Journal
ECOLOGICAL INDICATORS
Volume 9, Issue 5, Pages 1001-1008Publisher
ELSEVIER
DOI: 10.1016/j.ecolind.2008.11.011
Keywords
Foliar cover; Precision; Species accumulation curves; Rangeland vegetation; Rank-order correlation; Species richness
Categories
Funding
- National Science Foundation [DEB 0080412]
- Natural Resources Conservation Service
- Agricultural Research Service
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Vegetation cover and composition are two indicators commonly used to monitor terrestrial ecosystems. These indicators are currently quantified with a number of different methods. The interchangeability and relative benefits of different methods have been widely discussed in the literature, but there are few published comparisons that address multiple criteria across a broad range of grass- and shrub-dominated communities, while keeping sampling effort (time) approximately constant. This study compared the utility of three field sampling methods for ecological assessment and monitoring: line-point intercept, grid-point intercept, and ocular estimates. The criteria used include: (1) interchangeability of data, (2) precision, (3) cost, and (4) value of each method based on its potential to generate multiple indicators. Foliar cover by species was measured for each method in five plant communities in the Chihuahuan Desert. Line- and grid-point intercept provide similar estimates of species richness which were lower than those based on ocular estimates. There were no differences in the precision of the number of species detected. Estimates of foliar cover with line- and grid-point intercept were similar and significantly higher than those based on ocular estimates. Precision of cover estimates with line-point intercept was higher than for ocular estimates. Time requirements for the three methods were similar, despite the fact that the point-based methods included cover estimates for all canopy layers and the soil surface, while the ocular estimates included only the top canopy layer. Results suggest that point-based methods provide interchangeable data with higher precision than ocular estimates. Moreover these methods can be used to generate a much greater number of indicators that are more directly applicable to a variety of monitoring objectives, including soil erosion and wildlife habitat. Published by Elsevier Ltd.
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