Goulet-Scott, B. | Search bioRxiv

bioRxiv2023

A multi-dimensional selective landscape drives adaptive divergence between and within closely related Phlox species

Natural selection shapes diversity across micro and macro-evolutionary scales. Selection causes local adaptation across populations within species and is simultaneously responsible for much of the divergence between species. However, it is unclear if either the force of or the response to selection is the same or different across these scales. Here we show that natural selection drives adaptive divergence between closely related species in a pattern that is distinct from local adaptation within a species. We use reciprocal common-garden transplant experiments across three species of Phlox wildflowers to show widespread adaptive divergence causing species to have highest fitness in their native habitats. Using provenance trials, we also find that one of these Phlox species has strong local adaptation between populations. We compare the axes of divergence and selection between these two scales of diversity and discover that one suite of traits predicts fitness differences between species and that an independent suite of traits predicts fitness variation within species across individuals. Our work reveals how forces of selection can both drive key divergence between species, allowing for and causing speciation, while simultaneously causing extensive diversity that is maintained across populations within a species. The selection landscape is complex and multidimensional

evolutionary biology↗

bioRxiv2022

A dataset of 5 million city trees: species clustering and climate effects in urban forests

Sustainable cities depend on urban forests. City trees improve our health, clean the air, store CO2, and cool local temperatures. Comparatively less is known about urban forests as ecosystems, particularly their spatial composition, nativity statuses, biodiversity, and tree health. Here, we assembled and standardized a new dataset of N=5,132,890 trees from 63 of the largest US cities with detailed information on location, health, nativity status, and species. We further designed new tools to analyze the ecosystem structure of urban forests, including spatial clustering and abundance of native trees, and validate these tools in comparison to past methods. We show that city trees are significantly clustered by species in 93% of cities, potentially increasing pest vulnerability (even in cities with biodiverse urban forests). Further, non-native species significantly homogenize urban forests across cities, while native trees comprise 0.44%-85.6% (median=45.6%) of city tree populations. Native trees are less frequent in drier cities, and indeed climate significantly shapes both nativity and biodiversity in urban forests. Parks are more biodiverse than urban settings. Compared to past work which focused primarily on canopy cover and species richness, we show the importance of analyzing spatial composition and nativity statuses in urban forests (and we created new datasets and tools to do so). This dataset could be analyzed in combination with citizen-science datasets on bird, insect, or plant biodiversity; social and demographic data; or data on the physical environment. Urban forests offer a rare opportunity to intentionally design biodiverse, heterogenous, rich ecosystems.

ecology↗