Modelling Mātauranga: Simulation of traditional management strategies for sustainable harvesting of taonga species
Principal investigator: Professor Henrik Moller
Staff involved: Henrik Moller, Jamie Newman, Sam McKechnie, Ashli Akins,
National partnerships of science and Mātauranga Maori (Maori knowledge, 'ethnoscience') for improved environmental management are sought by MoRST's Vision Mātauranga strategic plan to secure the government's high-level goals of economic prosperity, national identity, and sustainability. Although concrete models of effective dialogue between Mātauranga and science are gradually emerging, there has been protracted and acrimonious public debate about whose knowledge system knows best how to secure sustainable customary and commercial exploitation of fish and other wild foods. There are few case studies where hard science and detailed, reliable recordings of Mātauranga (internationally called 'Traditional Ecological Knowledge') are put alongside one another to challenge and strengthen each other either in New Zealand or internationally.
Our UORG research uses computer modelling and population ecology to predict the relative harvest impact of harvesting when traditional harvesting tikanga is and is not applied. The basic questions under long-term test are therefore: (i) Does traditional Maori harvest management tikanga promote sustainability of harvesting of taonga species? and (ii) Are current fisheries management rules likely to secure sustainable fishing by commercial, recreational, and customary fishers?
Preliminary models were used to debate and conceptualise how the social-ecological models operate in two harvest systems: titi [muttonbird, Puffinus griseus] and kina [sea urchin, Evechinus chloroticus]. Our emerging meta-analysis of Mātauranga constructs identified two main aspects of traditional harvest management: (a) traditional tikanga that protects the adults and large size classes is paramount for harvest sustainability, and (b) seasonal rahui (harvest bans) promote escapement and population resilience.
Our research and strategic goals are to:
- Rebuild existing titi population models;
- Use the modified model to (i) reconstruct past population trajectory since 1946, and (ii) project population and harvest success trajectory for the next 50 years.