Research Article |
Corresponding author: Amy E. Kendig ( aekendig@gmail.com ) Academic editor: Curtis Daehler
© 2022 Amy E. Kendig, Susan Canavan, Patti J. Anderson, S. Luke Flory, Lyn A. Gettys, Doria R. Gordon, Basil V. Iannone III, John M. Kunzer, Tabitha Petri, Ian A. Pfingsten, Deah Lieurance.
This is an open access article distributed under the terms of the CC0 Public Domain Dedication.
Citation:
Kendig AE, Canavan S, Anderson PJ, Flory SL, Gettys LA, Gordon DR, Iannone III BV, Kunzer JM, Petri T, Pfingsten IA, Lieurance D (2022) Scanning the horizon for invasive plant threats using a data-driven approach. NeoBiota 74: 129-154. https://doi.org/10.3897/neobiota.74.83312
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Early detection and eradication of invasive plants are more cost-effective than managing well-established invasive plant populations and their impacts. However, there is high uncertainty around which taxa are likely to become invasive in a given area. Horizon scanning that combines a data-driven approach with rapid risk assessment and consensus building among experts can help identify invasion threats. We performed a horizon scan of potential invasive plant threats to Florida, USA—a state with a high influx of introduced species, conditions that are generally favorable for plant establishment, and a history of negative impacts from invasive plants. We began with an initial list of 2128 non-native plant taxa that are known invaders or crop pests. We built on previous invasive species horizon scans by developing data-based criteria to prioritize 100 taxa for rapid risk assessment. The semi-automated prioritization process included selecting taxa “on the horizon” (i.e., not yet in the target location and not on a noxious weed list) with climate matching, naturalization history, “weediness” record, and global commonness. We derived overall invasion risk scores with rapid risk assessment by evaluating the likelihood of each of the taxa arriving, establishing, and having an impact in Florida. Then, following a consensus-building discussion, we identified six plant taxa as high risk, with overall risk scores ranging from 75 to 100 out of a possible 125. The six taxa are globally distributed, easily transported to new areas, found in regions with climates similar to Florida’s, and can impact native plant communities, human health, or agriculture. Finally, we evaluated our initial and final lists for potential biases. Assessors tended to assign higher risk scores to taxa that had more available information. In addition, we identified biases towards four plant families and certain geographical regions of origin. Our horizon scan approach identified taxa conforming to metrics of high invasion risk and used a methodology refined for plants that can be applied to other locations.
certainty, consensus building, Florida, horizon scan, invasion, prevention, rapid risk assessment
Invasive species can negatively impact ecosystems, economies, and human health (
Horizon scanning is the systematic search to identify potential threats, emerging issues, and opportunities that can inform research and action (
Florida is one of the most important states for regulating invasive plants in the United States because nearly 85% of all non-native plants imported to the contiguous United States enter through one of Florida’s shipping ports or airports (
Here, we developed a horizon scan approach to create a ranked list of non-native plants that are likely to arrive and establish in Florida and have impacts on native biodiversity, the economy, or human health in the near future. We started with a large initial list of plant taxa that were associated with invasion. We then developed criteria and used publicly available datasets to prioritize taxa for risk assessment. This step builds on previous horizon scans, which were able to assess all taxa on initial lists. We present a ranked list of potential invasive plant threats to Florida, which can be used to inform research, management, and policy aimed at reducing invasive plant impacts.
This horizon scan was part of the Florida Invasion Threats Horizon Scan, which assessed invasion threats of freshwater and terrestrial plants (reported here), marine taxa, freshwater invertebrates, terrestrial invertebrates, and non-marine vertebrates (
We (the authors) formed the expert panel for freshwater and terrestrial plants, providing knowledge of Florida’s natural systems, existing invasive plants, relevant policy, and data analysis. Along with experts of other taxonomic groups described above, we convened a workshop for the Florida Invasion Threats Horizon Scan in December 2019. During the workshop, we designed criteria for prioritizing taxa to assess (see Assembling a list) and discuss the rapid risk assessment tool (see Assessing and scoring the taxa).
Using the horizon scan tool developed by the Centre for Agriculture and Biosciences International (CABI; an inter-governmental not-for-profit organization that provides information and expertise on agriculture and the environment), we generated an initial list of invasive taxa and crop pests (Suppl. material
We corrected the list for synonyms and accepted names using (in the order of our assigned authority): the Atlas of Florida Plants (
Nine assessors evaluated taxa using a rapid risk assessment tool modified from
We identified one or more potential pathways for taxa to arrive in Florida based on an established framework (
We scored the likelihoods of arrival, establishment, and negative impacts (environmental, socioeconomic, and human health) on a scale of 1 (very low) to 5 (very high; Fig.
