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Large Underestimation of Intraspecific Trait Variation and Its Improvements
- Source :
- Frontiers in Plant Science, Frontiers in Plant Science, Vol 11 (2020)
- Publication Year :
- 2020
- Publisher :
- Frontiers Media S.A., 2020.
-
Abstract
- Intraspecific trait variation (ITV) is common feature of natural communities and has gained increasing attention due to its significant ecological effects on community dynamics and ecosystem functioning. However, the estimation of ITV per se has yet to receive much attention, despite the need for accurate ITV estimation for trait-based ecological inferences. It remains unclear if, and to what extent, current estimations of ITV are biased. The most common method used to quantify ITV is the coefficient of variation (CV), which is dimensionless and can therefore be compared across traits, species, and studies. Here, we asked which CV estimator and data normalization method are optimal for quantifying ITV, and further identified the minimum sample size required for ±5% accuracy assuming a completely random sample scheme. To these ends, we compared the performance of four existing CV estimators, together with new simple composite estimators, across different data normalizations, and sample sizes using both a simulated and empirical trait datasets from local to regional scales. Our results consistently showed that the most commonly used ITV estimator (CV 1= σsample /μsample ), often underestimated ITV-in some cases by nearly 50%-and that underestimation varies largely among traits and species. The extent of this bias depends on the sample size, skewness and kurtosis of the trait value distribution. The bias in ITV can be substantially reduced by using log-transforming trait data and alternative CV estimators that take into consideration the above dependencies. We find that the CV4 estimator, also known as Bao's CV estimator, combined with log data normalization, exhibits the lowest bias and can reach ±5% accuracy with sample sizes greater than 20 for almost all examined traits and species. These results demonstrated that many previous ITV measurements may be substantially underestimated and, further, that these underestimations are not equal among species and traits even using the same sample size. These problems can be largely solved by log-transforming trait data first and then using the Bao's CV to quantify ITV. Together, our findings facilitate a more accurate understanding of ITV in community structures and dynamics, and may also benefit studies in other research areas that depend on accurate estimation of CV.
- Subjects :
- 0106 biological sciences
Normalization (statistics)
bias
individual variation
Coefficient of variation
Estimator
Plant Science
lcsh:Plant culture
010603 evolutionary biology
01 natural sciences
Intraspecific competition
Database normalization
coefficient of variation
Tiantong
Sample size determination
Statistics
Kurtosis
Trait
lcsh:SB1-1110
CV estimator
trait variability
010606 plant biology & botany
Mathematics
Original Research
Subjects
Details
- Language :
- English
- ISSN :
- 1664462X
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Frontiers in Plant Science
- Accession number :
- edsair.doi.dedup.....5778ac01d85f25921949f9d588670b45