Filtering of the functional diversity
To evaluate the filtering of the functional attributes in the WSEs, we
calculated the diversity of the functional characteristics, such as
functional divergence (FDiv), functional dispersion (FDis) and
functional richness (Fric) using the FD package (Laliberté &
Legendre, 2010) do Programa RStudio 2022.07.0. The Gower distance
(Gower, 1971) was used as a measure of dissimilarity between the species
because it allows the use of different types of traits, whether
continuous, ordinal, nominal or binary. The indices of the DAMOCLES
model (dynamic assemblage model of colonization, local extinction and
speciation) use estimated parameters of colonization (dispersal), local
extinction and speciation events. From the generated values, 1,000 null
models of community composition were simulated (Pigot and Etienne,
2015). For each simulated community, we calculated the functional
diversity metrics and evaluated the significance of functional diversity
using the quantis of 2.5 and 97.5% of these distributions of
null models of functional diversity. Negative and significant values of
functional diversity can indicate a grouping of the functional diversity
of birds in WSEs in relation to the species pool. Positive and
significant values would indicate greater dispersion of the functional
attributes of WSE specialist birds.
We evaluated whether WSE communities are comprised and maintained by (1)in loco speciation, and have low extinction rates and
diversification rates that are higher than the dispersion rates of
riparian communities; 2) whether they are comprised of a source-sink
dynamic. With the diversity in WSEs being formed by the dispersion of
species from riparian communities, and with the extinction rate in WSEs
being higher than its speciation rate. The diversification was evaluated
using the GeoHiSSE model (Caetano et al., 2018) from the hissev1.9.19 package (Beaulieu and O’Meara, 2016) of the software R. GeoHiSSE
allows you to model how the expansion or loss of geographical states
(e.g., WSE and riparian communities) (as described below) influences
diversification rates. In this way, we can model how the expansion or
loss of occurrence of species in WSE and riparian ecosystems can
influence the rates of speciation and extinction in these ecosystems.
Geographic states were defined as WSE specialists, riparian ecosystem
specialists, and generalists (occur in both ecosystems). A total of six
diversification models were constructed to represent the diversification
hypotheses. In Model 1, the riparian and WSE ecosystem communities are
formed by the dispersion rates between geographical states, with no
differences between their speciation and extinction rates. However,
direct changes between specialist states are not allowed, and expansion
to the generalist state is mandatory, for example specialist WSE species
cannot evolve directly to specialists in riparian ecosystems, since they
must expand their geographical distribution to generalist and lose the
WSE state to become specialists in riparian ecosystems. Model 2 has
different dispersion rates between geographic states, with the same
dispersion constraints as Model 1, but has different speciation and
extinction rates between geographic states. In Model 3, we add a hidden
state to the model, dispersion rates are equal to those of Model 1 with
the addition of dispersion between the hidden states. Speciation and
extinction rates are different between the hidden states, but are equal
between the geographic states. In this model, differences in speciation
and extinction are caused not by geographic states, but by attributes
not included in the model. Model 4 has dispersion rates that are equal
to Model 3, but there are no differences in speciation and extinction
rates between geographical states nor between hidden ones. In Model 5,
the direct change from the status of specialist of riparian environments
to WSE specialist is allowed. In Model 6, all events are present, but
specialist WSE species do not change to specialists of riparian
environments or to generalists. (Table 1). The models were ranked by the
weights of the Akaike information criterion corrected for low sampling
(wAICc) (Beier et al., 2001) and we calculated speciation, extinction
and dispersal rates using the average model of the six diversification
models .
Results
We found that the observed phylogenetic diversity was not different from
that expected for a random sampling of species from riparian ecosystems
(ses.MPD observed = 151.61, P = 0.25). However, WSE species presented
lower functional diversity than expected by a neutral diversification
and colonization process (Figure 1), thus indicating environmental
filtering of species attributes in WSEs.
