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.

Weed risk assessments (WRA) are used to identify plant invaders before introduction. Unfortunately, very few incorporate uncertainty ratings or evaluate the effects of uncertainty, a fundamental risk component. We developed a probabilistic model to quantitatively evaluate the effects of uncertainty on the outcomes of a question-based WRA tool for the United States. In our tool, the uncertainty of each response is rated as Negligible, Low, Moderate, or High. We developed the model by specifying the likelihood of a response changing for each uncertainty rating. The simulations determine if responses change, select new responses, and sum the scores to determine the risk rating. The simulated scores reveal potential variation in WRA risk ratings. In testing with 204 species assessments, the ranges of simulated risk scores increased with greater uncertainty, and analyses for most species produced simulated risk ratings that differed from the baseline WRA rating. Still, the most frequent simulated rating matched the baseline rating for every High Risk species, and for 87% of all tested species. The remaining 13% primarily involved ambiguous Low Risk results. Changing final ratings based on the uncertainty analysis results was not justified here because accuracy (match between WRA tool and known risk rating) did not improve. Detailed analyses of three species assessments indicate that assessment uncertainty may be best reduced by obtaining evidence for unanswered questions, rather than obtaining additional evidence for questions with responses. This analysis represents an advance in interpreting WRA results, and has enhanced our regulation and management of potential weed species.

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Since its introduction into the Southern Appalachians in the 1950s, the balsam woolly adelgid, Adelges piceae Ratzeburg (Hemiptera: Adelgidae), has devastated native populations of Fraser fir, Abies fraseri (Pursh) Poir. (Pinales: Pinaceae), and has become a major pest in Christmas tree plantations requiring expensive chemical treatments. Adelges piceae—resistant Fraser fir trees would lessen costs for the Christmas tree industry and assist in the restoration of native stands. Resistance screening is an important step in this process. Here, four studies directed toward the development of time— and cost—efficient techniques for screening are reported. In the first study, three methods to artificially infest seedlings of different ages were evaluated in a shade—covered greenhouse. Two—year—old seedlings had much lower infestation levels than 7 year—old seedlings. Placing infested bark at the base of the seedling was less effective than tying infested bark to the seedling or suspending infested bolts above the seedling. Although the two latter techniques resulted in similar densities on the seedlings, they each have positive and negative considerations. Attaching bark to uninfested trees is effective, but very time consuming. The suspended bolt method mimics natural infestation and is more economical than attaching bark, but care must be taken to ensure an even distribution of crawlers falling onto the seedlings. The second study focused on the density and distribution of crawlers falling from suspended bolts onto paper gridded into 7.6 × 7.6 cm cells. Crawler density in a 30 cm band under and to each side of the suspended bolt ranged from 400 to over 3000 crawlers per cell (1 to 55 crawlers per cm2). In the third study, excised branches from 4 year—old A. fraseri and A. vetchii seedlings were artificially infested with A. piceae to determine whether this technique may be useful for early resistance screening. The excised A. fraseri branches supported complete adelgid development (crawler to egg—laying adult), and very little adelgid development occurred on A. vetchii branches. The fourth study compared infestation levels and gouting response on excised versus intact branches of 4 year—old A. fraseri seedlings from three different seed sources, and excised branches from 4 year—old and 25 year—old trees. There were no differences in infestation levels between excised versus intact branches nor in very young versus mature trees; gouting response was observed only on intact branches.

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