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Research Article | Ecological and Evolutionary Science

Existing Climate Change Will Lead to Pronounced Shifts in the Diversity of Soil Prokaryotes

Joshua Ladau, Yu Shi, Xin Jing, Jin-Sheng He, Litong Chen, Xiangui Lin, Noah Fierer, Jack A. Gilbert, Katherine S. Pollard, Haiyan Chu
Olivia Mason, Editor
Joshua Ladau
aState Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China
bGladstone Institutes, San Francisco, California, USA
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Yu Shi
aState Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China
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Xin Jing
cDepartment of Ecology, College of Urban and Environmental Sciences and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing, China
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Jin-Sheng He
cDepartment of Ecology, College of Urban and Environmental Sciences and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing, China
dKey Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, China
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Litong Chen
dKey Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, China
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Xiangui Lin
aState Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China
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Noah Fierer
eDepartment of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado, USA
fCooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, USA
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Jack A. Gilbert
gBiosciences Division, The Microbiome Center, Argonne National Laboratory, Argonne, Illinois, USA
hDepartment of Surgery, University of Chicago, Chicago, Illinois, USA
iMarine Biological Laboratory, Woods Hole, Massachusetts, USA
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Katherine S. Pollard
bGladstone Institutes, San Francisco, California, USA
jDivision of Biostatistics and Institute for Human Genetics, University of California, San Francisco, California, USA
kChan-Zuckerberg Biohub, San Francisco, California, USA
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Haiyan Chu
aState Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China
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Olivia Mason
Florida State University
Roles: Editor
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DOI: 10.1128/mSystems.00167-18
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  • FIG 1
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    FIG 1

    Distributions of soil prokaryotes in Tibet lag behind shifts in climate by up to 50 years. (A) The number of OTUs associated with climate from different years. A given OTU can be associated with climate from multiple years; the 2011 category represents climate from the year of sample collection. Lags are indicated by the association of many OTUs with climate from prior to 2011 and in many cases prior to 1980. (B) OTUs were associated with climate from both contemporary and historic values of most climate variables (PC1, PC2, and PC3 are associated with temperature, precipitation, and temperature range, respectively). (C) Most OTUs associated with historic climate were also associated with contemporary climate. Symbol size is proportional to the strength of the association, and OTUs (x axis) are ordered by the earliest year of climate with which they were associated. (D) Soil properties were also associated with historic climate, suggesting that the lags in bacterial distributions may be mediated by or associated with lags in soil properties. Climate from all time periods competed in the model selection procedure for each edaphic factor, and only the resulting predictive associations are included in the histogram.

  • FIG 2
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    FIG 2

    With equilibration to contemporary climate, the distributions of soil prokaryotes in Tibet would shift substantially. (A) Across most of the locations sampled, richness would increase, although in some locations it would decrease. Red and blue indicate increases and decreases in richness, respectively. (B) Increases in richness would be greatest in locations that have relatively low richness; locations with higher contemporary richness would see little change, or even decreases in richness. (C) The magnitude of shifts in relative abundance of OTUs with equilibration would be comparable to contemporary intersample variability in their relative abundance. Red lines indicate current intrasample differences in relative abundance; black dots represent the projected shifts in relative abundance with equilibration.

  • FIG 3
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    FIG 3

    Model predictions in the Tibetan Plateau and North America show increasing prokaryotic diversity in both regions. Models of prokaryotic richness fitted on data from sampling locations were used to predict current richness across the Tibetan Plateau (top left) and northern North America (bottom left). Then the same models were used to predict future richness by plugging in current climate data. When these forecasted maps were compared to the current maps, they revealed large shifts in richness in both regions (right), with richness increasing in the majority of locations (red) but decreasing in others (blue).

  • FIG 4
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    FIG 4

    Associations between taxa and climate over time in North America. (A) The number of OTUs associated with climate from different years. (B) Most OTUs associated with historic climate were also associated with contemporary climate. Symbol size is proportional to the strength of the association, and OTUs (x axis) are ordered by the earliest year of climate with which they were associated. (C) The magnitude of shifts in relative abundance of OTUs with equilibration would be comparable to contemporary intersample variability in their relative abundance. Red lines indicate current intrasample differences in relative abundance; black dots represent the projected shifts in relative abundance with equilibration.

  • FIG 5
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    FIG 5

    Relationship between OTU richness and soil C:N ratios.

