Citizen science (CS) is a quickly evolving field, engaging millions of volunteers around the world in parts of the scientific process. New technologies have facilitated this rapid expansion by making CS programs attractive to a diverse set of participants and multiplying the ways in which researchers and citizen scientists interact together to address scientific questions. As many participants gather high volumes of data, CS can help researchers solve new problems or approach previous questions from a larger scale perspective. CS has already made important contributions to fields like ecology, conservation science, environmental protection, geographic information research, social sciences and epidemiology. In addition, CS simultaneously plays an important role in education and the public perception of science. This course will cover what citizen science is and the key components that form a CS program. Also, we will explore some of its current applications and weigh the investments needed to create a CS program. We will also compare different project categories, based on the activities that are carried out by the participants. During the course, students are going to get involved first-hand with local CS projects and exercise on planning reasonable new initiatives based on CS. Lastly, we will discuss some of the current promises of CS in terms of democratization, education and scientific discoveries, in the
context of the UN Sustainable Development Goals (SDGs). By the end, students will have a significant understanding of the potential and challenges of CS for achieving a sustainable future.
This course presents a compilation of ecological research methods, extending
from classical methodologies to modern tools and techniques. The course will emphasize
a practical approach, which will be conducted in different locations of the
university campus, like the UPeace Recreational Park. In addition, students
will visit the Insect Museum to complement the sampling methods component, and
prepare presentations intended to strengthen their associative skills and
concept assimilation among the different methodologies and their applications
in ecological research.
This course presents a combination of
lectures, discussions, literature review, writing essays, and field practice as
an attempt to understand diversity and conservation of bird life. The course
will overview classic and current topics in Ecology of Birds and how we can
integrate diverse disciplines to develop bird conservation strategies. The
course will incorporate specialized bird monitoring techniques and bird
behaviour observations in the field, which will be conducted in different
locations of the university campus, like the UPeace Recreational Park.
In this course we will become familiar with contemporary issues in the field of Ecology & Society. To provide context to our discussions, we begin with an analysis of key frameworks and principles including Social-Ecological Resilience, Environmental Justice and Community Based Research. Via contemporary case studies we put these frameworks and principles into practice. In this course we mainstream social justice to ensure that we understand how programs and policies affect countries and peoples differently
This course provides an opportunity for graduate students in the MSc Programme in Ecology to expand their breadth of knowledge and complexity of understanding and application of ecological principles. It is designed to provide the knowledge needed so students can focus on the more advanced experiences available to them in their future courses and research experiences concerning the concepts, current and future regional to international issues in the ecological sciences, and the application of ecological theory and methods to address these issues.
This course presents a review of multiple statistical methods for data
analysis, ranging from the most fundamental concepts to modern analysis techniques. The
course will be given with a practical and intuitive approach, which will be developed through
the use of the R program (no previous experience is required). In addition, the course will seek
to cultivate an appreciation for good practices in data visualization, as well as to foster students'
critical analysis of different problems related to the manipulation and interpretation of
statistical information.