Practical guidelines for modelling post-entry spread in invasion ecology

Establishment and new hosts of the non-native seed beetle Stator limbatus (Coleoptera, Chrysomelidae, Bruchinae) on acacias in Europe

Stator limbatus is a phytophagous beetle native to warm regions of North and Central America, feeding on Fabaceae seeds and one of the most polyphagous species within the subfamily Bruchinae, here reported for the first time in Europe and on new hosts. Adult beetles emerged from Acacia spp. seeds collected in the islands of Corsica (France), and Sardinia (Italy). The wide presence in Sardinia and Corsica supports the hypothesis that this alien species was introduced several years ago. In both islands, S. limbatus emerged from Acacia mearnsii seeds, with infestation rates of up to 74.2 and 90.8% in 2019 and 2020, respectively. This seed beetle also emerged from two previously unreported host species, Acacia saligna and A. pycnantha, showing highest infestation rates of 4.0 and 95.1%, respectively. Both Acacia species are reported as new host associations with S. limbatus. Overall, seed infestation rates recorded in 2019 and 2020 indicate that S. limbatus is well established and that Mediterranean bioclimatic conditions are suitable for its population increase in size. This study lays the foundations for further research on known and potential host species and the spread and distribution of S. limbatus in Europe.

A weed risk analytical screen to assist in the prioritisation of an invasive flora for containment

Prioritising weeds for control and deciding upon the type of control and its associated investment are fundamental to weed management planning. Risk analysis is central to this process, combining the activities of risk assessment, risk management and risk communication. Risk assessment methodology has a rich history, but management feasibility has typically been a secondary matter, dealt with separately or not at all. Determinants of management feasibility for weeds include the stage of invasion, weed biology, means of control and cost of weed control. Here, we describe a simple weed risk analytical screen that combines risk assessment with species traits that influence management feasibility. We consider stage of invasion, species biological/dispersal characteristics and plant community invasibility in a preliminary analysis of the risk posed by the non-native plant species on Christmas Island in the Indian Ocean. For each of 31 high-risk species considered to be ineradicable under existing funding constraints, we analyse the risk posed to two major plant communities: evergreen closed-canopy rainforest and semi-deciduous scrub forest. Weed risk ratings are combined with ratings for species-intrinsic feasibility of containment (based on a measure that combines time to reproduction with potential for long distance dispersal) to create preliminary rankings for containment specific to each community. These rankings will provide a key input for a more thorough analysis of containment feasibility – one that considers spatial distributions/landscape features, management aspects and the social environment. We propose a general non-symmetric relationship between weed risk and management feasibility, considering risk to be the dominant component of risk analysis. Therefore, in this analysis species are ranked according to their intrinsic containment feasibility within similar levels of risk to produce an initial prioritisation list for containment. Shade-tolerant weeds are of particular concern for the closed-canopy evergreen rainforest on Christmas Island, but a greater diversity of weeds is likely to invade the semi-deciduous scrub forest because of higher light availability. Nevertheless, future invasion of both communities will likely be conditioned by disturbance, both natural and anthropogenic. The plant communities of Christmas Island have undergone significant fragmentation because of clearing for phosphate mining and other purposes. With a substantial number of invasive plant species firmly established and having the potential to spread further, minimising future anthropogenic disturbance is paramount to reducing community invasibility and therefore conserving the island’s unique biodiversity.

Modelling for risk and biosecurity related to forest health

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.

Integrating an individual-based model with approximate Bayesian computation to predict the invasion of a freshwater fish provides insights into dispersal and range expansion dynamics

Short-distance dispersal enables introduced alien species to colonise and invade local habitats following their initial introduction, but is often poorly understood for many freshwater taxa. Knowledge gaps in range expansion of alien species can be overcome using predictive approaches such as individual based models (IBMs), especially if predictions can be improved through fitting to empirical data, but this can be challenging for models having multiple parameters. We therefore estimated the parameters of a model implemented in the RangeShifter IBM platform by approximate Bayesian computation (ABC) in order to predict the further invasion of a lowland river (Great Ouse, England) by a small-bodied invasive fish (bitterling Rhodeus sericeus). Prior estimates for parameters were obtained from the literature and expert opinion. Model fitting was conducted using a time-series (1983 to 2018) of sampling data at fixed locations and revealed that for 5 of 11 model parameters, the posterior distributions differed markedly from prior assumptions. In particular, sub-adult maximum emigration probability was substantially higher in the posteriors than priors. Simulations of bitterling range expansion predicted that following detection in 1984, their early expansion involved a relatively high population growth rate that stabilised after 5 years. The pattern of bitterling patch occupancy was sigmoidal, with 20% of the catchment occupied after 20 years, increasing to 80% after 30 years. Predictions were then for 95% occupancy after 69 years. The development of this IBM thus successfully simulated the range expansion dynamics of this small-bodied invasive fish, with ABC improving the simulation precision. This combined methodology also highlighted that sub-adult dispersal was more likely to contribute to the rapid colonisation rate than expert opinion suggested. These results emphasise the importance of time-series data for refining IBM parameters generally and increasing our understanding of dispersal behaviour and range expansion dynamics specifically.

Cereal aphid movement: general principles and simulation modelling

Cereal aphids continue to be an important agricultural pest, with complex lifecycle and dispersal behaviours. Spatially-explicit models that are able to simulate flight initiation, movement direction, distance and timing of arrival of key aphid species can be highly valuable to area-wide pest management programmes. Here I present an overview of how knowledge about cereal aphid flight and migration can be utilized by mechanistic simulation models. This article identifies specific gaps in knowledge for researchers who may wish to further scientific understanding of aphid flight behaviour, whilst at the same time provides a synopsis of the knowledge requirements for a mechanistic approach applicable to the simulation of a wide range of insect species. Although they are one of the most comprehensively studied insect groups in entomology, it is only recently that our understanding of cereal aphid flight and migration has been translated effectively into spatially-explicit simulation models. There are now a multitude of examples available in the literature for modelling methods that address each of the four phases of the aerial transportation process (uplift, transport in the atmosphere, initial distribution, and subsequent movement). I believe it should now be possible to draw together this knowledgebase and the range of modelling methods available to simulate the entire process: integrating mechanistic simulations that estimate the initiation of migration events, with the large scale migration modelling of cereal aphids and their subsequent local movement.