• TABLE OF CONTENTS
HIDE
 Title Page
 Abstract
 Introduction
 North Florida dairy farm syste...
 Objectives
 Methodology
 Limitations of the DNFDM
 General results of stimulation...
 Five-year management strategie...
 Conclusion
 Reference






Group Title: Staff paper - University of Florida. Food and Resource Economics Dept. - SP 03-2
Title: Economic and ecological assessment of groundwater nitrogen pollution from North Florida dairy farm systems
CITATION PAGE IMAGE ZOOMABLE PAGE TEXT
Full Citation
STANDARD VIEW MARC VIEW
Permanent Link: http://ufdc.ufl.edu/UF00053829/00001
 Material Information
Title: Economic and ecological assessment of groundwater nitrogen pollution from North Florida dairy farm systems an interdisciplinary approach
Series Title: Staff paper series
Physical Description: 15 p. : ill. ; 28 cm.
Language: English
Creator: Cabrera, Victor E
Hildebrand, Peter E
University of Florida -- Food and Resource Economics Dept
Publisher: University of Florida, Institute of Food and Agricultural Sciences, Food and Resource Economics Department
Place of Publication: Gainesville Fla
Publication Date: [2003]
 Subjects
Subject: Dairy farming -- Economic aspects -- Florida   ( lcsh )
Dairy farming -- Environmental aspects -- Florida   ( lcsh )
Water -- Nitrogen content -- Florida   ( lcsh )
Groundwater -- Pollution -- Florida -- Suwannee River   ( lcsh )
Genre: government publication (state, provincial, terriorial, dependent)   ( marcgt )
bibliography   ( marcgt )
non-fiction   ( marcgt )
 Notes
Statement of Responsibility: by Victor E. Cabrera and Peter E. Hildebrand.
Bibliography: Includes bibliographical references (p. 14-15).
General Note: Cover title.
General Note: "August 2003."
Funding: Florida Historical Agriculture and Rural Life
 Record Information
Bibliographic ID: UF00053829
Volume ID: VID00001
Source Institution: Marston Science Library, George A. Smathers Libraries, University of Florida
Holding Location: Florida Agricultural Experiment Station, Florida Cooperative Extension Service, Florida Department of Agriculture and Consumer Services, and the Engineering and Industrial Experiment Station; Institute for Food and Agricultural Services (IFAS), University of Florida
Rights Management: All rights reserved, Board of Trustees of the University of Florida
Resource Identifier: aleph - 002992744
oclc - 54394564
notis - APN4612

Table of Contents
    Title Page
        Title Page
    Abstract
        Abstract
    Introduction
        Page 1
    North Florida dairy farm systems
        Page 2
        Page 3
    Objectives
        Page 4
    Methodology
        Page 4
        Dynamic modeling of north Florida dairy farm systems
            Page 5
            Page 6
            Page 7
            Page 8
    Limitations of the DNFDM
        Page 9
    General results of stimulations
        Page 10
    Five-year management strategies
        Page 10
        Page 11
        Page 12
    Conclusion
        Page 13
    Reference
        Page 14
        Page 15
Full Text


SP 03-2


STAFF PAPER SERIES


UNIVERSITY OF
FLORIDA
Institute of Food and Agricultural Sciences
Food and Resource Economics Department
Gainesville, Florida 32611


ECONOMIC AND ECOLOGIC ASSESSMENT OF GROUNDWATER
NITROGEN POLLUTION FROM NORTH FLORIDA DAIRY
FARM SYSTEMS: AN INTERDISCIPLINARY APPROACH

by
Victor E. Cabrera and Peter E. Hildebrand


August 2003


Staff Paper SP 03-2










"Economic and Ecologic Assessment of Groundwater Nitrogen Pollution from
North Florida Dairy Farm Systems: an Interdisciplinary Approach"

Victor E. Cabrera
School of Natural Resources and Environment
University of Florida
vcabrera@ufl.edu

Peter E. Hildebrand
Professor Food and Resource Economics Department
University of Florida


Keywords: simulation, modeling, best management practices, Suwannee River Basin,
groundwater contamination, livestock forages, manure handling systems, nutrient
budgeting.



