Evoregions: Mapping shifts in phylogenetic turnover across biogeographic regions

Maestri, Renan; Duarte, Leandro da Silva

doi:10.1111/2041-210x.13492

Cited by 12 publications

(32 citation statements)

References 52 publications

(118 reference statements)

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“…Thus, shifts in ancestral area could alternatively influence trait evolution. Combining the tip‐based metrics we developed here with approaches that incorporate shifts in ancestral area (Maestri & Duarte, 2020 ) can help to show whether trait evolution is produced by shifts in distribution.…”

Section: Discussionmentioning

confidence: 99%

Is evolution faster at ecotones? A test using rates and tempo of diet transitions in Neotropical Sigmodontinae (Rodentia, Cricetidae)

Luza

Maestri

Debastiani

et al. 2021

Ecology and Evolution

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To disentangle the mechanisms producing the biological diversity seen in nature, ecologists increasingly seek to integrate ecology and evolution (Jetz et al., 2012;McGill et al., 2019;Wiens & Donoghue, 2004). Mapping traits onto phylogenies is essential for such integration, as mapping traits reveals the rates and tempo of evolution of behavioral, morphological, and ecological characteristics (Bollback, 2006). Knowledge of trait evolution has often been applied to evaluate the evolutionary mechanisms producing, for example, the appearance of ecological innovations and the bursts behind evo-

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Section: Discussionmentioning

confidence: 99%

Is evolution faster at ecotones? A test using rates and tempo of diet transitions in Neotropical Sigmodontinae (Rodentia, Cricetidae)

Luza

Maestri

Debastiani

et al. 2021

Ecology and Evolution

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“…These metrics can be used to map the effects of historical factors at different scales or as variables in common modeling frameworks allowing to test hypotheses in ecology, macroevolution, biogeography, and community ecology (e.g., Luza et al, 2021;Van Dijk et al, 2021). Additionally, Herodotools perform phylogenetic regionalization methods, map transition zones (Maestri & Duarte, 2020), and detect source and sink regions (functions evoregions, affiliation, and dispersal_from, respectively).…”

Section: General Description Of Herodotools Packagementioning

confidence: 99%

“…Methods aiming to define biogeographic regions based on either taxonomic (Edler et al, 2016;Holt et al, 2013;Kreft & Jetz, 2010;Olivero et al, 2013;Vilhena & Antonelli, 2015) or phylogenetic relationships among species of a given biological group (Daru et al, 2020;Holt et al, 2013;Maestri & Duarte, 2020) has been intensively developed over the last decade, using different site resemblance and clustering methods. While all methods are valuable as classification tools for historical biogeography and evolutionary macroecology, bioregions defined from either species composition or the Simpson index of phylogenetic beta diversity (Holt, et al 2013;Daru et al, 2020) , 2018).…”

Section: Phylogenetic Regionalization and Shifts In Phylogenetic Turn...mentioning

confidence: 99%

“…To calculate the importance of in-situ diversification, historical dispersal events and estimate the age of assemblages, we first applied a phylogenetic regionalization method based on evolutionary turnover (Maestri & Duarte, 2020) implemented in the function evoregion() of Herodotools package. Based on the groups generated by the phylogenetic regionalization, we estimated species' ancestral range using BioGeoBEARS (Matzke, 2013).…”

Section: Historical Biogeography Of Akodon Genusmentioning

confidence: 99%

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Herodotools: An R package to integrate macroevolution, community ecology, and biogeography

Nakamura¹,

Rodrigues²,

Luza³

et al. 2022

Preprint

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Historical processes like speciation, extinction and historical dispersal are the ultimate factors generating and maintaining biodiversity. Therefore, understanding how these factors affect the distribution of biodiversity is of great importance. To do so, it is necessary to integrate information from ancestral state reconstructions and current species distribution data and traits. Studies that integrated both information proved effective in unveiling questions in the intersection of macroecology, macroevolution, and community ecology. However, up to now, numerical methods that perform this integration are scattered, making integration difficult and hampering advances in these research fields. Here we developed Herodotools, an R package that integrates the macroevolutionary models with the distribution of species occurrence in assemblages to provide metrics that represent historical information, such as in-situ diversification, historical dispersal, and age of assemblages. We described the main functions and illustrated the use of our new package by analyzing the historical biogeography of the genus Akodon, a South American small rodent. Our package provides the first platform to investigate questions that require the integration of macroevolutionary information with ecological data (as species occurrence) and streamline analysis of historical biogeography, leveraging the investigation of the effects of historical processes in different levels of organization, from local assemblages to bioregions.

