Thin lines between native and invasive aquatic plants are common, posing challenges for response efforts
Data files
Jul 24, 2024 version files 1.26 MB
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R_AqTerInv.zip
1.25 MB
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README.md
9.22 KB
Abstract
Lines separating native and invasive plant species can be thin due to close relatedness, obscured by cryptic invasions, or breached by hybridization. Past work suggests these phenomena are especially prevalent in aquatic systems. This could arise from strong filters imposed by aquatic environments magnifying the importance of “preadaptation”—non-native species succeeding where closely related native species occur due to shared traits. If so, there should be stronger signals of preadaptation in aquatic than terrestrial plant invasions, with implications for management. I tested for a stronger influence of preadaptation in aquatic than terrestrial invasions by comparing the relatedness of invasive and native species in aquatic vs. terrestrial flora of the Midwestern USA using herbarium records and taxonomic and phylogenetic analyses. I predicted that aquatic species would constitute an evolutionarily distinct subset of plants; aquatic invaders would be more closely related, taxonomically and phylogenetically, to native aquatic plants than terrestrial invaders are to their native counterparts; and aquatic invaders from the Midwest’s primary donor region (the Palearctic) would be more closely related to Midwestern species than are Palearctic aquatic plants that are not invasive in the Midwest. Findings supported the evolutionary legacy of adaptation to aquatic environments being reflected in thin lines separating invasive and native aquatic plants. Aquatic species constituted an evolutionarily distinct subset of plants, and invasive aquatic plants were more closely related to native aquatic plants (taxonomically and phylogenetically) than terrestrial invaders were to terrestrial native species. Additionally, aquatic plants of the Palearctic that are invasive in the Midwest were more closely related to Midwestern natives (phylogenetically, but not taxonomically) than were their non-invasive counterparts, reinforcing the role of preadaptation.
Synthesis and applications: Thin lines separating native from invasive aquatic plants pose challenges for response efforts. For resource managers, the prevalence of cryptic invasions requires dedicated, robust approaches to surveillance. For outreach, finer distinctions between native and invasive necessitate nuanced approaches to communication and education. When control is needed, it should be implemented cautiously to minimize non-target impacts to close native relatives, but thoroughly enough to prevent native relatives being displaced by competition and/or introgression.
https://doi.org/10.5061/dryad.7h44j1030
Data, consisting of geographic species lists and a phylogeny, were derived from existing sources and adapted for this study. All sources of data are cited both within the associated manuscript and in the README. The data have been processed in R, and all processed data and R code necessary to reproduce the analyses are included with this submission.
The dataset includes:
data/processed_data/aq_terr.spp.rds: A list of aquatic and terrestrial plant species for the Midwestern study region. This list includes both invasive and native species. Identities of invasive species were assembled from priority lists of the Minnesota Aquatic Invasive Species Research Center (MAISRC 2022), the Minnesota Invasive Terrestrial Plants and Pests Center (Morey & Venette 2021), and the Invasive Plants Association of Wisconsin (IPAW 2003). A previously assembled list of invasive plants in Illinois and Wisconsin was also incorporated (Larkin 2012). For these invasive species and, additionally, the native plant species of the region, a comprehensive checklist of vascular plants was assembled using herbarium records. These included occurrences for all native and non-native species recorded in Minnesota, Wisconsin, and Illinois across 233 herbaria, with records accessed through SEINet (2022).
Column names
- “scientificName”: Scientific name
- “genus”: Genus for the scientific name
- “specificEpithet”: Specific epithet for the scientific name
- “taxonRank”: Whether the taxon is a designated species, subspecies, form, or variety
- “family”: The plant family to which the taxon belongs
- “majorGroup”: Whether the taxon is an angiosperm (A) or gymnosperm (G)
- “Hybrid”: Whether the taxon is designated as a hybrid taxon
- “speciesLevel”: The name of the taxon at the species level. These are synonymous with “scientificName” for taxa at the species level, or a higher rank version of taxa identified to variety, subspecies, or form.
- “aquatic”: Whether the taxon is treated as aquatic (1) or terrestrial (0)
- “MW.WIS”: The Wetland Indicator Status of the taxon for the Midwestern study region (FAC = Facultative, FACU = Facultative to upland, FACW = Facultative to wetland, OBL = Obligate wetland)
- “inv”: Whether the taxon is (1) or is not (0) one of the focal invasive species
- “hyb_nat”: Whether an invasive taxon hybridizes with a native species (1) or does not (0)
- “splicedScientificName”: The “scientificName” with spaces replaced with underscores
data/processed_data/nonnat.focal.rds: To exclude other non-native species (beyond the focal invasives), a comprehensive list of non-native vascular plants of the continental U.S. (Simpson et al. 2022) was adapted for the study region.
Column names
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“scientificName”: Scientific name
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“splicedScientificName”: The ”scientificName” with spaces replaced with underscores
data/processed_data/Palearc.Umw.spp.rds: To test whether species from this donor region that are more closely related to species of the Midwest were more likely to have become invaders there, a list of aquatic plant species from the Palearctic region published by Murphy et al. (2019) was adapted for the study and combined with the list of aquatic plant species for the Midwest study region.
