Managing invasive species with prevention and early‐detection strategies can avert severe ecological and economic impacts. Horizon scanning, an evidence‐based process combining risk screening and consensus building to identify threats, has become a valuable tool for prioritizing invasive species management and prevention. We assembled a working group of experts from academic, government, and nonprofit agencies and organizations, and conducted a multi‐taxa horizon scan for Florida, USA, the first of its kind in North America. Our primary objectives were to identify high‐risk species and their introduction pathways, to detail the magnitude and mechanism of potential impacts, and, more broadly, to demonstrate the utility of horizon scanning. As a means to facilitate future horizon scans, we document the process used to generate the list of taxa for screening. We evaluated 460 taxa for their potential to arrive, establish, and cause negative ecological and socioeconomic impacts, and identified 40 potential invaders, including alewife, zebra mussel, crab‐eating macaque, and red swamp crayfish. Vertebrates and aquatic invertebrates posed the greatest invasion threat, over half of the high‐risk taxa were omnivores, and there was high confidence in the scoring of high‐risk taxa. Common arrival pathways were ballast water, biofouling of vessels, and escape from the pet/aquarium/horticulture trade. Competition, predation, and damage to agriculture/forestry/aquaculture were common impact mechanisms. We recommend full risk analysis for the high‐risk taxa; increased surveillance at Florida's ports, state borders, and high‐risk pathways; and periodic review and revision of the list. Few horizon scans detail the comprehensive methodology (including list‐building), certainty estimates for all scoring categories and the final score, detailed pathways, and the magnitude and mechanism of impact. Providing this information can further inform prevention efforts and can be efficiently replicated in other regions. Moreover, harmonizing methodology can facilitate data sharing and enhance interpretation of results for stakeholders and the general public.

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.

Climate change is increasing the frequency and intensity of extreme events like drought and flooding, which threaten to amplify other global change drivers such as species invasion. We investigate the effect of wet and dry extreme precipitation regimes on invasive species' abundances in northern tallgrass prairies. Because soil moisture is a key determinant of prairie composition, theory and evidence suggest drought conditions will hinder invasion, whereas wetter conditions will enhance invasion. To test this hypothesis, we explored the effect of precipitation on invasive plant species abundance from 2010 to 2019 in 25 managed prairies using observations from 267 transects comprising 6675 plots throughout western Minnesota, USA. We estimated how increases in the number of extremely wet or dry months in a year altered overall invasive species abundance and the abundance of the highly invasive grasses Poa pratensis and Bromus inermis. We found that a greater occurrence of abnormally wet months increased invasive species abundance but found mixed evidence that abnormally dry conditions hindered invasion. Further, more moderately wet and dry months reduced native grass abundance. Together, these results suggest that more frequent extremely wet months may intensify invasive dominance and that dry months may not counterbalance these trends. Given the considerable uncertainty still surrounding the interactive effects of climate change and invasion on native plant communities, this research represents an important step toward quantifying the complex influence of precipitation extremes on invasion dynamics in managed ecosystems of critical conservation concern.

Diversity and nitrogen addition have positive relationships with plant productivity, yet climate‐induced changes in water availability threaten to upend these established relationships. Using long‐term data from three experiments in a mesic grassland (ranging from 17 to 34 yr of data), we tested how the effects of species richness and nitrogen addition on community‐level plant productivity changed as a function of annual fluctuations in water availability using growing season precipitation and the Standardized Precipitation‐Evapotranspiration Index (SPEI). While results varied across experiments, our findings demonstrate that water availability can magnify the positive effects of both biodiversity and nitrogen addition on productivity. These results suggest that productivity responses to anthropogenic species diversity loss and increasing nitrogen deposition could depend on precipitation regimes, highlighting the importance of testing interactions between multiple global change drivers.