PhD course Advances in forestry analysis and data management

Last changed: 14 December 2020
birch forest

This Ph.D. course focus on an advanced understanding of forest trials and inventories.

Advances in forestry analysis and data management (8 ECTS), Course code: PFS0177

Subject area: Forest Inventory, Inventory design, forest growth and yield and forest modelling.

Learning outcomes. After this course, the students are expected to:

  • Know about the advanced level statistics with large-scale inventory data
  • Understand the statistics of various experiments
  • Independently design their experiments and perform their inventories

Entry requirement: Basic knowledge in forest inventory, experimental design, science methodology, Statistics, and R software is a prerequisite. (There will be a module in the Canvas course page for update and repetition of entry requirements)

Objectives: This course provides an advanced understanding of how forest trials are designed and how inventories are performed. The course's target group comprises early-stage doctoral students who will initiate field trials, analyse larger quantities from long-term trials, design inventories, and implement and/or analyse more extensive inventories in forests.

Content. This course consists of four modules:

  • Forest models of trees and growth
  • Design and analysis of forestry experiment
  • Inventory design
  • Analysis of inventory data

Pedagogical form:

The course will be held online with two days of physical meetings (depending on the COVID situation). There will be various online lectures, discussions, group assignments and a final individual project to present the results. 

Timetable: Lectures on Tuesdays and Thursdays. Interactive questioning sessions and group discussions on Fridays.

Start date: 26 januari 2021

Physical meetings: Depending on the COVID situation

End date: 26 march 2021

Deadline to apply: 2021-01-01

Evaluation: Students’ performance during the whole course will be individually assessed along with the final submission of an assignment.

Contact: Narayanan.Subramanian@slu.se

Page editor: klas.pernebratt@slu.se