The best diversification models were Models 5 (wAICc = 0.39), 4 (wAICc =
0.35) and 6 (wAICc = 0.26), respectively (Table 1). In the average
diversification model, WSEs had low speciation rates and high extinction
rates. On the other hand, riparian ecosystems had low extinction rates
and high speciation rates. Generalist species had low rates of
speciation and extinction (Figure 2). We also found that there is a
hidden state effect on the speciation rates of riparian ecosystems and
WSE extinction rates (Figure 2). There are direct transitions between
species from riparian ecosystems to WSEs, but not the other way around.
In the hidden state A, the rate of transition from riparian ecosystems
to WSEs (0.079) was greater than the rate in the opposite flow (0.23).
In the hidden state B, the transition was greater between species from
WSEs to riparian ecosystems (74.3), than the opposite transition (24.1).
Therefore, WSEs are maintained mainly by the colonization of species
from riparian ecosystems, since they have a low speciation rate and a
high extinction rate. There is also a high flow of WSE species into
riparian ecosystems, but these ecosystems are maintained primarily by
their high speciation rate and low extinction rate.
Discussion
Specialist bird communities from white-sand ecosystems (WSEs) and
riparian environments were examined to try to determine whether there is
environmental filter in the WSEs and whether evolutionary processes such
as specialization, dispersal and extinction have shaped WSE communities.
We found evidence of high extinction in WSE communities, because living
in an environment different from the surroundings, with severe
conditions, led populations to adapt and specialize, since they either
adapt or become extinct. The results show that WSEs communities are
composed of species of different evolutionary lineages, and do not
differ from a random sample from riparian communities. However, WSEs
specialist species are morphologically more similar than species of
riparian ecosystem communities.
The models employed in this work were fundamental for answering whether
the specialist species of WSEs were filtered mainly by extinction
events. High adaptation to an insular environment may have driven the
high speciation and endemicity rates of WSEs species. Birds may or may
not be present in a given area, and may be affected by the heterogeneity
of the local forest, with variation in habitat structure being
fundamental in determining the distribution of species . In the GEOHISSE
model, more events were added. Including dispersal from riparian
environments These modifications made to models 5 and 6 were important
to test our hypotheses. WSEs and direct speciation from riparian
ecosystems to WSEs (0 to 1). These modifications made to models 5 and 6
were important to test our hypotheses. By increasing the possibility of
events, we obtained representative results to explain the composition of
the specialist bird communities of the WSEs.Direct speciation could be
performed within the models, which allows the possibility of species
from open areas to return to riparian forested areas, which did not
happen. Perhaps the environmental pressure is so strong that it causes
the species to no longer be able to return or not find vacant niches in
the riparian forest ecosystems.
With the GeoHISSE analyses, we investigated the dynamics of
diversification, with transitions of species over time from riparian
forest ecosystems to more open ecosystems such as WSEs. Through this
work, we reinforce the potential of riparian areas for the dispersion of
species in the landscape with probable corridors. In study by Capurucho
et al. (2013), phytogeographic analyses were conducted that showed the
expansion of populations of the specialist species black manakin
(Xenopipo atronitens ) that began after the Last Glacial Maximum.
This is evidence of a likely rise in local extinctions and subsequent
recolonization of patches of white sand ecosystem with species from
forest ecosystems. More evidence is found in the study by Azevedo et al.
(2020), which shows that open habitats in South America are younger than
forest habitats, and favor the colonization of open environments by
riparian forest species.
Via the models, the findings in this work show that transitions from
forest ecosystems to open areas were more common than the reverse. WSEs
could and can provide more empty niches and allow colonization of
species from riparian forest environments. This pattern of further
transitions from forest to open habitats have been covered in other
studies. For example, Antonelli et al. (2018) estimated evolutionary
events for six taxonomic groups of species in Neotropical biomes and
found that the Amazon was a source of species for all groups of open
areas. Zizka et al. (2020) identified more transition events of
Bombacoideae plants from evergreen forests (forest habitats) to
seasonally dry biomes (open habitats), with multiple colonization events
in open habitats. The work of Zizka et al. (2020) follows Antonelli et
al. (2018) in their analysis of their data at the biome level, but this
can confuse the real differences by contrasting two biomes that have
different extents and consequently have distinct biotic influences.
