New Zealand has enormous potential to use forests to sequester carbon dioxide as part of its contribution to mitigating climate change. This preliminary report sets out results of an analysis requested by the Green Party of New Zealand to examine the carbon sequestration potential of a range of alternative afforestation strategies. Erosion-prone land was chosen as a target because re-establishing forest greatly reduces the likelihood of further erosion, and such land is often relatively unproductive as farmland. The report was delivered in August 2015. As a reference, New Zealand typically emits approximately 80 million tonnes of CO2-e per year.
To produce estimates of potential carbon dioxide sequestration rates
by new forests we used Geographic Information System layers describing land titles[1],
Land Use Capability classes from the New Zealand Land Resource Inventory[2],
and Erosion Susceptibility classes defined in a study by Mark Bloomberg et al. (2011). Erosion susceptibility classes are
shown in Figure 1.
Figure 1 – ESC
classes by Bloomberg et al.
(2011)
We also created a mask that provided estimates of “Kyoto
compliant” land, that is, land that is not currently in forest but that could
reasonably be planted in forest. This
was based on the LCDB v4.0 dataset. The classes that were explicitly included
in our analysis were:
Gorse and/or broom
High producing exotic grassland
Low producing exotic grassland
Short-rotation cropland
Landslides
In addition, broad radiata pine
productivity classes were conservatively defined by mean annual rainfall and
mean annual temperature. Land was allocated into four productivity categories:
Unsuitable for radiata pine; low productivity; medium productivity; and highly
productive. This analysis was constrained by time, and we recommend that the
analysis be extended to define productivity using a physiological model
developed by Euan Mason. This latter model takes into account variation in
radiation, soil characteristics, rainfall, temperature and vapour pressure deficit on a monthly time step, and so would provide more
secure estimates of potential productivity across New Zealand than the quick
estimates we have used for this report.
The draft potential productivity categories are shown in Figure 2.
Figure 2 – Draft potential
productivity categories for radiata pine in New Zealand defined by rainfall and
temperature. Green=Highly productive,
Yellow=moderately productive, brown=low productivity, and white=unsuitable.
Table 1 summarises land that is
either highly or extremely erodible (based on erosion susceptibility classes of 'high' or 'very high')
and that might be planted in carbon forests by productivity classes.
Approximately 1.3 M ha are available in low, medium or high productivity
categories, or 5% of New Zealand’s land area.
Areas shown are in hectares. Most
of the erodable land was in Land Use Capability classes VI to VIII, with the
majority in class VII.
We stress that this is a draft
analysis, and numbers are subject to revision.
The areas identified as erodible and
available for planting are shown in Figure 3.
Table 1 – Provisional summaries of
highly erodible land available for planting (ha)
Threatened
environment class[1]
|
----------Productivity
class--------
|
TOTAL
|
||
Low
|
Medium
|
High
|
||
0
|
89
|
39
|
27
|
155
|
1
|
51457
|
112189
|
34435
|
198081
|
2
|
34545
|
97540
|
129380
|
261465
|
3
|
22914
|
59242
|
98758
|
180914
|
4
|
87952
|
38753
|
72864
|
199569
|
5
|
38508
|
9429
|
38038
|
85975
|
6
|
131892
|
65396
|
188505
|
385793
|
TOTAL
|
367357
|
382588
|
562007
|
1311952
|
Threatened
Class
|
Threatened
Class
|
0
|
No Data
|
1
|
Acutely Threatened
|
2
|
Chronically Threatened
|
3
|
At Risk
|
4
|
Critically Underprotected
|
5
|
Underprotected
|
6
|
Less Reduced and Better Protected
|
Three points in the landscape were selected that were roughly representative of average conditions in the low, medium and high productivity classes shown in Figure 2. Forecaster software created by Scion Research was used to run the 300 Index model at each location for a silvicultural regime that comprised planting 1000 radiata pine stems/ha and leaving them to grow, and also a regime that is considered typical in pruned crops of radiata pine, with 3 pruning lifts and low final crop stockings in the range of 300 stems/ha after early thinning to waste. Model C_CHANGE was employed to estimate carbon dioxide sequestration in these regimes. The plant and leave option was adjusted downwards for the following reasons:
1) We don't
have any data for a long-rotation plant and leave option, and so the growth and
yield model we used was extrapolating for that option.
2) Estimation of carbon contents of large trees was based on a tiny dataset.
3) Examination of model outputs suggested that the growth and yield model may have been underestimating tree death from competition during the simulation period.
4) The adjusted model brought data more into line with published data (Woollons & Manley, 2012) we do have over long rotations, and so we know the values can be achieved.
2) Estimation of carbon contents of large trees was based on a tiny dataset.
3) Examination of model outputs suggested that the growth and yield model may have been underestimating tree death from competition during the simulation period.
4) The adjusted model brought data more into line with published data (Woollons & Manley, 2012) we do have over long rotations, and so we know the values can be achieved.