INTRODUCTION
Population differentiation and speciation is a complex process that
depends on species-specific factors as well as extrinsic landscape
processes. An ongoing question in evolutionary biology is whether taxa
differentiate in communities in response to extrinsic forces—for
example, geographic or climatic change—or in species-specific manners
based on their intrinsic characteristics such as physiological thermal
tolerance or dispersal ability. In speciation scenarios dominated by
geologic or climatic change, entire communities may differentiate in
pulses synchronous with the changes in the Earth’s template (e.g.,
Barber & Klicka, 2010; Musher et al., 2019; O’Connell et al., 2018). In
contrast, when communities have species that vary in dispersal ability,
niche breadth, or population history, diversification may be
asynchronous across taxa based on those species’ intrinsic
characteristics (e.g., Naka & Brumfield, 2018; Oswald et al., 2017;
Papadopoulou et al., 2009).
In well-studied geographic regions, it has become clear that with
increasing taxonomic scope, a combination of both synchronous and
asynchronous diversification arises that depends on the taxonomic and
temporal breadth of study (Shafer et al., 2010; Smith et al., 2014).
These results demonstrate the need for sampling multiple taxonomic
groups, with a range of intrinsic characteristics and histories, to best
understand the drivers of diversification in different geographic
contexts. This work is arguably most needed in biodiversity hotspots,
the regions of the world that are richest in diversity while
simultaneously most at risk due to human activities (Myers et al., 2000;
Zachos & Habel, 2011). Not only are these regions some of the richest
in biodiversity on our planet, but undescribed biodiversity—especially
species and genetic diversity—is often concentrated in these regions
(Hamilton et al., 2010; Miraldo et al., 2016; Mora et al., 2011).
The Horn of Africa biodiversity hotspot is rich in species (Friis et
al., 2001; Largen & Spawls, 2010; Yalden & Largen, 1992), landscape
perturbation (Dessie & Kleman, 2007; Zeleke & Hurni, 2001), and
elevational heterogeneity; a majority of the topographic complexity is
found in Ethiopia, with elevations ranging from more than a hundred
meters below sea level in the Danakil Depression to greater than 4500
meters above sea level in the Simien Mountains (Fig. 1). The Ethiopian
Highlands are a largely continuous region of tropical high elevation
habitats with major lowland biogeographic barriers including the Great
Rift Valley (GRV) and the Blue Nile Valley (Fig. 1). Both the Blue Nile
Valley and the GRV are part of the large East African rift system
(Frisch, Meschede, & Blakey, 2010). These lowland biogeographic
barriers have shaped geographic population structure in a variety of
montane species, including mammals, frogs, and plants (Belay & Mori,
2006; Bryja et al., 2018; Evans et al., 2011; Freilich et al., 2016;
Gottelli et al., 2004; Kebede et al., 2007; Manthey et al., 2017;
Reyes-Velasco et al., 2018; Reyes‐Velasco et al., 2018; Silvestrini et
al., 2007; P. J. Taylor et al., 2011).
Birds are often assumed to be good dispersers, making them a good focal
taxon to identify whether the GRV is a significant biogeographic barrier
for relatively highly dispersive species. Despite the general
assumptions of bird dispersal ability due to flight, tropical
birds—especially those that are non-migratory—may not always
disperse long distances. For example, rivers have been shown to be
long-term dispersal barriers in Amazonian birds (Naka & Brumfield,
2018). Additionally, isolated sky islands in other regions of the East
African rift system have promoted diversification in some avian taxa,
suggesting at least some montane birds have limited dispersal across
lowland biogeographic barriers (Habel et al., 2015). These patterns
suggest that even in birds, species-specific diversification patterns
may exist due to intrinsic characteristics of each species such as
dispersal ability.
What remains lacking are studies of comparative population structure in
Ethiopian montane birds; to date, there have been no studies
investigating phylogeographic or population genetic patterns in this
diverse community. To help fill this gap, we used a comparative
framework to study the effects of the GRV on population genetic
differentiation in montane forest birds of the Ethiopian Highlands. We
included six bird species in this study: Cossypha semirufa(Rüppell’s Robin-chat), Crithagra tristriata (Brown-rumped
Seedeater), Melaenornis chocolatinus (Abyssinian Slaty
Flycatcher), Sylvia galinieri (Abyssinian Catbird), Turdus
abyssinicus (Abyssinian Thrush), and Zosterops poliogastrus(Ethiopian White-eye) (Table 1). We chose these species for several
reasons, as they are all (1) highland forest species in Ethiopia, (2)
relatively common where found locally, and (3) endemic to Ethiopia or
the Horn of Africa region. These six bird species are associated with
various types of forests and woodlands, including forest edge, and they
can often be found in the same communities; indeed, we observed and
captured all species for this study in the same general sampling areas
(Fig. 1). However, some of these species have different habitat
associations and minimum elevational affinities (Fig. 2). For example,
the Abyssinian Catbird and Rüppell’s Robin-chat often preferJuniperus and Podocarpus forests, the Abyssinian Thrush
and Brown-rumped Seedeater are occasionally found in highland scrub
habitat, and the Abyssinian Slaty Flycatcher is often found near
woodland streams (Clement, 2020; Collar, 2020; Collar & Robson, 2021;
del Hoyo, Collar, & Kirwan, 2020; B. Taylor, 2020; van Balen et al.,
2020). In addition to differential habitat preferences, the species
studied here have different wing shapes as measured by the hand-wing
index (HWI; Table 1) (Claramunt et al., 2011; Kipp, 1959). Because the
HWI is positively correlated with dispersal ability in birds, we may
expect species with higher HWI, such as the Abyssinian Thrush and
Ethiopian White-eye, to have maintained relatively higher population
connectivity relative to other species studied here.
We used genome resequencing data to estimate genomic diversity and
differentiation, timing of diversification, and demographic histories
for these six bird species on either side of the GRV. We then tested
whether species-specific characteristics, including dispersal ability
and demographic history, could explain the comparative patterns of
population genomic diversity and differentiation.