Therefore, when performing the inclusion of species that occur within a
single biome, we can understand how the environment shapes the dispersal
and colonization processes of species within a heterogeneous biome. We
therefore propose that future studies should include ecosystems, macro-
and micro-habitats of species and not only general biomes in the
analyses.
The models used were favorable for this work and sufficient to answer
the evolutionary questions regarding the species of WSEs. We were able
to show that extinction was the evolutionary process with the highest
rates for the WSE. In insular conditions, colonizers experience
environmental conditions that were not previously experienced by their
ancestors, which cause selective pressures due to new adaptations.
Pressures drive speciation rates, but they can be strong and rapid, and
extinction is the process that shapes communities since species either
adapt or become extinct. According to Barnosky et al. (2011), extinction
is very common, but it is usually balanced by speciation. In the Amazon,
several events occurred that favored the increase of in extinction and
speciation in open areas, such as the fire edaphic factors and seasonal
climatic factors that ended up isolating populations and increasing the
selective pressure on the species (Els et al., 2021).
Morphological features do not appear to restrict species of WSEs and
morphology does not preclude colonization and persistence of species in
other Amazonian ecosystems. As such, the evolutionary history of species
is more important in order to understand the distribution of species in
the various micro- and macro-habitats of Amazonian ecosystems. This
restricted association of species results in dependence and high
adaptation to be able to disperse in the landscape (Lanna et al., 2022).
Little is known about which corridors Amazonian birds use, and how the
gene flows of the species are maintained over time. When considering
transitions between ecosystems using only the species that are present
and their current distributions, it is necessary to consider other
factors. Species may have colonized other types of open ecosystems or
forest ecosystems from other regions or even from other continents, and
not transitioned between these two habitats.
Currently there are analyses with increasingly robust models to evidence
evolution and its main drivers. There is still limited understanding
about Amazonian communities or about species conservation within a
climate change scenario. Accelerated extinction ceases to be a driving
force of species selection in the Amazon and could be an unprecedented
catastrophe in the history of the planet. For this reason, WSEs are
considered increasingly vulnerable and are priority areas for
conservation, as they are already limited environments and prone to
fire. Wildfires in seasonally flooded riparian environments can abruptly
transform forests into a savanna state, thus contributing to
climate-induced disturbances and causing ecological transitions .
Conclusion
Via the results obtaining from combining phylogenetic and
ecomophological data to evidence the evolutionary history of bird
species in white-sand ecosystems and riparian ecosystems of the Amazon,
insights about the evolutionary processes that shape communities emerge.
As seen for other animal groups, our results demonstrate a predominant
pattern of transitions from forests to open habitats. The evolutionary
process of extinction in the Amazon seems to be much more common than we
imagined, and the WSEs are a species sink that has been important for
bird speciation over time. With ecomorphological and phylogeny data we
were able to generate more robust tests of evolutionary models. Tropical
regions are the regions with the greatest biodiversity on the planet and
are under threat, obtaining results with high numbers of extinctions is
crucial for further assessments of the populations of specialist species
in various ecosystems. We have identified the main drivers and have a
small part of the limited understanding of how species will cope, adapt
and change their distributions due to climate change. White-sand
ecosystems and riparian forest ecosystems are important within the
evolutionary process, and include an important tree of life dynamic
within the Amazon biome.
Acknowledgments
We would like to thank Marcelo Menin (in memoriam ) for his
support and suggestions, the Laboratory of Conservation Biology with the
collaboration of Cintia Cornelius, the Laboratory of Ecology and
Evolution of the Federal University of Goiás, and the CAPES Support
Program, a department of the Brazilian government that is focused on the
training of human resources.
References