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