Data from: Integrative taxonomy clarifies the evolution of a cryptic primate clade
Data files
Aug 07, 2024 version files 14.65 GB
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README.md
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vanElstetal_NatureEcologyEvolution_2024.tar.gz
Abstract
Global biodiversity is under accelerating threats, and species are succumbing to extinction before being described. Madagascar’s biota represents an extreme example of this scenario, with the added complication that much of its endemic biodiversity is cryptic. Here, we illustrate best practices for clarifying cryptic diversification processes by presenting an integrative framework that leverages multiple lines of evidence and taxon-informed cut-offs for species delimitation, while placing special emphasis on identifying patterns of isolation-by-distance. We systematically apply this framework to an entire, taxonomically controversial primate clade, the mouse lemurs (genus Microcebus, family Cheirogaleidae). We demonstrate that species diversity has been overestimated primarily due to the interpretation of geographic variation as speciation, potentially biasing inference of the underlying processes of evolutionary diversification. Following a revised classification, we find that crypsis within the genus is best explained by a model of morphological stasis imposed by stabilising selection and a neutral process of niche diversification. Finally, by clarifying species limits and defining evolutionarily significant units, we provide new conservation priorities, bridging fundamental and applied objectives in a generalisable framework.
README: Data from: Integrative taxonomy clarifies the evolution of a cryptic primate clade
https://doi.org/10.5061/dryad.b2rbnzsp3
This repository holds input, configuration and output files for the following analyses conducted as part of the publication van Elst et al. (2024), Nat. Ecol. Evol.:
- Genotyping
- Phylogenetic inference
- Species delimitation
- Divergence time estimation
- Biogeographic reconstruction
- Modelling morphological and climatic niche evolution
- Conservation_reassessment
1 Description of the data and file structure
1.1 Genotyping
./Genotyping
contains genotypes called with with GATK v4.1.9.0 and filtered with VCFtools v0.1.17 (Genotype_calls
), phased RAD loci extracted following Poelstra et al. (2021), Syst. Biol. (Loci
), and genotype likelihoods inferred with ANGSD v0.92 (Genotype_likelihoods
).
1.2 Phylogenetic inference
./phylogenetic_inference
contains data for maximum likelihood and quartet-based phylogenetic inference with IQ-TREE v2.2.0 (IQ-TREE
) and SVDquartets of PAUP* v4.0a (SVDquartets
), respectively.
1.3 Species delimitation
./Species_delimitation
contains the following subdirectories:
./Genomics
contains data for genomic tests for patterns of isolation-by-distance across species subsets (Isolation-by-distance
and directories for each species subset therein), individual ancestry inference with NGSadmix v32 (Admixture
), and estimation of genealogical divergence indices (gdi) between candidate species (Gdi
).
./Morphometry
contains data for estimation of overlap in morphometry in the R package 'dynRB' v0.18 (Overlap
) and for morphometric tests for patterns of isolation-by-distance (Isolation-by-distance
).
In Overlap/01_Microcebus_morphological_data.xlsx
and Isolation-by-distance/data.xlsx
, morphometric data are given in mm, elevation is given in m, and bioclimatic parameters and units are detailed at https://chelsa-climate.org/bioclim/.
./Climatic_niche
contains data for inference of climatic niche models and estimation of differentiation among these with the R package 'ENMtools' v1.0.7.
./Acoustic_communication
contains data for estimation of differentiation in acoustic communication.
Parameters in Acoustic_data.xlsx
and their units are described in detail in Supplementary Table S23 of the associated original publication.
./Reproductive_activity
contains data for estimation of differentiation in reproductive activity.
1.4 Divergence time estimation
./Divergence_time_estimation
contains data for inference of divergence times from phased RAD loci under a coalescent model in BPP v4.4.1.
1.5 Biogeographic reconstruction
./Biogeographic_reconstruction
contains data for ancestral biogeogeography reconstruction in the R package 'BioGeoBEARS' v1.1.2 under three alternative classification schemes: (1) dry vs. humid forest (Dry_humid
), (2) five major ecoregions as in Yoder et al. (2016), PNAS (Five_ecoregions
) and (3) the Köppen-Geiger climate classification (Beck et al. 2018, Sci. Data) (Koeppen_Geiger
).
1.6 Modelling morphological and climatic niche evolution
./Modelling_morphological_and_climatic_niche_evolution
contains the following subdirectories:
./Climatic_niche_evolution
contains data for modelling the evolution of climatic niches along the inferred Microcebus phylogeny.
./Morphological_evolution
contains data for modelling the evolution of morphology along the inferred Microcebus phylogeny, including cross-validation (Cross_validation
) with simulations under Brownian motion (BM_simulation
) and Ornstein–Uhlenbeck (OU_simulation
) models (data for each simulation is given in a separate directory therein).
Modelling was conducted with the R packages 'phytools' v2.3-0, 'dynRB' v0.18, 'phyloclim' v0.9.5, 'mvMORPH' v1.1.9, 'tmvtnorm' v1.6.
1.7 Conservation_reassessment
./Conservation_reassessment
contains data for reassessing conservation status of revised Microcebus species, using ArcGIS Pro v3.1.0, including climatic niche models (climatic_niche_models
).
Estimates in Output.xlsx
are given in km².
2 Sharing/Access information
All new raw sequencing data have been made available through NCBI BioProjects PRJNA560399 and PRJNA807164. Individual BioSample accessions are given in Supplementary Table S13 of the original publication.
3 Code/Software
Associated scripts are found at GitHub. For detailed information on used software, please see the GitHub repository and the original publication.
Methods
This is an interdisciplinary data set, including genomic (RADseq), morphometric, ecological, behavioral and life history data. Please refer to van Elst et al. Nature Ecology & Evolution (2024) for details on data collection and processing.