Bias in Estimating Niche Overlap

Abstract

Bias refers to the accuracy of a particular estimator. We evaluate bias, using analytic and simulation technics, for six measures of overlap: the likelihood ratio measure, the chi—square measure, the measure based on the Freeman—Tukey statistic, Morisita's adjusted index, Morista's original index, and Horn's information index. We present an exact formula for a seventh, the percentage similarity measure. We consider bias due to resource a sample size, total number of different resources, and evenness of resource distribution. Results indicate that of the seven measures, changes in evenness of resource of distribution produce significant bias only in the percentage similarity measure and Morista's adjusted index. All measures show increasing bias with increasing number of resources. For estimating unbiased overlap, Morisita's original measure of overlap gives the most accurate results, especially when using small sample sizes. The percentage similarity measure, one of the most commonly used measures among ecologists, is also one of the most biased and for this reason is not preferred.

Solapamiento trofico entre el lobo marino de un pelo Otaria flavescens y la pesqueria de arrastre demersal del golfo San Matias, Patagonia, Argentina

“…Estos índices fueron elegidos porque tienen propiedades estadísticas que permiten poner a prueba la hipótesis nula de un solapamiento total (Petraitis 1979(Petraitis , 1985Ludwig & Reynolds, 1988). Por otro lado, el GO es uno de los índices que presenta la menor cantidad de sesgos, ya sea debido a la variabilidad en la equitabilidad de los recursos o a variaciones en el tamaño muestral (Smith & Zaret, 1982). El GO es un índice simétrico (GO BA = GO AB ) que representa la probabilidad de que la curva de utilización de cada predador provenga de la curva de utilización común a todos ellos.…”

Feeding strategy of Menticirrhus americanus and Menticirrhus littoralis (Perciformes: Sciaenidae) juveniles in a sandy beach surf zone of southern Brazil

“…Until not long ago, little attention was given to the statistical properties of trophic overlap measurements, and overlap indexes were calculated without statistical significance (PETRAITIS 1979, RICKLEFS & LAU 1980, MAURER 1982, SMITH & ZARET 1982, MUELLER & ALTENBERG 1985. DIXON (2001) commented that it is easy to calculate such indexes but difficult to estimate their precision.…”

Trophic interactions among sympatric zooplanktivorous fish species in volume change conditions in a large, shallow, tropical lake

“…Incorporating sources of variance to compare diet overlap allowed the significance of the calculated niche overlap indices to be calculated (Lecomte & Dodson, 2005). To add statistical validity to the niche overlap, different authors have used a bootstrap approach to estimate confidence intervals around the mean overlap values or conducted simulations to estimate error (Smith & Zaret, 1982;Mueller & Altenberg, 1985). In the present case, the use of 0.6 as the threshold separating similar from dissimilar diets could be inappropriate as the species have closely related diets.…”

“…Schoener's D index (Schoener, 1968) was selected because it is commonly used and its simplicity facilitates the interpretation of values obtained (Lecomte & Dodson, 2005). In accordance with previous studies, a value of 0.6 was used as a threshold to delineate similar (> 0.6) from distinct feeding niches (< 0.6; Smith & Zaret, 1982). The Hurlbert index was also used to estimate overlap according to the way the species utilized each resource state in proportion to resource state abundance (Krebs, 1999).…”