Research
Spatial Phylogenetics of the North American Flora
Aim: A comprehensive spatial understanding of biodiversity across the globe requires multidimensional characterization. Spatial phylogenetics adds an evolutionarily and geographically explicit framework to biodiversity studies. Although phylogenetic trees are becoming increasingly comprehensive, they still represent only a fraction of the known terminal taxa in any biota. As an attempt to improve sampling, missing taxa are frequently imputed into a backbone phylogeny using their taxonomic classification. Here, we evaluated the effects of both incomplete taxon sampling and phylogenetic imputation on the quantitative, spatial patterns of phylodiversity.
Location: Japan.
Time period: Present day.
Major taxa studied: Ferns (Polypodiopsida).
Methods: Using a dataset that is nearly complete for known terminal taxa, we conducted sensitivity analyses for a set of phylodiversity and endemicity analyses. We analysed trees using three approaches: (1) an increasing proportion of tips pruned under different selection scenarios and (2) those tips phylogenetically imputed back into the tree using taxonomic classification. Tips were pruned at random and through two methods that mimicked biased sampling based on species spatial distribution using a simulated quantitative trait. We assessed predictive performance, accuracy, consistency, and spatial autocorrelation of phylogenetic diversity metrics and endemicity categorizations.
Results: As taxon sampling is reduced, predictive performance of endemicity categorization declines and uncertainty in all phylodiversity metrics increases, consistently across all pruning and imputation methods. However, the accuracy and consistency of metrics are even lower in trees with taxa imputed back into the tree at random or taxonomically at nodes, compared to estimates from pruned-only trees. The spatial autocorrelation of phylodiversity metrics is particularly affected by spatially biased pruning, demonstrating significant sensitivity to reduced and biased taxon sampling.
Main conclusions: Our work suggests exercising caution when conducting spatial phylogenetic analyses in cases of limited taxon sampling, particularly when sampling is spatially or phylogenetically biased. Taxonomic imputation using random placement within a subtree appears acceptable if sampling is phylogenetically random and at intermediate levels.
Elevational range limits in the Northwestern Himalaya
In this long-term study, I am evaluating a set of eco-evolutionary processes implicated in the establishment of elevational range limits in Betula utilis (Himalayan birch), as well as potential range shifts in response to phenological changes and biotic stressors. By integrating evolutionary ecology and genomic approaches, I aim to understand why and how species distributions are set along elevational gradients. This understanding will provide insights into the potential responses of trees in a montane system that has experienced a 1.2ºC increase in its mean temperature over the last century. My work is geared toward the dominant Himalayan birch, which establishes most treelines in the region and is a key resource for insects, birds, and humans. To achieve this, I integrate vegetation plots, microclimatic and phenological data, and functional traits to test whether biotic interactions primarily determine warmer limits, while abiotic factors set colder limits in two localities in the Northwestern Himalayas. Although both localities have a comparable elevational range, they offer a within-region comparison, as Manali receives summer monsoon rains while Sural is a drier locality set in the Himalayan rain shadow
