Summary Grey Willow (Salix cinerea L.) poses a significant threat to wetland ecosystems in New Zealand. To manage the ecological impacts and to control further spread, cost‐effective large‐scale control methods are needed. We investigated the response of Grey Willow and dominant wetland plant groups to the aerial boom‐spray application of glyphosate at 9 L/ha and triclopyr (amine) at 18 L/ha at three New Zealand wetlands. We found glyphosate substantially reduced the dominance of tall (>2 m) Grey Willow with commensurate increases in the dominance of most native plant groups. Triclopyr (amine) application resulted in poor Grey Willow control, was not associated with increased native plant group dominance, and some native plant groups declined where triclopyr (amine) was applied. We conclude that the aerial application of glyphosate is an effective large‐scale Grey Willow control tool and could be used to initiate the restoration of native plant communities in wetlands dominated by Grey Willow. But, evidence of Grey Willow recovery after control suggests that increases in native plant dominance will be reversed as Grey Willow re‐establish. Further research is needed to determine how to maintain and enhance native plant dominance after control, and to determine how to manage Grey Willow in fen areas where the Grey Willow canopy is discontinuous and nontarget herbicide impacts can occur. The aerial boom‐spray application of triclopyr (amine) for large‐scale Grey Willow control should be discontinued as it does not provide effective control and results in negative ecological outcomes.

Grey willow (Salix cinerea) is widely established in New Zealand's remaining swamps and fens, and in many areas has replaced endemic kahikatea (Dacrycarpus dacrydioides) forest. Conservation managers need to know how to restore willow-invaded wetlands to a resilient natural state, but knowledge on how to achieve this goal is limited. We planted kahikatea seedlings into an intact stand of grey willow and into areas where the herbicides glyphosate or triclopyr had been aerially applied to control willow ~1.5 years earlier. We measured canopy cover, light availability and the growth of planted kahikatea. In areas treated with glyphosate, grey willow canopy cover was reduced to 44% ± 3.7% (95% confidence interval), light availability increased to 64% ± 15% of full sunlight, and kahikatea grew an average of 44 cm ± 11.7 cm in 14 months. In contrast, there was little or no kahikatea growth under the intact willow canopy or in the triclopyr treatment area where grey willow canopy cover remained high and mean light availability was low (25% ± 4% of full sunlight). We conclude that the removal of the grey willow canopy through aerial glyphosate application created favourable conditions for the growth of planted kahikatea and may enable the restoration of kahikatea forest in wetlands dominated by grey willow.

Summary We investigated the potential of airborne laser scanning (ALS) for mapping the stand architecture of Grey Willow (Salix cinerea), an invasive wetland weed in New Zealand. In particular, we focused on two metrics, tree height and canopy density, both of which influence the efficacy and nontarget impacts of herbicides aerially broadcast by helicopter to control tree weeds. We compared ground‐based measures of Grey Willow height and canopy density with ALS‐derived data, and the relationship between canopy density as estimated by each method and aerial herbicide deposition at three wetland sites in New Zealand. Analysis revealed strong linear relationships between ground‐based and ALS metrics, indicating that ALS data could be used to generate accurate, high‐resolution digital maps of Grey Willow height and canopy density. These maps coupled with computer‐guided variable flow rate technologies, which enable optimal placement of herbicide, could maximise Grey Willow mortality while reducing the mortality of nontarget indigenous plants. We recommend the application of ALS‐derived maps and computer‐guided variable flow rate technology is investigated for more targeted large‐scale tree weed control.

Background: Landslides can cause substantial environmental, social and economic impacts. Under future climate scenarios the frequency of landslide-triggering events is likely to increase. Land managers, therefore, urgently require reliable high-resolution landslide susceptibility models to inform effective landslide risk assessment and management. Methods: In this study, gridded rainfall, topography, lithology and land cover surfaces were used to develop a high-resolution (10 m x 10 m) spatial model of landslides that occurred in Tasman, New Zealand during a period when ex-tropical Cyclone Gita brought heavy rain to the region. We separately modelled landslides in the same dataset as a function of the erosion susceptibility classification (ESC) data layer used to determine the level of control applied to forestry activities under the National Environmental Standards for Plantation Forestry (NES-PF). Models were fit using boosted regression trees. Results: Our preferred model had excellent predictive power (AUROC = 0.93) and included the parameters: aspect, elevation, mid-slope position, land cover, rainfall, slope, and a descriptive seven-class topographical index. Land cover, elevation, rainfall, slope and aspect were the strongest predictors of landslides with the land cover classes ‘seral native vegetation’ and clear-felled plantation forest’ predicting higher probabilities of landslides and tall native forest and closed canopy plantation forest predicting lower probabilities of landslides. The ESC was a poor predictor of landslides in the study area (AUROC = 0.65). Conclusions: Our study shows that accurate, high-resolution landslide probability surfaces can be developed from landslide distribution, land cover, topographical and rainfall data. We also show that landslide occurrence in the Tasman region could be substantially reduced by increasing the extent of permanent forest cover and by limiting clear-fell harvest of plantation forests on landslide-prone slopes. The ESC framework that underpins the NES-PF was a poor predictor of landslides and, therefore, an unreliable basis for regulating forestry activities in the Tasman, New Zealand.