Abstract

The presence of nitrogen (N) in water is an environmental hazard because it affects
human health and ecosystem welfare. The Suwannee River Basin in Florida has received
much attention in recent years due to increased N levels in water bodies. Dairy waste is
thought to be an important factor contributing to this water N pollution. Dairy farmers are
now required to comply with stricter environmental regulations either under permit or
under voluntary incentive-based programs. Dairy farmers are also aware that
environmental issues in the near future will be the greatest challenges they will have to
face. Evidence indicates that farms may reduce their total N loads by changing some
management strategies. Using published and stakeholders' information, a dynamic,
empirical, stochastic, interactive, and user-friendly model was created to simulate north
Florida dairy farms and use it to test management strategies that may reduce nitrogen
pollution and still maintain farm profitability. Testing different crop rotations, crude
protein contents, time spent on concrete by milking cows, and time of liquid manure in
the storage pond, it was found that intensive crop rotations have the greatest impact on
reducing N loss and at the same time improve profitability. It was also found that
reducing crude protein may reduce N release and increase profitability. Reduction in time
spent on concrete reduces the amount of manure N handled by the system and
consequently may reduce the amount of N lost to the environment. Increasing the time
liquid manure spends in the storage pond may reduce the risk of N lost to groundwater
but increases the amount of N lost to the air, which is not used by the crops and
consequently decreasing profitability. A combination of decreasing crude protein content
in the rations and efficient crop rotations may considerably increase profitability and
decrease N loss to the minimum.










1. Introduction


Dairy farming is an important part of Florida's agricultural industry. The Florida
Statistical Service has indicated that milk and cattle sales from dairies contributed $429
million directly into the Floridian economy in the year 2001. Florida is the leading dairy
state in the Southeast; it ranks 13t nationally in cash receipts for milk, 15th in milk
production and 15 in number of cows (Bos taurus). According to the USDA, there were
about 152,000 cows on about 220 dairy farms at the end of 2002, and more than 30% of
these dairy operations and cows are located in the Suwannee River Basin. These dairies
face an increased government regulation due to social pressure because they attract the
attention of neighbors and activists concerned with odors, flies and mostly with potential
leaching of nutrients that might influence water quality (Giesy et al., 2002).

The presence of nitrogen (N) in surface water bodies and ground water aquifers is
recognized as a significant water quality problem in many parts of the world (Fraisse et
al., 1996). The Suwannee River Partnership states that over the last 15 years, nitrate
levels in the middle Suwannee River basin have been on the increase and these elevated
nitrate levels can cause health problems in humans as well as negative impacts on water
resources. High nitrate levels in drinking water can cause methemoglobinemia or "blue
baby" sickness in infants and other health problems in humans in the form of enlargement
of the thyroid gland, increased sperm mortality, and even stomach cancer (Andrew,
1994). In addition to making water unsafe for humans and many other animals, high
nitrate concentrations can lower water quality in rivers and springs and elevated
concentrations of nitrate in rivers can cause eutrophication that results in algal blooms
and depletion of oxygen that affects survival and diversity of aquatic organisms (Katz et
al., 1999).

The Suwannee River basin has received much attention in recent years due to increased
nitrogen levels in the groundwater-fed rivers of the basin that could seriously affect the
welfare of the ecosystem (Albert, 2002). According to Katz (2000), nitrogen levels have
increased from 0.1 to 5 mg 1-' in many springs in the Suwannee basin over the past 40
years. Pittman et al (1997) found that nitrate concentrations in the Suwannee River itself
have increased at the rate of 0.02 mg 1' year'1 over the past 20 years and that over a 33
mile river stretch between Dowling Park and Branford, the nitrate loads increased from
2,300 to 6,000 kg day"1 while 89% of this appeared to come from the lower two-thirds,
where agriculture is the dominant land use.

Soils in this region are generally deep, well-drained sands, and nutrient management is a
major concern (Van Horn et al., 1998). Over-applying manure nutrients to these soils is
considered to be a major cause of nitrates, converted from manure ammonia sources
while in the soil, leaching to groundwater and contributing to surface runoff. One of the
most publicized concerns is N losses in the form of nitrate into the groundwater through
the deep sandy soils of the Suwannee River basin (Van Horn et al., 1998).










Environmental regulation of livestock waste disposal has become a major public concern,
and much of the focus for this issue in Florida has been on dairies. Dairy farmers are now
required to develop manure disposal systems in order to comply with Florida Department
of Environmental Protection water quality standards (Twatchtmann, 1990). This fact has
led to considerable research efforts that emphasize N recycling and address such issues as
maximum carrying capacity and nutrient uptake by crops (Fraisse et al, 1996). Dairymen
in the Suwannee River basin have expressed their willingness to participate in initiatives
that promote reduced environmental impacts, and in fact, many of them are already
involved in using Best Management Practices (BMPs) promoted by the Suwannee River
Partnership (Smith, 2002, Pers. Comm.). Staples et al. (1997) after interviewing 48 dairy
farms in north Florida found that the perception of the anticipated costs of having to
comply with probable upcoming environmental regulations was rated, by far, the top
challenge to successful dairying in the future.

