Detailed information about the course

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Title

Population ecology for conservation

Dates

TBD

Lang EN Workshop language is English
Organizer(s)

Prof Sergio Rasmann, UNINE

Speakers

Prof Jacob Koella, UNINE

Description

This course explores how concepts of population ecology can be used to help to conserve and manage natural populations. In particular the course will describe the basics of population viability analysis, a key tool of conservation biology that consists of a set of ecological methods that brings together species characteristics, demography and environmental variability to forecast the health of a population and the risk that it goes extinct. Population viability analysis requires models of populations, so this course also teaches how to build ecological models. Most of the models will be stochastic models, which are the most relevant for risk assessment.

We will focus on the main and simplest components of population dynamic models – density-dependence, age-structure and spatial structure. You will learn how two stochastic processes – demographic and environmental stochasticity – affect the dynamics of populations and risk of them disappearing, especially when they are small., and how this risk can be quantified with a population viability analysis.

Topics:

1. Stochasticity and risk assessment
2. Demographic and environmental stochasticity
3. Simple population models and population viability analysis: density dependence and the Allee effect
4. Age-structured and stage-structured populations
5. Spatially structured populations

Student learning outcomes
:

1. Explain how and why simulation models are used by ecologists and conservation biologists.
2. Understood the importance of stoachsiticy in small populations.
3. Apply population viabliity analysis and other ecological tools to the conservation and management of populations.
4. Evaluate the strength of inferences using sensitivity analysis.
5. Perform basic simulation modeling with R

Location

UNINE

Information
Places

10

Deadline for registration
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