Biology subjects

Debastiani, V.

Publications and source records attributed to Debastiani, V..

3 recordsLinked to original sources

bioRxiv2021

There and Back to the Present: An Evolutionary Tale on Biological Diversity

Ecologists often agree on the importance of macroevolution for niche-mediated distribution of biological diversity along environmental gradients. Yet, macroevolutionary diversification and dispersal in time and space generate uneven geographic distribution of phylogenetic pools, which affects the imprint let by macroevolution on local species pools. In this article we introduce an individual-based simulation approach coupled to Approximate Bayesian Computation (ABC) that allows to parameterize the adaptation rate of species niche positions along the evolution of a monophyletic lineage, and the intensity of dispersal limitation, associated with the distribution of biological diversity between assemblages potentially connected by dispersal (metacommunity). The analytical tool was implemented in an R package called mcfly. We evaluated the statistical performance of the analytical framework using simulated datasets, which confirmed the suitability of the analysis to estimate adaptation rate and dispersal limitation parameters. Further, we evaluated the role played by niche evolution and dispersal limitation on species diversity distribution of Phyllostomidae bats across the Neotropics. The framework proposed here shed light on the links between niche evolution, dispersal limitation and the distribution of biological diversity, and thereby improved our understanding of evolutionary imprints on ecological patterns. Perhaps more importantly, it offers new possibilities for solving the eco-evolutionary puzzle.

ecology↗

bioRxiv2021

The role of evolutionary modes for trait-based cascades in mutualistic networks

The erosion of functional diversity may foster the collapse of ecological systems. Functional diversity is ultimately determined by the distribution of species traits. As species traits are a legacy of species evolutionary history, one might expect that the mode of trait evolution influences community resistance under the loss of functional diversity. In this paper, we investigate the role of trait evolutionary dynamics on the robustness of mutualistic networks undergoing the following scenarios of species loss: i) random extinctions, ii) loss of functional distinctiveness and iii) extinctions biased towards larger sizes. We simulated networks defined by models of single trait complementary and evolutionary modes where traits can arise in recent diversification events with weak phylogenetic signal, in early diversification events with strong phylogenetic signal, or as a random walk through evolutionary time. Our simulations show that mutualistic networks are especially vulnerable to extinctions based on trait distinctiveness and more robust to random extinction dynamics. The networks show an intermediate level of robustness against size-based extinctions. Despite the small range of variation in network robustness, our results show that the mode of trait evolution matters for network robustness in all three scenarios. Networks with low phylogenetic signal are more robust than networks with high phylogenetic signal across all scenarios. As a consequence, our results predict that mutualistic networks based upon current adaptations are more likely to cope with extinction dynamics than those networks that are based upon conserved traits.

ecology↗

bioRxiv2018

HaploVectors: an integrative analytical tool for phylogeography

Sets of local populations show different degrees of gene flow due to dispersal barriers and environmental constraints, which renders genetic composition gradients among populations (genetic turnover). Unveiling biogeographic correlates of genetic turnover is paramount for phylogeography. While some processes (genetic drift, secondary contact) may erase the historical track of genetic turnover, vicariance or ancient dispersal likely leads to genetic divergence among populations. Yet available analyses do not permit direct inference about mechanisms driving genetic turnover. We propose a novel analytical approach called genvector analysis, which fulfills this gap by decomposing genetic compositional dissimilarities between populations based on either haplotypes or other genetic data into genetic eigenvectors. Such procedure allows exploring genetic turnover among sets of local populations, and analyzing their biogeographic correlates based on null model tests. We evaluate the statistical performance of the method on simulated datasets. We also analyzed biogeographic correlates of genetic turnover of Akodon cursor in the Brazilian Atlantic Forest. Results revealed that genvector analysis is robust to discriminate biogeographic drivers of genetic turnover. For Akodon cursor analysis, we observed that while for the entire species, all predictors considered (except for elevation) explained genetic turnover, within phylogroups some factors varied their importance. Genvector analysis was demonstrated to be useful for several different purposes in phylogeography, and complementary to classic analytical tools widely used by phylogeographers, such as AMOVA or DAPC. The role of ancient versus recent biogeographic events, the relationship between morphological divergence or abiotic variables and genetic turnover can easily be investigated using genvector analysis.

ecology↗