Agriculture Reference
In-Depth Information
functions. With large amounts of data for com-
parison, an uncertainty can be statistically
determined. For most farm components though,
these data do not exist. An alternative is to define
uncertainties through expert opinion. Expert
opinion takes advantage of any scientific
measurements and knowledge related to a
given variable and provides the invaluable and
immeasurable contribution of the synthesis of
specific and related knowledge by professional
experts in the field to determine expected value
ranges within the context of the defined bound-
aries. The IPCC emission assessment methodolo-
gies (IPCC, 2006b) and the Chesapeake Bay
Model (EPA, 2010) both use expert opinion to
determine the uncertainty in their prediction
of farm management effects on air and water
quality. For IFSM, the uncertainty of predicted
greenhouse gas emissions has been estimated
through expert opinion (Chianese
et al
., 2009).
For farm systems, a crucial and easily mod-
elled form of uncertainty is that due to the influ-
ence of weather. Daily and annual predictions
of nearly all aspects of the farm are controlled
by weather. By simulating farm performance
over multiple years, the IFSM predicts variation
in environmental impacts and farm economics
as influenced by weather (Rotz
et al
., 2011b).
This enables an evaluation of annual risks of
particular management practices with regard
to profit, environmental losses and other model
outputs. Large standard deviations in model
predictions highlight those that are highly sen-
sitive to annual weather patterns. Thus, on a
year-to-year basis, managing the farm to
achieve a certain value for these parameters is
high risk. But in the long term, the effects aver-
age out reducing risk.
N loss, energy use and carbon emission. Within
each management group, strategic changes are
compared to illustrate the resulting environmen-
tal effects along with the producer's costs and
profit.
These comparisons of simulated farming
systems are provided just as an illustration of
the use of the model and the interacting effects
of farm management on the environment. Only
brief descriptions of the simulated representa-
tive farms are presented. In-depth detail on all
model assumptions cannot be provided and the
results should not be viewed as conclusive com-
parisons of the simulated management options.
The results are specific to the farms simulated
and changes in farm parameters can influence
the results obtained. These results do provide
good examples of the trade-offs between various
environmental impacts and the costs and bene-
fits to the producer.
Animal management
To demonstrate the effects of animal manage-
ment, four management options were simulated
on a rather large dairy farm in Idaho. The dairy
herd included 3000 lactating and non-lactating
cows with 2600 replacement heifers raised on
the farm. For the base farm, the annual replace-
ment rate of the lactating cows was 40% with an
annual milk production of 10,000 kg per cow.
Animals were housed in free stall barns with
access to open lots. Manure was flushed from the
barns and stored in a lined earthen lagoon for
application to cropland in the spring and fall.
Manure solids were separated with 50% of the
solids exported to remove a portion of the nutri-
ents from the farm. Cropland consisted of 800 ha
of lucerne and 400 ha of maize on a clay loam
soil in a gently sloping terrain. A conservation
tillage system was used to establish crops, and
all cropland was irrigated to improve produc-
tion. Except for a small amount of side-dressed
N fertilizer, all crop nutrient requirements were
met through manure nutrients produced on the
farm. The lucerne hay and maize silage produced
provided two-thirds of the forage requirement of
the herd with the remainder of the forage and all
concentrate feed purchased. Animals were fed
total mixed rations with protein and P overfed by
10% to assure that requirements were met.
Production System Evaluations
To demonstrate the effects of management on
farm profitability, the environment and the inter-
actions between air and water quality, several
farm simulations were done with the IFSM. These
simulations consist of a few examples of animal,
manure handling and crop management in dairy
and beef farm systems. The simulations include
predictions for major pathways of nutrient
losses, whole farm balances of the major nutri-
ents and the environmental footprints of reactive
