Understanding the spatial dynamics of invasive alien plants is a growing concern for many scientists and land managers hoping to effectively tackle invasions or mitigate their impacts. Consequently, there is an urgent need for the development of efficient tools for large scale mapping of invasive plant populations and the monitoring of colonization fronts. Remote sensing using very high resolution satellite and Unmanned Aerial Vehicle (UAV) imagery is increasingly considered for such purposes. Here, we assessed the potential of several single- and multi-date indices derived from satellite and UAV imagery (i.e., UAV-generated Canopy Height Models—CHMs; and Bi-Temporal Band Ratios—BTBRs) for the detection and mapping of the highly problematic Asian knotweeds (Fallopia japonica; Fallopia × bohemica) in two different landscapes (i.e., open vs. highly heterogeneous areas). The idea was to develop a simple classification procedure using the Random Forest classifier in eCognition, usable in various contexts and requiring little training to be used by non-experts. We also rationalized errors of omission by applying simple “buffer” boundaries around knotweed predictions to know if heterogeneity across multi-date images could lead to unfairly harsh accuracy assessment and, therefore, ill-advised decisions. Although our “crisp” satellite results were rather average, our UAV classifications achieved high detection accuracies. Multi-date spectral indices and CHMs consistently improved classification results of both datasets. To the best of our knowledge, it was the first time that UAV-generated CHMs were used to map invasive plants and their use substantially facilitated knotweed detection in heterogeneous vegetation contexts. Additionally, the “buffer” boundary results showed detection rates often exceeding 90–95% for both satellite and UAV images, suggesting that classical accuracy assessments were overly conservative. Considering these results, it seems that knotweed can be satisfactorily mapped and monitored via remote sensing with moderate time and money investment but that the choice of the most appropriate method will depend on the landscape context and the spatial scale of the invaded area.

Many of the most invasive plant species in the world can propagate clonally, suggesting clonality offers advantages that facilitate invasion. Gaining insights into the clonal growth dynamics of invasive plants should thus improve understanding of the mechanisms of their dominance, resilience and expansion. Belonging to the shortlist of the most problematic terrestrial invaders, Reynoutria japonica var. japonica Houtt. (Japanese knotweed) has colonized all five continents, likely facilitated by its impressive ability to propagate vegetatively. However, its clonal growth patterns are surprisingly understudied; we still do not know how individuals respond to key environmental conditions, including light availability and disturbance. To contribute to filling this knowledge gap, we designed a mesocosm experiment to observe the morphological variation in R. japonica growth in homogeneous or heterogeneous conditions of light stress (shade) and disturbance (mowing). Rhizome fragments were planted in the middle of large pots between two habitat patches that consisted of either one or a combination of the following three environmental conditions: full light without mowing, full light with frequent mowing, or shade without mowing. At the end of the experiment, biomass and traits related to clonal growth (spacer and rhizome lengths, number of rhizome branches, and number of ramets) were measured. After 14 months, all individuals had survived, even those frequently mowed or growing under heavy shade. We showed that R. japonica adopts a ‘phalanx’ growth form when growing in full light and a ‘guerrilla’ form when entirely shaded. The former is characteristic of a space-occupancy strategy while the latter is more associated with a foraging strategy. In heterogeneous conditions, we also showed that clones seemed to invest preferentially more in favorable habitat patches rather than in unfavorable ones (mowed or shaded), possibly exhibiting an escape strategy. These observations could improve the management of this species, specifically by illustrating how aggressive early control measures must be, by highlighting the importance of repeated mowing of entire stands, as this plant appears to compensate readily to partial mowing, and by informing on its potential responses towards the restoration of a cover of competitive native plants.

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In a recent paper, Jones et al. (2020a) claimed that we recommended the use of mowing for the “landscape management of invasive knotweeds” in an article we published earlier this year (i.e. Martin et al. 2020), a recommendation with which they strongly disagreed. Since we never made such a recommendation and since we think that, in order to successfully control invasions by Japanese knotweed s.l. taxa (Reynoutria spp.; syn. Fallopia spp.), stakeholders need to acknowledge the general complexity of the management of invasive clonal plants, we would like to (i) clarify the intentions of our initial article and (ii) respectfully discuss some of the statements made by Daniel Jones and his colleagues regarding mowing and knotweed management in general. Although we agree with Jones et al. that some ill-advised management decisions can lead to “cures worse than the disease”, our concern is that the seemingly one-sided argumentation used by these authors may mislead managers into thinking that a unique control option is sufficient to tackle knotweed invasions in every situation or at any given spatial scale, when it is generally admitted that management decisions should account for context-dependency (Wittenberg and Cock 2001; Pyšek and Richardson 2010; Kettenring and Adams 2011).