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Predicting abundance from occupancy: a test for an aggregated insect assemblage
Article first published online: 9 MAY 2003
DOI: 10.1046/j.1365-2656.2003.00716.x
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How to Cite
Warren, M., Mcgeoch, M. A. and Chown, S. L. (2003), Predicting abundance from occupancy: a test for an aggregated insect assemblage. Journal of Animal Ecology, 72: 468–477. doi: 10.1046/j.1365-2656.2003.00716.x
Publication History
- Issue published online: 9 MAY 2003
- Article first published online: 9 MAY 2003
- Received 9 August 2002; accepted 5 February 2003
- Abstract
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Keywords:
- abundance–occupancy relationship;
- aggregation;
- Drosophilidae;
- negative binomial distribution;
- spatial heterogeneity
Summary
- 1The ubiquitous, positive abundance-occupancy relationship is of potential value to conservation and pest management because of the possibility of using it to predict species abundance from occupancy measures.
- 2He & Gaston (2000a) developed a model, and a parameterization method, for the prediction of abundance from occupancy based on the negative binomial distribution. There are to date few empirical tests of either the estimation method or model. Here we conduct such a test in a field-based mesocosm experiment using a Drosophilidae assemblage associated with decaying fruit.
- 3With individual (and groups of) fruit as minimum mapping units, abundance estimates derived using the parameterization method of the He-Gaston model differed significantly from measured values, and were least accurate for the most abundant species.
- 4Substitution of k-values corrected for species density in the model did not improve abundance predictions significantly. However, substitution of k-values calculated directly from the negative binomial distribution yielded highly accurate abundance predictions.
- 5Although the distribution of fly species did not deviate significantly from the negative binomial distribution, and the finest possible minimum mapping units were used (individual fruit), the parameterization method in the He-Gaston model consistently underestimated the abundance of species in the assemblage because individuals were very highly aggregated within fruit.
- 6Because of its potential importance, this model and parameterization method require further exploration at fine scales, commonly represented by individual habitat units, for highly aggregated species. The incorporation of spatially explicit information may provide a means of improving abundance predictions in this regard.