ScholarWorks@UMass Amherst

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  Data for "Breaking down barriers to consistent, climate-smart regulation of invasive plants - a case study of northeast states"

  Bethany A. Bradley, Evelyn M. Beaury, Emily J. Fusco, Lara Munro, Carrie Brown-Lima, Benjamin Kesler, Nancy Olmstead, and Jocelyn Parker

  We evaluated regulatory weed risk assessment protocols for six northeast states (Connecticut, Maine, Massachusetts, New Hampshire, New York, and Vermont) to identify potential barriers to 1) consistent regulated plant lists across state borders and 2) proactive regulation of species that are not yet present in the state (e.g., range-shifting invasive plant species). We present lists of evaluated, regulated, and range-shifting invasive species that northeast states could assess to achieve consistent and proactive regulation.

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  Sleeper Species Database O'Uhuru et. al. 2022

  Ayodelé O'Uhuru, Bethany A. Bradley, and Toni Lyn Morelli

  Thousands of non-native plant species have been introduced and naturalized outside of their native ranges. A small portion of these naturalized species go on to become invasive, spreading away from sites where they initially naturalized and causing negative ecological impacts. In some cases, abiotic limitations, such as cold temperatures, prevent naturalized species from becoming invasive within all or a portion of their non-native range. However, rising temperatures due to climate change could lead to rapid population growth of some naturalized populations, triggering new invasions of these ‘sleeper populations’. Here, we present a database of impact assessments for 179 species naturalized in one or more northeastern state (CT, MA, ME, NH, NY, RI, VT). This database can be used to prioritize invasive species management to prevent the awakening of high-impact sleeper populations.

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  Invasion and Global Change Meta-analysis Data

  Bianca E. Lopez, Jenica M. Allen, Jeffrey S. Dukes, Jonathan Lenoir, Montserrat Vilà, Dana M. Blumenthal, Evelyn M. Beaury, Emily J. Fusco, Toni Lyn Morelli, Cascade J. B. Sorte, and Bethany A. Bradley

  We conducted a global meta-analysis to investigate invasions, abiotic global environmental changes, and their combined effects on native species, communities, and ecosystems.We searched the Web of Science Core Collection for articles and reviews that were available in English through September 30, 2020. Search terms were chosen to identify papers reporting impacts of invasions with one of six abiotic global environmental changes (GECs: warming, nitrogen deposition, O₂ depletion, drought, CO₂ addition, and altered pH). We assessed the titles and abstracts of the 5,662 returned papers and retained those that reported the ecological effects of: (a) one or more invasive species; (b) one or more GECs; (c) both invasive species and a GEC together; and (d) also reported data for a control treatment (no invasion and at current or ambient environmental conditions). From each study, we recorded data on means and variances of each measured response in the three treatments and control; the response measures (categorized into "response classes"); the introduced invasive species and hypothesized mechanism by which the invasion impacted the ecosystem; the type of GEC factor(s) manipulated; the ecosystem setting where the experiment took place (marine, terrestrial, or freshwater); and the type of experiment (laboratory/greenhouse, field, or mesocosm).

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  Appendix 1. Database of impact assessments for 100 range-shifting invasive plants

  Mei Rockwell-Postel and Bethany A. Bradley

  Environmental Impacts Classification of Alien Taxa (EICAT) assessments of 100 invasive plants projected to shift their ranges into Connecticut, Massachusetts, New York, or Rhode Island by 2050.

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  Appendix 2. Database of impact assessment summaries for 100 range-shifting invasive plants

  Mei Rockwell-Postel and Bethany A. Bradley

  Summary reports of Environmental Impacts Classification of Alien Taxa (EICAT) assessments of 100 invasive plants projected to shift their ranges into Connecticut, Massachusetts, New York, or Rhode Island by 2050.

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  Biotic resistance to invasion is ubiquitous across ecosystems of the United States

  Evelyn M. Beaury, John T. Finn, Jeffrey D. Corbin, Valerie Barr, and Bethany A. Bradley

  The biotic resistance hypothesis predicts that diverse native communities are more resistant to invasion. However, past studies vary in their support for this hypothesis due to an apparent contradiction between experimental studies, which support biotic resistance, and observational studies, which find that native and non-native species richness are positively related at broad scales (small scale studies are more variable). Here, we present a novel analysis of the biotic resistance hypothesis using 24,456 observations of plant richness spanning four community types and seven ecoregions of the United States. Non-native plant occurrence was negatively related to native plant richness across all community types and ecoregions, although the strength of biotic resistance varied across different ecological, anthropogenic, and climatic contexts. Our results strongly support the biotic resistance hypothesis, thus reconciling differences between experimental and observational studies and providing evidence for the shared benefits between invasive species management and native biodiversity conservation.

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  Abundance vs. Impact (AvI) databases and code

  Bethany Bradley

  These data represent 1258 empirical studies presented in 201 scientific publications used to meta-analyze the relationship between invasive species abundance and ecological impact.

