DOI: 10.5061/dryad.p8cz8w9sw
title: Data from: Multiple origins of mountain biodiversity in New Zealand’s largest plant radiation

description: Aim: How mountains accumulate species diversity remains poorly understood,
 particularly the relative role of in situ cladogenesis compared with
 colonization from lower elevations. Here, we estimated the contributions
 of in situ cladogenesis and colonization in generating biodiversity of a
 large mountain plant radiation and determined the importance of niche
 adaptation and divergence in these processes. We expected cladogenesis
 would accompany novel habitats formed by mountain uplift but colonization
 would become more important with time as dispersal opportunities accrue.
 Location: New Zealand, Southern Alps Taxon: Veronica sect. Hebe
 (Plantaginaceae) Methods: We estimated the most complete time-calibrated
 phylogeny to date for Veronica sect. Hebe to quantify rates of in situ
 cladogenesis and colonization of mountain habitat based on historical
 biogeographical models. We used environmental niche modeling to quantify
 species’ climate niches and estimate niche disparity and divergence over
 time. Results: In situ cladogenesis generated more species in the
 mountains than colonization from lowlands. Whereas cladogenesis slowed
 over time, colonization increased, especially in the alpine zone. Both
 adaptive ecological speciation along climate niche axes and non-adaptive,
 vicariant speciation contributed to cladogenesis. However, climate niche
 disparity through time became saturated, suggesting competition for niche
 space was important. Colonization brought more divergent species into
 mountain niches. Main Conclusions: We suggest mountain diversity
 accumulates through three main stages: high cladogenesis after initial
 colonization, decreasing cladogenesis with increasing competition, and
 increasing colonization after niches saturate, likely promoted by niche
 divergence. Combining lineage and mountain uplift trajectories, these
 stages provide a conceptual model to understand how diversity accumulates
 elsewhere. Assuming these deep-time findings apply to anthropogenic
 conditions, alpine specialists could struggle to outcompete colonizers
 facilitated by climate change, especially from generalist clades.
 Considering novel competitive interactions alongside niche traits and
 biogeographical processes will be crucial for predicting the fate of
 alpine biodiversity in a changing world.
description: <strong>Phylogeny</strong> We
 sampled 115 of 124 New Zealand species of <em>Veronica</em> by
 adding 38 newly sequenced species to the 77 in Thomas et al. (2021). We
 followed Thomas et al. (2021) for sample collection, DNA extraction, and
 sequencing. Briefly, we used target capture enrichment on recent herbarium
 and fresh collected samples using the Angiosperms353 bait kit that targets
 353 low-copy nuclear genes (Johnson et al., 2018; McDonnell et al., 2021).
 Samples were sequenced on an Illumina NextSeq 500 with 2×150-bp paired-end
 reads. We processed sequences as in Thomas et al. (2021), retrieving
 target loci and flanking intron regions with HybPiper v1.2 (Johnson et
 al., 2016). We trimmed and filtered alignments using the “full” filtering
 scheme described in Thomas et al. (2021), which consisted of removing
 markers with taxon occupancy &lt;50%, alignment length less than 150
 bp and fewer than 20 parsimony informative sites, or average percent
 identity &lt;65.5%. To minimize gene tree conflict
 observed during phylogenetic reconstruction with maximum likelihood
 methods by Thomas et al. (2021), we used a Bayesian multispecies
 coalescent (MSC) model to estimate a time-calibrated phylogeny with
 StarBEAST2 (Ogilvie et al., 2017). We first used Sortadate (Smith et al.,
 2018) to reduce the Angiosperms353 dataset to the 50 most informative
 supercontigs (loci plus their flanking introns), as the full dataset was
 computationally intractable. Genes were selected by averaging the ranks
 for gene tree length (as a heuristic for information content) and
 congruence with a maximum likelihood species tree estimated by IQTREE v1.6
 (Nguyen et al., 2015; see Thomas et al., 2021). We partitioned the MSC
 model by locus and used a HKY site model with empirical base frequencies,
 strict clock with an estimated rate, and the Calibrated Yule speciation
 model (Heled & Drummond, 2012), all with default priors. Because
 there are no accepted <em>Veronica</em> fossils in New
 Zealand, we relied on secondary calibration from a Plantaginaceae-wide
 tree with <em>Plantago</em> fossils (Meudt et al., 2015). This
 calibration estimated the crown age of New Zealand
 <em>Veronica</em> as 5–10 Ma. Accordingly, we used a normal
 prior (mean = 7.5 Ma and standard deviation = 1 Ma) for the most recent
 common ancestor of the New Zealand <em>Veronica</em> sect.
 <em>Hebe</em>, excluding the Australian outgroup. We ran a
 Markov Monte Carlo chain for 1.6 billion generations in the CIPRES Science
 Gateway computing facility (Miller et al., 2015) and confirmed all
 relevant parameters had effective sample sizes (ESS) &gt; 200 in
 Tracer v1.7.1 (Rambaut et al., 2018) after a burn-in of 1 billion
 generations. The ‘RWTY’ R package (Warren et al., 2017) showed convergence
 for the species tree topology with ESS &gt; 1000. We sampled 1000
 trees from the posterior distribution and calculated the Maximum Clade
 Credibility tree in TreeAnnotator v2.6.3 (Bouckaert et al.,
 2019).
description: Alignments: text files; can be viewed with Geneious or
 Integrative Genomics Viewer Tree files: text files; can
 be manipulated with R package ape or viewed with FigTree; posterior tree
 distribution can be visualized with DensiTree Beauti
 XML: xml file; can be loaded with Beauti or run with BEAST2
 software