  • FIG 6
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    FIG 6

    Prokaryotic communities in Tibetan Plateau soils are associated strongly with soil C:N ratios. Prokaryotic community compositional structure in the Tibetan Plateau soils as indicated by nonmetric multidimensional scaling plots. Sites are color coded according to soil C:N ratios. (A) Based on Bray-Curtis distance. (B) Based on unweighted UniFrac distance. (C) Based on weighted UniFrac distance.

Supplemental Material

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  • FIG S1

    Overview of community composition, sampling sites, and climate data in the Tibetan Plateau. (A to C) Prokaryote community compositional structure in the Tibetan Plateau soils as indicated by nonmetric multidimensional scaling plots. Sites are color coded according to soil moisture content. (A) Based on Bray-Curtis distance. (B) Based on unweighted UniFrac distance. (C) Based on weighted UniFrac distance. (D) Relative abundance of the dominant phyla across samples from Tibetan Plateau. Relative abundances are based on the proportional frequencies of 16S rRNA sequences that could be classified at the phylum level. (E) Locations of sampling sites across Tibetan Plateau. (F) Principal components of climate data as a function of time show consistent trends or consistent trends followed by leveling off. There is one line for each grid cell in the climate data map that harbors one or more samples. Download FIG S1, PDF file, 0.2 MB.

    Copyright © 2018 Ladau et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • TABLE S1

    (A) Relative average abundances of phyla classified with the Greengenes database (http://greengenes.lbl.gov) across all soils. Column headers are sample names. (B) The shifts in relative abundance of the bacterial families (Tibetan Plateau). Column headers are defined in an adjacent sheet in the Excel file. (C) The shifts in relative abundance of the bacterial families (North American). Column headers are identically defined as for Table S1B (see column definition sheet). (D) Correlations of richness and phylogenetic diversity (PD) with soil characteristics, plant Shannon index, and plant species richness. (E) Soil variables significantly correlated with structure of prokaryote communities, as determined by Mantel tests. (F) Description of the geographic, climatic, and soil variables by study sites. Column headers are defined in an adjacent sheet in the Excel file. (G) Climate variables used in modeling. Download Table S1, XLSX file, 0.3 MB.

    Copyright © 2018 Ladau et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • FIG S2

    Results for soil bacterial families across the Tibetan Plateau. Abundances of 53 prevalent bacterial families (>40 samples) are associated with historical climate. (A) Importance of climate variables for predicting distributions of families. Historic climate variables tend to be as important as contemporary climate variables. (B to D) Same as Fig. 1A to C, but for families. (E) Same as Fig. 2C, but showing the distribution of current intersample differences in relative abundances of families. (F) Same as Fig. 2C, but showing the distribution of projected future intersample differences of relative abundances of families. (G) Shifts in the relative abundance of families as a function of their current relative abundance. Red, increases; blue, decreases. Shifts are significantly inversely associated with current relative abundance, as evidenced by blue symbols being clustered in the upper part of the graph. (H) Same as Fig. 2C, but showing the distribution of projected future intersample differences in relative abundances of families. Download FIG S2, PDF file, 0.3 MB.

    Copyright © 2018 Ladau et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • FIG S3

    Results for soil bacterial OTUs across the Tibetan Plateau. Abundances of 317 prevalent bacterial OTUs (present in >40 samples) are associated with historical climate. (A) Same as Fig. S2, but for OTUs. (B) Analogous to Fig. 2C, but showing the distribution of current intersample differences in relative abundances of OTUs. (C) Same as Fig. S2G, but for OTUs. (D) Analogous to Fig. 2C, but showing the distribution of projected future intersample differences in relative abundances of OTUs. Download FIG S3, PDF file, 0.3 MB.

    Copyright © 2018 Ladau et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • FIG S4

    Results for soil properties across the Tibetan Plateau. (A) Same as Fig. 1C, but for soil properties. DON, dissolved organic nitrogen; NO3, nitrate nitrogen; DOC, dissolved organic carbon; CN ratio, carbon/nitrogen ratio; DTN, dissolved total nitrogen. (B) Relationship between relative abundance of dominant bacterial phyla and soil C:N ratio. Linear regressions were used to test Pearson correlation between the relative abundance of each taxon and soil C:N ratio. (C) Relationship between relative abundance of dominant bacterial phyla and soil moisture (SM). Linear regressions were used to test Pearson correlation between each taxon’s relative abundance and SM. Download FIG S4, PDF file, 0.3 MB.

