Transdisciplinary weed research: new leverage on challenging weed problems?
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 multidimensional, 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 multidimensional and multilevel factors, via multiple ...