Document Type

Dataset/Spreadsheet

Media Type

Dataset/Spreadsheet

Abstract

Biological invasions resulting from anthropogenic activities are one of the greatest threats to maintaining ecosystem functioning and native biodiversity. Invasions are especially problematic when the invading species behaves as an ecosystem engineer that is capable of transforming ecosystem structure, function, and community dynamics. Of particular concern is the spread of emergent wetland grasses whose root systems alter hydrology and structural stability of soils, modify ecosystem functions, and change community dynamics and species richness. To address the threats posed to ecosystems across the globe, management practices focus on the control and removal of invasive grasses. However, it remains unclear how severely invasive grasses alter ecosystem functions and whether alterations persist after invasive grass removal, limiting our ability to determine if management practices are truly sufficient to fully restore ecosystems. Here, we conducted a meta-analysis to quantify ecological alterations and the efficacy of management following the invasion of Spartina alterniflora and Phragmites australis, two common and pervasive invaders in coastal wetlands. Our results indicate that S. alterniflora and P. australis significantly alter measures of ecosystem functioning and organismal abundance. Invaded ecosystems had significant elevations in abiotic carbon and nitrogen fixation and uptake in areas with invasive grasses, with differential photosynthetic pathways of these two grass species further explaining carbon fluxes. Moreover, evidence from our analyses indicates that management practices may not adequately promote recovery from invasion, but more data are needed to fully assess management efficacy. We call for future studies to conduct pairwise comparisons between uninvaded, invaded, and managed systems and provide research priorities.

DOI

10.1007/s10530-021-02540-5

Publication Date

1-1-2021

Comments

Includes data and R code

Wails et al BIOL INV data.xlsx (536 kB)
Dataset (536.7Kb)

Wails et al BIOL INV permutations.Rmd (23 kB)
R code - Permutational analysis (23.41Kb)

Wails et al BIOL INV bootstrapping.Rmd (7 kB)
R code - boostrapping (7.797Kb)

Department

Department of Biological Sciences

Language

eng

Publisher

Biological Invasions

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