Japanese hop (Humulus japonicus Sieb. & Zucc.) is an emerging invasive plant that has been observed to invade and spread throughout wetlands. As an annual vine, H. japonicus can smother native vegetation, forming dense stands and reducing biodiversity. At a restored floodplain forest in Joslin, Illinois, formerly used as an experimental site to test the effectiveness of different reforestation methods, H. japonicus has invaded stands of the previously dominant invasive, reed canarygrass (Phalaris arundinacea L.). We conducted an observational field study to examine the spatio-temporal dynamics of H. japonicus invasion relative to gradients in canopy cover and species composition. Ten transects, with half the transect extending into and half extending beyond H. japonicus patches, were established in October 2022. Seven quadrats per transect were surveyed for vegetation cover and canopy cover in October 2022, June 2023, and October 2023. Transects were evenly split between forested and open areas based on the reforestation treatments. H. japonicus cover significantly increased from October 2022 to October 2023, which has resulted in a slight decrease and replacement of P. arundinacea across the site. Shade reduced H. japonicus cover, indicating its preference for sunlit conditions. Species richness was higher in forested transects compared to open ones, most likely due to the absence of both P. arundinacea and H. japonicus in shaded transects. Along transects, quadrats that had been invaded by H. japonicus differed in species composition from quadrats that had not been invaded in both October 2022 and October 2023. H. japonicus cover was much lower in June than October, suggesting that temporal niche partitioning may allow P. arundinacea to persist, and indicating that monitoring for H. japonicus should occur late in the growing season. Both invasive species are shade intolerant, suggesting that planting fast-growing trees should be an effective long-term solution for controlling invasion.

Differential tolerances to dalapon (2,2-dichloropropionic acid), amitrole (3-amino-s-triazole) plus ammonium thiocyanate, and glyphosate [N-(phosphonomethyl)glycine] of 3- to 10-week-old seedlings of creeping red fescue (Festuca rubra L. ‘Boreal’) and redtop (Agrostis alba L.), which are desirable ditchbank grasses, and reed canarygrass (Phalaris arundianacea L.), a troublesome ditchbank weed, were evaluated in the field. Within each of four treatment dates (growth stages), dalapon affected all species similarly; effects among treatment dates ranged from none to severe. Amitrole at 4.5 kg/ha plus ammonium thiocyanate at 4.1 kg/ha reduced the stand of 3-week-old seedlings of redtop, creeping red fescue, and reed canarygrass by 0, 42, and 94%, respectively, but had little effect on older seedlings. Glyphosate at 1.1 kg/ha did not significantly reduce the stand of 5- to 10-week-old creeping red fescue seedlings, but killed nearly all reed canarygrass seedlings. Redtop was intermediate in its tolerance to glyphosate. Applications of amitrole plus ammonium thiocyanate or glyphosate should be effective in converting ditchbank vegetation from an undesirable stand of reed canarygrass to a desirable stand of redtop and creeping red fescue, respectively.

Although much is known about the physiological capabilities of reed canarygrass (RCG) and the consequences of invasion, less is known about the roles that wetland type and surrounding disturbances play in facilitating the spread of RCG in predominantly forested landscapes. Therefore, the goals of our study were to test if (1) certain wetland types in the Northern Great Lakes region were more susceptible to RCG invasion, (2) certain disturbances facilitated RCG, and (3) the level of road development and the presence or absence of a ditch bordering each observed road influences the frequency of adjacent RCG populations. We randomly selected 28 wetlands within the Keweenaw Bay Indian Community reservation in the Upper Peninsula of Michigan. At each wetland, we collected plant community and environmental data and catalogued disturbances. In all, 287 plant species were identified. Cluster analysis revealed 16 distinct vegetation communities, which were distributed among three broader wetland community types: (1) nonforested graminoid, (2) Sphagnum peatlands, and (3) forested wetlands. Occurrence of RCG was most common in the nonforested graminoid communities and was also positively correlated to disturbance. The most frequent disturbances were roads, off-road vehicle trails, and logging activity. Additionally, paved and graded roads, and roads with ditches, were more likely to have RCG alongside them than unpaved dirt roads. Our data suggest that RCG occurrence is controlled by interactions between wetland types and disturbance.

We assessed the ability of climatic, environmental, and anthropogenic variables to predict areas of high-risk for plant invasion and consider the relative importance and contribution of these predictor variables by considering two spatial scales in a region of rapidly changing climate. We created predictive distribution models, using Maxent, for three highly invasive plant species (Canada thistle, white sweetclover, and reed canarygrass) in Alaska at both a regional scale and a local scale. Regional scale models encompassed southern coastal Alaska and were developed from topographic and climatic data at a 2 km (1.2 mi) spatial resolution. Models were applied to future climate (2030). Local scale models were spatially nested within the regional area; these models incorporated physiographic and anthropogenic variables at a 30 m (98.4 ft) resolution. Regional and local models performed well (AUC values > 0.7), with the exception of one species at each spatial scale. Regional models predict an increase in area of suitable habitat for all species by 2030 with a general shift to higher elevation areas; however, the distribution of each species was driven by different climate and topographical variables. In contrast local models indicate that distance to right-of-ways and elevation are associated with habitat suitability for all three species at this spatial level. Combining results from regional models, capturing long-term distribution, and local models, capturing near-term establishment and distribution, offers a new and effective tool for highlighting at-risk areas and provides insight on how variables acting at different scales contribute to suitability predictions. The combinations also provides easy comparison, highlighting agreement between the two scales, where long-term distribution factors predict suitability while near-term do not and vice versa.