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Rapid sampling of plant species composition for assessing vegetation patterns in rugged terrain
Authors:Meentemeyer  Ross K  Moody  Aaron
Institution:(1) Department of Geography, University of North Carolina at Chapel Hill, NC 27599-3320, USA
Abstract:Detailed species composition data are rapidly collected using a high-powered telescope from remote vantage points at two scales: site level and patch level. Patches constitute areas of homogeneous vegetation composition. Multiple samples of species composition are randomly located within the patches. These data are used as site-level data and are also aggregated to provide species composition data at the patch level. The site- and patch-level data are spatially integrated with high resolution (10 m), topographically-derived fields of environmental conditions, such as solar radiation, air temperature, and topographic moisture index in order to evaluate the applicability of the sampling method for modeling relationships between species composition and environmental processes.The methodology provides a balance between sampling efficiency and the accuracy of field data. Application of the method is appropriate for environments where terrain and canopy characteristics permit open visibility of the landscape. We evaluate the nature of data resulting from an implementation of the remote sampling methodology in a steep watershed dominated by closed-canopy chaparral. Analyses indicate that there is minimal bias associated with scaling the data from the site level to the patch level, despite variable patch sizes. Analysis of variance and correlation tests show that the internal floristic and environmental variability of patches is low and stable across the entire sample of patches. Comparison of regression tree models of species cover at the two scales indicates that there is little scale-dependence in the ecological processes that govern patterns of species composition between the site level and patch level. High explanatory power of the regression tree models suggests that the vegetation data are characterized at an appropriate scale to model landscape-level patterns of species composition as driven by topographically-mediated processes. Patch-level sampling reduces the influence of local stochasticity and micro-scale processes. Comparison of models between the two scales can be useful for assessing the processes and associated scales of variability governing spatial patterns of plant species.
Keywords:chaparral  landscape scale  remote sensing  vegetation pattern  vegetation sampling
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