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Aim To document the species richness patterns of breeding birds along elevational gradients and explore its drivers in the Horn of Africa region. Location Horn of Africa region. Taxon Breeding birds. Methods Distributional data for breeding birds were collected. Elevational distribution data were extracted, interpolated, and assembled for all birds, passerines, and nonpasserines. In order to tease apart how different environmental factors contributed to the variation in species richness, we found it is necessary to divide the area into four subregions with different climatic regimes and topographic structure, namely western slope, eastern slope, wet side, and dry side. Then, the species richness in each 100-m elevational band was counted along the elevational gradients of each subregion. Pearson's correlation analyses and ordinary least squares (OLS) regressions were used to examine the relationships between species richness and factors. Results The variation in species richness followed hump-shaped patterns for all subregions, although with peak values at different elevations. The bird species groups on the western and eastern slopes showed low and high plateaus with mid-elevation peaks, respectively, but very low species diversities at the highest elevations. Species richness was significantly correlated with temperature range and productivity in each subregion. The temperature range, area, and productivity explained 82% of the species richness variations for all birds on the western slope. Main conclusions The separate analyses of four area subdivisions provide strong indications of how various factors interact. Productivity and temperature range were the major driving factors for shaping the richness patterns, but deviations from expected patterns suggest modifying roles of mist formation zones in the valleys that deeply intersect the large highlands in the west and rich riparian vegetation where water from cool and humid environments at high elevation reaches lower elevations in the arid east. Conservation is recommended in each subregion based on the elevational richness scenarios.