Revista Chilena de Historia Natural 84 (3): 391-406, 2011
RESEARCH ARTICLE
Relationship between the genetic structure of the Andean toad Rhinella
spinulosa (Anura: Bufonidae) and the northern Chile landscape (21°- 24° S)
We analyzed the relationship of landscape and environmental features on the
genetic differentiation of Rhinella spinulosa (Wiegmann, 1834) in the Altiplano of Antofagasta (Chile). We
performed three types of analyses at different spatial scales: (1) Considering all populations; (2) Grouping
populations by watershed and by sub-watershed; and (3) Using the results of a spatial analysis of molecular
variation (SAMOVA). Landscape features were incorporated using Geographic Information Systems, with three
hypothetical dispersal models: (1) Euclidean distance (null model); (2) Least cost based on wetland locations;
and (3) Least cost based on least slopes. We also included differences in temperature, precipitation and
altitude among localities. The Akaike information criterion was used to select the best model and the relative
importance of each variable in the model was estimated with partial regressions. We found a high genetic
differentiation among populations (F<sub>st</sub> = 0.693) and isolation by distance (r = 0.767). AMOVA
showed that the watersheds explained 8.67 % of the genetic variance and sub-watersheds 35.99 %. At the
largest spatial scale, considering all populations, the model that best explained genetic differentiation
included Euclidean distance, altitude and annual precipitation. At a smaller scale, in two of three sub
watersheds (Río San Pedro and Salar de Atacama) the genetic differentiation was best explained by landscape
variables (principally temperature and altitude). At the smallest scale, considering those populations that have
diverged recently detected by SAMOVA, the genetic differentiation was best explained by the wetland-based
route and annual precipitation. This approach revealed the importance of landscape features in the
colonization of R. spinulosa in this zone.
Key words:
altiplano,
amphibian, landscape genetics, least cost models, mtDNA
