“In real life, there have been instances where different people have gone to the same farm and created a nutrient budget which looks totally different to the other two – this undermines farmer confidence in the nutrient budget model,” Ravensdown’s Ants Roberts told the Fertilizer and Lime Research Centre’s workshop at Massey University in February.
Variability with Overseer was highlighted at last year's conference when South Island Dairy Development Centre executive director Ron Pellow showed that depending on input decisions the model outputs ranged from annual minimums of 19-24 kg N/ha/year to maximums of 44-69kg N/ha/year.
The draft standards were developed by a technical advisory group he chaired, drawing on expertise from AgResearch, the Foundation for Arable Research, Fonterra, DairyNZ, regional councils and the fertiliser industry. They were reviewed by a stakeholder group then approved by the owners, AgResearch, the Ministry for Primary Industries, and the Fertiliser Association of New Zealand.
“Most sections contain some impact statements about what the input does, why it’s important, and some sections contain additional information to help the user,” Roberts said.
“Where there is more than one input option, the preferred option is always the first one, the next best option second, and so on.”
He emphasised that the standards had not been developed to teach people how to use Overseer, but rather to provide guidance about which inputs to use.
His co-presenter, AgResearch’s Natalie Watkins, said some inputs affect the nutrient budget in subtle ways, such as entering a location and the information the model taps into such as some climate defaults and some animal characteristics. The standards were designed to help users produce the best representation of the farm in terms of a nutrient budget.
Another recent initiative has been the development of the Nutrient Management Adviser Certification Programme, led by DairyNZ as part of a Primary Growth Partnership programme. It aims to build a transparent set of standards for nutrient management advisers, who need to show formal qualifications and proof of competency. To maintain certification they must complete at least 15 hours of continuing professional development every year.
The Overseer model has two key parts. The first is the farm system model, built up from using values entered by the user. The second part mimics the flow of nutrients through the environment and is made up of a series of sub-models, calibrated against data generated in field trials and on small plots.
Although Overseer generates annual average nutrient outputs, the default datasets are generally long-term averages, such as the default climate pattern based on 30-year averages.
David Wheeler, a senior scientist at AgResearch and lead developer of Overseer, told the workshop if it was being used as a monitoring tool, caution was needed when entering farm management information.
“What’s unclear at the moment is the number of years you need to average input data over to get a good estimate of what long-term annual average nitrogen losses are.”
His best guess is that a minimum of three to five years of farm management input data should be averaged. If a nutrient budget for each year and then an average on nitrogen losses was being used a minimum of a five-year rolling average should be used.
One of Overseers sub-models represents a urine patch – accounting for a significant amount of nitrogen leaching.
“The proportion of nitrogen leached is very dependent on the month that the animal deposits the excreta, but also your site characteristics like soil and temperature, and rainfall,” he said.
Links:
The nutrient management adviser certification programme
More models
While Overseer is widely used in the industry, other environmental models are also used to inform decisions around nutrient management.
The Agricultural Production Systems Simulator (APSIM) models the effects of environmental variables and management decisions on production, profits and the environment. Developed in Australia, it is considered to be particularly applicable in New Zealand for arable and cropping systems. In contrast to Overseer, APSIM models changes in real-time rather than long-term averages.
The Catchment Land Use for Environmental Sustainability (CLUES) system models the effects of land-use change on water quality. Working to a minimum scale of a sub-catchment (about 10km2 and above), CLUES can run scenarios simulating percentage changes in stocking rates. The model was developed by NIWA, building on existing models and maps generated by organisations like Landcare Research, AgResearch, and Plant and Food Research. It uses Overseer loss estimates as a data source for the catchment model.
The Rural Futures Multi-Agent Simulation (RF-MAS) model has been developed over the past six years as part of the Rural Futures programme led by AgResearch. Multi-agent systems model the interaction of “intelligent agents” – entities that make decisions, act, and learn from past actions – with an environment. In RF-MAS, farmers are the intelligent agents who are subjected to behaviour drivers like drought, price fluctuations and new policies. The farmer’s decisions drive farming policy and land use which the model then uses to calculate production, costs, profits, nitrogen leaching, and phosphorus loss.
The Soil Plant Atmosphere System Model (SPASMO) has been developed over the past 20 years, mainly by Plant and Food Research. SPASMO models water and solute (eg, nitrogen and phosphorus) transport through a one-dimensional soil profile. It calculates the soil water balance and predicts carbon, nitrogen and phosphorus cycling within the soil profile. This allows for a calculation of plant growth and uptake of both nutrients.
