Author

Aaron S. David

Archbold Biological StationORCID 0000-0002-0802-7799Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:ecology & biodiversity· 3 Organism:plant (other)· 3 Assay:field survey / ecological data· 2 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Assay:metagenomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Christopher A. SearcyiD· 2 shared Michelle E. AfkhamiiD· 2 shared Adam Thomas ClarkiD· 1 shared Brianna K. AlmeidaiD· 1 shared Caitlin C. MothesiD· 1 shared Catalina EstradaiD· 1 shared Daniel RevilliniiD· 1 shared Daniela Konrad· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersEcology

Christopher A. SearcyORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

Drivers of individual plant species contributions to β-diversity are scale-dependent

Rona Learmonth, Francis Q. Brearley, Adam Thomas Clark, Aaron S. David, Catalina Estrada, Fatih Fazlioglu, Ivan de Klee, Daniela Konrad, Lizzie Lemon, Olivia Millen, Nell J. Pates, Linda Pieber, Megan Sherlock, Elizabeth G. Simpson, Scott G. Ward, , William D. Pearse

The paper examines how species traits, phylogeny, and introduction status affect β-diversity contributions across different spatial scales using plant community data.

Oikos · Jun 22, 2026Peer-reviewedEcology

Climate variability disrupts mutualism-driven increases in population persistence

Vicki W. Li, Joshua C. Fowler, Aaron S. David, Sharon Y. Strauss, Christopher A. Searcy, Michelle E. Afkhami

The paper shows mutualistic fungal endophytes increase grass population persistence but decline under high climate variability, threatening long-term species survival.

Nature Ecology & Evolution · Jan 5, 2026Peer-reviewedEcology

The microbial landscape: soil microbiome properties predict plant species distributions

Daniel Revillini, Caitlin C. Mothes, Brianna K. Almeida, Katherine T. Charton, Stephanie M. Koontz, Aaron S. David, Michelle E. Afkhami, Christopher A. Searcy

The paper uses machine learning to show that soil microbiome properties can predict plant species distributions, with microbial predictors being as important as abiotic factors for some species.

bioRxiv · Oct 14, 2025 · PreprintEcology