The Netherlands has implemented the Mineral Accounting System (MINAS) which
focuses on nutrient (nitrogen and phosphorus) flows on individual farms, and taxes farms
whose nutrient surplus exceeds a defined limit. MINAS embodies a new approach to
environmental problems caused by agriculture. According to Ondersteijn et al. (2002)
focusing on individual farmers has two major advantages. First, individuals are
considered polluters and are individually held accountable for their pollution, according
to the 'polluter pays' principle. Second, individuals have control over their pollution
problem and will be able to deal with it on an individual level instead of being forced to
comply with general measures that may be ineffective for their specific situation. The
same authors found, after interviewing 240 farmers over three years, that large variations
in nitrogen and phosphate surpluses exist within and between land-based farm types in
The Netherlands and that these farmers stated that MINAS provided an enormous and
often surprising insight into the results of their management practices.

Nitrate overflow in dairy systems is affected by adopted management practices and by
environmental conditions. Change of management practices might have a great impact on
overflow amounts. Agronomic measures of nutrient balance and tracking of inputs and
outputs for various farm management units can provide the quantitative basis for
management to better allocate manure to fields, modify dairy rations, or develop
alternatives to on-farm manure application (Lanyon, 1994).

2. North Florida Dairy Farm Systems

Most dairies in Florida manage animals under semi-intensive or intensive systems.
Florida dairy decisions are based on profit maximization and operation regulations. North
Florida dairies are business enterprises and have full access to credit opportunities,
information, and new technologies (Adams, 1998). Components of any north Florida
dairy farm system are the herd and the crops. The herd is composed of young and
productive livestock, while the crops are rotations of different crops in defined fields.
Most dairy farms have a young stock herd, which is for replacement of productive cows.










Young stock includes recently born calves to heifers ready for first delivery (0 to 24
months, approximately). When a heifer has her new calf, that heifer enters the productive
group as a fresh cow first lactation, and her calf, depending if it is male or female, is
sold or kept. All male calves are sold the day after they are born. Young livestock are
usually managed in a different facility outside the main production facility. In the young
stock facility, there are calves and heifer groups, according to physiological development.
Calves and heifers are moved from group to group in time frames.

Heifers start their breeding program, which consists of heat detection and artificial
insemination at approximately one year of age. When a heifer achieves pregnancy, nine
months of gestation will follow until this heifer delivers and becomes a fresh first
lactation cow. During young and adult livestock periods, a number of animals will be
culled from the herd because of their production performance, age, weight gained,
general health, fertility, etc. Culling rates are characteristic of management and vary
greatly across dairy farms.

The adult or productive herd develops in approximately yearly cycles. A fresh cow will
produce milk for approximately ten or eleven months after delivery (300-330 days as a
milking cow) after which she will be dried out for approximately two months (60 days as
a dry cow). After the dry period, the cow delivers again and starts her next lactation. This
intense productive cycle is possible because a cow that starts her lactation after a delivery
is quickly inseminated again and can be pregnant after only a two month period
(Voluntary Waiting Period (VWP)). Therefore, most of the milking cows are
simultaneously, pregnant cows.

Cycles continue several times depending of the management decisions of the dairy farm.
Some farms prefer to keep cows only for three lactations, while others may want to keep
them for six, seven or more lactations. After the second and third lactations, milk
production performance may decrease. Keeping cows for more lactations saves the cost
of replacement, but at the same time has an opportunity cost of giving up higher expected
rates of production with new cows entering the herd. During the 300-day milking period
cows follow a typical milk productivity curve that increases rapidly at the beginning until
reaching a peak. After that peak, production steadily decreases until the dry period.

In general, milking cows are confined (or at least, most of the time) while dry cows and
young stock are kept in less intensive production facilities. The same happens with the
diet: milking cows receive the highest nutrient-concentrated diet depending of their
productivity. These diets are closely related to the nitrogen balance in and out of the
farm. Different categories of milking cows are managed in the "intensive" facilities,
which are the free stalls, walkways, and the milking parlor.
Florida dairies are required by official agencies to manage their on-farm waste. In north
Florida, the most common practice of management of waste disposal is through a
flushing removal of solids storage and crop systems. Free stalls and milking parlor
(and other adjacent intensive facilities) are implemented with open canals that allow










constant flushing of manure to a treatment lagoon, then to a storage pond from where
liquid manure is applied to cropland (sprayfields). Before reaching the treatment lagoon
manure is screened for solids, which are separated and do not reach the lagoon.

Less intensively-managed cows such as dry cows and young stock are usually not
included in the waste management program because they produce much less manure (and
much lower nitrogen quantities) and spend most of their time grazing. In the case of
milking cows, time spent out of confined areas also will determine the amount of
reduction of manure produced. Dairy farm systems have surrounding crop fields where
pasture, forage and silage crops can be produced as a complement for cow diets. Crops
are also the main means of farm nitrogen recycling. Some or all farm fields have liquid
manure applied as a means of fertilization and recycling nutrients. Extra quantities of
nitrogen applied to crops that cannot be up taken by plants are lost to groundwater
constituting a pollution hazard.

