DOI: 10.5061/dryad.ht76hdrnm
title: Data from: Abiotic legacies mediate plant-soil feedback during early vegetation succession on rare earth element mine tailings

description: An increasing number of studies have shown how feedback interactions
 between plants and soil can influence primary and secondary succession.
 However, very little is known about the patterns and mechanisms of such
 plant-soil feedbacks on stressed mine tailings ecosystem, which can be
 severely contaminated by a range of toxic elements.  In a
 two-phase plant-soil feedback experiment based on the rare earth element
 (REE) mine tailing soil, we investigated biotic (changes in bacterial and
 fungal community) and abiotic legacies (changes in chemical properties) of
 three pioneer grass species, and examined feedback effects of three
 grasses, two legumes and two woody plants with different root traits.
 Positive plant-soil feedback was found in Miscanthus sinensis, Paspalum
 thunbergii and Tephrosia candida, and neutral feedback was observed in
 other four plants. These effects corresponded with an increase of
 nutrients and total organic carbon, as well as a decrease of acidity and
 extractable aluminum and REEs. There were less signs of biotic changes in
 the conditioned tailings.  The correlation analysis suggested a
 relationship between responses to soil legacies and root traits, as well
 as root economics spectrum. On the mine tailings, acquisitive species with
 higher specific root length appeared to have greater potential for
 positive feedback.  Synthesis and application: Our study shows
 that early succession on contaminated REE mine tailings may lead to more
 positive plant-soil feedback than predicted based on results of
 non-contaminated soils, mainly due to the alleviation of abiotic stress in
 tailings. Therefore, the improvement of specific abiotic soil stress and
 the trait-based selection of acquisitive plants should be preferentially
 considered to promote the primary restoration of degraded land.
description: In a two-phase plant-soil feedback experiment based on the rare
 earth element (REE) mine tailing soil, we investigated biotic (changes in
 bacterial and fungal community) and abiotic legacies (changes in chemical
 properties) of three pioneer grass species, and examined feedback effects
 of three grasses, two legumes and two woody plants with different root
 traits.  The soils for the experiment were collected
 from several patches of REE mine tailings that had been abandoned since
 2007. The grass species, comprising M. sinensis, Paspalum thunbergii and
 Digitaria sanguinalis, were planted in both the conditioning and feedback
 phases.Besides grasses, the legume species, comprising of
 <em>Tephrosia candida</em> and <em>Cajanus
 cajan</em>, and the woody species, comprising of <em>P.
 massoniana</em> and <em>C. lanceolate</em>, were planted
 in the feedback phase.  The conditioning phase lasted
 for 18 weeks. At the end of this phase, the shoots and coarse roots were
 removed, soil samples were collected for chemical properties (abiotic
 legacies) and microbial communities(biotic legacies) measurement. [The
 collection of data in "SoilAbioticData" and
 "SoilBioticData"]  The feedback phase lasted
 for 16 weeks. At the end of this phase, the plant shoots and roots were
 harvested for plant functional trait analyses. [The collection of data in
 "PlantTraitData"] More details about
 materials and methods can be found in the paper.
description: # Abiotic legacies mediate plant-soil feedback during early vegetation
 succession on rare earth element mine tailings These datasets are derived
 from a two-phase plant-soil feedback experiment based on the rare earth
 element (REE) mine tailing. We investigated biotic (changes in bacterial
 and fungal community) and abiotic legacies (changes in chemical
 properties) of three pioneer grass species, and examined feedback effects
 to three grasses, two legumes and two woody plants with different root
 traits. More details about the study please find in the paper of Zhu et al
 (the same name as this dataset) or contact the corresponding author.
 Dataset DOI link: ##
 Description of the data and file structure ### File list: * (1)
 SoilAbioticData\Soil_Abiotic_Properties.csv * (2)
 SoilBioticData\Bacterial_feature_table.txt * (3)
 SoilBioticData\Bacterial_taxonomy.tsv * (4)
 SoilBioticData\Fungal_feature_table.txt * (5)
 SoilBioticData\Fungal_taxonomy.tsv * (6) PlantTraitData\Plant_Info.csv *
 (7) PlantTraitData\Plant-soil_Feedback.csv * (8)
 PlantTraitData\Root_Functional_Traits.csv ### Additional related data
 collected that was not included in the current data package: * The raw
 sequences of the soil bacterial and fungal communities have been deposited
 in the Genome Sequence Archive in the publicly accessible Beijing
 Institute of Genomics Data Centre, Chinese Academy of Sciences, under
 accession number PRJCA009170 ().
