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Climate biogeography of Arabidopsis thaliana: Linking distribution models and individual variation

Cite this dataset

Lasky, Jesse et al. (2024). Climate biogeography of Arabidopsis thaliana: Linking distribution models and individual variation [Dataset]. Dryad. https://doi.org/10.5061/dryad.zkh1893hr

Abstract

Patterns of individual variation are key to testing hypotheses about the mechanisms underlying biogeographic patterns. If species distributions are determined by environmental constraints, then populations near range margins may have reduced performance and be adapted to harsher environments. Model organisms are potentially important systems for biogeographical studies, given the available range‐wide natural history collections, and the importance of providing biogeographical context to their genetic and phenotypic diversity. We fit occurrence records to climate data and then projected the distribution of Arabidopsis under the last glacial maximum, current, and future climates. We confronted model predictions with individual performance measured on 2194 herbarium specimens, and we asked whether predicted suitability was associated with life history and genomic variation measured on ~900 natural accessions. The most important climate variables constraining the Arabidopsis distribution were winter cold in northern and high-elevation regions and summer heat in southern regions. Herbarium specimens from regions with lower habitat suitability in both northern and southern regions were smaller, supporting the hypothesis that the distribution of Arabidopsis is constrained by climate‐associated factors. Climate anomalies partly explained interannual variation in herbarium specimen size, but these did not closely correspond to local limiting factors identified in the distribution model. Late‐flowering genotypes were absent from the lowest suitability regions, suggesting slower life histories are only viable closer to the centre of the realized niche. We identified glacial refugia farther north than previously recognized, as well as refugia concordant with previous population genetic findings. Lower latitude populations, known to be genetically distinct, are most threatened by future climate change. The recently colonized range of Arabidopsis was well‐predicted by our native‐range model applied to certain regions but not others, suggesting it has colonized novel climates. Integration of distribution models with performance data from vast natural history collections is a route forward for testing biogeographical hypotheses about species distributions and their relationship with evolutionary fitness across large scales.

README: Climate biogeography of Arabidopsis thaliana: Linking distribution models and individual variation

https://doi.org/10.5061/dryad.zkh1893hr

MaxEnt model projections, occurrence data, and herbarium specimen data from this article are included here.

Description of the data and file structure

MaxEnt model projections come as rasters. Occurrence data and herbarium specimen data are in Excel and tab-delimited tables.

HerbariumDataPublic_JBIpaper_20Mar2024.xlsx

This file contains measurements of herbarium specimens used in the paper. The units for latitude and longitude are degrees. The units for inflorescence height, maximum rosette leaf length, and maximum rosette diameter are in centimeters. The ratio of maximum rosette leaf length to inflorescence height and habitat suitability are unitless.

OccurrenceDataUsedToFitModels_JBI_20March2024.txt

This file contains the latitude and longitudes of occurrences used to fit the models in the paper. The units are degrees.

At_pred_50kmbuffer_28Feb2023.grd and At_pred_50kmbuffer_28Feb2023.gri

This is the MaxEnt model prediction for current conditions.

futenvMean_4.5_500kmbuffer_28Feb2023.grd and futenvMean_4.5_500kmbuffer_28Feb2023.gri

This is the predicted future suitability averaged over the multiple climate models described in the paper, under the RCP 4.5 emissions scenario.

futenvSD_4.5_500kmbuffer_28Feb2023.grd and futenvSD_4.5_500kmbuffer_28Feb2023.gri

This is the standard deviation of future suitabilities among the multiple climate models described in the paper, under the RCP 4.5 emissions scenario.

At_limMap_50kmbuffer_28Feb2023.gri and At_limMap_50kmbuffer_28Feb2023.grd

This is the limiting factor map.

At_pred_lgm_500kmbuffer_28Feb2023.grd and At_pred_lgm_500kmbuffer_28Feb2023.gri

This is the predicted suitability at the Last Glacial Maximum.

futenvMean_6.0_500kmbuffer_28Feb2023.grd and futenvMean_6.0_500kmbuffer_28Feb2023.gri

This is the predicted future suitability averaged over the multiple climate models described in the paper, under the RCP 6.0 emissions scenario.

futenvSD_60_500kmbuffer_28Feb2023.gri and futenvSD_60_500kmbuffer_28Feb2023.grd

This is the standard deviation of future suitabilities among the multiple climate models described in the paper, under the RCP 6.0 emissions scenario.

Funding

National Institutes of Health, Award: R35GM138300

National Institutes of Health, Award: R35GM138300