Predicted Potential Natural Vegetation of New Zealand

Knowledge of New Zealand's historic biodiversity assets is essential for understanding and managing the value of its surviving indigenous ecosystems. It is particularly important in highly modified landscapes where it provides a context for assessing the conservation value of surviving forest remnants or when this information guides the development of realistic objectives in ecosystem restoration projects.

The survival of native vegetation has been uneven across New Zealand's landscape, with the most extensive tracts of native forest occurring in environments unsuited to intensive human land uses because of their cool temperatures, high rainfall, and/or steep terrain. Little indigenous biodiversity now survives in much of New Zealand's lowlands, the greatest devastation having occurred in warm, dry climates on landforms prone to fire and/or suited to agriculture. In the past, reconstructions of historic vegetation cover have been largely qualitative in nature or derived from historic records. However, recently developed statistical tools, both for the interpolation of point climate data and the analysis of spatial patterns, greatly extend the ability to reconstruct the biological character of New Zealand's prehuman past.

The vegetation pattern shown on this map was generated using a mix of environmental and geographic information layers. The tree line or upper altitudinal limit of forest was predicted from data layers describing the average temperature of the warmest month and summer day length. The upper limit of vegetation was set at an average summer temperature of 8.5 degrees C. All sites below the tree line were allocated a vegetation of forest except (1) sites with very poorly drained soils that were mapped as wetlands, (2) sites with recent soils on dune sand that were mapped as dunelands, (3) sites with average extreme minimum temperatures less than -10 degrees C or ultramafic soils that were mapped as woodland and scrub.

The forest pattern was defined using statistical modeling techniques that coupled extensive plot data describing forest composition and 15 climate and soil layers. Geographic limits for New Zealand's four Nothofagus or beech species were determined from distributional and historic data, and their abundances within these limits were predicted from the environment. Abundances of 33 other forest tree species were individually predicted from the environment, while also taking into account the abundance of Nothofagus. Predicted abundances for the individual tree species were then combined and classified to derive the 20 forest classes shown here.