 \#########################################################################
 ### DATA-SPECIFIC INFORMATION FOR: (1)
 SoilAbioticData\Soil\_Abiotic\_Properties.csv 1\. Number of variables: 18
 2\. Number of cases/rows: 20 3\. Variable List: * sample ID: soil
 identities, 4 Treatments (5 replicates for each) in conditioning phase. *
 pH_water: soil pH, analysed at a ratio of 1:2.5 (soil: deionized water,
 w/v). * CaCl2_Al: soil extractable aluminum content, extracted by 0.01 M
 CaCl2 solution. * CaCl2_K: soil extractable potassium content, extracted
 by 0.01 M CaCl2 solution. * CaCl2_Mg: soil extractable potassium content,
 extracted by 0.01 M CaCl2 solution. * CaCl2_Mn: soil extractable potassium
 content, extracted by 0.01 M CaCl2 solution. * CaCl2_Na: soil extractable
 potassium content, extracted by 0.01 M CaCl2 solution. * CaCl2_P: soil
 extractable potassium content, extracted by 0.01 M CaCl2 solution. *
 CaCl2_S: soil extractable potassium content, extracted by 0.01 M CaCl2
 solution. * CaCl2_REEs: soil extractable potassium content, extracted by
 0.01 M CaCl2 solution. * Total_C: total carbon content. * Total_N: total
 nitrogen content. * Total_Organic_C: total organic carbon content. *
 CN_ratio: the ratio of carbon:nitrogen content. * Total_P: total content
 of phosphorus. * Available_N: available nitrogen content. * Available_P:
 available phosphorus content. * Available_K: available potassium content.
 4\. Missing data codes: None 5\. Specialized formats or other
 abbreviations used: None
 \#########################################################################
 ### DATA-SPECIFIC INFORMATION FOR: (2)
 SoilBioticData\Bacterial\_feature\_table.txt 1\. Number of
 variables: 21 2\. Number of cases/rows: 17322 3\. Variable List: * \#ASV
 ID: amplicon sequence variants of bacterial community, clustered by
 high-quality reads. * column 2~21: soil identities, 4 Treatments (5
 replicates for each) in conditioning phase. 4\. Missing data codes: None
 5\. Specialized formats or other abbreviations used: * (1) CK - control
 soil * (2) M.s. - Miscanthus sinensis * (3) P. t. - Paspalum thunbergii *
 (4) D.s. - Digitaria sanguinalis
 \#########################################################################
 ### DATA-SPECIFIC INFORMATION FOR: (3)
 SoilBioticData\Bacterial\_taxonomy.tsv 1\. Number of variables: 3 2\.
 Number of cases/rows: 17322 3\. Variable List: * Feature ID: the same as
 "#ASV ID", amplicon sequence variants of bacterial community,
 clustered by high-quality reads. * Taxon: taxonomy of each ASV. *
 Confidence: confidence of taxonomy classfication. 4\. Missing data codes:
 None 5\. Specialized formats or other abbreviations used: None
 \#########################################################################
 ### DATA-SPECIFIC INFORMATION FOR: (4)
 SoilBioticData\Fungal\_feature\_table.txt 1\. Number of variables: 21 2\.
 Number of cases/rows: 2660 3\. Variable List: * \#ASV ID: amplicon
 sequence variants of fungal community, clustered by high-quality reads. *
 column 2~21: soil identities, 4 Treatments (5 replicates for each) in
 conditioning phase. 4\. Missing data codes: None 5\. Specialized formats
 or other abbreviations used: * (1) CK - control soil * (2) M.s. -
 Miscanthus sinensis * (3) P. t. - Paspalum thunbergii * (4) D.s. -
 Digitaria sanguinalis
 \#########################################################################
 ### DATA-SPECIFIC INFORMATION FOR: (5) SoilBioticData\Fungal\_taxonomy.tsv
 1\. Number of variables: 3 2\. Number of cases/rows: 2660 3\. Variable
 List: * Feature ID: the same as "#ASV ID", amplicon sequence
 variants of fungal community, clustered by high-quality reads. * Taxon:
 taxonomy of each ASV. * Confidence: confidence of taxonomy classfication.
