The Australian weed risk assessment has been promoted as a simple and effective screening tool that can help prevent the entry of weeds and invasive plants into new areas. On average, the Australian model identifies major-invaders more accurately than it does non-invaders (90% vs. 70% accuracy). While this difference in performance emphasizes protection, the overall accuracy of the model will be determined by its performance with non-invaders because the frequency of invasive species among new plant introductions is relatively low. In this study, we develop a new weed risk assessment model for the entire United States that increases non-invader accuracy. The new screening tool uses two elements of risk, establishment/spread potential and impact potential, in a logistic regression model to evaluate the invasive/weedy potential of a species. We selected 204 non-invaders, minor-invaders, and major-invaders to develop and validate the new model, and compare its performance to the Australian model using the same set of species. Performing better than the Australian model, our new model accurately identified 94.1% of major-invaders and 97.1% of non-invaders, without committing any false positives or false negatives. The new secondary screening tool we developed reduced the number of species requiring secondary evaluation from 22 to 12%. We expect that the new weed risk assessment model should significantly enhance the United State's timeliness and accuracy in regulating potential weeds.

No abstract

As part of national biosecurity programs, cargo imports, passenger baggage, and international mail are inspected at ports of entry to verify compliance with phytosanitary regulations and to intercept potentially damaging nonnative species to prevent their introduction. Detection of organisms during inspections may also provide crucial information about the species composition and relative arrival rates in invasion pathways that can inform the implementation of other biosecurity practices such as quarantines and surveillance. In most regions, insects are the main taxonomic group encountered during inspections. We gathered insect interception data from nine world regions collected from 1995 to 2019 to compare the composition of species arriving at ports in these regions. Collectively, 8,716 insect species were intercepted in these regions over the last 25 yr, with the combined international data set comprising 1,899,573 interception events, of which 863,972 were identified to species level. Rarefaction analysis indicated that interceptions comprise only a small fraction of species present in invasion pathways. Despite differences in inspection methodologies, as well as differences in the composition of import source regions and imported commodities, we found strong positive correlations in species interception frequencies between regions, particularly within the Hemiptera and Thysanoptera. There were also significant differences in species frequencies among insects intercepted in different regions. Nevertheless, integrating interception data among multiple regions would be valuable for estimating invasion risks for insect species with high likelihoods of introduction as well as for identifying rare but potentially damaging species.

The annual broadleaved weeds Ammannia auriculata Wild, and A. coccinea Rottb. are widespread and competitive in California rice (Oryza saliva L,) fields. We studied Ammannia spp. biology in a greenhouse pot experiment. Weeds were grown alone and in competition with rice (cv. M-202), and harvested six times over 122 days. Compared with growth alone, competition reduced Ammannia spp. total plant dry weight (DW), shoot DW and leaf area in all but the first harvest. However, weed height differed at only one harvest (85 days after planting). Ammannia spp. responded to competition with increased shoot:root DW ratios, increased stem:other shoot DW ratios, decreased stem diameters, fewer but elongated internodes and fewer branches. This suggests that light capture was more important than nutrient capture for maintaining Ammannia spp. growth. The weeds appear to lodge easily in rice fields because competitive growth responses make them top heavy and unstable. Weed seed DW declined by 97% in competition, which showed the importance of crop interference to Ammanma spp. controL Plasticity may help Ammannia spp. to escape common controJ practices (e.g. high crop plant densities or early herbicide application), and probably contributes to its widespread distribution. Thus, Ammannia spp. plasticity should be more fully considered when designing management strategies.introductioD

Because of the large number of potentially invasive species, and the time required to complete weed risk assessments (WRAs) with the use of the current, mandated system in the United States, species need to be prioritized for assessment and possible listing as Federal Noxious Weeds. Our objective was to rank the potential invasiveness of weedy or pest plant species not yet naturalized in the United States. We created a new model of invasiveness (hereafter the U.S. weed-ranking model) based on scoring factors within four elements: (1) invasiveness potential, or likelihood to exhibit invasive behavior; (2) geographic potential, or habitat suitability; (3) damage potential, or likely impact; and (4) entry potential, or likelihood to be introduced. The ranking score was the product of the four elements. We scored 250 species satisfactorily, from a list of 700 +. We analyzed model sensitivity to scoring factors, and compared results to those from a WRA model for Hawaii. For species not in cultivation in the United States, the top 25 species included a mix of annuals, perennials, sedges, shrubs, and trees. Most had exhibited invasive behavior in at least several other countries. Because of greater entry potential scores, the highest-scoring species were weeds in cultivation. Twenty-nine such species, out of 44 total, had scores greater than the highest scoring species not in cultivation. In comparison to the Hawaii WRA model, correlation and regression analyses indicated that the U.S. weed-ranking model produced similar, but not exact, results. The ranking model differs from other WRAs in the inclusion of entry potential and the use of a multiplicative approach, which better suited our objectives and United States regulations. Two highly ranked species have recently been listed as Federal Noxious Weeds, and we expect most top-tier species to be similarly assessed.