The smooth is better than the rough : an exploitation of reporting rate information in Southern Africa bird atlas data

Doctoral Thesis


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University of Cape Town

The Southern African Bird Atlas Project (Harrison at el. 1997a, b) and the Mozambique Bird Atlas Project (Parker 1999) generated data on reporting rates for birds that takes into account the likelihood of species detection in a given area. Our main objective in this thesis is to explore methods for analysing and summarising reporting rate data. The observed reporting rate data are subject to bias due to differential sampling effort and observer errors. We use a logistic regression model suitable for binomial type data to replace the observed reporting rates with smoothed probabilities of detection. To base our prediction on data from the surrounding neighbourhood, we choose as explanatory variables the north-south and west-east coordinates relative to the target grid cell for which the prediction is being made. We explore some variants of our general smoothing approach that relates to the presentation of the smoothed distributions. The smoothed distributions of detection probabilities are presented as multicoloured maps. We consider two alternative ways of subdividing the range of detection probabilities into sub-intervals. One approach is species-specific, while the other imposes an absolute subdivision on all species distributions. For species with highly fragmented distributions, we introduce the possibility of using a weighted average between observed reporting rates and smoothed detection probabilities as the final value to be plotted. The weights are based on the extent of coverage and the underlying degree of fragmentation. The identification of patterns of distributions for species is an important part of biogeography and plays a major role in the identification of areas where conservation efforts should be targeted. Interest centres around identifying areas of species richness, centres for narrow eudemism and zones of transition in species composition. We explore the benefits of using a range of detection probabilities in comparison to the use of presence-absence data to identify areas rich in species and rich in narrow-endemic species. We transform existing measures for species richness and species endemism by replacing presence-absence data with detection probability deciles that reflect the relative likelihood of detecting a species in a given grid cell. The resulting measures give more weight to the areas where species have the core of their distributions and down-weight the peripheral edges of the species distributions, where detection probabilities may be too small to guarantee continued survival. The use of a mathematical model to generate smoothed distributions of detection probabilities enables us to calculate gradients for the detection probability surfaces for species. We can define the concept of individual species gradients that reflect the relative degree of change among detection probabilities within the overall range of occurrence for the species. We combine the gradients for all species in several different ways. Large values for the overall sums of the gradients indicate areas of large fluctuation in species composition. On the other hand, small values for the overall gradient sums indicate areas of relative stability. We also sum the gradients in one of 16 directions. These directional gradient sums distinguish between areas where the changes in species detection probability distributions occur in isolated directions, thus indicating ecological transition zones, and areas of random fluctuation, indicative of species fragmentation. In this thesis we do not derive new statistical methods. We adapt existing techniques to deal with the abundance component of the data generated by the bird atlas projects. We show how the measures based on reporting rate data, rather than presence-absence data, add substantial insight into patterns of distribution of bird species in southern Africa.

Includes bibliographical references.