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Chromolaena odorata (Asteraceae: Eupatorieae) is a sprawling shrub native to the Americas, and a destructive invader of much of the humid tropics and subtropics of the Old World. Opportunistic native-range exploration in 1995 identified a stem-boring weevil, Lixus aemulus, as a promising biological control candidate agent. Host-specificity testing was conducted on L. aemulus in South Africa using laboratory no-choice and paired-choice tests. Three invasive alien plants closely related to C. odorata may be utilized by L. aemulus but no indigenous, ornamental or crop species in South Africa was or is expected to be attacked by the weevil. A native-range field survey was conducted in Brazil to determine the exact identity of the host plant L. aemulus had been collected in 1995, and to identify additional host-plant species. Genetic assessments of the Lixus sp.(p.). adults collected on the three host plants (C. odorata, Chromolaena laevigata and Heterocondylus vitalbae) reveal these individuals are L. aemulus and the weevil can be classed as an oligophage in its native range. Over 5,500 adults were released in South Africa, but overall establishment has been poor. The most likely explanation appears to be a climate mismatch between the region of South Africa invaded by C. odorata and the collection locality in Rio Branco, Acre state, Brazil. Additionally, because the full extent of the native range of L. aemulus is unknown, it is uncertain whether individuals can be sourced from an area whose climate resembles that of South Africa. Furthermore, despite being oligophagous, L. aemulus may perform sub-optimally on the southern African C. odorata biotype.

Digital aerial photogrammetry (DAP) data acquired by unmanned aerial vehicles (UAV) have been increasingly used for forest inventory and monitoring. In this study, we evaluated the potential of UAV photogrammetry data to detect individual trees, estimate their heights (ht), and monitor the initial silvicultural quality of a 1.5-year-old Eucalyptus sp. stand in northeastern Brazil. DAP estimates were compared with accurate tree locations obtained with real time kinematic (RTK) positioning and direct height measurements obtained in the field. In addition, we assessed the quality of a DAP-UAV digital terrain model (DTM) derived using an alternative ground classification approach and investigated its performance in the retrieval of individual tree attributes. The DTM built for the stand presented an RMSE of 0.099 m relative to the RTK measurements, showing no bias. The normalized 3D point cloud enabled the identification of over 95% of the stand trees and the estimation of their heights with an RMSE of 0.36 m (11%). However, ht was systematically underestimated, with a bias of 0.22 m (6.7%). A linear regression model, was fitted to estimate tree height from a maximum height metric derived from the point cloud reduced the RMSE by 20%. An assessment of uniformity indices calculated from both field and DAP heights showed no statistical difference. The results suggest that products derived from DAP-UAV may be used to generate accurate DTMs in young Eucalyptus sp. stands, detect individual trees, estimate ht, and determine stand uniformity with the same level of accuracy obtained in traditional forest inventories.