bioRxivEvolutionary Biology
Increasing phylogenetic stochasticity at high elevations on summits across a remote North American wilderness
Abstract
PREMISE OF THE STUDYAt 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 of the Sawtooth National Forest, USA, we analyzed phylogenetic structure within and between nine summit communities.\n\nMETHODSWe 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 assed how maximum elevation explains phylogenetic structure. To evaluate similarities between summits we quantified phylogenetic turnover, taking into consideration micro-habitats (talus vs. meadows).\n\nKEY RESULTSWe found different patterns of community phylogenetic structure within the six most species-rich orders, but across all vascular plants phylogenetic structure was largely no different from random. There was a significant negative correlation between elevation and tree-wide phylogenetic diversity (MPD) within summits: significant overdispersion degraded as elevation increased. Between summits we found high phylogenetic turnover, which was driven by greater niche heterogeneity on summits with alpine meadows.\n\nCONCLUSIONSThis study provides further evidence that stochastic processes shape the assembly of vascular plant communities in the high-alpine at regional scales. However, order-specific patterns suggest adaptations may be important for assembly of specific sectors of the plant tree of life. Further studies quantifying functional diversity will be important to disentangle the interplay of eco-evolutionary processes that likely shape broad community phylogenetic patterns in extreme environments.
- organism: plant (other)
- assay: metagenomics
- research focus: ecology & biodiversity
- approach: statistical model
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