TY - JOUR
T1 - A comparison of sampling designs for monitoring recreational trail impacts in rocky mountain national park
AU - Pettebone, David
AU - Newman, Peter
AU - Theobald, David
PY - 2009/3/1
Y1 - 2009/3/1
N2 - The dual goals of the Organic Act of 1916 and Wilderness Act of 1964 are to protect natural resources and provide quality visitor experiences. Park managers need metrics of trail conditions to protect park resources and quality of visitor experiences. A few methods of sampling design for trails have been developed. Here, we describe a relatively new method, spatially balanced sampling, and compare it to systematic sampling. We evaluated the efficiency of sampling designs to measure recreation-related impacts in Rocky Mountain National Park. This study addressed two objectives: first, it compared estimates of trail conditions from data collected from systematic versus spatially balanced sampling data; second, it examined the relationship between sampling precision and sampling efficiency. No statistically significant differences in trail condition were found between the 100-m interval and the spatially balanced datasets. The spatially balanced probability-based dataset was found to be a good estimate of trail conditions when analyses were conducted with fewer sample points. Moreover, spatially balanced probability-based sampling is flexible and allows additional sample points to be added to a sample.
AB - The dual goals of the Organic Act of 1916 and Wilderness Act of 1964 are to protect natural resources and provide quality visitor experiences. Park managers need metrics of trail conditions to protect park resources and quality of visitor experiences. A few methods of sampling design for trails have been developed. Here, we describe a relatively new method, spatially balanced sampling, and compare it to systematic sampling. We evaluated the efficiency of sampling designs to measure recreation-related impacts in Rocky Mountain National Park. This study addressed two objectives: first, it compared estimates of trail conditions from data collected from systematic versus spatially balanced sampling data; second, it examined the relationship between sampling precision and sampling efficiency. No statistically significant differences in trail condition were found between the 100-m interval and the spatially balanced datasets. The spatially balanced probability-based dataset was found to be a good estimate of trail conditions when analyses were conducted with fewer sample points. Moreover, spatially balanced probability-based sampling is flexible and allows additional sample points to be added to a sample.
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U2 - 10.1007/s00267-008-9261-9
DO - 10.1007/s00267-008-9261-9
M3 - Article
C2 - 19184575
AN - SCOPUS:64549105253
SN - 0364-152X
VL - 43
SP - 523
EP - 532
JO - Environmental Management
JF - Environmental Management
IS - 3
ER -