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BirdLife International's Important Bird Areas (IBA) program is the most developed global system for identifying sites of conservation priority There have been few assessments, however, of the conservation value of IBAs for nonavian taxa. We combined past data with extensive new survey results for Uganda's IBAs in the most comprehensive assessment to date of the wider biodiversity value of a tropical country's IBA network. The combined data set included more than 35,000 site x species records for birds, butterflies, and woody plants at 86 Ugandan sites (23,400 km2), including 29 of the country's 30 IBAs, with data on additional taxa for many sites. Uganda's IBAs contained at least 70% of the country's butterfly and woody plant species, 86% of its dragonflies and 97% of its birds. They also included 21 of Uganda's 22 major vegetation types. For butterflies, dragonflies, and some families of plants assessed, species of high conservation concern were w'ell represented (less so for the latter). The IBAs successfully represented wider biodiversity largely because many have distinctive avifaunas and, as shown by high cross-taxon congruence in complementarity, such sites tended to be distinctive for other groups too. Cross-taxon congruence in overall species richness was weaker and mainly associated with differences in site size. When compared with alternative sets of sites selected using complementarity-based, area-based, or random site-selection algorithms, the IBA network was efficient in terms of the number of sites required to represent species but inefficient in terms of total area. This was mainly because IBA selection considers factors other than area, however which probably improves both the cost-effectiveness of the network and the persistence of represented species.

Timed Species Counts (TSCs) have been found to provide useful data for assessing the relative abundances of birds in conservation studies, particularly in species-rich areas, such as many tropical habitats. An index is conventionally based upon the mean TSC from a number of counts. In this paper, we develop a new statistic, l, which is based upon the assumption that the number of encounters with a species in unit time has a Poisson distribution. Using the same assumptions on detectability that underlie earlier analyses of TSC data, values of l, unlike the simple mean TSC, are directly proportional to abundance. However, TSC data are a¡ected by detectability, so that comparisons of relative abundance for the same species between similar sites have greater validity than those between di¡erent species. Explicit formulae for calculating an estimate of l and its SE from sample data are described. Although l can be estimated from either TSC data or the simple proportion of counts in which the species was encountered, for the commonest species a simulation study shows that only data in full TSC form provide accurate estimates.The di¡erence becomes negligible for scarcer species. The use of l in preference to mean TSC scores is recommended where it is important to compare values of relative abundance.Re¨sumeÖ une simulation montre que seules les donne¨es de TSC comple© tes permettent des estimations correctes. La di¡e¨rence devient ne¨gligeable pour des espe© ces plus rares. On recommande l'utilisation de l de pre¨fe¨rence aux moyennes de TSC quand il est important de comparer des valeurs d'abondance relative.

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