A GIS-based modeling approach to predicting cave disturbance in karst landscapes: a case study from west-central Florida

Abstract

We present a GIS-based cave disturbance model (CDM) that can be used as a tool to predict the disturbance of cave systems. To validate our model, we compare results to an in situ cave disturbance index (CDI) that was applied to 36 terrestrial caves during the year 2007 in west-central Florida. The CDM demonstrated high-performance skill and produced similar disturbance scores compared to the CDI. The CDM disturbance scores ranged from 0.22 (minimum) to 0.78 (maximum), and the mean disturbance score for all 36 caves was 0.45. The mean of the CDI scores was 0.40, but the difference between means was not significantly different (p = 0.147, t-test). Disturbance scores from the CDM and CDI were significantly correlated (R = 0.45, R2 = 0.20; p < 0.001), but a linear model of the data only explains ca. 20% of the variance. We demonstrate that land managers, who are unable to conduct an in situ inventory of caves to determine inherent disturbance, can use the GIS-based CDM tool as a proxy. In theory, the design of the CDM makes it applicable to other areas, but more research is needed to increase model accuracy in west-central Florida, as well as in other karst regions around the world.