AI Summary & Key Takeaways
AI InsightChao 2 generally outperforms other estimators since it attains near-asymptotic stability and, therefore, more accurate prediction of earthworm species richness.
📌 3 Key Takeaways
Abstract
The concept of species richness is currently the most basic and most often used parameter in quantitative assessments of biodiversity. The species richness of Lumbricidae was investigated in East Serbia, one of the highly complex areas in the eastern and central part of the Balkan Peninsula. Our database included 2615 individuals from a total of 54 species. Quantification of species richness was done by using the observed number of species and richness estimators. A nonparametric approach was used to evaluate the performance of various estimation techniques: Chao 2, Jackknife 2, and Bootstrap. However, only Chao 2 reached the asymptote, maintaining values of 77 until the end of the curve. A total of 70.12% of the estimated number of Lumbricidae living in East Serbia were detected in our field study and we should expect that 23 lumbricid taxa will be added to the inventory in the future. The sampling effort needed to find additional species undetected during the sampling is 214 individuals. Chao 2 generally outperforms other estimators since it attains near-asymptotic stability and, therefore, more accurate prediction of earthworm species richness.