Global mycorrhizal status drives leaf δ15N patterns
Data files
Feb 14, 2025 version files 188.62 MB
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Gd15N_Random_Forest.zip
188.62 MB
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README.md
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Abstract
Nitrogen (N) availability, which can be represented by the natural abundance of the stable N isotope δ15N, is crucial to understanding ecosystem-level N dynamics. Specific ecosystems are dominated by different types of mycorrhizae, which can relate to biogeochemistry and affect ecosystem functioning. However, few studies have addressed the impacts of different mycorrhizal associations on variations in foliar δ15N due to climatic and soil physicochemical factors; prior instances of foliar δ15N modeling have not included mycorrhizal types. Here, we used machine learning to produce a global map of foliar δ15N based on climatic, edaphic, vegetation, and dominant mycorrhizal factors. The predicted global average foliar δ15N value was 0.69‰. Plants in tropical areas were predicted to have significantly larger foliar δ15N values than plants from subtropical, temperate, and boreal areas. The mean annual temperature was identified as the primary driver of spatial foliar δ15N patterns. These results provide isotopic evidence of greater N limitations in temperate and boreal regions than tropical or subtropical regions. Furthermore, non-mycorrhizal plant species had the highest foliar δ15N values, followed by plants associated with arbuscular mycorrhizae, orchid mycorrhizae, ectomycorrhiza, then ericoid mycorrhizae. Overall, changes in foliar δ15N were predicted to be closely associated with the type of mycorrhizal association. This study highlights the importance of incorporating mycorrhizal data to accurately assess patterns of foliar δ15N on a global scale. Ultimately, our findings contribute to a greater understanding of N cycling dynamics across plant types and global ecosystems.
https://doi.org/10.5061/dryad.bg79cnpj9
Description of the data and file structure
Foliar δ15N values were obtained from a recent version of the global dataset described by Craine et al. (2018) that was updated with newly published data. Please see the detailed information below.
Files and variables
File: Gd15N_Random_Forest.zip
File: Relative_Importance_of_factors_in_the_9_fold_cross_validation.xlsx
Description: This file contains the relative importance of factors in the nine-fold cross-validation.
File: Relative_Importance.csv
Description: This file contains the relative importance of factors in Random forest.
File: Simulate_results
Description: Spatial distribution of the mean of foliar δ15N simulations results based on nine-fold cross validation.
File: Sites_RF.csv
Description: This file contains the foliar δ15N and 17 predictors. Accrounding to longitude and latitude,multi-year average mean annual temperature, mean annual precipitation, and potential evatransportation maps with a spatial resolution of 4 km × 4 km for 1982 through 2018 were extracted from the TerraClimate dataset (Abatzoglou et al., 2018). Aridity index values (defined as the ratio of precipitation to potential evatransportation) were calculated from mean annual precipitation and potential evatransportation values. Digital elevation model map with a spatial resolution of 1 km × 1 km was extracted from the Global Land One km Base Elevation (GLOBE) Project (https://www.ngdc.noaa.gov/mgg/topo/globe.html). A slope map was generated from the digital elevation model map. Soil clay, silt, sand, soil organic carbon, and total nitrogen contents with a spatial resolution of 250 m × 250 m were obtained from the SoilGrids dataset (Hengl et al., 2017). Multi-year (1982–2018) gross primary production values were calculated using data from the Global Land Surface Satellite (GLASS) project (Liang et al., 2021). Multi-year (1982–2015) average normalized difference vegetation index (NDVI) values were calculated from the GIMMS3g dataset (Tucker et al., 2005). The mycorrhizal plant type map (showing the distribution of arbuscular mycorrhizae, ectomycorrhizae, ericoid mycorrhizae, and non-mycorrhizaeplants) was generated from maps showing the proportional aboveground plant biomass of arbuscular mycorrhizae, ectomycorrhizae, ericoid mycorrhizae, and non-mycorrhizae plants (Soudzilovskaia et al., 2019) for Random Forest. This file is used for the Random forest in this paper.
Variables
- ObservationID: The unique sample ID assigned to each observation
- Species: The species of the plants that were sampled
- Lon: The longitude coordinates at which each individual was sampled
- Lat: The latitude coordinates at which each individual was sampled
- Leaf15N: The leaf δ15N value (‰)
- Fixer: The sampled plants are nitrogen-fixing or non-fixing plants
- AMT: The mean annual temperature at which geographic coordinates (℃)
- Apre: The mean annual precipitation at which geographic coordinates (mm)
- APET: The annual potential evapotranspiration at which geographic coordinates (mm d-1)
- AI: The ardity index at which geographic coordinates
- DEM: The digital elevation model at which geographic coordinates (m)
- Slop: The slop at which geographic coordinates (°)
- GPP: The gross primary production at which geographic coordinates (g C m-2 d-1)
- NDVI: The normolized difference vehetation index at which geographic coordinates
- Clay: The clay content of soil at which geographic coordinates (%)
- Sand: The sand content of soil at which geographic coordinates (%)
- Slit: The slit content of soil at which geographic coordinates (%)
- SOC: soil organic carbon at which geographic coordinates (g kg-1)
- TN: total nitrogen at which geographic coordinates (g kg-1)
- LeafN: The leaf nitrogen content (g kg-1)
- AM: The coverage of arbuscular mycorrhizae plants at which geographic coordinates (%)
- ECM: The coverage of ectomycorrhizae plants at which geographic coordinates (%)
- ER: The coverage of ericoid mycorrhizae plants at which geographic coordinates (%)
- NM: The coverage of non-mycorrhizae plants at which geographic coordinates (%)
- n/a: not available
Data was derived from the following sources:
- Collected from https://doi.org/10.1038/s41559-018-0694-0 and newly published papers
Foliar δ15N values were obtained from a recent version of the global dataset described by Craine et al. (2018) that was updated with newly published data for Meta-analyses. Multi-year average MAT, MAP, and PET maps with a spatial resolution of 4 km × 4 km for 1982 through 2018 were extracted from the TerraClimate dataset (Abatzoglou et al., 2018). AI values (defined as the ratio of precipitation to PET) were calculated from MAP and PET values. A digital elevation model (DEM) map with a spatial resolution of 1 km × 1 km was extracted from the Global Land One km Base Elevation (GLOBE) Project (https://www.ngdc.noaa.gov/mgg/topo/globe.html). A slope map was generated from the DEM map. Soil clay, silt, sand, soil organic carbon (SOC), and TN contents with a spatial resolution of 250 m × 250 m were obtained from the SoilGrids dataset (Hengl et al., 2017). Multi-year (1982–2018) GPP values were calculated using data from the Global Land Surface Satellite (GLASS) project (Liang et al., 2021). Multi-year (1982–2015) average normalized difference vegetation index (NDVI) values were calculated from the GIMMS3g dataset (Tucker et al., 2005). The mycorrhizal plant type map (showing the distribution of AM, ECM, ERM, and NM plants) was generated from maps showing the proportional aboveground plant biomass of AM, ECM, ERM, and NM plants (Soudzilovskaia et al., 2019) for Random Forest.