Open AccessSquares of different sizes: effect of geographical projection on model parameter estimates in species distribution modeling
Author(s) -
Budic Lara,
Didenko Gregor,
Dormann Carsten F.
Publication year - 2016
Publication title -
ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.17
H-Index - 63
ISSN - 2045-7758
DOI - 10.1002/ece3.1838
Subject(s) - latitude , statistics , distribution (mathematics) , longitude , species distribution , land cover , skewness , weighting , spatial distribution , collinearity , mathematics , environmental science , physical geography , ecology , land use , physics , geography , geodesy , biology , mathematical analysis , habitat , acoustics
In species distribution analyses, environmental predictors and distribution data for large spatial extents are often available in long‐lat format, such as degree raster grids. Long‐lat projections suffer from unequal cell sizes, as a degree of longitude decreases in length from approximately 110 km at the equator to 0 km at the poles. Here we investigate whether long‐lat and equal‐area projections yield similar model parameter estimates, or result in a consistent bias. We analyzed the environmental effects on the distribution of 12 ungulate species with a northern distribution, as models for these species should display the strongest effect of projectional distortion. Additionally we choose four species with entirely continental distributions to investigate the effect of incomplete cell coverage at the coast. We expected that including model weights proportional to the actual cell area should compensate for the observed bias in model coefficients, and similarly that using land coverage of a cell should decrease bias in species with coastal distribution. As anticipated, model coefficients were different between long‐lat and equal‐area projections. Having progressively smaller and a higher number of cells with increasing latitude influenced the importance of parameters in models, increased the sample size for the northernmost parts of species ranges, and reduced the subcell variability of those areas. However, this bias could be largely removed by weighting long‐lat cells by the area they cover, and marginally by correcting for land coverage. Overall we found little effect of using long‐lat rather than equal‐area projections in our analysis. The fitted relationship between environmental parameters and occurrence probability differed only very little between the two projection types. We still recommend using equal‐area projections to avoid possible bias. More importantly, our results suggest that the cell area and the proportion of a cell covered by land should be used as a weight when analyzing distribution of terrestrial species.