Niche models differentiate potential impacts of two aquatic invasive plant species on native macrophytes

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Abstract

Potamogeton crispus (curlyleaf pondweed) and Myriophyllum spicatum (Eurasian watermilfoil) are widely thought to competitively displace native macrophytes in North America. However, their perceived competitive superiority has not been comprehensively evaluated. Coexistence theory suggests that invader displacement of native species through competitive exclusion is most likely where high niche overlap results in competition for limiting resources. Thus, evaluation of niche similarity can serve as a starting point for predicting the likelihood of invaders having direct competitive impacts on resident species. Across two environmental gradients structuring macrophyte communities-water depth and light availability-both P. crispus and M. spicatum are thought to occupy broad niches. For a third dimension, phenology, the annual growth cycle of M. spicatum is typical of other species, whereas the winter-ephemeral phenology of P. crispus may impart greater niche differentiation and thus lower risk of native species being competitively excluded. Using an unprecedented dataset comprising 3404 plant surveys from Minnesota collected using a common protocol, we modeled niches of 34 species using a probabilistic niche framework. Across each niche dimension, P. crispus had lower overlap with native species than did M. spicatum; this was driven in particular by its distinct phenology. These results suggest that patterns of dominance seen in P. crispus and M. spicatum have likely arisen through different mechanisms, and that direct competition with native species is less likely for P. crispus than M. spicatum. This research highlights the utility of fine-scale, abundance-based niche models for predicting invader impacts.

Original languageEnglish (US)
Article number162
JournalDiversity
Volume12
Issue number4
DOIs
StatePublished - Apr 1 2020

Bibliographical note

Funding Information:
This research was funded by the Minnesota Environmental and Natural Resources Trust Fund as recommended by the Minnesota Aquatic Invasive Species Research Center (MAISRC) and the Legislative-Citizen Commission on Minnesota Resources. The APC was funded by MAISRC. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. CON-75851, project 00074041. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. We thank Justin Townsend, Noah Berg, Carolyn Kalinowski, James Dickson, and Natalie Holmes for their help in inventorying plant survey data. We are very grateful to all of the surveyors who generously organized and shared their data with us. For their exceptional contributions of data, we are particularly indebted to James Johnson of Freshwater Scientific Services, Matt Berg of Endangered Resource Services, Meg Rattei of Barr Engineering, Eric Fieldseth of AIS Consulting Services, Steve McComas of BlueWater Science, Jill Sweet of the Minnhehaha Creek Watershed District, Cole Loewen of the Clearwater River Watershed District, Britta Belden of the Capitol Region Watershed District, the Minnesota Department of Natural Resources Invasive Species Program and Lake Ecology Unit, Andrea Prichard of Ramsey Conservation District, and Rob Brown of the Minneapolis Parks District. We thank Ray Newman for the invitation to contribute to this special issue and three anonymous reviewers for comments that substantially improved the manuscript.

Funding Information:
Funding: This research was funded by the Minnesota Environmental and Natural Resources Trust Fund as recommended by the Minnesota Aquatic Invasive Species Research Center (MAISRC) and the Legislative-Citizen Commission on Minnesota Resources. The APC was funded by MAISRC. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. CON-75851, project 00074041. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Publisher Copyright:
© 2020 by the authors.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Abundance-based niche
  • Competition
  • Depth
  • Light availability
  • Macrophyte
  • Phenology
  • Probabilistic niche model
  • Trait probability distribution

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