1 / 8

Nutrient allocation: Two modelled examples

Nutrient allocation: Two modelled examples. Darran.Austin@mpi.govt.nz Thanks to Adam Daigneault ( Landcare ), Levi Timar ( Motu & GNS), and Dan Marsh (Waikato Uni ). Lake Rotorua. Over-allocated in N, ~60% reduction to meet final cap

haru
Download Presentation

Nutrient allocation: Two modelled examples

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Nutrient allocation:Two modelled examples Darran.Austin@mpi.govt.nz Thanks to Adam Daigneault (Landcare), Levi Timar (Motu & GNS), and Dan Marsh (Waikato Uni)

  2. Lake Rotorua • Over-allocated in N, ~60% reduction to meet final cap • Motu modelled trading, with grandparenting versus sector average allocation • EBoP benchmarked farms (~25 dairy, >100 dry stock) Sector average Sector average Classification?

  3. Most mitigation is carried out on dry stock farms (afforestation), and is “purchased” by dairy farmers • Grandparenting results in a tighter distribution of costs across farms

  4. Hinds management zone • Over-allocated in terms of N • 45% reduction in N (after new irrigation) to protect 80% of species in lowland streams (90% in Hinds River) • Landcare modelled a range of policies, MacFarlanes mitigation costs

  5. Allocation methods • Grandparenting and equal allocation • Nutrient vulnerability • Based on soils ability to “filter” N • Base set to dryland S&B • Rest of load proportional to soil filtering, • more filtering = more allocation • or high vulnerability = less allocation • Land use capability • Based on lands carrying capacity • Allocation proportional to a theoretical deficit irrigated, zero fert, dairy farm’s leaching in each class

  6. Trading is cheaper, should be in a frictionless optimisation model • Without trading, overall impact of allocation depends on specifics of mitigation costs and amount to mitigate

  7. 45% reduction in N • Except grandparenting, costs are concentrated with dairy and dairy support on lighter soils, small gains in S&B revenue through land use change

More Related