R. Hijmans

Publications145
h-index50
Citations41,991
Highly Influential Citations4,413
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Very high resolution interpolated climate surfaces for global land areas
We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1‐km spatial resolution). The climate elements…
WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas
We created a new dataset of spatially interpolated monthly climate data for global land areas at a very high spatial resolution (approximately 1 km2). We included monthly temperature (minimum,…
Novel methods improve prediction of species' distributions from occurrence data
TLDR
This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
Computer tools for spatial analysis of plant genetic resources data: 1. DIVA-GIS
TLDR
The DIVA-GIS software allows analysis of genebank and herbarium databases to elucidate genetic, ecological and geographic patterns in the distribution of crops and wild species to improve data quality.
Effects of sample size on the performance of species distribution models
A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is…
Geographic Data Analysis and Modeling
Locating Pleistocene Refugia: Comparing Phylogeographic and Ecological Niche Model Predictions
TLDR
Comparing ENM-based reconstructions of LGM refugial locations with those resulting from the more traditional molecular genetic and phylogeographic predictions confirms that ENM scenario exploration can provide a useful complement to molecular studies, offering a less subjective, spatially explicit hypothesis of past geographic patterns of distribution.
Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null model.
  • R. Hijmans
  • Environmental Science
    Ecology
  • 1 March 2012
TLDR
P pairwise distance sampling removed spatial sorting bias, yielding null models with an AUC close to 0.5, such that AUC was the same as null model calibrated AUC (cAUC), which strongly decreased AUC values and changed the ranking among species.
The point-radius method for georeferencing locality descriptions and calculating associated uncertainty
TLDR
This work describes a method for georeferencing locality descriptions that accounts for the idiosyncrasies, sources of uncertainty, and practical maintenance requirements encountered when working with natural history collections, and allows for the use of uncertainty in analyses that use these data.
Increasing Rice Production in Sub-Saharan Africa: Challenges and Opportunities
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