Ecological Modeling

Code:

BIOL4053

Acronym:

BIOL4053

Level:

400

Keywords
Classification	Keyword
OFICIAL	Biology

Instance: 2021/2022 - 2S

Active?	Yes
Responsible unit:	Department of Biology
Course/CS Responsible:	Master in Bioinformatics and Computational Biology

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
E:BBC	0	PE_Bioinformatics and Computational Biology	1	-	6	42	162
M:BBC	1	The study plan since 2018	1	-	6	42	162

Teaching language

Suitable for English-speaking students

Objectives

1. Understanding the usefulness and the limitations of ecological models in the analysis of modern environmental problems.

2. Understanding the steps in the construction of ecological models, and identifying the main data types and sources in ecological modeling.

3. Conceptualizing, calibrating, evaluating and spatializing ecological models for specific applications.

4. Implementing scenarios of environmental change and interpreting the predictions of models on ecological grounds.

Learning outcomes and competences

1. To identify situations in which ecological models may be applied.

2. To make informed judgment about the selection of methods and techniques for ecological modelling.

3. To analyze, interpret and apply results from ecological modelling routines.

4. To develop skills for communicating scientific results.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Not applicable.

Program

Introduction to ecological models. Diversity of ecological models. Modern challenges in ecological and environmental sciences – the role of ecological models. Applications of ecological models.

Steps in the construction of ecological models. Ecological theory and conceptual models in support of model development and application.

Types and sources of data in ecological modelling. Handling and analysing geographic data and remote sensing data. Stratifications and sampling design, data collection methods.

Predictive distribution models for species and habitats. Diversity of approaches and modelling techniques. The study of biological communities and ecosystems through models: rationale, examples and applications.

Methods and tools in ecological modelling. The R software in ecological modelling. Calibration of ecological models. Evaluation of ecological models. Spatialization of ecological models. Scenarios and conflict dynamics.

Mandatory literature

Jorgensen, S.; Bendoricchio, G.; Fundamentals of ecological modelling, Elsevier, 2011
Soetaert K., Herman P.M.J.; A Practical Guide to Ecological Modelling. Using R as a Simulation Platform., Springer, 2009

Teaching methods and learning activities

The theoretical contents will be addressed through formal classes, using power-point presentations to promote discussion on relevant topics.

The practical component will include the elaboration by the students, using specific software, of practical projects on the development and application of ecological models, the implementation of scenarios and the ecological interpretation of model predictions.

Software

R

keywords

Natural sciences > Environmental science > Global change
Natural sciences > Environmental science > Ecology
Physical sciences > Mathematics > Applied mathematics > Biomathematics
Natural sciences > Biological sciences > Biodiversity

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	50,00
Trabalho escrito	25,00
Trabalho prático ou de projeto	25,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Apresentação/discussão de um trabalho científico	30,00
Elaboração de projeto	60,00
Frequência das aulas	42,00
Trabalho escrito	30,00
Total:	162,00

Eligibility for exams

Attendance of the classes under the law and regulations in force.

Approval by obtaining the minimum rating (9.5 on a scale of 0 to 20, in accordance with regulations in force) in the overall evaluation (final exam + written essay + group project).

Calculation formula of final grade

Final exam (50%) + Written essay (25%) + Group project (25%)

Examinations or Special Assignments

Not applicable.

Internship work/project

Not applicable.

Special assessment (TE, DA, ...)

Not applicable.

Classification improvement

Classification improvement is done according to law and regulations in force, through repetition of the final exam.

The written essay and the group project cannot be repeated.

Observations

Students that don’t speak Portuguese may be subjected to alternative forms of evaluation.

Coordinator: João Honrado.