This is the data from the article

Landscape-scale range filling and dispersal limitation of woody plants (DOI: 10.1111/jbi.14485)

Matilda Arnell and Ove Eriksson

RANGE FILLING ESTIMATES

We estimated landscape-scale range filling for 64 species, each representing a different genera of woody plants, from two different dispersal systems:vertebrate dispersal and abiotic dispersal (mainly wind dispersed).

Landscape-scale range filling was estimated as the proportion realized range within the potential range, at a 1km2 resolution.

We estimated potential ranges using species distribution models (SDMs) in continuous suitability scores (Seliger et al. 2020). This method avoids loss of information by not converting the SDM outputs into presence/absence using an arbitrary threshold of suitability.

Realized ranges were estimated from presence records, restricting the estimations to areas with high sampling efforts: low ignorance areas (Ruete 2015), in order to increase the likelihood that absences represented true absences.

Regional range filling was estimated for a 5000 pixel subset of the low ignorance areas. The aditional low ignorance pixels and accompanying occurence datat was used when trining the SDMs.

Please consult to the original article as well as the R-script "range filling analyses_Arnell_Eriksson_2022.R" for details on regional range filling estimates.

LOCATION

We estimated regional range filling in the nemoral and boreo-nemoral vegetation zones in Sweden. The species distribution models providing the estimated suatability scores were trained with ocurrence data, climate and land-use data from all of Sweden.

PHYLOGENETIC REGRESSION

We thested the effect of dispersal system and habitat affinities on landscape-scale range filling using phylogenetic regressions. Phylogenetic information was obtained from Zanne et al. (2014).

Please consult the original article as well as the R-script "PGLS models_Arnell_Eriksson_2022.R" for details on regional range filling estimates.

HABITAT AFFINITIES

Plant indicator values (Tyler et al. 2021) used to assess the effect of habitat affinities:

Light indicator value

Moisture indicator value

Please contact Matilda Arnell (matilda.arnell@su.se) for information or collaboration.

Please cite also the original article when using these data (DOI: 10.1111/jbi.14485).

REFERENCES

Ruete, A. (2015). Displaying bias in sampling effort of data accessed from biodiversity databases using ignorance maps. Biodiversity Data Journal, 3, e5361. https://doi.org/10.3897/BDJ.3.e5361

Seliger, B. J., McGill, B. J., Svenning, J., & Gill, J. L. (2020). Widespread underfilling of the potential ranges of North American trees. Journal of Biogeography, 48(2), 359–371. https://doi.org/10.1111/jbi.14001

Tyler, T., Herbertsson, L., Olofsson, J., & Olsson, P. A. (2021). Ecological indicator and traits values for Swedish vascular plants. Ecological Indicators, 120, 106923. https://doi.org/10.1016/j.ecolind.2020.106923

Zanne, A. E., Tank, D. C., Cornwell, W. K. et al. (2014). Three keys to the radiation of angiosperms into freezing environments. Nature, 506(7486), 89–92. https://doi.org/10.1038/nature12872