Abstract
Aims: Large vegetation plot databases enable the estimation of niche width from species co-occurrence data. Different indices have been proposed for this purpose, but do not give unbiased (i.e. independent of species pool size) and robust estimates over a wide range of conditions. The aims of the paper are to: (1) demonstrate the limitations of different methods, and (2) propose a new algorithm that results in unbiased and robust estimates.
Results: Whittaker's β-diversity, calculated from raw data, is an unbiased niche width measure only if the relationship between γ-diversity and local richness is linear. However, this requirement is satisfied only in specific conditions, if both γ-diversity and local richness are linear functions of the species pool size with zero intercept. I propose the use of Beals smoothing to estimate species pools. It has been proved through analysis of simulated data that Whittaker's β calculated from species pool data is an unbiased estimate of niche width. I have shown that the robustness of the estimate can be improved by excluding extremely species-rich plots. The relative role of methodological decisions during niche width estimation was explored through analysis of a large field data set (>8000 relevés).
Conclusions: The proposed algorithm results in robust, unbiased estimation, even in saturated communities, thus it avoids the drawbacks of the co-occurrence-based niche width measures proposed earlier.
Results: Whittaker's β-diversity, calculated from raw data, is an unbiased niche width measure only if the relationship between γ-diversity and local richness is linear. However, this requirement is satisfied only in specific conditions, if both γ-diversity and local richness are linear functions of the species pool size with zero intercept. I propose the use of Beals smoothing to estimate species pools. It has been proved through analysis of simulated data that Whittaker's β calculated from species pool data is an unbiased estimate of niche width. I have shown that the robustness of the estimate can be improved by excluding extremely species-rich plots. The relative role of methodological decisions during niche width estimation was explored through analysis of a large field data set (>8000 relevés).
Conclusions: The proposed algorithm results in robust, unbiased estimation, even in saturated communities, thus it avoids the drawbacks of the co-occurrence-based niche width measures proposed earlier.
Keywords
Generalists, Niche width, Saturation, Simulation, Specialists, Species pool, Whittaker's β, β-diversity
Nincsenek megjegyzések:
Megjegyzés küldése