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  Source data for "Invasive grasses increase fire occurrence and frequency across U.S. ecoregions."

  Emily J. Fusco, John T. Finn, Jennifer K. Balch, R. Chelsea Nagy, and Bethany A. Bradley

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  Source data for "Accounting for aboveground carbon storage in shrubland and woodland ecosystems in the Great Basin"

  Emily J. Fusco, Benjamin M. Rau, Michael Falkowski, Steven Filippelli, and Bethany A. Bradley

  ESRI File Geodatabase contains 15 raster files for the Great Basin region.

  Compiled using data from years 2011-2014.

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  Data sheets for assessment of invasive species impacts

  Bethany A. Bradley

  These data sheets are an adaptation of the IUCN supported Environmental Impacts Classification of Alien Taxa (EICAT) protocol for assessment of impacts of invasive species. A text version of the protocol is available in Hawkins et al. 2015 (see readme file). The data sheets provide a standard format for reporting and summarizing invasive species impacts.

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  Cheatgrass (Bromus tectorum) percent cover data

  Bethany Bradley

  A compilation of cheatgrass (Bromus tectorum) percent cover data across the western U.S. used to train a regional land cover map as well as assess relationships to fire.

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  Model of cheatgrass (Bromus tectorum) distribution across the Great Basin, USA

  Bethany Bradley

  A description of the methods associated with this model can be found in:

  Bradley, B.A., C.A. Curtis, E.J. Fusco, J.T. Abatzoglou, J.K. Balch, S. Dadashi, and M.N. Tuanmu. “Cheatgrass (Bromus tectorum) distribution in the intermountain western United States and its relationship to fire frequency, seasonality, and ignitions”, In Press, Biological Invasions

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  Northeast Invasive Plants Data

  Tyler Cross, John T. Finn, and Bethany Bradley

  The data are distribution and ranked abundance data for thirteen invasive plants in the Northeast US compiled from various spatial repositories for invasive species. iMAP invasives data are not included in this dataset because they are not publicly available. iMAP data can be requested from individual states.

  These data form the basis of analyses presented in Cross et al. 2017. "Frequency of invasive plant occurrence is not a suitable proxy for abundance in the Northeast US Ecosphere".

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  Distribution Locations of Invasive Species (Out of the Weeds? Reduced Plant Invasion Risk with Climate Change in the Continental United States)

  Bethany Bradley and Jenica Allen

  The comma-delimited data file includes the species code (see Supplemental Online Table S2 for full species names), latitude, and longitude in decimal degrees (WGS84) for the occurence points used in model fitting. Some data use agreements prohibit the publication of coordinate data and those points have been removed.

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  Species Potential Range Predictions (Out of the Weeds? Reduced Plant Invasion Risk with Climate Change in the Continental United States)

  Bethany Bradley and Jenica Allen

  This PDF file contains the binary potential range prediction maps for each species in the dataset under current climate. The prediction map for each species lists the species code (see Supplemental Online Table S2 for full species names), areas predicted to be climatically suitable/unsuitable under current climate, and the occurrence points for the species. See the main publication for model fitting details.

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  Ignition Cause

  Emily J. Fusco, John Abatzoglou, Jennifer K. Balch, John T. Finn, and Bethany Bradley

  This dataset contains ignition points derived from the MODIS Burned Area Product (MCD45) from 2000-2012), It also contains the determined cause for each ignition.

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  Anthropogenic Ignitions

  Emily J. Fusco, John Abatzoglou, Jennifer K. Balch, John T. Finn, and Bethany Bradley

  This dataset contains ignition points derived from the MODIS Burned Area Product (MCD45) from 2000-2012), It also contains a random subset of unburned points. Both ignition and unburned points have associated anthropogenic feature data.

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  Lights, Camera...Citizen Science: Assessing the Effectiveness of Smartphone-based Video Training in Invasive Plant Identification dataset

  Jared Starr, Charles M. Schweik, Nathan Bush, Lena Fletcher, John T. Finn, Jennifer Fish, and Charles T. Bargeron

  The rapid growth and increasing popularity of smartphone technology is putting sophisticated data-collection tools in the hands of more and more citizens. This has exciting implications for the expanding field of citizen science. With smartphone-based applications (apps), it is now increasingly practical to remotely acquire high quality citizen-submitted data at a fraction of the cost of a traditional study. Yet, one impediment to citizen science projects is the question of how to train participants. The traditional “in-person” training model, while effective, can be cost prohibitive as the spatial scale of a project increases. To explore possible solutions, we analyze three training models: 1) in-person, 2) app-based video, and 3) app-based text/images in the context of invasive plant identification in Massachusetts. Encouragingly, we find that participants who received video training were as successful at invasive plant identification as those trained in-person, while those receiving just text/images were less successful. This finding has implications for a variety of citizen science projects that need alternative methods to effectively train participants when in-person training is impractical. This file is the raw data that accompanies the PLoS article.