Information Package / Course Catalogue
Ecological Niche Modeling
Course Code: ZPM626
Course Type: Area Elective
Couse Group: Third Cycle (Doctorate Degree)
Education Language: Turkish
Work Placement: None
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 8
Objectives of the Course

Fundamental approaches to ecological niche modeling (ENM) and species distribution modeling methods, GIS-based ENM mapping, modeling, analysis and evaluation according to different climate scenarios.

Course Content

Ecological Niche Modeling (ENM) theory, preparation of environmental variables used in ENM, introduction of the programs to be used and detailed information, application of model statistics.

Name of Lecturer(s)
Learning Outcomes
1.Having in-depth knowledge in one or more areas of expertise in the field of Landscape Architecture.
2.Having the ability to develop a design, plan or an idea that brings an original method, application or innovation in the field of landscape architecture, or to apply a known method.
3.Following current developments in planning, design, conservation, and management issues related to the field of profession; Having the ability to use remote sensing, geographic information systems, computer-aided design and visualization software.
4.Having the skills to conduct research in the field of landscape architecture science, collect and analyse data, gather and synthesize findings, interpret the results and develop scenarios and solution suggestions
5.Having lifelong learning and research awareness.
6.Having social and environmental sensitivity, awareness and ethical values.
7.Having the ability to follow the literature related to the field of science in at least one foreign language, to use foreign sources in teaching and research activities, and to write articles in English in his/her own research field.
Recommended or Required Reading
1.Guisan, A., Thuiller, W., & Zimmermann, N. E. (2017). Habitat suitability and distribution models: with applications in R. Cambridge University Press
2.Muscarella, R., Galante, P. J., Soley-Guardia, M., Boria, R. A., Kass, J. M., Uriarte, M., & Anderson, R. P. (2014). ENM eval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods in ecology and evolution, 5(11), 1198-1205.
3.Cobos, M. E., Peterson, A. T., Barve, N., & Osorio-Olvera, L. (2019). kuenm: an R package for detailed development of ecological niche models using Maxent. PeerJ, 7, e6281.
Weekly Detailed Course Contents
Week 1 - Theoretical
General introduction of the course
Week 2 - Theoretical
The concept of niche, the importance of historical and geographical distribution
Week 3 - Theoretical
Information on R statistics software and introduction of MaxEnt
Week 4 - Theoretical
Information on R statistics software and introduction of MaxEnt
Week 5 - Theoretical
Preparation of environmental variables
Week 6 - Theoretical
Introduction of ENM algorithms
Week 7 - Theoretical
Implementation of the model in MaxEnt software
Week 8 - Theoretical
Evaluation of model statistics
Week 9 - Theoretical
Testing model accuracy
Week 10 - Theoretical
Projection according to different periods
Week 11 - Theoretical
Projection according to different periods
Week 12 - Theoretical
Modeling a threatened plant species with MaxEnt according to IUCN - case study 1
Week 13 - Theoretical
Modeling a threatened plant species with MaxEnt according to IUCN - case study 1
Week 14 - Theoretical
Modeling an invasive plant species with MaxEnt - case study 2
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%30
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory14102168
Term Project1617
Midterm Examination110111
Final Examination113114
TOTAL WORKLOAD (hours)200
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
OÇ-1
5
5
5
3
3
5
4
OÇ-2
5
5
5
3
3
4
5
OÇ-3
4
4
4
2
2
3
4
OÇ-4
3
3
3
1
1
2
5
OÇ-5
3
4
5
5
5
3
4
OÇ-6
OÇ-7
Adnan Menderes University - Information Package / Course Catalogue
2026