Estimators of tree species richness: An assessment for Central and Eastern Canada
Journal of Sustainable Forestry, ISSN: 1054-9811, Vol: 26, Issue: 1, Page: 77-96
2008
- 5Citations
- 13Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
A total of 11 sample-based estimators of tree species richness (S) are evaluated in terms of accuracy and precision in a Monte Carlo simulated simple random sampling from 39,779 forest inventory plots with 7.8 million trees belonging to 85 species. The plots represent a 108 million hectare forested region in central and eastern Canada. Sample sizes varied from 50 to 800. A weighted index combining estimates of accuracy and precision identified Chao's first estimator (CHAO1) as overall best with an estimator based on the assumption of a gamma mixed Poisson distribution of species occurrence as a close runner-up. The observed sample species richness was almost always the most negatively biased estimate. A sample size of 400-700 conventional fixed area forest inventory plots are needed to produce results with bias <20%. © 2008 by The Haworth Press. All rights reserved.
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