PhD course Individual-based forest ecology and management, 3.0 credits

Last changed: 11 November 2022
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The purpose of the course is to give the student an opportunity to go in-depth in a certain subject of silviculture, and together with other students and senior researchers discuss concepts and conflicts of the topic.

 

 

 

 

Thematic course in a specific silviculture topic (3.0 ECTS), Course code PFS0153

Subject area: Forest Management

Contact: Arne Pommerening, Professor at the Department of Forest Ecology and Management; Mathematical Statistics Applied to Forest Sciences 

Time: 1-12 March 2021

Last day of application: 20 February

Language: English

Prior knowledge: MSc

Content:

The course starts off with theories and concepts of individual-based forest ecology and management.  These play an important role in continuous cover forestry (CCF). CCF is currently much discussed in Sweden and is considered as a means to mitigate climate change. Then the students are introduced to aspects of point process statistics including measures of spatial tree diversity and how these methods can be used to carry out research on interactions between trees. As part of this we will also discuss how environmental conditions and forest management modify these interactions. Time permitting and based on the findings from interaction research, the students will be introduced to the concept of individual-based modelling, i.e. how results from interaction research can be used to design and parameterise individual-based tree models.

Assignment:

The students will either submit a literature review and selected, previously agreed topics or they will carry out an analysis of spatial tree interaction. It is also possible to critically discuss a research paper in the spirit of a literature seminar. The options will be discussed in class at the beginning of this theme and topics/data will be provided.

Pre-requisites: 

The students should have a basic understanding of statistics and the R software. A two-days R primer course can be taken online here. There are also R drop-in sessions available throughout the term, monitor the Faculty screens for more information.

 

Additional resources relevant to this module are available in my textbook (Links to an external site.) and on my website.