Campanula lingulata populations on Mt. Olympus, Greece: where's the "abundant centre"?

Background: The abundant-centre hypothesis (ACH) assumes that a species becomes more abundant at the centre of its range, where the environmental conditions are most favorable. As we move away from this centre, abundance and occupancy decline. Although this is obvious intuitively, efforts to confirm the hypothesis have often failed. We investigated the abundance patterns of Campanula lingulata across its altitudinal range on Mt. Olympus, Greece, in order to evaluate the "abundant centre" hypothesis along an elevation gradient. Furthermore, we explored the species' presence and dynamics at multiple spatial scales.

Methods: We recorded flowering individuals during the summer months of 2012 and 2013 along a series of transects defined by paths. We investigated whether the probability of acquiring a larger number of individuals is larger toward the centre of its altitudinal distribution. We also calculated mean presence and turnover at different spatial scales that ranged from quadrats of 10 × 10 m² to about 10 × 10 km².

Results: We were able to identify an abundant centre but only for one of the years of sampling. During the second year, we noted a two-peak abundance pattern; with the first peak occurring at 650-750 m and the second at 1100-1300 m. Variability in the species-presence pattern is observed across a wide range of spatial scales. The pattern along the transect displays fractal characteristics, consistent with a dimension of 0.24-0.29. We found substantial changes of state between the 2 years at all resolutions.

Conclusions: Our results do not contradict the ACH, but indicate that ecological distributions exhibit types of variability that make the detection of abundant centres more difficult than expected. When a random fractal disturbance is superimposed upon an abundant centre, we can expect a pattern in which the centre is difficult to discern from a single instance. A multi-resolution or fractal approach to environmental variability is a promising approach for describing this phenomenon.