Prerequisite:

Finished bachelor’s in Biology or equivalent program of study

Content (Syllabus outline):

• Abiotic and biotic factors in environment
• Relations between plants and the environment
• Ecological niche and ecosystem
• Sampling of plants and plant communities and data processing
• Spatial data processing
• Formation of large databases
• Numerical methods
• Macro-ecology
• Plants as part of the landscape

Readings:

• Schultze E.D., Beck E., Müller-Hochenstein K. (2005). Plant ecology. Springer, Heidelberg.
• Tremp H. (2005). Aufnahme und Analyse vegetationsökologische Daten, Ulmer, Stuttgart.

Objectives and competences:

Ecology studies interactions between organisms and their environment. The purpose of this course is to familiarize students with the basic concepts of plant ecology. The course deals with individual plants and their interactions with other plants and the environment, plant communities and their spatial distribution. We will also deal with ecosystems that include all living organisms and nonliving components in a given area. We will study plant ecology at all levels of organization, from cells, organisms, to plant communities and biomes, the broadest community of organisms. Because plants in ecosystems are not static but constantly change we will get familiar with directed changes (successions) and fluctuations. The aim of the course is for students to understand the relationship between plants and plant communities, and the environment, ecosystems and their functioning as well as get acquainted with the sampling and data processing.

Intended learning outcomes:

• Understanding basic ecological concepts (population niches, habitats, ecosystems, landscapes, biomes).
• Understanding the interactions between plants and the environment, the formation of ecosystems.
• Understanding ecosystems and their functioning (e.g. food chains) and dynamics (e.g. successions).
• Understanding the distribution of plants on the planet (from the community to the biome).
• Knowledge of basic methods of sampling and data processing.

Assessment:

Exam (80%), written paper (20 %).