The DOI matches its Crossref record; 194 of the 194 references it cites were found in a registry or an index.
An ecological future for weed science to sustain crop production and the environment. A review
Open accessAbstract
Sustainable strategies for managing weeds are critical to meeting agriculture’s potential to feed the world’s population while conserving the ecosystems and biodiversity on which we depend. The dominant paradigm of weed management in developed countries is currently founded on the two principal tools of herbicides and tillage to remove weeds. However, evidence of negative environmental impacts from both tools is growing, and herbicide resistance is increasingly prevalent. These challenges emerge from a lack of attention to how weeds interact with and are regulated by the agroecosystem as a whole. Novel technological tools proposed for weed control, such as new herbicides, gene editing, and seed destructors, do not address these systemic challenges and thus are unlikely to provide truly sustainable solutions. Combining multiple tools and techniques in an Integrated Weed Management strategy is a step forward, but many integrated strategies still remain overly reliant on too few tools. In contrast, advances in weed ecology are revealing a wealth of options to manage weeds at the agroecosystem level that, rather than aiming to eradicate weeds, act to regulate populations to limit their negative impacts while conserving diversity. Here, we review the current state of knowledge in weed ecology and identify how this can be translated into practical weed management. The major points are the following: (1) the diversity and type of crops, management actions and limiting resources can be manipulated to limit weed competitiveness while promoting weed diversity; (2) in contrast to technological tools, ecological approaches to weed management tend to be synergistic with other agroecosystem functions; and (3) there are many existing practices compatible with this approach that could be integrated into current systems, alongside new options to explore. Overall, this review demonstrates that integrating systems-level ecological thinking into agronomic decision-making offers the best route to achieving sustainable weed management.
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Cites
Grime, J. P. (1977) · The American Naturalist · doi:10.1086/283244 · Cited by 5,754 · cited 3×
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BackgroundOERKE, E.-C. (2006) · The Journal of Agricultural Science · doi:10.1017/s0021859605005708 · Cited by 5,283
The Limiting Similarity, Convergence, and Divergence of Coexisting Species
Macarthur, R., & Levins, R. (1967) · The American Naturalist · doi:10.1086/282505 · Cited by 4,611
Landscape perspectives on agricultural intensification and biodiversity—Ecosystem service management
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The world‐wide ‘fast–slow’ plant economics spectrum: a traits manifesto
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Soil carbon sequestration to mitigate climate change
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The global spectrum of plant form and function
Díaz, S., Kattge, J., Cornelissen, J. H. C., Wright, I. J., Lavorel, S., Dray, S., Reu, B., Kleyer, M., Wirth, C., Colin Prentice, I., et al. (2016) · Nature · doi:10.1038/nature16489 · Cited by 3,365
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Cited by
A history of conservation agriculture in South Africa
Strauss, J., Swanepoel, P., Smith, H., & Smit, E. (2021) · South African Journal of Plant and Soil · doi:10.1080/02571862.2021.1979112 · Cited by 17
Metadata
- Authors
- MacLaren, C., Storkey, J., Menegat, A., Metcalfe, H., & Dehnen-Schmutz, K.
- Venue
- Agronomy for Sustainable Development
- Published
- 2020-07-08
- Volume
- 40
- Issue
- 4
- ISSN
- 1773-0155 (ISSN-L)
- 1774-0746
- OpenAlex
- W3041798200
- Cited by
- 348
- References
- 194
- FWCI
- 22.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- MacLaren, C., Storkey, J., Menegat, A., Metcalfe, H., & Dehnen-Schmutz, K. (2020). An ecological future for weed science to sustain crop production and the environment. A review. Agronomy for Sustainable Development. https://doi.org/10.1007/s13593-020-00631-6
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.