Land-use modelling in New Zealand: current practice and future needs

Land Use Modelling Executive Summary (714 KB) Land-use modelling in New Zealand: current practice and future needs (1.5 MB)

Published: 2018

Authors: Jo Hendy, Anne-Gaelle Ausseil, Isaac Bain, Élodie Blanc, David Fleming, Joel Gibbs, Alistair Hall, Alexander Herzig, Patrick Kavanagh, Suzi Kerr, Catherine Leining, Laëtitia Leroy, Edmund Lou, Juan Monge, Adolf Stroombergen, Jim Risk, Tarek Soliman, Tony van der Weerdan, Christian Zammit, Andy Reisinger, Dom White, Levente Timar

a computer motherboard opened up and being used as a steeplejump raceLand-use modelling    
needs research, data, networks,    
and sustained funding.    

New Zealand faces the challenge of using our land in ways that are not only resilient to future pressures and sustain our rural communities but also enhance our natural environment. For the public and private sectors to make robust land-use decisions under uncertainty, high-quality modelling tools and data are essential. The drivers of land-use decisions are complex and models provide a structured methodology for investigating these. While New Zealand is fortunate to have a range of different modelling tools, these have historically been used in a sporadic and ad hoc way, and underlying datasets are deficient in some areas. As the foundation for more strategic development of New Zealand’s modelling capability, this paper profiles the main land-sector and farm- and production-related models and datasets currently applied in New Zealand. It also explores priority policy areas where modelling is needed, such as achieving emission reduction targets; managing freshwater, biodiversity and soil quality; and understanding the distributional impacts of policy options as well as climate change. New Zealand’s modelling capability could be strengthened by collecting and sharing land-use data more effectively; building understanding of underlying relationships informed by primary research; creating more collaborative and transparent processes for applying common datasets, scenarios and assumptions, and conducting peer review; and conducting more integrated modelling across environmental issues. These improvements will require strategic policies and processes for refining model development, providing increased, predictable and sustained funding for modelling activity and underlying data collection and primary research, and strengthening networks across modellers inside and outside of government.





Aotearoa Foundation, Ministry for Primary Industries