Abstract
A species distribution model (SDM) was developed for the endangered Smith's Blue butterfly, Euphilotes enoptes smithi (Lycaenidae), to predict target areas where it might be found in the rugged Santa Lucia Mountains that extend for 230 km along the Big Sur coast in Monterey County, CA. Field surveys identified 1,506 locations of the butterfly's larval foodplant and primary adult nectar plant, Eriogonum parvifolium (Polygonaceae), in this mountain range. Vegetation, soil, and geology types were identified for each of these known locations. Because all life stages of the endangered butterfly are closely associated with this foodplant, it served as a surrogate to identify new locations that might support the butterfly. Binary logistic regression analysis was used to evaluate the relationships between foodplant occurrence and each of these environmental attributes. Logistic regression identified specific soil and geology types that were useful predictors of potential foodplant occurrence, but it was unable to identify comparable specific vegetation types. GIS analyses were performed to identify target areas that share the same combinations of these environmental attributes in locations known to support the foodplant. The top target areas were all characterized by soil and geology types that the logistic regression analyses corroborated were the best predictors of potential foodplant occurrence. To validate our SDM, field surveys for the foodplant and butterfly were performed at 300 predicted target locations. The foodplant and butterfly were observed at 88.4% and 80.7% of target areas or immediately adjacent to them, respectively. Results of this SDM not only provide a better understanding of this endangered butterfly's potential and actual geographic range but also the environmental attributes that constitute its suitable habitat. Furthermore, these findings will assist resource agencies in their conservation efforts to benefit this endangered butterfly.
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