Predicting species abundance by implementing the ecological niche theory

de la Fuente, Alejandro, Hirsch, Ben T., Cernusak, Lucas A., and Williams, Stephen E. (2021) Predicting species abundance by implementing the ecological niche theory. Ecography, 44 (11). pp. 1723-1730.

PDF (Published Version) - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (584kB) | Preview
View at Publisher Website:


Species are not uniformly distributed across the landscape. For every species, there should be few favoured sites where abundance is high and many other sites of lower suitability where abundance is low. Consequently, local abundance could be thought of as a natural expression of species response to local conditions. The correlation between abundance and environmental suitability has been well documented, and a recent meta-analysis has suggested that this relationship could be a generality. Despite the importance and potential implication of the abundance–suitability relationship, its predictive power for meaningful extrapolations has been surprisingly poorly explored. In this study, we showed how a highly predictable trend can be extracted from the abundance–suitability relationship, accurately predicting the variation in species abundance at a high spatial resolution. We produced high-quality environmental suitability estimations for 50 endemic species in the Australian Wet Tropics. Environmental suitability derived from species distribution models was related to observed abundance estimated using data from 29 years of uninterrupted monitoring effort. We used the fitted relationship to accurately predict abundance at a fine scale across the species range. Our results showed that the abundance–suitability relationship was strong for endemic species in the Australian Wet Tropics. The predictive power of our models was high, explaining, on average, 55% of the deviance across taxa. Despite interspecific variation in the strength of the abundance–suitability relationship associated with potential intrinsic estimation biases, our approach provides a powerful tool for predicting abundance across the species range at a fine scale. The potential for robust abundance predictions from occurrence-based species distribution models shown in this study are numerous, and it could have a significant impact in enhancing species conservation and management decisions.

Item ID: 73107
Item Type: Article (Research - C1)
ISSN: 1600-0587
Copyright Information: © 2021 The Authors. Ecography published by John Wiley & Sons Ltd on behalf of Nordic Society Oikos. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Funders: James Cook University (JCU)
Date Deposited: 30 Mar 2022 04:26
FoR Codes: 31 BIOLOGICAL SCIENCES > 3103 Ecology > 310308 Terrestrial ecology @ 100%
SEO Codes: 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280102 Expanding knowledge in the biological sciences @ 100%
Downloads: Total: 715
Last 12 Months: 100
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page