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Summary A geographic information system (GIS) was used to analyse field data on the abundance of elephant dung‐piles. For each country, the GIS was used to create contours representing distances from roads or rivers. The area of forest between each contour was then calculated. The curvilinear relationships between dung‐pile density and distance to the nearest road or village were then used to calculate the numbers of dung‐piles between contours and the total for each country. Comparisons between undisturbed and heavily poached elephant populations suggest that the total forest elephant population in central Africa has been reduced by about 44% as a result of ivory poaching. Forest elephants may be more vulnerable to poaching than previously thought because, for example, two‐thirds of Congo's elephants live within two days' walk of a road or navigable river. Résumé On a employé un systéme d'information géographique (en anglais GIS) pour analyser les données sur la présence des excréments d'éléphants. Pour chaque pays, le GIS a servi à créer des tracés représentant les distances par rapport aux routes et aux riviéres. On calculait alors la zone forestiére comprise entre chaque tracé. Les relations curvilinéaires entre la densité des excréments et la distance par rapport à la route ou au village les plus proches étaient alors employées pour calculerle nombre d'excréments entre les tracés, et le total pour chaque pays. La comparaison entre les populations d'eléphants non dérangées et celles qui sont lourdement braconnées laisse penser que la population totale d'éléphants de forêt en Afrique centrale a été réduite de prés de 44%à cause du braconnage pour l'ivoire. Les éléphants de forêt sont plus vulnérables qu'on ne le pensait avant au braconnage parce que, au Congo par exemple, 2/3 des éléphants vivent à moins de deux jours de marche d'une route ou d'une riviére navigable.

This paper presents a method for estimating monkey numbers in a large area of forest where there is a gradient of monkey densities. The method is illustrated using data collected in the northeastern forests of Gabon during an earlier project. These forests are sparsely populated and there are few roads. The density of Cercopithecus nictitans increases with distance from the nearest road. A geographic information system (GIS) divided the forest into bands of increasing distance from the nearest road. The number of monkeys in each band is the product of the monkey density in that band and the area of the band. Summing across bands gives the population estimate; the standard error can be estimated by bootstrapping. The optimum sample size can be estimated by simulation. Combining estimates of the density gradient with a GIS is a cost-effective method of censusing primates in extensive forests.

Understanding species’ elevational distributions in mountain ecosystems is needed under climate change, but remote biodiverse mountain areas may be poorly documented. National Forest Inventories (NFIs) offer a potential source of data. We used NFI records from Bhutan to ask three questions about elevational richness patterns of Himalayan woody plant species. First, does the mean elevation for all species differ from those species whose entire elevational distribution is recorded in the survey? Second, how does the elevation of maximum richness differ when combining species originating from temperate and tropical regions vs. analyzing them separately? And third, do the highest species turnover rates adjoin elevation zones of maximum species richness? We used 32,198 species records from 1685 forest plots along a 7570 m gradient to map species elevation ranges. Species whose entire range was documented were those whose lowest records are located above 400 m, while bare rock defined all species’ upper limits. We calculated species richness and turnover using 400 m elevation bands. Of 569 species, 79% of temperate and 61% of tropical species’ elevation ranges were fully sampled within the NFI data. Mean elevation of tree and shrub species differed significantly for temperate and tropical species. Maximum combined species richness is from 1300 to 1700 m (277 species), differing significantly from maximum tropical (900–1300 m, 169) and temperate species richness (2500–2900 m, 92). Temperate tree turnover rate was highest in the bands adjoining its maximum species richness (2500–2900 m). But turnover for tropical trees was highest several bands above their maximum species richness, where turnover and decrease in richness interact. Shrub species turnover patterns are similar, but rates were generally higher than for trees. Bhutan’s NFI records show that woody plant species are arrayed on the Himalaya in part according to floristic origins, and that combining temperate- and tropical-originating floras for gradient-based studies such as species richness and turnover obscures actual elevational patterns. In addition, species whose ranges extend below the Himalayan elevation gradient should be accounted for in future studies that correlate climate and environment factors with elevational species richness patterns.