    Copyright © 2018 Ladau et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • FIG S5

    Results for diversity in the Tibetan Plateau. (A) Distributions of projected shifts in prokaryote richness within samples compared to current and future intersample differences in richness. Projected intrasample changes in richness are of similar magnitude to existing and projected future intersample differences in richness. (B) Same as panel A, but for Shannon diversity. (C) Same as Fig. 2B, but for Shannon diversity. (D) Amount of extrapolation necessary to make geographic projections of diversity. Maps show multivariate environmental similarity surface (MESS) values, which give how far out of the observed range climate conditions are at each location. Almost all locations within the Tibetan Plateau are less than 20% out of range (greater than −20 on the map) for both current and future projections, indicating that to make geographic projections, minimal extrapolation beyond the range of the observed data is necessary. Download FIG S5, PDF file, 0.2 MB.

    Copyright © 2018 Ladau et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • FIG S6

    Maps for northern North America. (A) Locations of sampling sites. (B) Analogous to Fig. 2A, but for richness. Download FIG S6, PDF file, 0.2 MB.

    Copyright © 2018 Ladau et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • FIG S7

    Results for soil bacterial families in northern North America. (A) Analogous to Fig. 4A, but for families. (B) Analogous to Fig. 4B, but for families. (C) Analogous to Fig. S2A, but for families across North America. (D) Analogous to Fig. 1B, but for families across North America. (E) Analogous to Fig. 2C, but showing the distribution of current intersample differences in relative abundances of families across northern North America. (F) Projected shifts in bacterial family relative abundances, analogous to Fig. 2C, but for families across North America. (G) Analogous to Fig. S2G, but for families across North America. (H) Analogous to Fig. 2C, but showing the distribution of predicted future intersample differences in relative abundances of families across northern North America. Download FIG S7, PDF file, 0.4 MB.

    Copyright © 2018 Ladau et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • FIG S8

    Results for soil OTUs across northern North America. (A) Analogous to Fig. S2A, but for OTUs across North America. (B) Analogous to Fig. 1B, but for OTUs in North America. (C) Analogous to Fig. 2C, but showing the distribution of current intersample differences in relative abundances of OTUs across North America. (D) Analogous to Fig. S2G, but for OTUs across North America. (E) Analogous to Fig. 2C, but showing the distribution of predicted future intersample differences in relative abundances of OTUs across North America. Download FIG S8, PDF file, 0.4 MB.

    Copyright © 2018 Ladau et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • FIG S9

    Results for diversity across northern North America. (A) Analogous to Fig. S5A, but for richness across North America. (B) Analogous to Fig. S5A, but for Shannon diversity across North America. (C) Analogous to Fig. 2B, but for richness across North America. (D) Analogous to Fig. 2B, but for Shannon diversity across North America. (E) Amount of extrapolation necessary to make geographic projections of diversity. The maps show multivariate environmental similarity surface values (MESS values), which give how far out of the observed range climate conditions are at each location. Almost all locations within North America are less than 20% out of range (greater than −20 on the map) for both current and future projections, indicating that to make geographic projections, minimal extrapolation beyond the range of the observed data is necessary. Download FIG S9, PDF file, 0.3 MB.

    Copyright © 2018 Ladau et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

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Existing Climate Change Will Lead to Pronounced Shifts in the Diversity of Soil Prokaryotes
Joshua Ladau, Yu Shi, Xin Jing, Jin-Sheng He, Litong Chen, Xiangui Lin, Noah Fierer, Jack A. Gilbert, Katherine S. Pollard, Haiyan Chu
mSystems Oct 2018, 3 (5) e00167-18; DOI: 10.1128/mSystems.00167-18

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Existing Climate Change Will Lead to Pronounced Shifts in the Diversity of Soil Prokaryotes
Joshua Ladau, Yu Shi, Xin Jing, Jin-Sheng He, Litong Chen, Xiangui Lin, Noah Fierer, Jack A. Gilbert, Katherine S. Pollard, Haiyan Chu
mSystems Oct 2018, 3 (5) e00167-18; DOI: 10.1128/mSystems.00167-18
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    • ABSTRACT
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KEYWORDS

soil bacterial diversity
niche modeling
climate change
microbial biogeography
biogeography
diversity
soil microbiology

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