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Research Article Open access CC BY 4.0

Theoretical Derivation of a Bias-reduced Expression for the Extrapolation of the Species Accumulation Curve and the Associated Estimation of Total Species Richness

Jean Béguinot

Advances in Research · pp. 1–16 · Published 2 Jun 2016

10.9734/AIR/2016/26387

Abstract

Under-sampling becomes the current situation for an increasing part of biodiversity surveys, as more and more speciose assemblages and increasingly complex taxonomic groups are progressively addressed. Accordingly, (i) extrapolating the Species Accumulation Curve and (ii) estimating the total species richness of partially-sampled species assemblages (or taxonomic-groups) both become major issues for many naturalists nowadays. Numerous different solutions have been proposed to address these issues. Yet, no general consensus has been reached regarding which particular solution among them should be preferred according to each case. This unsatisfactory situation follows from the empirical nature of traditional approaches, especially regarding the extrapolation of the Species Accumulation Curve. Fortunately, reconsidering the problem on decidedly more theoretical basis, including the consideration of general mathematical relationships universally constraining the expression of any theoretical (or rarefied) Species Accumulation Curves, allows a more relevant modeling for the extrapolation of species accumulation. In turn, this theoretical approach provides a rational key to select the more appropriate, less biased type of species-richness estimator and the associated, less biased expression for the extrapolation of the Species Accumulation Curve, according to the context of sampling. In particular, the wide relevance of the series of ‘Jackknife-type’ estimators is highlighted (as had been already argued for specific cases, on semi-empirical basis). In practice, selecting the less biased extrapolation of the Species Accumulation Curve allows to forecast the supplementary sampling effort necessary to reach a given increase of sampling completeness more accurately than the usual procedures, involving arbitrarily chosen empirical models.

Extrapolation species accumulation curve estimator Chao Jackknife minimum bias mathematical constraint under sampling incomplete sample

References (23)

  1. 1 Estimating terrestrial biodiversity through extrapolation [DOI]
  2. 2 The Use of Species Accumulation Functions for the Prediction of Species Richness [DOI]
  3. 3 Evaluating the performance of species richness estimators: sensitivity to sample grain size [DOI]
  4. 4 ESTIMATING SPECIES RICHNESS: SENSITIVITY TO SAMPLE COVERAGE AND INSENSITIVITY TO SPATIAL PATTERNS [DOI]
  5. 5 Comparative performance of species richness estimation methods [DOI]
  6. 6 An improved nonparametric lower bound of species richness via a modified good–turing frequency formula [DOI]
  7. 7 BIAS, PRECISION, AND ACCURACY OF FOUR MEASURES OF SPECIES RICHNESS [DOI]
  8. 8 Comparison of Three Estimators of Species Richness in Parasite Component Communities [DOI]
  9. 9 Performance of nonparametric species richness estimators in a high diversity plant community [DOI]
  10. 10 Assessing biodiversity with species accumulation curves; inventories of small reptiles by pit‐trapping in Western Australia [DOI]
  11. 11 ESTIMATING SPECIES RICHNESS OF TROPICAL BIRD COMMUNITIES FROM RAPID ASSESSMENT DATA [DOI]
  12. 12 Estimating marine species richness: an evaluation of six extrapolative techniques [DOI]
  13. 13 On the estimation of species richness based on the accumulation of previously unrecorded species [DOI]
  14. 14 Application of species richness estimators for the assessment of fungal diversity [DOI]
  15. 15 Choosing the best non-parametric richness estimator for benthic macroinvertebrates databases
  16. 16 Performance of species richness estimators across assemblage types and survey parameters [DOI]
  17. 17 Estimating Species Richness of Tropical Bird Communities From Rapid Assessment Data [DOI]
  18. 18 Basic Theoretical Arguments Advocating Jackknife-2 as Usually being the Most Appropriate Nonparametric Estimator of Total Species Richness [DOI]
  19. 19 Assessment of richness estimation methods on macroinvertebrate communities of mountain ponds in Castilla y León (Spain) [DOI]
  20. 20 Bias, Precision, and Accuracy of Four Measures of Species Richness [DOI]
  21. 21 Estimating the snake species richness of the Santubong Peninsula (Borneo) in two different ways [DOI]
  22. 22 Extrapolation of the Species Accumulation Curve for Incomplete Species Samplings: A New Nonparametric Approach to Estimate the Degree of Sample Completeness and Decide when to Stop Sampling [DOI]
  23. 23 Measuring and Estimating Species Richness, Species Diversity, and Biotic Similarity from Sampling Data [DOI]

Cited by 41

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