The influence of sampling interval on the accuracy of trail impact assessment

Trail impact assessment and monitoring (IA&M) programs have been growing in importance and application in recreation resource management at protected areas. Census-based and sampling-based approaches have been developed in such programs, with systematic point sampling being the most common survey design. This paper examines the influence of sampling interval on the accuracy of estimates for selected trail impact problems. A complete census of four impact types on 70 trails in Great Smoky Mountains National Park was utilized as the base data set for the analyses. The census data were resampled at increasing intervals to create a series of simulated point data sets. Estimates of frequency of occurrence and lineal extent for the four impact types were compared with the census data set. The responses of accuracy loss on lineal extent estimates to increasing sampling intervals varied across different impact types, while the responses on frequency of occurrence estimates were consistent, approximating an inverse asymptotic curve. These findings suggest that systematic point sampling may be an appropriate method for estimating the lineal extent but not the frequency of trail impacts. Sample intervals of less than 100 m appear to yield an excellent level of accuracy for the four impact types evaluated. Multiple regression analysis results suggest that appropriate sampling intervals are more likely to be determined by the type of impact in question rather than the length of trail. The census-based trail survey and the resampling-simulation method developed in this study can be a valuable first step in establishing long-term trail IA&M programs, in which an optimal sampling interval range with acceptable accuracy is determined before investing efforts in data collection.