The 7th International Plant Functional Traits Course will be held in Drakensberg, South Africa, 1 - 19 December 2023.
Plant Functional Traits Courses (PFTC) offer hands-on training in applications of plant functional trait ecology within a real-life field research project setting. During this 7th PFTC course, students will collect and explore plant functional trait data in the field and use trait-based approaches within community and ecosystem ecology. Following the course, students will have opportunities to participate in / lead publications using the data. See our current publications.
Trait-based ecology incorporates methods that enable powerful approaches to predict how climate and biotic interactions shape plant community dynamics and ecosystem functioning. This course will provide students with essential background knowledge and the practical field, lab, and computational skills needed for conducting their own research within trait-based ecology.
Application deadline: 28 February, 2023.
Update 9 March: Any applications received from now on can unfortunately not be considered.
The PFTC7 course will be held in the Drakensberg Mountains in South Africa, between the 1st and 19th of December 2023 with online pre-course preparatory work in September - November 2023. We will work alpine grasslands, from c. 2000 to 3000 m a.s.l., in the Witsieshoek area of the Drakensberg mountains. It is a fascinating and truly beautiful study system, located within a very biodiverse area (c. 3000 plant species in the eastern Drakensberg region, with c. 9% endemism; Carbutt 2019 S. Afr. J. Bot).
Students will be introduced to the environmental, microenvironmental, ecological, and taxonomic diversity of the region, and given hands-on instruction in relevant theory and methods of ecophysiology; community, functional traits and ecosystem ecology; population biology; computational biology; and data management. Students will work in four groups:
- Plant trait responses along an elevational gradient (~10 students). This large group will assess trait responses along an elevational gradient. Within this larger group, students will focus on specific projects such as grasses vs. forbs, ridge vs. depression microhabitats, C3 vs C4 grasses, grazing quality, and/or explore consequences for plant community assembly and ecosystem functioning. This group will collaborate with groups 2, 3, and 4 to understand plant and ecosystem functional consequences of these community shifts. Group leaders: Julia Kemppinen & TBDs
- Leaf traits as a tool to understand environmental impacts on photosynthesis and respiration (~5 students). This group will study how leaf temperatures and physiological fluxes vary between plants from different elevations, origins, functional types, and photosynthetic pathways. Group 2 will collaborate with the group 1 sub-groups to put these responses in context of broader plant and community responses to the environment. Group leaders: Sean Michaletz & TBD
- Environmental impacts on traits and ecosystem functioning (~5 students). This group will study how trait composition influences ecosystem functioning by measuring CO2-flux within and across plant communities. Group 3 will collaborate with group 1 to access data on community trait shifts, and mainly focus on ecosystem carbon dynamics in response to environmental variation. Group leaders: Brian Enquist & TBD
- Remote assessment of plant traits and ecosystem functioning (~8 students). This group will assess how remotely-sensed data can capture plant and ecosystem functional traits from individual plants to landscape-scale. We will work on two projects:
- a) Passive Sensors/reflectance: leaf spectroscopy in the field to capture intra- and inter-specific variability as it is linked to landscape properties, and to study how the multi- and hyper-spectral reflectance data can inform on plant traits.
- b) Active Sensor/radar: we will employ a Ground-penetrating Radar (GPR) to infer belowground plant biomass and root structure.
- Group 4 will collaborate with groups 1-3 over community-level data. Students applying for this group should have experience with geospatial analyses. Group leaders: Nicola Kühn, Nicole Bison, & Marc Macias-Fauria.
Through developing and conducting these research projects to explore the potential of plant functional trait-based approaches in understanding the biodiversity and ecosystem functioning of the study area, PFTC students will build key research skills in planning and conducting trait-based field campaigns. You will gain practical experience in measuring plant functional traits and related physiological, plant community, and ecosystem data in the field using standard protocols. Group 1 will be focussing especially on the biodiversity and plant functional trait data, group 2 and 3 students will become especially familiar with taking measurements using ecophysiological equipment including LiCor 6800 and LiCor 7500, and group 4 with spectral data. You will learn about the structure and analysis of trait data, be introduced to best practice data management and reproducible coding, as well as having the opportunity to analyse and interpret data yourself. You can read about previous courses in China, Peru, and Norway here.
