Position: Science technician and research assistant, Field: Ecology, Organisation: School of Biological Sciences, University of Canterbury.
As part of her job as Terrestrial Ecology Technician, Jenny runs practical laboratory sessions for undergraduate students and organises field trips for them. She also helps postgraduates design and set up their research. This means being involved in fascinating experiments and meeting students from all around the world. It can also be frustrating when researchers leave it to the last minute when asking for special equipment!
As well as these teaching assistance roles, Jenny’s time is spent as a research assistant. Since completing her MSc research on New Zealand mistletoes, Jenny has worked with Dave Kelly on bird-plant interactions and their effects on ecosystems. After deciding which ideas need testing, Jenny searches for sites to run the experiments at and collects the data. This then gets analysed and written up back in the office, mostly by Dave.
Field trips and research get done all over the country, but one of the places Jenny uses a lot is the University of Canterbury’s Cass Field Station, near Arthur’s Pass in the South Island. She uses Cass as a base while working on mistletoes in the nearby Craigieburn Forest. Jenny also helps scientists who use the land around Cass for their research. For example, Jenny helps mark and monitor wētā there for a long-term survey.
“Cass can be a lovely place to work, with its huge open skies and wide landscapes. It can also be miserable – cold, wet and very windy.”
Cass is used for student field trips, which, as science technician, Jenny gets to organise. This involves everything from arranging gear and transport to organising food and cooks. These trips are vital for students, making real what they learn in class. For some of them, it is their first experience of ‘the big outdoors’. Being so isolated, they get to rely on each other, and some lasting friendships are made there.
See this news story,
Nature of science
Science experiments require both a good theoretical question and carefully collected data (experiments or observations). Good data collection needs good hands-on skills, a careful watch for the unexpected, and consistency.
This article is based on information current in 2012.