Column names
- “scientificName”: Scientific name
- “family”: The plant family to which the taxon belongs
- “genus”: Genus for the scientific name
- “region”: Whether the species is from the Murphy et al. (2019) Palearctic list (“PA”) or the Midwestern list assembled for the current study (“UMW”)
- “taxonRank”: Whether the taxon is a designated species, subspecies, form, or variety
For phylogenetic analyses:
- All phylogenies are stored as R objects of class “phylo” with edge, node, and tip attributes
- data/processed_data/aq_terr.tr.rds, aq.tr.rds, terr.tr.rds: A synthesis tree for the Midwestern study region (composed of native and non-native and aquatic and terrestrial species) was built using a megaphylogeny of >350,000 seed plants (Smith & Brown 2018). Aquatic and terrestrial subtrees were also built.
- data/processed_data/Palearc.Umw.spp.rds: A separate phylogeny combining aquatic species native to the Midwestern study region plus those native to the Palearctic donor region, also derived from the Smith & Brown (2018) megaphylogeny.
- data/processed_data/aq_terr.match.rds, aq.match.rds, terr.match.rds, spp.Palearc.match.rds: These are files for which the focal species lists described above and the phylogenies have been matched/aligned to enable phylogenetic analyses.
- data/processed_data/phydist.dat.rds: This data data file is generated by the script file “11**DataAnal**PhyDist.R” and includes the phylogenetic distance and its z-score for focal invasive species and their nearest native relative.
- Column names
- “Type”: Whether an “Aquatic” or “Terrestrial” invasive species
- “phydist.z”: Z-transform of phylogenetic distance
- “phydist”: Untransformed phylogenetic distance
- Column names
- data/processed_data/phydist.palearc.dat.rds: This data file is generated by the script file “13**DataAnal**PalearcRelatedness.R” and includes the phylogenetic distance and its z-score for focal Palearctic aquatic plant species and their nearest Midwestern native relative.
- Column names
- “Species”: Scientific name of Palearctic species
- “Type”: Whether the species is an “Invader” or “Non-invader” in the Midwest study region
- “phydist.z”: Z-transform of phylogenetic distance
- “phydist”: Untransformed phylogenetic distance
- Column names
The “scripts” subfolder contains 9 R script files for analyzing these data and generating the figures included in the study.
Wherever “NA” occurs throughout the above data sets, it represents “not applicable,” indicating that a given column for a given row is missing or undefined.
Description of the data and file structure
- All data and code necessary to repeat the analyses in this study are included in a compressed (.zip) folder associated with an R Project (RAqTerInv).
- All code files are contained within a ‘scripts’ subfolder.
- The scripts depend upon data held within ‘data/processed_data’.
- Running the scripts produces HTML Markdown files in ‘output/html’ and figures in ‘output/figs_tables’.
- Scripts are set up to be executed by running their respective calls in ‘00_Render’. To run a script directly from the script file, rather than by calling it from the render file, the ‘../’ prefix associated with all file paths in the script needs to be removed. e.g., readRDS(“../data/processed_data/aq_terr.match.rds” should be changed to readRDS(“data/processed_data/aq_terr.match.rds”).
Sharing/Access information
Species names were derived from the following sources:
- IPAW (2003) IPAW’s Working List of Invasive Plants of Wisconsin. Invasive Plants Association of Wisconsin. https://ipaw.org/the-problem/new-threats/. 26-Oct-2022.
- Larkin, D.J. (2012) Lengths and correlates of lag phases in upper-Midwest plant invasions. Biological Invasions, 14, 827-838. 10.1007/s10530-011-0119-3
- MAISRC (2022) Priority Species List. Minnesota Aquatic Invasive Species Research Center, St. Paul, MN. https://maisrc.umn.edu/about-ais. 26-Oct-2022.
- Morey, A.C. & Venette, R.C. (2021) A participatory method for prioritizing invasive species: Ranking threats to Minnesota’s terrestrial ecosystems. Journal of Environmental Management, 290, 112556. https://doi.org/10.1016/j.jenvman.2021.112556
- Murphy, K., Efremov, A., Davidson, T.A., Molina-Navarro, E., Fidanza, K., Crivelari Betiol, T.C., Chambers, P., Tapia Grimaldo, J., Varandas Martins, S., Springuel, I., Kennedy, M., Mormul, R.P., Dibble, E., Hofstra, D., Lukács, B.A., Gebler, D., Baastrup-Spohr, L. & Urrutia-Estrada, J. (2019) World distribution, diversity and endemism of aquatic macrophytes. Aquatic Botany, 158, 103127-103127. 10.1016/j.aquabot.2019.06.006
- SEINet (2022) SEINet data portal. SEINet. https://swbiodiversity.org/seinet/collections/index.php. 28-Oct-2022.
- Simpson, A., Fuller, P., Faccenda, K., Evenhuis, N., Matsunaga, J. & Bowser, M. (2022) United States Register of Introduced and Invasive Species (US-RIIS) (ver. 2.0, November 2022). U.S. Geological Survey.
- Smith, S.A. & Brown, J.W. (2018) Constructing a broadly inclusive seed plant phylogeny. American Journal of Botany,105, 302-314. https://doi.org/10.1002/ajb2.1019
Code/Software
The code structure and its workflow and relationship to the datasets are described above. All data processing and analysis was performed in R (versions 4.2.3 up to 4.4.1) via R Studio. The specific R version and all loaded packages and dependencies are provided as an “R Information” section at the end of each HTML markdown associated with each R script.