PARENT SESSION
Oral Session 16: Statistics and Biometrics.
Presiding: E Garton and T Simons
Monday, August 2, 8:00 AM to 11:30 AM, Meeting Room D 139.

Developing a sampling protocol for long-term vegetation monitoring: Maximizing environmental representation, minimizing sampling effort.

Jobe, R.^*,1, McKnight, Meghan^*,1, ¹ Ecology Curriculum, Chapel Hill, NC, 27599-3275

ABSTRACT- The development of sampling protocols which maximize environmental representation and statistical power while minimizing sampling effort is vital to ecological assessment and long-term ecological monitoring. In addition, sample protocols that provide adequate representation for both long-term monitoring goals, and for case studies involving single species are vital in an era of data-mining and cross-study analyses. With these goals in mind, we developed a protocol to select permanent vegetation sample plots for the Great Smoky Mountains National Park using data derived from digital elevation models (DEMs). We followed a stratified clustered design. The clustered design (plots/cluster = 3, maximum cluster extent = 1km) allowed us to control for spatial autocorrelation and will permit analyses at both small and large extents. To maximize environmental representation, plots were stratified using 'ecological zipcodes' developed by Urban, Kintsch, and White. These 'ecological zipcodes' categorize the environment along 3 factors, all of which can be derived from DEMs: elevation (5 levels), hillshade (3 levels), and topographic convergence index (3 levels). To minimize the effort required to collect data from these plots, we constrained potential plot locations using a model of human accessibility, which is also derived from DEMs. We analyzed the overall representation of ecological zipcodes achieved using our protocol, and compared the results to the frequency of different environments throughout the park. Additionally, we analyzed the representation of our samples for a single, conservationally important species: Canada Hemlock (Tsuga candaensis). We hope this protocol will serve as a consistent, powerful, and cost-effective model for future ecological assessment and long-term monitoring projects.

Key words: environmental hetereogeneity, ecological assessment, sampling design, long-term monitoring