Invasive species present significant threats to global agriculture, although how the magnitude and distribution of the threats vary between countries and regions remains unclear. Here, we present an analysis of almost 1,300 known invasive insect pests and pathogens, calculating the total potential cost of these species invading each of 124 countries of the world, as well as determining which countries present the greatest threat to the rest of the world given their trading partners and incumbent pool of invasive species. We find that countries vary in terms of potential threat from invasive species and also their role as potential sources, with apparently similar countries sometimes varying markedly depending on specifics of agricultural commodities and trade patterns. Overall, the biggest agricultural producers (China and the United States) could experience the greatest absolute cost from further species invasions. However, developing countries, in particular, Sub-Saharan African countries, appear most vulnerable in relative terms. Furthermore, China and the United States represent the greatest potential sources of invasive species for the rest of the world. The analysis reveals considerable scope for ongoing redistribution of known invasive pests and highlights the need for international cooperation to slow their spread.NIS | insect pests | fungal pathogens | trade

Prioritization is indispensable for the management of biological invasions, as recognized by the Convention on Biological Diversity, its current strategic plan, and specifically Aichi Target 9 that concerns invasive alien species. Here we provide an overview of the process, approaches and the data needs for prioritization for invasion policy and management, with the intention of informing and guiding efforts to address this target. Many prioritization schemes quantify impact and risk, from the pragmatic and action-focused to the data-demanding and science-based. Effective prioritization must consider not only invasive species and pathways (as mentioned in Aichi Target 9), but also which sites are most sensitive and susceptible to invasion (not made explicit in Aichi Target 9). Integrated prioritization across these foci may lead to future efficiencies in resource allocation for invasion management. Many countries face the challenge of prioritizing with little capacity and poor baseline data. We recommend a consultative, science-based process for prioritizing impacts based on species, pathways and sites, and outline the information needed by countries to achieve this. This should be integrated into a national process that incorporates a broad suite of social and economic criteria. Such a process is likely to be feasible for most countries.

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Summary Classical biological control remains the only tool available for permanent ecological and economic management of invasive alien species that flourish through absence of their co‐evolved natural enemies. As such, this approach is recognized as a key tool for alien species management by the Convention on Biological Diversity (CBD), the European and Mediterranean Plant Protection Organization (EPPO) and the European Strategy on Invasive Alien Species (ESIAS). Successful classical biological control programmes abound around the world, despite disproportionate attention being given to occasional and predictable non‐target impacts. Despite more than 130 case histories in Europe against insect pests, no exotic classical biological control agent has been released in the EU against an alien invasive weed. This dearth has occurred in the face of increasing numbers of exotic invasive plants being imported and taking over National Parks, forests and amenity areas in this region, as well as a global increase in the use of classical biological control around the world. This paper reviews potential European weed targets for classical biological control from ecological and socioeconomic perspectives using the criteria of historical biological control success, taxonomic isolation from European native flora, likely availability of biological control agents, invasiveness outside Europe and value to primary industry and horticulture (potential for conflicts of interest). We also review why classical biological control of European exotic plants remains untested, considering problems of funding and public perception. Finally, we consider the regulatory framework that surrounds such biological control activities within constituent countries of the EU to suggest how this approach may be adopted in the future for managing invasive exotic weeds in Europe.

Anthropogenic impacts increasingly drive ecological and evolutionary processes at many spatio-temporal scales, demanding greater capacity to predict and manage their consequences. This is particularly true for agro-ecosystems, which not only comprise a significant proportion of land use, but which also involve conflicting imperatives to expand or intensify production while simultaneously reducing environmental impacts. These imperatives reinforce the likelihood of further major changes in agriculture over the next 30–40 years. Key transformations include genetic technologies as well as changes in land use. The use of evolutionary principles is not new in agriculture (e.g. crop breeding, domestication of animals, management of selection for pest resistance), but given land-use trends and other transformative processes in production landscapes, ecological and evolutionary research in agro-ecosystems must consider such issues in a broader systems context. Here, we focus on biotic interactions involving pests and pathogens as exemplars of situations where integration of agronomic, ecological and evolutionary perspectives has practical value. Although their presence in agro-ecosystems may be new, many traits involved in these associations evolved in natural settings. We advocate the use of predictive frameworks based on evolutionary models as pre-emptive management tools and identify some specific research opportunities to facilitate this. We conclude with a brief discussion of multidisciplinary approaches in applied evolutionary problems.

