that, combined with the proposed problems, this study selected the typical area of the Ebinur Lake Basin in the arid region as the study area, took the sentinel data as the main data source, and used the Sentinel-1A (radar data), the Sentinel-2A and the Sentinel-3A (multispectral data), combined with 16 kinds of DEM derivatives and climate data (annual average temperature MAT, annual average precipitation MAP) as analysis. The five different types of data are reconstructed by spatial data and divided into four spatial resolutions (10, 100, 300, and 500 m). Seven models are constructed and predicted by machine learning methods RF and Cubist. The results show that the prediction accuracy of RF model is better than that of Cubist model, indicating that RF model is more suitable for small areas in arid areas. Among the three data sources, Sentinel-1A has the highest SOC prediction accuracy of 0.391 at 10 m resolution under the RF model. The results of the importance of environmental variables show that the importance of Flow Accumulation is higher in the RF model and the importance of SLOP in the DEM derivative is higher in the Cubist model. In the prediction results, SOC is mainly distributed in oasis and regions with more human activities, while SOC is less distributed in other regions. This study provides a certain reference value for the prediction of small-scale soil organic carbon spatial distribution by means of remote sensing and environmental factors.

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Soil carbon and nitrogen storage in recently restored and mature native Scirpus marshes in the Yangtze Estuary, China: Implications for restoration

Cited by 22 publications

References 38 publications

Variation of soil organic carbon and physical properties in relation to land uses in the Yellow River Delta, China

Variation of soil organic carbon and physical properties in relation to land uses in the Yellow River Delta, China

Harnessing Positive Species Interactions to Enhance Coastal Wetland Restoration

Digital Mapping of Soil Organic Carbon Using Sentinel Series Data: A Case Study of the Ebinur Lake Watershed in Xinjiang

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