Wesley J. Glisson

Nitellopsis obtusa (starry stonewort) is an invasive macroalga subject to substantial control efforts in the Midwestern United States; however, there has not been systematic evaluation of treatment effectiveness. We synthesized management approaches and outcomes using monitoring performed over a decade-long period across 38 lakes in Indiana, Wisconsin, and Minnesota. Copper-based algaecide treatments were the primary means of control, followed by physical removal methods or combination treatments. Control efforts and associated monitoring data varied by spatial scale, as did surveyors’ N. obtusa sampling methods. At the largest (whole-lake) scale, we found no evidence that algaecide treatments were slowing expansion or reducing abundance of N. obtusa within infested lakes. At smaller, within-lake scales, we found that algaecide and physical treatments could reduce N. obtusa frequency and biomass, but outcomes were highly variable. At the smallest scales, hand pulling was an effective containment strategy for small, localized populations that were detected early. These results highlight the need to set realistic goals for N. obtusa control and develop improved management techniques. There were also critical gaps in monitoring that limited our ability to evaluate treatment effectiveness. In particular, increased monitoring of unmanaged reference lakes and untreated areas within managed lakes is needed.

To efficiently detect aquatic invasive species early in an invasion when control may still be possible, predictions about which locations are likeliest to be occupied are needed at fine scales but are rarely available. Occupancy modeling could provide such predictions given data of sufficient quality and quantity. We assembled a data set for the macroalga starry stonewort (Nitellopsis obtusa) across Minnesota and Wisconsin, USA, where it is a new and high-priority invader. We used these data to construct a multi-season, single-species spatial occupancy model that included biotic, abiotic, and movement-related predictors. Distance to the nearest access was an important occurrence predictor, highlighting the likely role boats play in spreading starry stonewort. Fetch and water depth also predicted occupancy. We estimated an average detection probability of 63% at sites with mean non-N. obtusa plant cover, declining to ~ 38% at sites with abundant plant cover, especially that of other Characeae. We recommend that surveyors preferentially search for starry stonewort in areas of shallow depth and high fetch close to boat accesses. We also recommend searching during late summer/early fall when detection is likelier. This study illustrates the utility of fine-scale occupancy modeling for predicting the locations of nascent populations of difficult-to-detect species.

Hybridization has been associated with increased invasiveness in plants. In North America, the hybrid aquatic plant Myriophyllum spicatum × Myriophyllum sibiricum (hybrid watermilfoil, hereafter HWM) is a cross between non-native invasive Eurasian watermilfoil (M. spicatum, EWM) and native northern watermilfoil (M. sibiricum, NWM). Lab-based trials have demonstrated higher growth rates in HWM compared to EWM and NWM, but these patterns have not been systematically examined in the field. In this study, we compared the invasiveness of HWM to its parental taxa, EWM and NWM, by examining the amount and timing of: (1) flowering, (2) surface cover, and (3) biomass (using stem counts as a proxy). We conducted repeat surveys of Myriophyllum beds at eight lakes (2–3 lakes/taxon) in the Minneapolis–St. Paul Metropolitan area (Minnesota, USA) between June 2017 and November 2018. HWM produced more flower spikes earlier and overall, and maintained consistently more flower spikes throughout the growing season than EWM and NWM. In addition, surface cover reached greater annual peaks and was higher for longer throughout the growing season for HWM than for both parental taxa. We did not observe a significant difference in stem counts among the three taxa, but HWM did reach a higher maximum number of stems than either parental taxon. This study provides field-based evidence of increased invasiveness associated with hybridization between EWM and NWM; specifically, greater reproductive potential via flowering and greater surface cover may increase HWM spread, have greater impacts on native species, and pose more of a nuisance to lake users.

Potamogeton crispus (curlyleaf pondweed) and Myriophyllum spicatum (Eurasian watermilfoil) are widely thought to competitively displace native macrophytes in North America. However, their perceived competitive superiority has not been comprehensively evaluated. Coexistence theory suggests that invader displacement of native species through competitive exclusion is most likely where high niche overlap results in competition for limiting resources. Thus, evaluation of niche similarity can serve as a starting point for predicting the likelihood of invaders having direct competitive impacts on resident species. Across two environmental gradients structuring macrophyte communities—water depth and light availability—both P. crispus and M. spicatum are thought to occupy broad niches. For a third dimension, phenology, the annual growth cycle of M. spicatum is typical of other species, whereas the winter-ephemeral phenology of P. crispus may impart greater niche differentiation and thus lower risk of native species being competitively excluded. Using an unprecedented dataset comprising 3404 plant surveys from Minnesota collected using a common protocol, we modeled niches of 34 species using a probabilistic niche framework. Across each niche dimension, P. crispus had lower overlap with native species than did M. spicatum; this was driven in particular by its distinct phenology. These results suggest that patterns of dominance seen in P. crispus and M. spicatum have likely arisen through different mechanisms, and that direct competition with native species is less likely for P. crispus than M. spicatum. This research highlights the utility of fine-scale, abundance-based niche models for predicting invader impacts.

