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| ORM7350 | Modeling of Forest Ecosystems | 3+0+0 | ECTS:7.5 | | Year / Semester | Fall Semester | | Level of Course | Third Cycle | | Status | Elective | | Department | DEPARTMENT of FOREST ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Prof. Dr. Nuray MISIR | | Co-Lecturer | N0ne | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | To acquaint the students with concept of forest ecosystems, to teach them the growth process and to help them use their knowledge to model this process mathematically. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | Understand processing forest ecosystems. | 3 - 5 | 1,3,5 | | PO - 2 : | Comprehend the growth process in forest ecosystems. | 1 - 3 - 5 | 1,3,5 | | PO - 3 : | Model growth in forest | 10 - 11 | 1,3,5 | | PO - 4 : | Run models and compare and analyze the performance of each model with a number of outputs. | 3 - 5 | 1,3,5 | | PO - 5 : | Stratify the growth models. | 3 | 1,3,5 | | PO - 6 : | Validate growth models and make evaluation. | 3 - 5 | 1,3,5 | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | | |
| Concepts within forest growth modelling, growth and yield process, modeling approaches, models to understanding and estimating, empirical models, mechanistic models, biological-process-based models, deterministic and stochastic models, individual tree growth models, stand-level growth models, database design for models, evaluation and validation. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Concepts within tree growth modelling | | | Week 2 | The process of growth in forest ecosystems | | | Week 3 | Modelling process and components | | | Week 4 | Modelling approaches | | | Week 5 | Models to understanding | | | Week 6 | Models to estimating | | | Week 7 | Empirical models | | | Week 8 | Mechanistic models | | | Week 9 | Mid-term exam | | | Week 10 | Process-oriented pyhsiologic models | | | Week 11 | Deterministic models | | | Week 12 | Stochastic models | | | Week 13 | Evaluting models and validation | | | Week 14 | Student presentations | | | Week 15 | Discussion | | | Week 16 | End-of-term exam | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 2021 | 3 | 30 | | Homework/Assignment/Term-paper | 13
14 | 2021 | 3 | 20 | | End-of-term exam | 16 | 2022 | 3 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 6 | 14 | 84 | | Arasınav için hazırlık | 5 | 4 | 20 | | Arasınav | 3 | 1 | 3 | | Ödev | 3 | 2 | 6 | | Dönem sonu sınavı için hazırlık | 6 | 4 | 24 | | Dönem sonu sınavı | 3 | 1 | 3 | | Total work load | | | 182 |
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