Introduction
A central goal in ecology is to determine what forces structure local
communities, and to understand why community membership varies across
space. According to theory, the composition of local communities
reflects a balance between regional inputs, via speciation and
dispersal, and local controls, such as environmental filtering and
competition (MacArthur & Wilson 1967; Rosenzweig 1995; Vellend 2016;
Leibold & Chase 2018). If local forces control diversity equilibria,
communities in similar environments are expected to be similar in
composition, regardless of the size of their regional species pools;
conversely, if regional forces predominate, regions with more species
should also possess greater local diversity (Ricklefs 1987). Debate over
whether local or regional forces dominate has reached an uneasy détente,
as macroecological patterns suggest local control in some systems, and
pervasive regional influences in others (Ricklefs & Schluter 1994;
Myers et al. 2013; Cornell & Harrison 2014). What is thus
crucial is to identify the reasons for this variation in controls of
local diversity, and to establish a framework to explain why one
system’s local diversity is set by local processes, while another’s
reflects inputs from the regional species pool (Cornell 1999; Harrison
& Cornell 2008; Lessard et al. 2012).
We approach this challenge by focusing on a pair of linked mechanisms by
which macroevolutionary inputs could ultimately determine community
structure. First, we consider the attributes of biogeographic landscapes
that foster (or limit) the evolution of diverse regional species pools
(McPeek & Brown 2000; Swenson 2011; Zobel et al. 2011;
Mittelbach & Schemske 2015; Craven et al. 2019). Second, we
consider how these richer regional species pools could then lead to
saturated communities (competition-structured communities where richness
reaches a stable equilibrium; Rabosky & Hurlbert 2015; Storch & Okie
2019). Crucially, species pools are generated by an interplay of
ecological and evolutionary factors at spatial scales intermediate to
the local versus regional scales of traditional assembly models (Emerson
& Gillespie 2008; Jetz & Fine 2012). The hierarchical organization of
regions (e.g., large, evolutionarily-independent areas such as
continents or oceanic islands) into environmentally-distinctive
”sub-regions” (e.g., biomes) may shape the evolutionary buildup of
species pools, thereby influencing the structure of local communities
(Qian & Ricklefs 2000; Zobel et al. 2011; Jetz & Fine 2012;
Mittelbach & Schemske 2015).
If competition is relatively weak, increased diversification within a
region should increase local community richness by increasing species
additions relative to losses (Hubbell 2001; Leibold et al. 2004).
Alternatively, if increased diversification produces species that
specialize on particular sub-regions (e.g., Mayr 1947; Glor et
al. 2003; Rundle & Nosil 2005; Gray et al. 2019), it may spur
the emergence of local richness controls. Sub-regional specialists may
better monopolize local resources, resulting in competition-structured
communities that can resist migrants (MacArthur 1972; Cornell &
Harrison 2014). Therefore, under this region/sub-region/local model, a
principal determinant of whether local or regional effects on diversity
predominate is the availability of evolutionary opportunity – a term we
use to describe the conditions necessary for clades to diversify and
specialize on unique local ecological conditions (e.g., sufficient time
and geographic space for speciation among or within ecologically
distinct sub-regions to complete; Losos & Parent 2010; Zobel et
al. 2011; Cornell 2013; Algar & Mahler 2015).
If greater evolutionary opportunities indeed facilitate local control,
we predict the emergence of several ecological patterns in
local-community abundance, species diversity, and organization across
space (beta-diversity). First, for communities to exhibit local
diversity controls requires that they be saturated at the level of
individuals competing for limited resources (Cornell 1999; Gaston 2000).
Thus, numbers of individuals in such communities should scale with
resource availability, yielding correlations between local abundance and
proxies of productivity, such as temperature or elevation (Wright 1983;
Gaston 2000). If individuals can utilize local resources efficiently
regardless of the diversity of the evolutionary fauna, the scaling of
abundance and productivity should be similar across systems that differ
in evolutionary diversity. Conversely, greater diversification could
fundamentally change how ecological limits manifest by generating
specialists on previously unutilized resources and thereby enhancing
community-level abundances (Cornell 2013; Storch et al. 2018;
Storch & Okie 2019). In that case, regions with greater evolutionary
opportunity may exhibit greater local abundances in otherwise-similar
environments.
