| Research activity 2015/16 Key Achievements |
Core Funding Investment ($M excl GST) |
| |
2015/16 (planned) |
2015/16 (actual) |
| Mitigating Greenhouse Gases |
$1.09 |
$1.12 |
| End-users: MfE; MPI; AgResearch; SCION, PFR; local body councils; Ngai Tahu; Massey University; LEARN; NZAGRC; GRA; Ballance; researchers; primary industries and sector groups, notably the forestry industry and New Zealand Beef + Lamb. |
| Model and Upscale GHG Emissions – Outcome 3 |
$0.33 |
$0.33 |
- Modelled the trade-offs between milk production and soil organic carbon storage in dairy systems under different management and environmental factors. Soil organic carbon changes depended on the complex interplay of these factors. Of particular importance was the trade-off between carbon removed in grazing and carbon available for soil organic carbon formation.
|
| Agricultural GHG Emissions and Mitigation – Outcome 3 |
$0.51 |
$0.52 |
- Demonstrated that adding lime or urine to soils affects the microbial community richness, composition (denitrifier genes), and ability to consume N2O. Although lime application enhances reduction of N2O to N2, it can also increase total N2O production.
- Developed a simple, farm-scale GHG calculator in collaboration with Beef + Lamb NZ combining the NZ Inventory methodology with recent improvements in hill country emissions. This gained interest from the Pastoral Greenhouse Gas Research Consortium (PGgRc) and MPI for potential application by beef and sheep farmers.
- Established that the methodology developed last year to account for the effects of slope in estimating N2O emissions from the dung and urine of ruminant animals can be extended to account for slope effects on fertiliser N emissions. This methodology has been recommended for adoption in the NZ Inventory.
- Supplied closed chamber equipment to Kenya Agricultural Research Institute for initiating GHG measurements research with funding from UNDP.
|
| Carbon Storage in Soil and Biomass – Outcome 3 |
$0.25 |
$0.28 |
- Developed a digital soil mapping method to predict soil carbon stocks at farm scale. The method uses high resolution data to disaggregate a national model and guide local sampling. It was implemented at a 460-ha hill country farm and reduced the uncertainty of the national model by up to 69 tC/ha for a mean soil carbon stock value of 94 tC/ha.
- Established a soil spectroscopy research method to remove the effect of soil moisture from Vis-NIR spectra. This enables the use of large soil spectral libraries, derived from air-dry archived soil samples, for predicting soil carbon concentration in field moist soils.
- Assisted the hosting of international delegations from Uruguay and Brazil, sharing research developments in assessing soil carbon stocks using soil spectroscopy and advanced spatial modelling methods.
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