Rubrics for scoring likelihood of arrival, establishment, and impacts of potential invasive plants.
Category | Criteria | Score |
---|---|---|
Arrival† | Closest observation to target location‡ and closest online seller to target location are outside of region§. | 1 |
Closest observation to target location is within region, but not nearby§, and closest online seller to target location is outside of region. | 2 | |
Closest observation to Florida and closest online seller to target location are within region, but not nearby or closest observation to target location is nearby, but not in target location, and closest online seller to target location is outside region. | 3 | |
Closest observation to target location is nearby, but not in target location, and closest online seller is within region or nearby, but not in target location. | 4 | |
The taxon has been observed or sold within target location. | 5 | |
Establishment† | No observations in areas with matching Köppen-Geiger (KG) zones to target location|. | 1 |
Few observations in one area with matching KG zones to target location. | 2 | |
Many observations in one area or few observations in multiple areas with matching KG zones to target location. | 3 | |
Many observations in multiple areas with matching KG zones to target location. | 4 | |
Criteria for score 4 plus evidence of a biological strategy that aids establishment or evidence of establishment in target location. | 5 | |
Impact | Unlikely to cause negative impacts on the native biota or abiotic environment, human well‐being, or economic systems. | 1 |
Likely to cause (a) declines in the performance (e.g., biomass, body size) of native biota, but no decline in native population sizes or (b) income loss, minor health problems, higher effort or expense to participate in activities, increased difficulty in accessing goods, or minor disruption of social activities, but no significant impact on participation in normal activities. | 2 | |
Likely to cause (a) declines in the population size(s) of native species, but no changes to the structure of communities or to the abiotic or biotic composition of ecosystems or (b) changes in the size of social activities, with fewer people participating, but the activity is still carried out. These changes to social activities could be linked to accessibility to the activity area or mild effects to human health (e.g., allergies). | 3 | |
Likely to cause (a) the local or population extinction of at least one native species, leading to reversible changes in the structure of communities, the abiotic or biotic composition of ecosystems or (b) the local disappearance of a social or economic activity from all or part of the area invaded by the alien taxon, collapse of the specific activity, switch to other activities, abandonment of activity without replacement, emigration from region, or moderate effects to human health. | 4 | |
Likely to cause (a) the replacement and local extinction of native species and will produce irreversible changes in the structure of communities and the abiotic or biotic composition of ecosystems or (b) local disappearance of a social or economic activity from all or part of the area invaded by the alien taxon or major effects to human health. | 5 |
Methods for selecting and evaluating taxa as invasive plant threats for a target location (Florida, United States). Data-based list processing led to the prioritization of 100 taxa for risk assessment. Rapid risk assessments performed by an expert panel included pathways for arrival and likelihood scores and certainty ratings for arrival, establishment, and impact. The three component likelihood scores were multiplied to get an overall score and certainty ratings were roughly averaged to get an overall certainty. Each risk assessment was evaluated with two rounds of review and a consensus-building discussion before the expert panel confirmed taxa rankings.
To estimate the likelihood of establishment (i.e., developing a self-sustaining population), we considered the distribution and number of records of the taxon within regions with Köppen-Geiger climate zones matching Florida (Table
To estimate the likelihood of negative impacts, we used a scoring rubric modified from the Invasive Species Environmental Impact Assessment protocol (
Assessments were peer-reviewed by the panel (Suppl. material
We evaluated whether peer-review and consensus building significantly affected overall risk scores with a paired two-sample t-test (before vs. after). We also evaluated how assessors and characteristics of the taxa affected overall risk scores. We fit a generalized linear regression with a negative binomial error structure to the overall risk scores with the expert who completed the assessment (N = 9), expert certainty about the overall score (very low, low, medium, or high), whether the typical habitat is terrestrial or aquatic, the number of records in the United States, and the year of the earliest occurrence record in the United States (cultivated, naturalized, and otherwise) as independent variables. We assumed the number of records and earliest record were proxies for propagule pressure (the former metric), residence time (the latter metric;
We evaluated whether plant taxonomic families were under- or overrepresented in the CABI plant list and in the final list using a resampling procedure (
To evaluate the native and introduced ranges of taxa in the final list, we researched their distributions using the Plants of the World database (for 95 of the 99 taxa;
Data and code are available at https://doi.org/10.5281/zenodo.6211243.
