Ramona Maggini

The international spread of emerging and novel plant pests is increasing rapidly due to the expansion of global trade and poses substantial economic, socio-cultural, and environmental risks across ecosystems worldwide. Horizon scanning offers a proactive means of identifying emerging pests before they establish in new regions, creating valuable opportunities for prevention and risk mitigation. However, current horizon scanning approaches are largely qualitative, relying on extensive literature reviews and expert consultation that are both time-consuming and resource intensive. The Euphresco project presented here aims to strengthen and accelerate traditional horizon scanning by introducing a quantitative, highly automated modelling framework capable of screening large numbers of potential plant pests and identifying and prioritising those posing the greatest risk. The approach integrates multiple analytical components, including automated data retrieval from databases and web sources, high-throughput climate-suitability and ecological modelling, machine learning-assisted screening and analysis for informing and quantifying risk criteria, quantitative prioritisation of species according to risk, and sensitivity analysis to test the robustness of the ranking. The new approach will support evidence-based triage, enabling the most concerning pests to be rapidly identified for formal pest risk assessment and targeted surveillance. Ultimately, the project seeks to develop an open-source, robust, and maintainable toolkit that enables efficient, scalable, and automated horizon scanning for any country or region, supporting more effective integration of quantitative risk intelligence into phytosanitary decision-making.

In response to the global increase in biological invasions, the effective management of potentially high-impact invasive alien species requires spatially-explicit tools that provide regional insights to support anticipatory and targeted strategies. This study presents a regional impact risk prediction framework combining habitat suitability modeling (SDM) with impact assessments based on the (S)EICAT protocols. Land use / land cover serves as a common spatial context for both habitat suitability modeling and impact prediction, enabling fine-scale, spatially-explicit projections of risk to inform management across different ecological and socio-economic sectors. We illustrate this framework using Sorghum halepense (Johnsongrass), a globally recognized rhizomatous weed that is rapidly spreading in Central Europe, including Switzerland. A hierarchical SDM, integrating global climate and high-resolution regional land use data, identified the Swiss Plateau, Lake Geneva Basin, the foothills of the Vaud Pre-Alps and the Ticino valley bottoms as highly suitable areas for the species. Land use-specific assessments revealed that main impacts are expected on pastures (toxicity to livestock), arable land (competition, disease transmission), urban green spaces (allergenic effects on human health and high management costs), transportation areas (management costs), and natural environments (competition with and chemical inhibition on native flora, ecosystem structural changes). Regional Impact Risk Classification (RIRC) maps show that different impact mechanisms frequently co-occur geographically, resulting in regions with an increased cumulative impact risk. Integrated and land use–based, the RIRC framework offers a transferable, flexible and scalable tool for planning regional management of biological invasions, in particular for new and emerging invasive species.

Aromia bungii Faldermann (Coleoptera: Cerambycidae) is an emerging invasive pest of economically important Prunus species that is native to China, Mongolia, the Russian Far East, Korea, and Vietnam. It was recently introduced to Japan, Germany, and Italy, where it is spreading and damaging crops and ornamental trees. It exhibits an adaptable lifecycle, a high reproductive output, and the larvae live concealed under the bark of infested trees, which are traits that promote its invasiveness. Detection and monitoring of A. bungii currently rely upon visual identification of infested trees that are usually already damaged, which is inefficient and not target-specific. Current control methods rely primarily upon the labour-intensive physical removal of infested trees. Although native parasitoid natural enemies of A. bungii provide control in Chinese orchards, none are appropriate for classical biological control in invaded areas due to biosafety concerns surrounding their broad host ranges. However, entomopathogenic fungi and nematodes may provide viable options for biological control in invaded ranges. Recent advancements in semiochemical baited traps may provide sustainable, target-specific, and efficacious methods to monitor and control A. bungii. There remains much to learn about the biology and control of A. bungii, and continued advancements in the study of sustainable control tools are needed for the management of this emerging pest.

The evaluation of the potential for newly arrived species to survive and the determination whether a founder population can become established and subsequently spread and cause negative impacts are crucial considerations when performing a pest risk assessment in plant health. Climate change has clear consequences concerning the potential range of pests, and their potential for spread and impacts. Despite its importance, no guidance exists to support the evaluation of whether and how climate change should be incorporated into pest risk assessment. This paper reviews how climate change has been considered so far, not only in the area of pest risk assessment but also in other domains and provides guidance on how its incorporation could affect the overall assessment. Furthermore, from this analysis, some possible solutions for incorporating climate change into pest risk assessment are provided, taking into account that its outcomes have profound political, economic, social and environmental implications.

Climate change is widely recognized as a critical global challenge with far-reaching consequences. It affects pest species by altering their population dynamics, actual and potential distribution areas, as well as interactions with their hosts and natural enemies. Climate change thus has potentially important implications for multiple areas of the pest risk analysis (PRA) process. The importance of including climate change in PRA may vary depending on the climatic context of the PRA area in relation to the speed of climate change. If climatic changes within the time horizon of interest are minimal, their potential impact on pest risk is reduced accordingly. For PRAs in a changing climate, we need to be concerned with how future climates could alter our assessment of the risks currently posed by each pest species. While climate can influence the distribution and abundance of pests and hosts alike, its significance will vary depending on the situation. The inclusion of climate change within a PRA also presents challenges. The dynamic nature of climate change, with its complex interactions and uncertainties, can make it difficult to predict and assess the future risks posed by pests accurately. Uncertainties related to future predictions may be much greater than the potential effects associated with climate change and species’ responses to it. This paper outlines examples of the effects of climate change on hosts and different groups of pests, including invertebrates, pathogens, weeds and vector species. The aim is to review the opportunities and challenges of incorporating climate change into PRA, offering insights for a variety of stakeholders including policymakers on this topic.

