Using a robust multi‐settings inference framework on published datasets still reveals limited support for the abundant centre hypothesis: More testing needed on other datasets

Type Article
Date 2021-11
Language English
Author(s) Chevalier MathieuORCID1, 2, Broennimann Olivier1, 3, Guisan AntoineORCID1, 3, Schrodt Franziska
Affiliation(s) 1 : Department of Ecology and Evolution ,University of Lausanne Lausanne, Switzerland
2 : IFREMER, Centre de Bretagne DYNECO Laboratoire d’Ecologie Benthique Cotière (LEBCO) Plouzané ,France
3 : Institute of Earth Surface Dynamics ,University of Lausanne Lausanne, Switzerland
Source Global Ecology And Biogeography (1466-822X) (Wiley), 2021-11 , Vol. 30 , N. 11 , P. 2211-2228
DOI 10.1111/geb.13376
WOS© Times Cited 2
Keyword(s) abundance, Bayesian inference, centroid, convex hull, distance, ellipsoids, kernel density, margins, mixed-effect models, nonlinearity


The abundant centre hypothesis (ACH) predicts a negative relationship between species abundance and the distance to the geographical range centre. Since its formulation, empirical tests of the ACH have involved different settings (e.g. the distance to the ecological niche or to the geographical range centre), but studies found contrasting support for this hypothesis. Here, we evaluate whether these discrepancies might stem from differences regarding the context in which the ACH is tested (geographical or environmental), how distances are measured, how species envelopes are delineated, how the relationship is evaluated and which data are used.


The Americas.

Time period


Major taxa studied

Mammals, birds, fish, and tree seedlings.


Using published abundance data for 801 species, together with species range maps, we tested the ACH using three distance metrics in both environmental and geographical spaces with range and niche envelopes delineated using two different algorithms, totalling 12 different settings. We then evaluated the distance–abundance relationship using correlation coefficients (traditional approach) and mixed-effect models to reduce the effect of sampling noise on parameter estimates.


Similar to previous studies, correlation coefficients indicated an absence of effect of distance on abundance for all taxonomic groups and settings. In contrast, mixed-effect models highlighted relationships of various strengths and shapes, with a tendency for more theoretically supported settings to provide stronger support for the ACH. The relationships were however not consistent across taxonomic groups and settings, and were sometimes even opposite to ACH expectations.

Main conclusions

We found mixed and inconclusive results regarding the ACH. These results corroborate recent findings, and suggest either that our ability to predict abundances from the location of populations within geographical or environmental spaces is low, or that the data used here have a poor signal-to-noise-ratio. The latter calls for further testing on other datasets using the same range of settings and methodological framework.

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How to cite 

Chevalier Mathieu, Broennimann Olivier, Guisan Antoine, Schrodt Franziska (2021). Using a robust multi‐settings inference framework on published datasets still reveals limited support for the abundant centre hypothesis: More testing needed on other datasets. Global Ecology And Biogeography, 30(11), 2211-2228. Publisher's official version : , Open Access version :