We found no significant difference in the means of overall risk scores before and after peer-review and consensus building (t = -1.41, 95% CI = -4.43–1.61, df = 97, P = 0.357) with an average score (± SE) of 21.3 ± 2.1 before and 22.7 ± 2.1 after. However, the overall risk scores of 14 taxa increased enough to move them into a higher risk category, with one taxon (Avena fatua) moving two categories higher. Additionally, the overall risk scores of ten taxa decreased enough post-review and consensus building to move them into a lower risk category, with one taxon (Campylopus introflexus) moving two categories lower. These larger changes in overall risk scores resulted from assessors reconsidering how to interpret available information following consensus building and rubric review (Table
There was strong evidence that the assessor and certainty level affected the overall risk score (Table
Model summary of overall risk scores, evaluated with likelihood ratio tests of nested models.
Variable | χ2 | df | P |
---|---|---|---|
Assessor | 27.02 | 8 | < 0.001 |
Certainty | 21.40 | 3 | < 0.001 |
Earliest U.S. record | 3.85 | 1 | 0.05 |
Records in United States | 1.67 | 1 | 0.20 |
Habitat (terrestrial vs. aquatic) | 0.07 | 1 | 0.79 |
Overall likelihood scores from the horizon scan of potential invasive plant threats to Florida A the overall risk scores for 99 taxa, divided into groups of high risk (score ≥ 64), medium risk (27 ≤ score < 64), and low risk (score < 27) and shaded by overall certainty rating B the number of taxa associated with each of the pathways of arrival. Multiple pathways could be assigned to a single taxon. C the relationship between certainty and the overall risk score, averaged across all taxa. Letters above bars indicate significant differences in overall risk score among certainty ratings with P < 0.05.
Earliest record and number of records. The overall risk score and A the year of the earliest record in the United States and B the number of records (displayed on a log10 scale for clarity) in the United States for the 99 taxa on the final list. Points represent data while line and shading represent model-estimated mean ± SE.
Four families were significantly overrepresented in the final list of 99 taxa compared to the number of accepted species in the family (Suppl. material
The majority (93%) of taxa on the final list had native ranges that included Europe and Central Asia, 75% included the Middle East and North Africa, and 67% included East Asia and the Pacific (Fig.
Six plant taxa received risk scores of at least 64 (Figs
Summary of the six high risk species using three of the main references used in rapid risk assessment.
Species | Native range† | Introduced countries‡ | Common uses§ | Potential impacts§ | Management approaches§ | States listed| |
---|---|---|---|---|---|---|
Ligustrum vulgare | Europe, western Asia, northern Africa | Argentina, Australia, Brazil, Canada, New Zealand, South Africa, United States | landscape (planted as a hedge or border), medicinal | host crop pests, compete with native plants, pollen allergens, poisonous berries | mechanical (pulling, digging, cutting), herbicides | 11 |
Phalaris arundinacea | Asia, Europe, Central America, North America¶, southern/eastern/ northern Africa | Ethiopia, Kenya, Tanzania, Uganda | erosion control, fodder crop, fiber, ornamental, biofuel | obstruct waterways, compete with native plants, reduce wildlife habitat quality | integrated control, burning, discing, mowing, herbicides | 10 |
Cytisus scoparius | Europe | Argentina, Australia, Bolivia, Brazil, Canada, Chile, China, India, Iran, Japan, New Zealand, South Africa, United States | ornamental, medicinal, nurse plant | compete with native plants, facilitate other invasive species, alter nutrient and water availability | integrated control, burning, grazing, mulching, pulling, cutting, herbicides, biological control | 14 |
Agrostis capillaris | central/western/ southwestern Asia, Europe, North Africa, | Argentina, Australia, Bhutan, Brazil, Canada, Chile, Greenland, India, New Zealand, Saint Helena, Saint Pierre and Miquelon, South Georgia and the South Sandwich Islands, United States | turf grass (lawns and golf), fodder, pasture, erosion control, landscape rehabilitation | competes with native plants, indirectly reduce moth population sizes through loss of native plants, pollen allergens | crop rotations, pulling, herbicides | 5 |
Avena fatua | Central Asia | Canada, United States (present in 74 other countries, but “introduced” status not provided) | fodder, forage, gene source for disease resistance, medicinal | reduce crop yields | straw burning, crop rotation, herbicides, soil cultivation, soil solarization | 4 |
Persicaria hydropiper | Europe | “introduced” status not provided, but present in 48 countries | culinary, medicinal | crop and pasture weed | herbicides | 1 |
The six taxa that were designated as high risk for invasion in Florida. Overall risk scores are in black circles (maximum possible score is 125). (Photos: Meneerke bloem, Isidre blanc, Andreas Eichler, Stefan.lefnaer, CC BY-SA 4.0; Robert Flogaus-Faust, CC BY 4.0; Rasbak, CC BY-SA 3.0; Willow, CC-BY 2.5; Mary Joyce, Katrice Baur, scottq1, rae117, CC BY-NC 4.0; Christian Grenier, CC0 1.0).
