Capturing the spatial distribution of organisms at the correct scale is a fundamental aspect of ecology. Given that ecosystem engineers largely and consistently alter landscape structure, quantifying the spatial patterning of engineered habitats is of heightened interest. Potential for spatial pattern recognition has increased in the past fifteen years due in part to access to free and open remote sensed imagery. For some ecosystem engineers, including termites, ants and kangaroo rats, technological advancement in landscape visualization is supporting progress in the understanding of spatial-temporal patterns. Here we describe spatial patterns of prairie dog colonies for understanding the consequences of ecological engineering. We used remote imagery from 1999 through 2019 to characterize the spatial structure of eight prairie dog colonies in Boulder County. Ripley’s K and pair correlation function were employed for point-pattern analysis. We used Voronoi tessellation to estimate the network connectivity of each burrow and mixed effect models to predict colony density as a function of colony size and site.
Results/Conclusions
In preliminary results, burrow spacing was random at small scales (0-30 m) and aggregated at large scales (30-500 m). Within and among site effects of the mixed model suggest that clustering and infilling take place to benefit cooperative behavior until the density capacity is reached and growth takes place by edge expansion, changing total colony size. Interestingly, in this 20-year time series analysis, despite large differences in colony size, burrow density and scaling coefficient is conserved. Improved understanding of the spatial-temporal structure of prairie dog towns can be critical for conservation. Furthermore, it should advise mitigation actions for potential areas of human-prairie dog conflict and benefit human engineers in their own community development.