Carduus nutans (nodding or musk thistle) is an important invasive plant of Eurasian origin. Biological control of this species, using insects that attack rosettes or developing seed heads, has met with varied success in different parts of its invaded range. Here we develop and compare simple demographic matrix models for populations of this species in Australia and New Zealand, to explore reasons for these differences. In a New Zealand population, rapid population growth of C. nutans is driven by early life history transitions. In an Australian population, fecundity of C. nutans is of reduced importance, and survivorship of rosettes plays an increased role. These differences suggest how biocontrol agents that are successful at providing control in one situation may fail in another. Theoretical explorations of the models show which life history transitions drive the differences in matrix elasticities. We suggest that characteristics of the invaded community also play a role in invasion success of this species, and develop theoretical and empirical approaches to assess what factors may drive population growth, and hence what control methods are most likely to work, under different circumstances.

Summary 1.Invasive species usually exhibit different spatial population dynamics in their native and invaded range. This is often attributed to demographic differences, but may be due to differences in dispersal as well. 2. Regardless of how these dispersal and demographic differences from the native range arose, studying how they contributed to increases in population spread rates will increase our understanding of what has made these species invasive. Here we investigate which vital rates and dispersal parameters of the invasive thistle Carduus nutans drive the increases in spread rate in different invaded ranges compared to that in the native range in Eurasia. 3. We construct and analyse spatial integrodifference models that combine structured, local population models with mechanistic (WALD) models of seed dispersal by wind across a homogeneous landscape. Published and new demographic and dispersal data for single populations from the native (France) and invaded (Australia, New Zealand, Kansas and Pennsylvania) ranges were used for the parameterization. 4. We developed a variance decomposition method ( c *-LTRE) to analyse the contributions of the changes in the vital rates and dispersal parameters to the increases in the invasion wave speed ( c *) estimates for the different invaded ranges compared to that for the native range. 5. The c *-LTRE analysis showed that the net contribution of the dispersal parameters to c * increases varied among the populations from 51% (Australia), to 79% (Kansas), to 80% (New Zealand) and to 85% (Pennsylvanian experiment). Escape from natural enemies that reduce seed set by floral herbivory was important in all invaded ranges. Large positive contributions were also made by increases in rapid growth of seedlings and small rosettes, increases in flowering probabilities and potential seed production, as well as by increased plant height and lower falling velocities of the plumed seeds. 6. Synthesis . By incorporating a mechanistic dispersal model with a structured population model, and by linking this joint model to field data from several continents, we demonstrate the relative importance of dispersal and demography to invasion success. This approach can be used to analyse which aspects of an invader's life history have changed most importantly from the native range.Key-words: fixed-factor life table response experiment (LTRE), integrodifference equations, matrix population models, musk or nodding thistle, native vs. invaded range, plant height, seed terminal velocity, vital rates, Wald analytical long-distance model, wind speed

We explore the evolution of delayed, size-dependent reproduction in the monocarpic perennial Onopordum illyricum, using a range of mathematical models, parameterized with long-term field data. Analysis of the long-term data indicated that mortality, flowering, and growth were age and size dependent. Using mixed models, we estimated the variance about each of these relationships and also individual-specific effects. For the field populations, recruitment was the main density-dependent process, although there were weak effects of local density on growth and mortality. Using parameterized growth models, which assume plants grow along a deterministic trajectory, we predict plants should flower at sizes approximately 50% smaller than observed in the field. We then develop a simple criterion, termed the "1-yr look-ahead criterion," based on equating seed production now with that of next year, allowing for mortality and growth, to determine at what size a plant should flower. This model allows the incorporation of variance about the growth function and individual-specific effects. The model predicts flowering at sizes approximately double that observed, indicating that variance about the growth curve selects for larger sizes at flowering. The 1-yr look-ahead approach is approximate because it ignores growth opportunities more than 1 yr ahead. To assess the accuracy of this approach, we develop a more complicated dynamic state variable model. Both models give similar results indicating the utility of the 1-yr look-ahead criterion. To allow for temporal variation in the model parameters, we used an individual-based model with a genetic algorithm. This gave very accurate prediction of the observed flowering strategies. Sensitivity analysis of the model suggested that temporal variation in the parameters of the growth equation made waiting to flower more risky, so selected for smaller sizes at flowering. The models clearly indicate the need to incorporate stochastic variation in life-history analyses.