The world’s forests have never been more threatened by invasions of exotic pests and pathogens, whose causes and impacts are reinforced by global change. However, forest entomologists and pathologists have, for too long, worked independently, used different concepts and proposed specific management methods without recognising parallels and synergies between their respective fields. Instead, we advocate increased collaboration between these two scientific communities to improve the long-term health of forests. Our arguments are that the pathways of entry of exotic pests and pathogens are often the same and that insects and fungi often coexist in the same affected trees. Innovative methods for preventing invasions, early detection and identification of non-native species, modelling of their impact and spread and prevention of damage by increasing the resistance of ecosystems can be shared for the management of both pests and diseases. We, therefore, make recommendations to foster this convergence, proposing in particular the development of interdisciplinary research programmes, the development of generic tools or methods for pest and pathogen management and capacity building for the education and training of students, managers, decision-makers and citizens concerned with forest health.

The coastal vegetation of islands is expected to be affected by future sea-level rise and other anthropogenic impacts. The biodiverse coastal vegetation on the eastern part of the Dutch Wadden Island of Ameland has experienced land subsidence caused by gas extraction since 1986. This subsidence mimics future sea-level rising through increased flooding and raising groundwater levels. We studied the effects of this relative sea-level rise and other environmental factors (i.e. insect outbreaks, temperature and precipitation) on the population dynamics (i.e. cover and age structure and annual growth) of the shrub seabuckthorn (Hippophae rhamnoides L.) in young (formed after 1950) and old (formed before 1950) dune areas over a period of 56 years (1959-2015). We found an increase in seabuckthorn cover in the young dune areas since 1959, while over time the population in the old dunes decreased due to successional replacement by other species. With the increasing age of the young dunes, we found also a decrease in sea-buckthorn after 2009. However the sharp decrease indicated that other environmental factors were also involved. The most important determinant of annual shrub growth appeared to be five outbreaks of the browntail moth (Euproctis chrysorrhoea L.), in the last decade. Relative sea-level rise caused more frequent flooding and reduced growth at lower elevations due to inundation or soil water saturation. This study clearly indicates that sea-buckthorn is affected by relative sealevel rise, but that other ecological events better explain its variation in growth. Although shrub distribution and growth can be monitored with robust methods, future predictions of vegetation dynamics are complicated by unpredictable extreme events caused by (a)biotic stressors such as insect outbreaks.

Modelling the invasion and emergence of forest pests and pathogens (PnPs) is necessary to quantify the risk levels for forest health and provide key information for policy makers. Here, we make a short review of the models used to quantify the invasion risk of exotic species and the emergence risk of native species. Regarding the invasion process, models tackle each invasion phase, e.g. pathway models to describe the risk of entry, species distribution models to describe potential establishment, and dispersal models to describe (human-assisted) spread. Concerning the emergence process, models tackle each process: spread or outbreak. Only a few spread models describe jointly dispersal, growth, and establishment capabilities of native species while some mechanistic models describe the population temporal dynamics and inference models describe the probability of outbreak. We also discuss the ways to quantify uncertainty and the role of machine learning. Overall, promising directions are to increase the models’ genericity by parameterization based on meta-analysis techniques to combine the effect of species traits and various environmental drivers. Further perspectives consist in considering the models’ interconnection, including the assessment of the economic impact and risk mitigation options, as well as the possibility of having multi-risks and the reduction in uncertainty by collecting larger fit-for-purpose datasets.

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