Glisson WJ, Wagner CK, McComas SR, Farnum K, Verhoeven MR, Muthukrishnan R, Larkin DJ. 2018. Response of the invasive alga starry stonewort (Nitellopsis obtusa) to control efforts in a Minnesota lake. Lake Reserv Manage. 00:00–00. Starry stonewort (Nitellopsis obtusa), an invasive green macroalga in the family Characeae, has recently been found for the first time in several Midwestern states. This aquatic invasive species is of increasing concern to management agencies, lakeshore property owners, and other stakeholders. Starry stonewort has proven difficult to control, partly due to its ability to reproduce via bulbils (asexual reproductive structures). There has also been a lack of applied research addressing the efficacy of current management practices for controlling starry stonewort. We examined the effects of mechanical and algaecide treatments on starry stonewort biomass, bulbil density, and bulbil viability by monitoring treated areas and untreated reference locations concurrent with management implemented on Lake Koronis in Minnesota. Chelated copper algaecide applications alone and in combination with mechanical harvesting significantly reduced starry stonewort biomass, but algaecide treatment alone failed to reduce the capacity of starry stonewort to regenerate via bulbils. A second, granular algaecide application following an initial treatment with liquid algaecide did not further reduce biomass in any treated area and was associated with a substantial increase in bulbil density in an area treated with algaecide alone. Bulbil viability was greatest in the area treated only with algaecide (86%) and an untreated reference area (84%) and was lowest in an area treated with both mechanical harvest and algaecide (70%). The ability of starry stonewort to regenerate and persist following algaecide treatment is concerning. Multi-pronged management incorporating both chemical and mechanical approaches may improve outcomes of starry stonewort control efforts.

Understanding species–habitat relationships for endangered species is critical for their conservation. However, many studies have limited value for conservation because they fail to account for habitat associations at multiple spatial scales, anthropogenic variables, and imperfect detection. We addressed these three limitations by developing models for an endangered wetland bird, Yuma Ridgway's rail (Rallus obsoletus yumanensis), that examined how the spatial scale of environmental variables, inclusion of anthropogenic disturbance variables, and accounting for imperfect detection in validation data influenced model performance. These models identified associations between environmental variables and occupancy. We used bird survey and spatial environmental data at 2473 locations throughout the species' U.S. range to create and validate occupancy models and produce predictive maps of occupancy. We compared habitat‐based models at three spatial scales (100, 224, and 500 m radii buffers) with and without anthropogenic disturbance variables using validation data adjusted for imperfect detection and an unadjusted validation dataset that ignored imperfect detection. The inclusion of anthropogenic disturbance variables improved the performance of habitat models at all three spatial scales, and the 224‐m‐scale model performed best. All models exhibited greater predictive ability when imperfect detection was incorporated into validation data. Yuma Ridgway's rail occupancy was negatively associated with ephemeral and slow‐moving riverine features and high‐intensity anthropogenic development, and positively associated with emergent vegetation, agriculture, and low‐intensity development. Our modeling approach accounts for common limitations in modeling species–habitat relationships and creating predictive maps of occupancy probability and, therefore, provides a useful framework for other species.

Wetland loss, biological invasions, and ecological restoration are major factors altering wetland resources in the Midwestern United States. Large‐scale plant‐community change associated with these factors is an under‐investigated, potentially strong driver of habitat suitability for wetland‐dependent wildlife, such as secretive marsh birds (SMBs), which are of widespread conservation concern. We employed multi‐year, hierarchical Bayesian occupancy modeling to investigate sensitivity of 3 SMB species (American bittern, sora, and Virginia rail) to habitat and vegetation characteristics in Wisconsin, USA. We contrasted habitat characteristics and SMB occupancy in natural wetlands with those restored under the federally funded Wetlands Reserve Program (WRP). We also examined the extent to which SMB occupancy was explained by 3 levels of habitat assessment that encompassed different spatial scales and levels of sampling effort (landscape, rapid, and intensive). All species were significantly associated with variables derived from intensive assessment, and showed high sensitivity to differences in plant‐community composition and vegetation quality. Both American bittern and Virginia rail were negatively associated with abundance of the invasive wetland grass, Phalaris arundinacea (reed canarygrass), and were positively associated with an indicator of plant‐community quality (mean coefficient of conservatism, or C‐value). Sora occupancy was positively associated with Typha (cattail) abundance. For all 3 species, occupancy was greater in natural sites than in restored sites, which were characterized by greater Phalaris abundance and lower mean C‐values. Our results show broad agreement between botanical and avian indicators of wetland quality, suggesting that enhancing the condition of wetland vegetation can yield ancillary benefits for SMBs. In this region, efforts to control Phalaris and restore diverse, native‐dominated plant communities are likely to increase wetlands’ capacity to support SMBs. © 2015 The Wildlife Society.