SummaryWeedy plants pose a major threat to food security, biodiversity, ecosystem services and consequently to human health and wellbeing. However, many currently used weed management approaches are increasingly unsustainable. To address this knowledge and practice gap, in June 2014, 35 weed and invasion ecologists, weed scientists, evolutionary biologists and social scientists convened a workshop to explore current and future perspectives and approaches in weed ecology and management. A horizon scanning exercise ranked a list of 124 pre‐submitted questions to identify a priority list of 30 questions. These questions are discussed under seven themed headings that represent areas for renewed and emerging focus for the disciplines of weed research and practice. The themed areas considered the need for transdisciplinarity, increased adoption of integrated weed management and agroecological approaches, better understanding of weed evolution, climate change, weed invasiveness and finally, disciplinary challenges for weed science. Almost all the challenges identified rested on the need for continued efforts to diversify and integrate agroecological, socio‐economic and technological approaches in weed management. These challenges are not newly conceived, though their continued prominence as research priorities highlights an ongoing intransigence that must be addressed through a more system‐oriented and transdisciplinary research agenda that seeks an embedded integration of public and private research approaches. This horizon scanning exercise thus set out the building blocks needed for future weed management research and practice; however, the challenge ahead is to identify effective ways in which sufficient research and implementation efforts can be directed towards these needs.

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Transdisciplinary weed research (TWR) is a promising path to more effective management of challenging weed problems. We define TWR as an integrated process of inquiry and action that addresses complex weed problems in the context of broader efforts to improve economic, environmental and social aspects of ecosystem sustainability. TWR seeks to integrate scholarly and practical knowledge across many stakeholder groups (e.g. scientists, private sector, farmers and extension officers) and levels (e.g. local, regional and landscape). Furthermore, TWR features democratic and iterative processes of decision-making and collective action that aims to align the interests, viewpoints and agendas of a wide range of stakeholders. The fundamental rationale for TWR is that many challenging weed problems (e.g. herbicide resistance or extensive plant invasions in natural areas) are better addressed systemically, as a part of broad-based efforts to advance ecosystem sustainability, rather than as isolated problems. Addressing challenging weed problems systemically can offer important new leverage on such problems, by creating new opportunities to manage their root causes and by improving complementarity between weed management and other activities. While promising, this approach is complicated by the multi-dimensional, multilevel, diversely defined and unpredictable nature of ecosystem sustainability. In practice, TWR can be undertaken as a cyclic process of (i) initial problem formulation, (ii) 'broadening' of the problem formulation and recruitment of stakeholder participants, (iii) deliberation, negotiation and design of an action agenda for systemic change, (iv) implementation action, (v) monitoring and assessment of outcomes and (vi) reformulation of the problem situation and renegotiation of further actions. Notably, 'purposive' disciplines (design, humanities and arts) have central, critical and recurrent roles in this process, as do integrative analyses of relevant multidi-mensional and multilevel factors, via multiple natural and social science disciplines. We exemplify this process in prospect and retrospect. Importantly TWR is not a replacement for current weed research; rather, the intent is to powerfully leverage current efforts.

A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, populated and analysed, initially using data for 19 common European weeds, to begin to consolidate trait data in a single repository. The initial choice of traits was driven by the requirements of empirical models of weed population dynamics to identify correlations between traits and model parameters. These relationships were used to build a generic model, operating at the level of functional traits, to simulate the impact of increasing herbicide and fertiliser use on virtual weeds along gradients of seed weight and maximum height. The model generated ‘fitness contours’ (defined as population growth rates) within this trait space in different scenarios, onto which two sets of weed species, defined as common or declining in the UK, were mapped. The effect of increasing inputs on the weed flora was successfully simulated; 77% of common species were predicted to have stable or increasing populations under high fertiliser and herbicide use, in contrast with only 29% of the species that have declined. Future development of the WTDB will aim to increase the number of species covered, incorporate a wider range of traits and analyse intraspecific variability under contrasting management and environments.

Concerns around herbicide resistance, human risk, and the environmental impacts of current weed control strategies have led to an increasing demand for alternative weed management methods. Many new weed management strategies are under development; however, the poor availability of accurate weed maps, and a lack of confidence in the outcomes of alternative weed management strategies, has hindered their adoption. Developments in field sampling and processing, combined with spatial modelling, can support the implementation and assessment of new and more integrated weed management strategies. Our review focuses on the biological and mathematical aspects of assembling within-field weed models. We describe both static and spatio-temporal models of within-field weed distributions (including both cellular automata (CA) and non-CA models), discussing issues surrounding the spatial processes of weed dispersal and competition and the environmental and anthropogenic processes that affect weed spatial and spatio-temporal distributions. We also examine issues surrounding model uncertainty. By reviewing the current state-of-the-art in both static and temporally dynamic weed spatial modelling we highlight some of the strengths and weaknesses of current techniques, together with current and emerging areas of interest for the application of spatial models, including targeted weed treatments, economic analysis, herbicide resistance and integrated weed management, the dispersal of biocontrol agents, and invasive weed species.