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“…Many bioregionalizations have delineated precise geographic units based on differences in species composition (Kreft & Jetz, 2010; Wallace, 1876) and/or discontinuities in the abiotic environment (Olson et al, 2001; Omernik, 2004). Recently, biogeographic frameworks have focused instead on either using phylogenetic data (Daru, Elliott, Park, & Davies, 2017; Holt et al, 2013; Maestri & Duarte, 2020) to define those hard boundaries, or have taken a ‘softer’ approach to their geographic delineation by identifying transition zones (Edler, Guedes, Zizka, Rosvall, & Antonelli, 2017; Vilhena & Antonelli, 2015). Another key difference is that while some biogeographers have sought to define systems of small units nested within larger ones— such is the case of World Wildlife Fund (WWF) Terrestrial Ecoregions (Dinerstein et al, 2017; Olson et al, 2001)—others have rejected this as a desirable outcome of the study system (Ebach & Parenti, 2015).…”

Section: Introductionmentioning

confidence: 99%

Robust, data-driven bioregionalizations emerge from diversity concordance

Mancheno¹,

Buettel

Ondei³

et al. 2021

Preprint

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Aim: Despite the increasing interest in developing new bioregionalizations and assessing the most widely accepted biogeographic frameworks, no study to date has sought to systematically define a system of small bioregions nested within larger ones that better reflect the distribution and patterns of biodiversity. Here, we examine how an algorithmic, data-driven model of diversity patterns can lead to an ecologically interpretable hierarchy of bioregions. Location: Australia. Time period: Present. Major taxa studied: Terrestrial vertebrates and vascular plants. Methods: We compiled information on the biophysical characteristics and species occupancy of Australia′s geographic conservation units (bioregions). Then, using cluster analysis to identify groupings of bioregions representing optimal discrete-species areas, we evaluated what a hierarchical bioregionalization system would look like when based empirically on the within- and between-site diversity patterns across taxa. Within an information-analytical framework, we then assessed the degree to which the World Wildlife Fund′s (WWF) biomes and ecoregions and our suite of discrete-species areas are spatially associated and compared those results among bioregionalization scenarios. Results: Information on biodiversity patterns captured was moderate for WWF′s biomes (50–58% for birds′ beta, and plants′ alpha and beta diversity, of optimal discrete areas, respectively) and ecoregions (additional 4–25%). Our plants and vertebrate optimal areas retained more information on alpha and beta diversity across taxa, with the two algorithmically derived biogeographic scenarios sharing 86.5% of their within- and between-site diversity information. Notably, discrete-species areas for beta diversity were parsimonious with respect to those for alpha diversity. Main conclusions: Nested systems of bioregions must systematically account for the variation of species diversity across taxa if biodiversity research and conservation action are to be most effective across multiple spatial or temporal planning scales. By demonstrating an algorithmic rather than subjective method for defining bioregionalizations using species-diversity concordances, which reliably reflects the distributional patterns of multiple taxa, this work offers a valuable new tool for systematic conservation planning.

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Evoregions: Mapping shifts in phylogenetic turnover across biogeographic regions

Abstract: 1. Biogeographic regionalization offers context to the geographical evolution of clades. The positions of bioregions inform both the spatial location of clusters in species distribution and where their most important boundaries are.

Cited by 12 publications

References 52 publications

Is evolution faster at ecotones? A test using rates and tempo of diet transitions in Neotropical Sigmodontinae (Rodentia, Cricetidae)

Is evolution faster at ecotones? A test using rates and tempo of diet transitions in Neotropical Sigmodontinae (Rodentia, Cricetidae)

Herodotools: An R package to integrate macroevolution, community ecology, and biogeography

Robust, data-driven bioregionalizations emerge from diversity concordance

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