Robert Bradford, Utah Valley University
Most organisms exhibit latitudinal gradients in diversity (i.e., taxonomic richness decreases as latitude increases). Few studies have sought latitudinal gradients in lichens, especially in the midlatitudes. Our primary questions were: 1) do lichens along the west coast of the United States show latitudinal gradients? 2) If so, what is the rate of change and does the level of taxonomic richness affect this rate? We hypothesized that lichens would show a reverse latitudinal gradient in the region, as has been documented for lichens elsewhere in the northern hemisphere, but at a considerably smaller scale. This study fills in the gap in our understanding of lichen latitudinal gradients over large areas of North America. It also functions as a baseline for future climate change and conservation efforts. Our study area is bound at the south by the California-Mexico border (32.331° N) and at the north by the Washington-Canada border (47.178° N), and extends inland from the coastline to the crest of the Sierra Nevada Mountains (116.083° W, at its eastern -most point). We divided the region into 218 roughly equal-area (cite) grid cells using GIS, each bordered with latitudinal and longitudinal lines. We derived a list of all vouchered lichen specimens in each grid cell using Consortium of North American Lichen Herbaria, an online database. The data were synonymized, and species, generic, and familial richness were calculated for each grid cell. We found no correlation (R2 = 0.2306) between latitude and species richness, using the raw vouchered data. What we did find was a strong correlation (R2=0.9069) between sample density and species richness. These results are biased by sample density and do not reflect what is naturally occurring. We hypothesize that we can get an unbiased estimate of richness with MaxEnt models. Using the georeferenced lichen distributions and related climate data, we constructed species distribution models of all species with five or more occurrences (990 species). In GIS, we projected all 990 distribution models and our 218 grid cells together to calculate species richness for each cell at various thresholds (i.e. likelihood of occurrence at 10%, 20%, 30%, etc.).