Stella the kākāpō on Codfish Island.
Image: Sabine Bernert | ©


Use this resource to uncover why the kākāpō is so important to New Zealand.

This resource has been developed by our partners Meridian Energy.

This resource introduces students to:

  • kākāpō ecology: where they live, what they eat, their adaptations, and how they stay alive
  • kākāpō challenges: kākāpō threats and how people contribute to these
  • kākāpō conservation: the role of people in protecting kākāpō.

Kākāpō Recovery education resource cover.

Download the resource

Kākāpō Recovery education resource (PDF, 2,693K)

Kākāpō infographic

This infographic explains what a kākāpō is, why they are so vulnerable and how people are working together to help them survive. 

Kākāpō infographic (PDF, 495K)

Learning outcomes

Using this resource, students can:

  • build knowledge and understanding of kākāpō
  • raise awareness of the current situation for kākāpō
  • understand how people are involved in kākāpō recovery
  • contribute to a positive future for kākāpō.

Curriculum links

Level 1-4 Science

Living World: Ecology

  • Recognise that living things are suited to their particular habitats.

Living World: Life processes

  • Recognise that living things are suited to their particular habitats.

Nature of Science: Investigating in science

  • Ask questions, find evidence, explore simple models and carry out investigations to develop simple explanations.

Science capabilities:

  • Gather and interpret data
  • Use evidence
  • Interpret representations
  • Engage with science

Level 1-4 Social science

  • Understand how people make decisions about access to and use of resources
  • Understand how formal and informal groups make decisions that influence communities

Level 1-4 Mathematics and statistics

  • Statistical Investigation: Conduct investigations using the statistical enquiry cycle: gathering, sorting, and displaying multivariate category and whole-number data and simple time-series data to answer questions.
  • Identifying patterns and trends in context within and between data sets


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