Occupancy–abundance relationship

Although this relationship appears to be pervasive (e.g. Gaston 1996[1] and references therein), and has important implications for the conservation of endangered species, the mechanism(s) underlying it remain poorly understood.

The EOO can best be thought of as the minimum convex polygon encompassing all known normal occurrences of a particular species and is the measure of range most commonly found in field guides.

For example, in describing O–A relationships for common British birds, Quinn et al.[7] found that the occupancy at the finest resolution (10 x 10 km squares) best explained abundance patterns.

In macroecological investigations that are primarily biogeographical in nature, the variables of interest can be expected to vary most from one extent of occurrence to the opposite, and less so through discontinuities contained within the total EOO.

However, when investigating O-A relationships, the area occupied by a species is the variable of interest, and the inclusion of discontinuities within the EOO could significantly influence results.

No matter which concept we use in studies, it is essential to realize that occupancy is only a reflection of species distribution under a certain spatial scale.

[13] This prediction is readily falsified, given that exceptionally well studied taxa such as breeding birds (e.g. Zuckerberg et al. 2009, Gaston[2]) show well documented O-A relationships.

This explanation suggests that due to the underlying distribution of aggregation and density, and observed O–A relationship would be expected.

Indeed, Gaston et al.[2] suggest that "to argue that spatial aggregation explains abundance-occupancy relationships is simply to supplant one poorly understood pattern with another".

This hypothesis suggests that, as closely related species are not truly independent their inclusion into analyses artificially inflates the degrees of freedom available for testing the relationship.

However Gaston et al.[2] cite several studies documenting significant O–A relationships in spite of controlling for phylogenetic non-independence.

[22] In experimental systems using moss-dwelling microarthropods[23] showed that the fragmentation of habitat caused declines in abundance and occupancy.

By causing habitat quality to vary (increasing or decreasing birth and death rates) Holt was able to generate a positive intraspecific O–A relationship.

Holt et al.'s[25] model requires many data to test even for intraspecific relationships (i.e. vital rates of all populations through time).

Freckleton et al.[9] use a version of the model proposed by Holt et al., but with varying habitat quality between patches to evaluate parameters that could be observed in species O–A data.

Freckleton et al. show that aggregation of individuals within sites, and the skewness of population size should correlate with density and occupancy, depending on specific arrangements of habitat quality, and demonstrate that these parameters vary in accordance with positive intra- and interspecific O–A relationships for common farmland birds in Britain.

Most of the different explanations that have been forwarded to explain the regularities in species abundance and geographic distribution mentioned above similarly predict a positive distribution–abundance relationship.

Modelling this type of dynamics can simulate many of the patterns in species abundance including a positive occupancy–abundance relationship.