Second, if greater macroevolutionary inputs enhance local control on
species diversity then the relationship between environmental resources
and local species richness should in theory be similar across regions.
However, this relationship will depend on whether clades in different
regions have had sufficient opportunity to diversify into the niches
available in local environments—in other words, whether they have
produced sub-regional environmental specialists that can saturate
communities at the species level (Jetz & Fine 2012; Cornell 2013). If a
given region has had insufficient time or space for diversification to
fill available sub-regional niches, we would expect local richness
patterns across regions to diverge (MacArthur 1972; Mittelbach &
Schemske 2015).
Finally, if evolutionary opportunity shapes communities by facilitating
local control, we expect greater regional diversity to sort primarily
among communities (i.e., as beta-diversity) rather than within them
(elevated alpha-diversity) (MacArthur 1965; Cornell 2013). Evolutionary
opportunity should thus precipitate the emergence of spatial structure
within faunas through the evolution of sub-regional environmental
specialists. When opportunity is substantial in environmentally similar
areas, whole-community properties such as total richness and functional
characteristics may converge, even among evolutionarily-independent
regions (Orians & Paine 1983; Cornell 1999; Ricklefs 2006). By
contrast, faunas lacking in evolutionary opportunity should consist of
environmental generalists, and the local communities within these faunas
should exhibit comparatively little turnover and potentially low
convergence between faunas.
Testing how diversification affects local community structure is
difficult, in part because of the challenge locating empirical systems
that are ecologically similar, but differ in histories of
macroevolutionary diversification (Lessard et al. 2012). Regions
differing in evolutionary richness often also differ in climate and
habitat, or the deep phylogenetic history of the biota, either of which
may confound straightforward comparison (Rosenzweig 1995; Price et
al. 2000). Ideally one would seek a system in which replicate regions
are similar in environment, and contain faunas that radiated from recent
phylogenetic stock, but differ in macroevolutionary diversity.
Here we leverage a natural experiment to examine the effects of
macroevolution on the structure of local communities: independent
radiations of anole lizards (Anolis ) distributed across similar
environmental gradients on the Caribbean island of Jamaica and the
northern paleoisland of adjacent Hispaniola (this region corresponds to
a biogeographically distinctive unit within the island; Fig. 1). Anoles
have diversified to play similar ecological roles on both islands, but
Hispaniola has a richer anole fauna than its smaller neighbor Jamaica
(Williams 1983; Losos 2009; Mahler et al. 2013). The two islands
possess similar climates, vegetation types, and macrohabitat diversity
(Ricklefs & Bermingham 2008; Losos 2009). Notably, both feature vast
expanses of hot lowland tropical forest that grade into tall inland
mountains featuring cool cloud-forest habitats. Their key environmental
difference is that Hispaniola’s highlands are much more extensive than
Jamaica’s, creating divergent evolutionary prospects in this sub-region
type (Fig. 1b). Crucially, while the lowlands of both islands cover more
than 3,000km2, the proposed minimum area required forin situ speciation in anoles (Losos & Schluter 2000), only
Hispaniola’s highlands clear this threshold, leading to the expectation
that Jamaica’s highland communities should be evolutionarily
constrained.
We conducted mark-resample surveys of Anolis communities across
matched elevational gradients on Jamaica and Hispaniola to test whether
greater macroevolutionary diversity, and especially differences in
highland evolutionary opportunity, trickle down to structure local
communities. We begin by asking (1) whether the abundance ofAnolis within local communities across elevations is similar
between islands, as predicted if local temperature is primarily
responsible for controlling community size, and macroevolutionary inputs
have little effect on abundance. Next, we ask (2) whether differences in
sub-regional area trigger divergence in community structure across
elevations, such that community convergence exists between islands in
the lowlands (where evolutionary opportunity is substantial), but is
lacking in the highlands (for which Jamaica is more limited). We then
investigate (3) whether greater evolutionary opportunity in the
Hispaniolan highlands leads to ecologically distinct sub-faunas via the
evolution of local environmental specialists. If so, we predict that
Hispaniolan anole communities will exhibit greater beta-diversity than
their Jamaican counterparts. Finally, we (4) test the importance of
sub-regional faunas in impacting convergence in abundance and richness
between islands across the elevational gradient.