Dataset Information

Modeling of Trace Metal Migration and Accumulation Processes in a Soil-Wheat System in Lihe Watershed, China.

ABSTRACT: Samples of wheat and soil were collected in the Lihe watershed in East China, the migration and accumulation processes of four common trace metals (Cu, Pb, Cd and Ni) in each part of the wheat plant (root, stem, leaf and grain) were analyzed, and a mechanistic model was proposed to simulate these processes based on wheat growth techniques. Model results show that Cu and Cd migrate more easily with wheat grains, while most Pb and Ni accumulate in roots. Modeling results were shown to be relatively good, with an error of 25.29% in value and 26.38% in fluctuation, and had smaller dispersion degree than actual measurement results. Monte Carlo simulation results also match quite well with actual measurement results, and modeling results are slightly smaller in the simulation of Leaf-Cu, Grain-Cu and Leaf-Ni. Trace metal pollution risk in wheat is evaluated based on this model; our results show that the northwest and northeast parts in the research area are not suitable for growing wheat. In general, this model is relatively accurate, and can evaluate the wheat pollution risk before seeding wheat, providing scientific references for the early selection of wheat safety sowing areas.

SUBMITTER: Tong G

PROVIDER: S-EPMC6266972 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Modeling of Trace Metal Migration and Accumulation Processes in a Soil-Wheat System in Lihe Watershed, China.

Tong Guijie G Wu Shaohua S Yuan Yujie Y Li Fufu F Chen Lian L Yan Daohao D

International journal of environmental research and public health 20181101 11

Samples of wheat and soil were collected in the Lihe watershed in East China, the migration and accumulation processes of four common trace metals (Cu, Pb, Cd and Ni) in each part of the wheat plant (root, stem, leaf and grain) were analyzed, and a mechanistic model was proposed to simulate these processes based on wheat growth techniques. Model results show that Cu and Cd migrate more easily with wheat grains, while most Pb and Ni accumulate in roots. Modeling results were shown to be relativel ...[more]

PMID: 30388794

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Project description:The dataset presented in this article is related to the work "Evaluation and Analysis of SMAP, AMSR2, and MEaSUREs Freeze/Thaw Products in China [1]". Soil moisture and temperature are important variables of land-atmosphere energy exchange, monitoring vegetation growth, predicting drought disasters and climate and hydrological modelling [2], [3], [4], [5], [6]. This work provides detailed information on in situ soil moisture and temperature data network established in the Genhe watershed and Saihanba area in China, respectively. The Genhe watershed represents the complex surface heterogeneity in Northeast China. Therefore, data from 22 in situ sites were established in the Genhe watershed since March 2016 to improve the dynamic analysis and modeling of remotely sensed information for complex land surfaces. Saihanba is currently China's largest manmade forest and has a unique alpine wetland and a complete aquatic ecosystem. There are 29 in situ sites deployed in Saihanba since August 2018 for studying the cold temperate continental monsoon climate and estimating forest carbon storage capacity and carbon emissions from manmade forests. Soil temperature and permittivity data in the network were measured using ECH2O EC-5TM probes (Decagon Devices, Inc., Washington, USA, https://www.metergroup.com/) and XingShiTu (XST) probes (BEIJING XST Co., Ltd., www.xingshitu.com) every 30 min at depths of 3, 5, and 10 cm for the Genhe watershed continuous automatic observation network, and depths of 5 and 10 cm for the Saihanba continuous automatic observation network. In the Genhe watershed, soil moisture and soil temperature data in the network were automatically collected using the EM50 data collection system. The Saihanba area has the XST data collection system to record soil temperature and permittivity. The permittivity data collected with the XST data collector were transformed to soil moisture data (volumetric water content) based on the formula developed by [7]. The datasets of the Genhe watershed and Saihanba area consist of raw data acquired by the data collector and processed data of soil moisture and temperature. The Saihanba dataset also includes the calibration data based on soil texture. The result of temporal variations analysis in observed data in the Genhe Watershed and the processing in observed data in the saihanba area show that the long-term in situ soil moisture and temperature datasets can be used for the validation/calibration and improvement of the soil moisture and soil freeze/thaw algorithm.

Project description:Soil microeukaryotes play a pivotal role in soil nutrient cycling and crop growth in agroecosystems. However, knowledge of microeukaryotic community distribution patterns, assembly processes, and co-existence networks is greatly limited. Here, microbial eukaryotes in bulk and rhizosphere soils of the North China Plain were investigated. The results showed that soil pH was the driving factor for the microeukaryotic community composition in the bulk and rhizosphere soils. The soil microeukaryotic community could significantly differ between alkaline and acidic soils. The results indicated that the soil pH had a stronger effect than niche differences on community composition. Partial Mantel tests showed that soil pH and spatial distance had similar effects on the microeukaryotic community composition in the bulk soil. However, in the rhizosphere soil, spatial distance had a stronger effect than soil pH. Infer Community Assembly Mechanisms by Phylogenetic bin-based null model (iCAMP) analysis revealed that drift was the most important process driving microeukaryotic community assembly, with an average relative importance of 37.4-71.1%. Dispersal limitation displayed slightly greater importance in alkaline rhizosphere than in alkaline bulk soils. Meanwhile, the opposite trend was observed in acidic soils. In addition, the contribution of each assembly process to each iCAMP lineage "bin" varied according to the acidic or alkaline conditions of the soil and the niche environment. High proportions of positive links were found within the four ecological networks. Alkaline soil networks, especially the alkaline bulk soil network, showed greater complexity than the acidic soil networks. Natural connectivity analysis revealed that the rhizosphere community had a greater stability than the bulk soil community in alkaline soil. This study provides a foundation for understanding the potential roles of microbial eukaryotes in agricultural soil ecosystem functioning.

Dataset Information

Modeling of Trace Metal Migration and Accumulation Processes in a Soil-Wheat System in Lihe Watershed, China.

Publications

Modeling of Trace Metal Migration and Accumulation Processes in a Soil-Wheat System in Lihe Watershed, China.

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