Monitoring Biodiversity for Science and Conservation

Purpose and scope

Monitoring is a crucial part of every scientific research project and study. It is important that the monitoring/data collection is well designed, structured, planned and executed so that it fulfills the goals of the project or the study. This involves knowledge of various theoretical and practical aspects that are to be considered when collecting scientific data at different scales. Appropriate study design, sampling theory, effort, scale, bias, precision and accuracy, choosing the right metric, and replication are among the crucial theoretical aspects that are necessary for monitoring. The extent and strength of the inferences drawn will therefore vary, depending on the study design used in monitoring. Moreover, the use and the analyses of already collected monitoring data also requires skill and knowledge to be able to identify the biases and errors.

Many existing monitoring programmes suffer from various design deficiencies. Specifically, many programmes appear to be developed without paying adequate attention to three basic questions: (1) Why monitor? (2) What should be monitored? and (3) How should monitoring be carried out?

This course is targeted towards offering knowledge about census methods for monitoring the state of species, communities, populations and ecosystems as well as their attributes in space and time. Secondly, we will discuss how the biodiversity monitoring information is used at various law and policy levels and what are the challenges encountered by the stakeholders in monitoring and conservation of biodiversity.

Course content

1. Basics of census methods and sampling theory, biases and errors
2. Planning a census and experimental design (R power analyses)
3. Monitoring species, communities and ecosystems
4. Population Density methods, animal biotelemetry and removal methods (R distance analyses, movement analyses, electrofishing)

5. Camera trapping, Mark recapture methods, including Genetic MRM (R lab)
6. Citizen science and Indexes – Catch Per Unit Effort (R lab)
7. Comparing census methods (R lab)
8. Remote sensing methods for monitoring biodiversity and spatial data (R lab)
9. Monitoring biodiversity – global conservation and policy perspective
10. Business and Biodiversity – offsets, standards, banking and methodologies

Pedagogical form

Onsite Lectures in the morning and computer lab exercises in the afternoon.

Pass grade requirements

Examination will be in the form of an assignment

Literature

Ecological Census Techniques handbook

Lecture handouts

Peer reviewed articles and reports

Course material

Handouts, reading material and exercises with R codes and datasets

The number of available places are limited to 25.