 4\. Missing data codes: None 5\. Specialized formats or other
 abbreviations used: None
 \#########################################################################
 ### DATA-SPECIFIC INFORMATION FOR: (6) PlantTraitData\Plant\_Info.csv 1\.
 Number of variables: 3 2\. Number of cases/rows: 11 3\. Variable List: *
 Cultivating_Phase: the experimental phase, including "conditioning
 phase" and "feedback phase". * Plant_Species: plant species
 (control pots were planting nothing) in both cultivating phase. *
 Data_Processing_ID: the abbreviation ID for each treatment during data
 presenting and processing. 4\. Missing data codes: None 5\. Specialized
 formats or other abbreviations used: as it shown in the file.
 \#########################################################################
 ### DATA-SPECIFIC INFORMATION FOR: (7)
 PlantTraitData\Plant-soil\_Feedback.csv 1\. Number of variables: 4 2\.
 Number of cases/rows: 140 & 105 3\. Variable List: * Sample_ID_1:
 sample ID of plant samples in feedback phase. * Aver_total_biomass(g):
 Averaged individual biomass (including roots and shoots) of plant samples
 in feedback phase. * Sample_ID_2: sample ID of plant samples in feedback
 phase (for PSF calculating result). * PSF_value: Plant-soil feedback value
 (The feedback effect was calculated as the difference in biomass (BM) of a
 focal plant *a* grown on plant A conditioned and control soils divided by
 the maximum biomass of the focal plant *a* on either plant A conditioned
 or control soils: PSFA-*a* = (BMA-*a* – BMcontrol-*a*) / max(BMA-*a*,
 BMcontrol-*a*)). 4\. Missing data codes: None 5\. Specialized formats or
 other abbreviations used: as it shown in the file (6).
 \#########################################################################
 ### DATA-SPECIFIC INFORMATION FOR: (8)
 PlantTraitData\Root\_Functional\_Traits.csv 1\. Number of variables: 13
 2\. Number of cases/rows: 140 3\. Variable List: * Sample ID: sample ID of
 plant samples in feedback phase. * Shoot_Biomass(g): averaged individual
 shoot biomass of plant samples in feedback phase. * Root_Biomass(g):
 averaged individual root biomass of plant samples in feedback phase. *
 Root_Length(cm): total root length of plant samples in feedback phase. *
 Root_Volume(cm3): total root volume of plant samples in feedback phase. *
 Average_Diameter(mm): average root diameter of plant samples in feedback
 phase. * Root_Carbon_Content(mg/g): root carbon content of plant samples
 in feedback phase. * Root_Nitrogen_Content(mg/g): root nitrogen content of
 plant samples in feedback phase. * CN_Ratio: The ratio of root carbon to
 nitrogen content of plant samples in feedback phase. *
 Specific_Root_Length(cm/g): The root length divided by root mass of plant
 samples in feedback phase. * Root_Tissue_Density(g/cm3): The ratio of root
 mass to the volume of plant samples in feedback phase. *
 Fine_Root_Diameter(mm): The diameter of fine roots (diameter &lt; 2mm) of
 plant samples in feedback phase. * Root_Shoot_Ratio: The ratio of root
 mass to shoot mass of plant samples in feedback phase. 4\. Missing data
 codes: None 5\. Specialized formats or other abbreviations used: as it
 shown in the file (6). ## Sharing/Access information Data was derived from
 the following source: Zhu, S.-C., Liu, W.-S., Chen, Z.-W., Liu, X.-R.,
 Zheng, H.-X., Chen, B.-Y., Zhi, X.-Y., Chao, Y., Qiu, R.-L., Chu, C.-j.,
 Liu, C., Morel, J.L., van der Ent, A. & Tang, Y.-T. Abiotic legacies
 mediate plant-soil feedback during early vegetation succession on Rare
 Earth Element mine tailings. Journal of Applied Ecology.