Scanning the horizon for invasive plant threats using a data-driven approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985939%3A_____%2F22%3A00561066" target="_blank" >RIV/67985939:_____/22:00561066 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.3897/neobiota.74.83312" target="_blank" >https://doi.org/10.3897/neobiota.74.83312</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3897/neobiota.74.83312" target="_blank" >10.3897/neobiota.74.83312</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Scanning the horizon for invasive plant threats using a data-driven approach

Popis výsledku v původním jazyce

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 per-formed 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 databased 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 ar-riving, 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 evalu-ated 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.

Název v anglickém jazyce

Scanning the horizon for invasive plant threats using a data-driven approach

Popis výsledku anglicky

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 per-formed 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 databased 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 ar-riving, 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 evalu-ated 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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10618 - Ecology

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Neobiota

ISSN

1619-0033

e-ISSN

1314-2488

Svazek periodika

74

Číslo periodika v rámci svazku

Jul 15

Stát vydavatele periodika

BG - Bulharská republika

Počet stran výsledku

26

Strana od-do

129-154

Kód UT WoS článku

000847999700002

EID výsledku v databázi Scopus

2-s2.0-85134758212