About this course

Silviculture (regeneration, thinning, silvicultural systems, certification, exotic tree species) and forest genetics.

Learning outcome

Knowledge:

Students will learn about the most common silvicultural methods and their effects on the development of trees and forest stands. Students will learn about exotic tree species in order to identify them and evaluate their use and spreading potential. Students will learn the basics of forest genetics, genetic variation, choice of provenances, breeding and adaptation to future climate. The knowledge should be based on research and updated.

Competence:

Students will be able to select silvicultural options depending on management objectives, conditions for growth, and stand development. Students will be able to evaluate effects of the chosen silvicultural method on growth and development of forest stands.

Attitudes:

Students should be able to see advantages of of knowledge-based forest management as opposed to traditions and hierachical orders.

General competance:

Students will be able to find, read, and communicate the content of relevant research literature within the field.

  • Learning activities

    Student reading, lectures, field trips, exercises, and term assignment.

  • Teaching support

    Teachers will be available for questions during office hours.

  • Syllabus

    A collection of textbooks and articles.

  • Prerequisites

    SKOG100, SKOG200, ECOL100.

  • Assessment method

    The evaluation comprises three parts:

    • Tests (30%)
    • Semester assignment (20%)
    • Oral exam (50%)

    Students who have previously passed one or more components of the combined assessment in the course are not required to retake these when repeating the course.



    Term paper Karakterregel: Letter grades Oral exam Karakterregel: Letter grades Tests Karakterregel: Letter grades

  • About use of AI

    Tests: K1 - No use of AI

    Semester assignment: K2 - Specified Use of AI.

    AI shall not be used to generate summaries or discussion assignments. These texts shall be written by the student after having read the research papers. Communication of the content of research papers is an essential part of the learning process and cannot be substituted by generating text using AI.

    It is specified in NMBU's regulations that exams and assignments shall be a student's own work.

    Students must supply a detailed description of their use of AI (for example for language editing) in a separate section at the beginning of the semester assignment. These descriptions shall in detail describe which AI programs have been used for which parts of the learning og writing process and in which way.

    The use of AI must comply with the Guidelines for Use of Artificial Intelligens (AI) at NMBU.

    Oral exam: K1 - No use of AI

    Mandatory activity: K3 - Full use of AI.

    The use of AI is permitted, but it must comply with the Guidelines for Use of Artificial Intelligens (AI) at NMBU.

    Descriptions of AI-category codes.

  • Examiner scheme

    External examiner evaluates the oral exam.

  • Mandatory activity

    Field trips and exercises. Exercise on plagiarism signed before term assignment delivers.

  • Teaching hours

    In the block period: 6 hours per day, field trips, exercises, lectures.

    In the parallel period: 4 hours per week, lectures, seminars, field trips.

  • Reduction of credits

    10 credit overlapp with the old version of SKOG220 V16 (15 credit course that were taught last time autumn 2015).

  • Admission requirements

    Minimum requirements for entrance to higher education in Norway (generell studiekompetanse)