PS 59-185 - The Great Smoky Mountains All Taxa Biological Inventory: Lessons for sampling design, management, and citizen science

Wednesday, August 5, 2009
Exhibit Hall NE & SE, Albuquerque Convention Center
Sarah A. Seiter1, R. Todd Jobe2, Andrea Anton3, Emily P. Bidgood3, Ian Breckheimer4, Susan C. Caplow3, Brian Evans3, Megan Faestel3, Jeffrey D. Muehlbauer5, Kyle Palmquist6, Stephanie D. Seymour3, Samantha M. Tessel3 and Aaron Moody7, (1)Curriculum in Ecology, University of North Carolina Chapel Hill, Chapel Hill, NC, (2)Geography Department, University of North Carolina, Chapel Hill, NC, Chapel Hill, NC, (3)Curriculum In Ecology, University of North Carolina Chapel Hill, Chapel Hill, NC, (4)Department of Biology, University of Washington, Seattle, WA, (5)Curriculum for the Environment & Ecology, University of North Carolina Chapel Hill, Chapel Hill, NC, (6)Curriculum for the Environment and Ecology, University of North Carolina, Chapel Hill, NC, (7)Curriculum in Ecology, University of North Carolina, Chapel Hill, NC
Background/Question/Methods

The US National Park Service has called for the establishment of All Taxa Biodiversity Inventories (ATBIs) as part of its Centennial Challenge Initiative.  The goals of these surveys include cataloging taxa in the parks, discovering new species, and understanding ecological patterns of species distribution.  The first ATBI, conducted in the Great Smoky Mountains National Park, was successful at cataloguing taxa present and discovering new species; however, the data have not yet been used to test ecological questions.  Here, we use available ATBI data to assess ecological patterns related to congruence between different taxonomic levels, between functional groups and between rates of spatial turnover.

Results/Conclusions

Our analyses reveal significant correlations between richness at different trophic levels, between spatial turnover of different taxonomic groups, and between species richness and richness at higher taxonomic levels. In addition, we use a Maxent modeling approach to show a significant correlation between modeled and observed vegetation and arthropod richness. However, the current ATBI dataset is limited in its ability to make ecological inferences due to the non-standardized, taxonomy-oriented approach used in data collection. Our call for ecologically meaningful ATBI data was echoed during interviews we conducted with National Park representatives; interviewees unanimously cited ecological information (such as how climate change might affect species composition) as a key ATBI outcome. Thus, we also suggest pragmatic changes in data collection methods to improve the ability of future ATBIs to answer ecological questions.

Copyright © . All rights reserved.
Banner photo by Flickr user greg westfall.