Riders in the sky (islands): Using a mega‐phylogenetic approach to understand plant species distribution and coexistence at the altitudinal limits of angiosperm plant life

et al. 2019

Ecology

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Should we build our own phylogenetic trees based on gene sequence data, or can we simply use available synthesis phylogenies? This is a fundamental question that any study involving a phylogenetic framework must face at the beginning of the project. Building a phylogeny from gene sequence data (purpose‐built phylogeny) requires more effort, expertise, and cost than subsetting an already available phylogeny (synthesis‐based phylogeny). However, we still lack a comparison of how these two approaches to building phylogenetic trees influence common community phylogenetic analyses such as comparing community phylogenetic diversity and estimating trait phylogenetic signal. Here, we generated three purpose‐built phylogenies and their corresponding synthesis‐based trees (two from Phylomatic and one from the Open Tree of Life, OTL). We simulated 1,000 communities and 12,000 continuous traits along each purpose‐built phylogeny. We then compared the effects of different trees on estimates of phylogenetic diversity (alpha and beta) and phylogenetic signal (Pagel's λ and Blomberg's K). Synthesis‐based phylogenies generally yielded higher estimates of phylogenetic diversity when compared to purpose‐built phylogenies. However, resulting measures of phylogenetic diversity from both types of phylogenies were highly correlated (Spearman's normalρ > 0.8 in most cases). Mean pairwise distance (both alpha and beta) is the index that is most robust to the differences in tree construction that we tested. Measures of phylogenetic diversity based on the OTL showed the highest correlation with measures based on the purpose‐built phylogenies. Trait phylogenetic signal estimated with synthesis‐based phylogenies, especially from the OTL, was also highly correlated with estimates of Blomberg's K or close to Pagel's λ from purpose‐built phylogenies when traits were simulated under Brownian motion. For commonly employed community phylogenetic analyses, our results justify taking advantage of recently developed and continuously improving synthesis trees, especially the Open Tree of Life.

Section: Methodsmentioning

confidence: 99%

For common community phylogenetic analyses, go ahead and use synthesis phylogenies

Trotta

et al. 2019

Ecology

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“…To test whether closely related species are more or less likely to co-occur, one common approach is to calculate the phylogenetic diversity of communities and then compare the observed phylogenetic diversity with those expected by chance through different null models. There is a growing body of literature using this community phylogenetic approach, documenting the phylogenetic structure of ecological communities across taxa and scales (Webb et al 2002, Cavender-Bares et al 2006, Helmus et al 2007, Vamosi et al 2009, Cardillo 2011, Smith et al 2014, Li et al 2017, Marx et al 2017). Complementing analyses of phylogenetic community structure, phylogenetic signal of ecologically important traits may also be tested (e.g., Cavender-Bares and Reich 2012, Li et al 2017); traits that have strong phylogenetic signal (i.e., closely related species have more similar trait values than expected by chance) can then provide insights into potential causes of the observed phylogenetic community structure (Webb et al 2002, Cavender-Bares et al 2009, Vamosi et al 2009).…”

Section: Introductionmentioning

confidence: 99%

For common community phylogenetic analyses, go ahead and use synthesis phylogenies

Trotta

et al. 2018

Preprint

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Running headline: Phylogenetic analyses based on di erent treesAbstract:Should we build our own phylogenetic trees based on gene sequence data, or can we simply use available synthesis phylogenies? This is a fundamental question that any study involving a phylogenetic framework must face at the beginning of the project. Building a phylogeny from gene sequence data (purpose-built phylogeny) requires more e ort, expertise, and cost than subsetting an already available phylogeny (synthesis-based phylogeny). However, we still lack a comparison of how these two approaches to building phylogenetic trees in uence common community phylogenetic analyses such as comparing community phylogenetic diversity and estimating trait phylogenetic signal. Here, we generated three purpose-built phylogenies and their corresponding synthesis-based trees (two from Phylomatic and one from the Open Tree of Life [OTL]). We simulated , communities and , continuous traits along each purpose-built phylogeny. We then compared the e ects of di erent trees on estimates of phylogenetic diversity (alpha and beta) and phylogenetic signal (Pagel's λ and Blomberg's K). Synthesis-based phylogenies generally yielded higher estimates of phylogenetic diversity when compared to purpose-built phylogenies. However, resulting measures of phylogenetic diversity from both types of phylogenies were highly correlated (Spearman's > . in most cases). Mean pairwise distance (both alpha and beta) is the index that is most robust to the di erences in tree construction that we tested. Measures of phylogenetic diversity based on the OTL showed the highest correlation with measures based on the purpose-built phylogenies. Trait phylogenetic signal estimated with synthesis-based phylogenies, especially from the OTL, were also highly correlated with estimates of Blomberg's K or close to Pagel's λ from purpose-built phylogenies when traits were simulated under Brownian Motion. For commonly employed community phylogenetic analyses, our results justify taking advantage of recently developed and continuously improving synthesis trees, especially the Open Tree of Life.

“…While these archives have proven useful for comparisons of alpine community 518 phylogenetic structure at macro-ecological scales (e.g. Jin et al, 2015;Marx et al, 2017), the 519 impact of taxon sampling on quantification and interpretations of community phylogenetic 520 patterns is of growing concern (Park et al, 2018). Therefore, we leveraged a targeted high-521 were collected throughout the region.…”

Section: Brassicales 455mentioning

confidence: 99%

Increasing phylogenetic stochasticity at high elevations on summits across a remote North American wilderness

Richards

Johnson

et al. 2018

Preprint

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Premise At the intersection of ecology and evolutionary biology, community phylogenetics can provide insights into overarching biodiversity patterns, particularly in remote and understudied ecosystems. To understand community assembly of the high alpine flora in the Sawtooth National Forest, USA, we analyzed phylogenetic structure within and between nine summit communities. Methods We used high‐throughput sequencing to supplement existing data and infer a nearly completely sampled community phylogeny of the alpine vascular flora. We calculated mean nearest taxon distance (MNTD) and mean pairwise distance (MPD) to quantify phylogenetic divergence within summits, and assessed whether maximum elevation explains phylogenetic structure. To evaluate similarities between summits, we quantified phylogenetic turnover, taking into consideration microhabitats (talus vs. meadows). Results We found different patterns of community phylogenetic structure within the six most species‐rich orders, but across all vascular plants phylogenetic structure was largely not different from random. There was a significant negative correlation between elevation and tree‐wide phylogenetic diversity (MPD) within summits: overdispersion degraded as elevation increased. Between summits, we found high phylogenetic turnover driven by greater niche heterogeneity on summits with alpine meadows. Conclusions Our results provide further evidence that stochastic processes may also play an important role in the assembly of vascular plant communities in high alpine habitats at regional scales. However, order‐specific patterns suggest that adaptations are still important for assembly of specific sectors of the plant tree of life. Further studies quantifying functional diversity will be important in disentangling the interplay of eco‐evolutionary processes that likely shape broad community phylogenetic patterns in extreme environments.