About

The Daru lab studies why plant species are distributed the way they are, how they achieved these present-day distributions and how to set conservation priorities to safeguard their future. We do this through integrated approaches from the fields of biodiversity informatics (methods and tools development), herbarium collections, phylogenetics and genomics. We work in the field, herbarium, wet lab, and on high-performance computing clusters.

Research topics

• Ecology
• Biology
• Evolutionary biology
• Geography
• Cartography

Selected publications

• Widespread homogenization of plant communities in the Anthropocene

  Nature Communications · 2021 · 162 citations

  1st authorCorresponding
  • Ecology
  • Biology
  • Geography

  Native biodiversity decline and non-native species spread are major features of the Anthropocene. Both processes can drive biotic homogenization by reducing trait and phylogenetic differences in species assemblages between regions, thus diminishing the regional distinctiveness of biotas and likely have negative impacts on key ecosystem functions. However, a global assessment of this phenomenon is lacking. Here, using a dataset of >200,000 plant species, we demonstrate widespread and temporal decreases in species and phylogenetic turnover across grain sizes and spatial extents. The extent of homogenization within major biomes is pronounced and is overwhelmingly explained by non-native species naturalizations. Asia and North America are major sources of non-native species; however, the species they export tend to be phylogenetically close to recipient floras. Australia, the Pacific and Europe, in contrast, contribute fewer species to the global pool of non-natives, but represent a disproportionate amount of phylogenetic diversity. The timeline of most naturalisations coincides with widespread human migration within the last ~500 years, and demonstrates the profound influence humans exert on regional biotas beyond changes in species richness.

  DOI

• phyloregion: R package for biogeographical regionalization and macroecology

  Methods in Ecology and Evolution · 2020 · 154 citations

  1st authorCorresponding
  • Ecology
  • Biology
  • Evolutionary biology

  Abstract Biogeographical regionalization is the classification of regions in terms of their biota and is key to our understanding of the ecological and historical drivers affecting species distribution in macroecological or large‐scale conservation studies. However, despite the mass production of species distributions and phylogenetic data, statistical and computational infrastructure to successfully incorporate, manipulate and analyse such massive amounts of data had not been fully developed. Here, we present phyloregion , a statistical package for the analysis of biogeographical regionalization and macroecology in the R computing environment, tailored for mega phylogenies and macroecological datasets of ever‐increasing size and complexity. Compared to available packages, phyloregion is several times faster and allocates less memory than other packages for analysis of alpha diversity (including phylogenetic diversity, phylogenetic endemism and evolutionary distinctiveness and global endangerment) and beta diversity (including cluster analysis, determining optimal number of clusters and evolutionary distinctiveness of regions). We demonstrate the scalability of the package to large datasets with comprehensive phylogenies and global distribution maps of squamate reptiles (amphisbaenians, lizards and snakes), and show that different phyloregions differ strongly in evolutionary distinctiveness across scales. Visualization tools allow graphical exploration of the generated patterns of biogeographical regionalization and macroecology in geographical space. Ultimately, phyloregion will facilitate rapid biogeographical analyses that will accommodate the ongoing mass production of species occurrence records and phylogenetic datasets at any scale and for any taxonomic group into completely reproducible R workflows.

  DOI

• Endemism patterns are scale dependent

  Nature Communications · 2020 · 113 citations

  1st authorCorresponding
  • Ecology
  • Geography
  • Biology

  Areas of endemism are important in biogeography because they capture facets of biodiversity not represented elsewhere. However, the scales at which they are relevant to research and conservation are poorly analysed. Here, we calculate weighted endemism (WE) and phylogenetic endemism (PE) separately for all birds and amphibians across the globe. We show that scale dependence is widespread for both indices and manifests across grain sizes, spatial extents and taxonomic treatments. Variations in taxonomic opinions-whether species are treated by systematic 'lumping' or 'splitting'-can profoundly affect the allocation of WE hotspots. Global patterns of PE can provide insights into complex evolutionary processes but this congruence is lost at the continental to country extents. These findings are explained by environmental heterogeneity at coarser grains, and to a far lesser extent at finer resolutions. Regardless of scale, we find widespread deficits of protection for endemism hotspots. Our study presents a framework for assessing areas for conservation that are robust to assumptions on taxonomy, spatial grain and extent.

  DOI

Recent grants

• Collaborative Research: Leveraging historical collections and new surveys to characterize foundational shifts in vital symbioses in the threatened Arctic

  NSF · $144k · 2020–2023

• Collaborative Research: Leveraging historical collections and new surveys to characterize foundational shifts in vital symbioses in the threatened Arctic

  NSF · $30k · 2023–2025

• Collaborative Research: phyloregion, computational infrastructure for biogeographic regionalization and macroecology in the R computing environment

  NSF · $585k · 2021–2024

• Collaborative Research: phyloregion, computational infrastructure for biogeographic regionalization and macroecology in the R computing environment

  NSF · $427k · 2023–2026

Frequent coauthors

• T. Jonathan Davies

  University of British Columbia

  44 shared

• Kowiyou Yessoufou

  University of Johannesburg

  42 shared

• Michelle van der Bank

  University of Johannesburg

  38 shared

• Olivier Maurin

  Royal Botanic Gardens, Kew

  22 shared

• Tristan Charles‐Dominique

  AgroParisTech

  12 shared

• William J. Bond

  University of Cape Town

  11 shared

• A. Muthama Muasya

  University of Cape Town

  8 shared

• Rikki Gumbs

  Zoological Society of London

  8 shared

Labs

• Daru LabPI

Similar researchers at Stanford University

• Yi Cuih-287
• Zhenan Baoh-224
• Karl Deisserothh-218
• Michael Snyderh-215
• Roger Blandfordh-205