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Abstract Detail

The Botany of Invasions

Marx, Hannah [1].

Plant community transcriptomics: extending axes of functional diversity to inform invasion dynamics.

An important focus of invasion biology is to investigate patterns in functional traits across species and communities to test hypotheses about how abiotic, biotic, and neutral assembly processes generate the diversity we observe. These observations are a critical component for predicting the future spread and impact of invasive species. However, it is challenging to decide which traits to compare because the function of certain traits may be contingent on the study system or stage of the introduction. Additionally, certain traits that are traditionally examined for evolutionary and systematic studies are not necessarily suitable for studies of invasive species, so restricted species-level trait data limits the feasibility of macro-ecological comparisons of invasive traits. In this talk, I present work from a pilot-study exploring the potential for using the diversity of expressed genes—functional genomic diversity (FGD)—to understand the ecological dynamics of a recent and ongoing invasion in an alpine plant streambed community. We quantified FGD with RNA-seq data sampled from 26 dominant plant species occurring along adjacent invaded and pristine communities. We summarized transcriptomic diversity (FGD) in a few different ways. We then compared FGD with more conventional analyses by quantifying functional trait diversity from a suite of characters traditionally considered for invasion ecology. From these results, I will discuss novel insights that functional genomic diversity may contribute to invasion biology, and perhaps community ecology more broadly.

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1 - University of New Mexico, Department of Biology & Museum of Southwestern Biology, Castetter Hall 1480, MSC03-2020, 219 Yale Blvd NE, Albuquerque, NM, 87131-0001, USA

functional traits
community ecology.

Presentation Type: Symposium Presentation
Session: SY2, The Botany of Invasions
Location: /
Date: Monday, July 19th, 2021
Time: 10:45 AM(EDT)
Number: SY2003
Abstract ID:902
Candidate for Awards:None

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