Twenty-three taxa received medium risk scores (27 ≤ score < 64; Fig.
Seventy taxa received low risk scores (< 27; Fig.
The most likely pathway of arrival for the taxa on the final list was escape from confinement (Fig.
Our horizon scan of invasive plant threats to Florida identified six taxa that have a high risk of becoming invasive in the state in the near future (5–15 years). The horizon scanning process helped us identify taxa that should undergo more thorough risk assessments and potentially receive policy restrictions or research priority. Our reliance on existing databases allowed us to quickly evaluate many taxa in a manner than can be applied to future horizon scans. Further, we used this case study to assess biases in the horizon scan process that should be taken into consideration in future horizon scans of invasive plants.
Although we used databases to reduce the number of taxa on our list, it was necessary to use expertise to perform rapid risk assessments, review, and consensus building. These expert-based processes are therefore not repeatable, but we aimed to increase transparency by providing the assessments and reviews (Suppl. material
Overall risk scores were positively related to overall certainty ratings. We hypothesize that this occurred because more available data can contribute to higher certainty and provide more evidence that a taxon may arrive, establish, or have impacts. Similarly, risk scores were negatively related to the year of the earliest U.S. record. We hypothesize that taxa with earlier and more records of occurrence in the United States are likely to be better represented in English-language texts than less common or more recently detected taxa, leading to more evidence for arrival, establishment, and impacts. Efforts to synthesize and standardize information about invasive species (
We evaluated taxonomic and geographic biases in the final horizon scan list and taxonomic biases in the initial CABI list. These biases may indicate shared characteristics of invasive plants or cultural biases in the CABI databases. While we cannot distinguish between these two causes, we look to previous studies for insights. The families Juncaceae (rushes), Poaceae (grasses), Polygonaceae (knotweeds), and Rosaceae (roses) were significantly overrepresented in both the final horizon scan list and the initial CABI list compared to the number of taxa in these families. These families are similarly overrepresented in global lists of naturalized plants (
Most of the taxa that made our final list were native to Europe, Asia, and North Africa. This result is likely a combination of shared characteristics of invasive plants and cultural biases in the initial CABI list. Europe is the native range for a disproportionately high number of naturalized plant species relative to the number of native plant species (
Overall scores were calculated by multiplying likelihoods of arrival, establishment, and impact (
We identified “escape from confinement” as the most likely pathway for taxa on our final list to arrive in Florida’s natural areas, which is consistent with a global analysis of invasive plants (
Taxa on our final list were also likely to arrive in Florida’s natural areas as transport contaminants or transport stowaways. Florida’s seaports are some of the most active in the country (
This horizon scan of invasive plant threats to Florida provides a first step in reducing the impacts of invasive species on Florida’s natural systems. Like other horizon scans of potential invasive species, the generated list informs future research efforts and policy (e.g.,
Here we presented a horizon scan of 2128 plant taxa, identifying six with a high invasion risk for Florida in the near future and 93 with medium or low invasion risk. The horizon scan process therefore can potentially reduce the number of taxa requiring thorough risk assessments by three orders of magnitude. The results provide researchers, regulators, and private and public land managers with a practicable list of high risk taxa to focus on. Given the substantial impacts and costs of invaders in Florida, the ability to differentiate and focus efforts on high probability threats is critical.
We thank Dale Laughinghouse and Seokmin Kim for help with processing the list, Julie Lockwood and Helen Roy for guidance on the horizon scan process, and all other participants of the Florida Invasion Threats Horizon Scan for constructive discussions. We thank Jane Molofsky, Gerry Moore, Curtis Daehler, and an anonymous reviewer for helpful feedback on the manuscript. Fig.
We thank the Florida Fish and Wildlife Conservation Commission and UF/IFAS Dean for Research for funding this project.
Methods S1
Data type: Supplementary methods
Explanation note: Methods for trimming the list of potential invasive species based on several criteria.
Table S1
Data type: Horizon scan criteria.
Explanation note: Potential invasive plant species provided by the CABI Horizon Scan Tool, their synonyms, and their values for criteria described in Suppl. material
Table S2
Data type: Rapid risk assessments.
Explanation note: Reviewed rapid risk assessments of the 99 plant species in the final list, ordered by overall score.
Table S3
Data type: Statistical results.
Explanation note: Test of under- or overrepresentation of plant families in the final horizon scan list based on resampling of accepted species from The Plant List database.
Table S4
Data type: Statistical results.
Explanation note: Test of under- or overrepresentation of plant families in the initial CABI list based on resampling of accepted species from The Plant List database.