COS 52-4 - CANCELLED - Testing a theoretical framework for the environment-species abundance paradigm: a new approach to the Abundant Centre Hypothesis

Background/Question/Methods

The linkage between environment, a species’ fitness and its abundance is central to the theory of evolution. So far, all studies investigating this linkage have been heuristic and empirical due to an inability to determine fitness experimentally (independent of abundance) or theoretically (from species-environment interaction). One category of such studies involves the Abundant Centre Hypothesis (or ACH) which posits that the abundance of a species peaks at the centre of its geographical distribution. We argue that the confusing welter of results from ACH studies arises from ignoring the central premise that species distributions cannot be studied independent of the environment. First, we employ a theoretical framework to identify an environmental context that is likely to favour ACH (a 200-2800 m elevational transect in the eastern Himalayas). We then improve upon some previously identified conceptual and methodological shortcomings of ACH studies. We test the ACH using systematically collected bird data from our transect (15867 records across 245 species).

Results/Conclusions

Overall, we find that the community average abundance profile is symmetric, and therefore consistent with ACH. Notwithstanding which, abundance profiles of individual species show a small degree of asymmetry that is correlated with elevation. This elevational dependence may be due to the hard elevational limits at the lower and upper ends of the mountain, as expected from theoretical considerations. We also show that the average shape of abundance profiles is best described as gaussian, while ruling out uniform and inverted-quadratic shapes. This work demonstrates that selecting a particular category of environmental contexts can help in integrating theoretical tools into a field dominated by empirical studies. Such a union should spur the development of more detailed and testable theoretical models for better insights in both biodiversity and macroecology.