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Published: 2008
Authors: James D Shepherd, Anne M Sutherland, Ian Payton, Wei Zhang, William Power, Suzi Kerr
This report was commissioned as Landcare Research Contract Report: LC809/033
GOAL
Determine the areas of indigenous forest/shrubland and exotic shrubland types that have regenerated since 1990, and that could potentially regenerate on marginal erosion-prone lands where economic returns tend to be low. Identify the broad ownership of these areas and predict the extent and likely location of indigenous reversion under an emission trading scheme
APPROACH
Areas of forest and shrubland that regenerated on marginal grasslands between 1990 and 2000 were determined using data from the Land Use and Carbon Analysis System (LUCAS) 1990 baseline mapping project. The Corax Mobile data layer of New Zealand cadastral boundaries (derived from data held by Land Information New Zealand), and GIS shape files of Conservation land, other Crown land, and Māori land were intersected to give an ‘ownership’ shape file showing broad land-ownership information (Conservation land, other publically owned or
covenanted land, Māori land, and privately owned land).
This ‘ownership’ file was used to extract and tabulate the areas and types of regeneration in each land ownership category for both the North and South Island. Grasslands marginal for agriculture but with the potential to undergo reversion to shrubland and indigenous forest were determined by intersecting areas mapped as Class 6 (with a moderate to severe erosion rating), 7 and 8 by the New Zealand Land Resources Inventory (NZLRI) with areas identified by the Vegetation Cover Map (Newsome 1987) as likely to have seed sources that would allow natural reversion to indigenous forest, indigenous broadleaved shrubland, mānuka/kānuka shrubland, or gorse.
Landcare Research
The Land Use in Rural New Zealand (LURNZ) model was used to assess how much land is likely to enter the ETS as indigenous reversion. The model uses historical relationships between output prices and land uses (where all land uses depend on all prices) and projections of commodity prices, to predict shifts in land use at a national scale. Three scenarios were modelled:
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