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Summary While plant δ15N values have been applied to understand nitrogen (N) dynamics, uncertainties regarding intraspecific and temporal variability currently limit their application. We used a 28 yr record of δ15N values from two Mojave Desert populations ofEncelia farinosato clarify sources of population‐level variability.We leveraged > 3500 foliar δ15N observations collected alongside structural, physiological, and climatic data to identify plant and environmental contributors to δ15N values. Additional sampling of soils, roots, stems, and leaves enabled assessment of the distribution of soil N content and δ15N, intra‐plant fractionations, and relationships between soil and plant δ15N values.We observed extensive within‐population variability in foliar δ15N values and found plant age and foliar %N to be the strongest predictors of individual δ15N values. There were consistent differences between root, stem, and leaf δ15N values (spanningc. 3‰), but plant and bulk soil δ15N values were unrelated.Plant‐level variables played a strong role in influencing foliar δ15N values, and interannual relationships between climate and δ15N values were counter to previously recognized spatial patterns. This long‐term record provides insights regarding the interpretation of δ15N values that were not available from previous large‐scale syntheses, broadly enabling more effective application of foliar δ15N values.
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Assessing the utility of SoilGrids250 for biogeographic inference of plant populations
Abstract Inclusion of edaphic conditions in biogeographical studies typically provides a better fit and deeper understanding of plant distributions. Increased reliance on soil data calls for easily accessible data layers providing continuous soil predictions worldwide. Although SoilGrids provides a potentially useful source of predicted soil data for biogeographic applications, its accuracy for estimating the soil characteristics experienced by individuals in small‐scale populations is unclear. We used a biogeographic sampling approach to obtain soil samples from 212 sites across the midwestern and eastern United States, sampling only at sites where there was a population of one of the 22 species inLobeliasect.Lobelia. We analyzed six physical and chemical characteristics in our samples and compared them with predicted values from SoilGrids. Across all sites and species, soil texture variables (clay, silt, sand) were better predicted by SoilGrids (R2: .25–.46) than were soil chemistry variables (carbon and nitrogen,R2 ≤ .01; pH,R2: .19). While SoilGrids predictions rarely matched actual field values for any variable, we were able to recover qualitative patterns relating species means and population‐level plant characteristics to soil texture and pH. Rank order of species mean values from SoilGrids and direct measures were much more consistent for soil texture (SpearmanrS = .74–.84; allp < .0001) and pH (rS = .61,p = .002) than for carbon and nitrogen (p > .35). Within the speciesL. siphilitica, a significant association, known from field measurements, between soil texture and population sex ratios could be detected using SoilGrids data, but only with large numbers of sites. Our results suggest that modeled soil texture values can be used with caution in biogeographic applications, such as species distribution modeling, but that soil carbon and nitrogen contents are currently unreliable, at least in the region studied here.
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- PAR ID:
- 10495120
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Ecology and Evolution
- Volume:
- 14
- Issue:
- 3
- ISSN:
- 2045-7758
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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