High spatial and thematic resolution of Land Use/Cover (LU/LC) maps are central for accurate watershed analyses, improved species, and habitat distribution modeling as well as ecosystem services assessment, robust assessments of LU/LC changes, and calculation of indices. Downscaled LU/LC maps for Switzerland were obtained for three time periods by blending two inputs: the Swiss topographic base map at a 1:25,000 scale and the national LU/LC statistics obtained from aerial photointerpretation on a 100 m regular lattice of points. The spatial resolution of the resulting LU/LC map was improved by a factor of 16 to reach a resolution of 25 m, while the thematic resolution was increased from 29 (in the base map) to 62 land use categories. The method combines a simple inverse distance spatial weighting of 36 nearest neighbors’ information and an expert system of correspondence between input base map categories and possible output LU/LC types. The developed algorithm, written in Python, reads and writes gridded layers of more than 64 million pixels. Given the size of the analyzed area, a High-Performance Computing (HPC) cluster was used to parallelize the data and the analysis and to obtain results more efficiently. The method presented in this study is a generalizable approach that can be used to downscale different types of geographic information.

Cities are investing billions of dollars in climate change adaptation to combat the effects of sea‐level rise, temperature extremes, increasingly intense storm events, flooding and water scarcity. Natural ecosystems have enormous potential to contribute to city resilience, and so, actions that rely on this approach could sustain considerable co‐benefits for biodiversity. In this paper we identify the prevalence of key themes of human adaptation response that could have biodiversity conservation outcomes in cities. We then quantify the area of impact for actions that identify specific targets for greening or green infrastructure that could involve natural ecosystems, providing an indicator of potential co‐benefits to biodiversity. We then extrapolate to explore the total area of land that could benefit from catchment management approaches, the area of waterways that could benefit from nature‐based improvement of these spaces, and finally the number of threatened species that could benefit across these cities. From 80 city climate adaptation plans analysed, we found that urban greening plays a key role in most adaptation strategies, and represents an enormous opportunity for biodiversity conservation, given the diversity of animal and plant species in urban environments. We show that the ranges of at least 270 threatened species overlap with the area covered by just 58 city adaptation plans, including watershed catchments totalling over 28 million km². However, an analysis of 80 city adaptation plans (of a total 151 found globally) shows that this opportunity is being missed. Just 18% of the plans assessed contained specific intentions to promote biodiversity. We highlight this missed opportunity, as climate adaptation actions undertaken by cities represent an enormous incipient opportunity for nature conservation. Finally, we encourage planners and city governments to incorporate biological conservation into climate adaption plans, for the mutual benefit of urban societies and their biodiversity.

Australia's northern savannas are one of the few remaining large and mostly intact natural areas on Earth. However, their biodiversity and ecosystem values could be threatened if proposed agricultural development proceeds. Through land‐use change scenarios, we explored trade‐offs and synergies among biodiversity conservation, carbon farming and agriculture production in northern Australia. We found that if all suitable soils were converted to agriculture, habitat at unique recorded locations of three species would disappear and 40 species and vegetation communities could lose more than 50% of their current distributions. Yet, strategically considering agriculture and biodiversity outcomes leads to zoning options that could yield >56,000 km ² of agricultural development with a significantly lower impact on biodiversity values and carbon farming. Our analysis provides a template for policy‐makers and planners to identify areas of conflict between competing land‐uses, places to protect in advance of impacts, and planning options that balance agricultural and conservation needs.

Climate change is a major threat to global biodiversity, and its impacts can act synergistically to heighten the severity of other threats. Most research on projecting species range shifts under climate change has not been translated to informing priority management strategies on the ground. We develop a prioritization framework to assess strategies for managing threats to biodiversity under climate change and apply it to the management of invasive animal species across one‐sixth of the Australian continent, the Lake Eyre Basin. We collected information from key stakeholders and experts on the impacts of invasive animals on 148 of the region's most threatened species and 11 potential strategies. Assisted by models of current distributions of threatened species and their projected distributions, experts estimated the cost, feasibility, and potential benefits of each strategy for improving the persistence of threatened species with and without climate change. We discover that the relative cost‐effectiveness of invasive animal control strategies is robust to climate change, with the management of feral pigs being the highest priority for conserving threatened species overall. Complementary sets of strategies to protect as many threatened species as possible under limited budgets change when climate change is considered, with additional strategies required to avoid impending extinctions from the region. Overall, we find that the ranking of strategies by cost‐effectiveness was relatively unaffected by including climate change into decision‐making, even though the benefits of the strategies were lower. Future climate conditions and impacts on range shifts become most important to consider when designing comprehensive management plans for the control of invasive animals under limited budgets to maximize the number of threatened species that can be protected.