An important element of this course is its cross-disciplinarity, spanning from detailed measurements of physiological rates to remote sensing. While students will receive in-depth training within their speciality, they will also contribute to, collaborate on, and gain insight into the work of the other groups.
The course is primarily aimed at graduate students, both MSc and PhD, but both earlier and later career stages may be considered given appropriate justification. The course will give a broad introduction to and hands-on experience in different aspects of trait-based ecology. You will work with international instructors, in teams, and collect research-grade data in the field to address a specific research question. There will be opportunities for participating in publications based on the course data.
Students are selected based on:
- How well this course fits into and will contribute to their career plans.
- The student's specific need for practical experience in the research approaches offered (e.g. students applying for group 1 should not have extensive prior experience with measuring plant traits). Note the exception for group 4, where specific prior experience is requested.
- Location, with within-continent students prioritized.
- Diversity of educational, academic, cultural/ethnic backgrounds of the team as a whole will be considered.
- Other relevant factors - students are encouraged to motivate their need and interest for participating in the course by including any information that they see fit.
- The course fee covers costs for accommodation, food, and local transport during the course. The course fee is NOK 18.000 for students from high-income countries, NOK 8000 for students from upper middle-income countries, and NOK 4000 for students from lower middle income and low income countries and from Africa (Based on World Bank country classifications 2022-2023). Students for which these costs are prohibitive may apply to be considered for a reduced fee, noting that such reductions will only be available to a limited number of students.
- For students from the course partner institutions (University of Arizona, University of British Columbia, University of Pretoria, University of Bergen, Norges Miljø og Biovitenskaplige Universitet, The Institute for Mountain Hazards and Environment at the Chinese Academy of Sciences, and Oxford University) funding is available to help offset the cost of travel to South Africa.
- Students should plan to arrive at Johannesburg airport during December 1st, and leave during December 19th. Transport from Johannesburg to Witsieshoek will be organized by the course leaders. Please do not book you travels until we have confirmed receipt of your course payment.
- In case of cancellations due to Covid-19 or other Force Majeure situations, course fees will be reimbursed in full. A condensed online course will then be offered, consisting of some traits DIY practicals, but making use of existing data from previous courses for hands-on data management and analyses. This will be offered for a reduced course fee.
- The course is led by Professors V. Vandvik from the University of Bergen, Norway and B. Enquist from the University of Arizona, USA with collaborators, and hosted by Prof. Peter le Roux, University of Pretoria.
- The course is 5 ECTS credits, with possibility for an additional 5 ECTS extension for students involved in scientific publication of course outcomes. Credits are awarded by the University of Bergen.
Pre-course timeline: 2023
- Feb 28th: Applications due
- Mid-March: Students will be notified of acceptance
- April 15th: course fee and paperwork for UiB due
- Early September: Group leaders will contact you with a list of publications relevant to each project to read and review.
- September-October: online lectures and discussions over theoretical and empirical approaches to trait-based ecology, and the natural history of the study system and region.
- November: Group leaders will schedule at least 2 sessions to discuss literature, and at least 1 session to discuss project design and data documentation. These sessions will consist of a combination of student submitted written summaries of specific themes or papers, and interactive commenting and sharing of ideas within the group via communication channels appropriate for interactive classrooms.
- TBD: Deadline 1 for paper review.
- TBD: Deadline 2 for paper review.
- TBD: Deadline for the first draft of the course data documentation files.
- TBD: Deadline for the final course data documentation files.
Apply for the course
To apply, please send one document containing 4 pages:
- First page: a brief description (max. 300 words) of how the course fits into your career plans. In this essay, please minimise personal information (i.e., do not specify your gender / background / nationality / institutional affiliation) to help us make an unbiased selection!
- Second page: indication of which group you would like to apply for, and a ranking if you apply for several groups. If relevant, state any special considerations/needs/reasons or other information about you or your background to support us in being fair and inclusive in our candidate selection.
- Third page: CV, with information about education and relevant work experience, relevant skills and competences, and familiarity with relevant field and lab techniques and relevant coding, statistical, modeling, and geospatial software.
- Fourth page: contact information
Application deadline: 28 February 2023.