Weed Ecology and Evolution
Weedy plants are among the most adaptable, successful, and economically impactful plant species. The weed ecology and evolution group is working to understand the ecological, evolutionary, and genetic processes and mechanisms that lead to the establishment, adaptation, spread and persistence of weeds in agroecosystems. We apply this understanding to the design of sustainable weed management strategies.
We span basic to applied research questions, believing that the best applied outcomes rest on a thorough understanding of the fundamentals of weed biology. We believe that weedy plants are excellent models for basic studies of rapid, human-mediated plant adaptation. Equally, we recognize that attempts to develop sustainable weed management strategies must acknowledge and mitigate these rapid evolutionary processes.
Our group adopts a ‘gene to landscape’ approach to weed population biology applying techniques and principles from plant ecology, evolutionary biology, population and quantitative genetics, genomics, epidemiology, modelling and crop science.
- The evolution of weedy plants.
- Weed-crop competition.
- Plant-plant-microbe interactions in cropping systems.
- Population genomics of weeds.
- Evolution of resistance to herbicides.
- Site-specific weed management.
- Weed population dynamics.
- Agroecological approaches to crop health and protection (One Crop Health)
- Smart plant protection
- One Crop Health
- Novo Nordisk Foundation start package: Basic research on ecology, evolution, and sustainable management of weedy plants in agroecosystems (as PI).
- University of Copenhagen PhD scholarship: Exploring local adaptation an evolution of weediness in a global collection of Alopecurus myosuroides (as PI).
- Miljøstyrelsens Program for Bekæmpelsesmiddelforskning: Biology and management of herbicide resistance in Poa annua (as Co-PI).
- CSIRO Postdoctoral Fellowship: Harnessing modern spatial analysis to better predict the emergence and management of pesticide resistance in agricultural systems (as Co-PI).
Group members
| Name | Title | Phone | |
|---|---|---|---|
| Augustin Ambroise O Baussay | Research Assistant | +4535322122 | |
| Célia Neto | Postdoc | +4535337565 | |
| Paul Neve | Professor | +4535322161 | |
| Quanjing Zheng | PhD Fellow | +4535330603 |
MSc students
- Ziyan Zhou