|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
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