For this study, the dairy farm boundaries are defined spatially as the physical farm limits.
One meter below the surface is the farm limit. Any resource that enters these farm
boundaries will be recognized as a source (input) and any resource that exits these farm
boundaries will be called a sink (output). This study emphasizes the flows of nitrogen
entering the dairy farm system, its interactions within system, and its flows leaving the
dairy farm system.

3. Objectives

The main aim of this research is to create a north Florida dairy farm simulation model
and simulate north Florida dairy farm systems to assess the economic impact of
management strategies that may decrease nitrogen leaching. This study intends to: a)
understand north Florida dairy systems, b) create a north Florida dairy farm model, c)
simulate north Florida dairy farms under different management strategies, d) estimate
economic and ecological impacts of north Florida dairy farm systems, and e) create a
user-friendly computer model for the benefit of dairy producers and other stakeholders.

User-friendliness and interactivity of models are required to gain understanding and
direct feedback from stakeholders. The model developed in this research is intended to be
a discussion tool for system understanding and at the same time an analyses tool.

4. Methodology

Analysis in the systems approach is marked by recognition of the whole system and the
interactions within that system rather than looking only at a system component. A
systems approach employs specific techniques and tools, such as rapid appraisal, pattern
analysis, diagrams, and modeling, often in a multidisciplinary fashion, to identify system
boundaries and recognize component interactions (Kelly, 1995).










constant flushing of manure to a treatment lagoon, then to a storage pond from where
liquid manure is applied to cropland (sprayfields). Before reaching the treatment lagoon
manure is screened for solids, which are separated and do not reach the lagoon.

Less intensively-managed cows such as dry cows and young stock are usually not
included in the waste management program because they produce much less manure (and
much lower nitrogen quantities) and spend most of their time grazing. In the case of
milking cows, time spent out of confined areas also will determine the amount of
reduction of manure produced. Dairy farm systems have surrounding crop fields where
pasture, forage and silage crops can be produced as a complement for cow diets. Crops
are also the main means of farm nitrogen recycling. Some or all farm fields have liquid
manure applied as a means of fertilization and recycling nutrients. Extra quantities of
nitrogen applied to crops that cannot be up taken by plants are lost to groundwater
constituting a pollution hazard.

For this study, the dairy farm boundaries are defined spatially as the physical farm limits.
One meter below the surface is the farm limit. Any resource that enters these farm
boundaries will be recognized as a source (input) and any resource that exits these farm
boundaries will be called a sink (output). This study emphasizes the flows of nitrogen
entering the dairy farm system, its interactions within system, and its flows leaving the
dairy farm system.

3. Objectives

The main aim of this research is to create a north Florida dairy farm simulation model
and simulate north Florida dairy farm systems to assess the economic impact of
management strategies that may decrease nitrogen leaching. This study intends to: a)
understand north Florida dairy systems, b) create a north Florida dairy farm model, c)
simulate north Florida dairy farms under different management strategies, d) estimate
economic and ecological impacts of north Florida dairy farm systems, and e) create a
user-friendly computer model for the benefit of dairy producers and other stakeholders.

User-friendliness and interactivity of models are required to gain understanding and
direct feedback from stakeholders. The model developed in this research is intended to be
a discussion tool for system understanding and at the same time an analyses tool.

4. Methodology

Analysis in the systems approach is marked by recognition of the whole system and the
interactions within that system rather than looking only at a system component. A
systems approach employs specific techniques and tools, such as rapid appraisal, pattern
analysis, diagrams, and modeling, often in a multidisciplinary fashion, to identify system
boundaries and recognize component interactions (Kelly, 1995).










Rationality in the simulation models follows the logic of budgeting or accounting for the
flows ofN in the system, as developed by Van Horn (1997), Van Horn et al. (1998), and
Van Horn et al. (2001). The simulation model accounts for N inputs (sources), within-
system interactions, and outputs (sinks), according to a defined dairy farm system
boundary.

Changes in alternative management strategies such as: 1) crude protein included in the
diet, 2) time herd spends in confined areas, 3) time of liquid manure in waste storage
pond, 4) crops planted, and 5) area planted will be tested in five-year time frames to
compare economic and ecological outputs. Information was collected from published
sources, personal observations, and stakeholders' communication, of which are
documented in the modeling section.

Dynamic Modeling of North Florida Dairy Farm Systems

A dynamic, event-controlled, empirical, stochastic model was created to represent north
Florida dairy farm systems and in it the flows of economic and environmental variables
are accounted for.

The Dynamic North Florida Diary Model (DNFDM, Figure 1) was intended to be user
friendly as an interactive spreadsheet in Excel software that could be shown to dairy
farmers and other stakeholders in a way easy for them to understand. Creation of the
DNFDM was suggested by a stakeholder as a way to gain dairy farmers' interest. The
DNFDM also intends to be a powerful analyses tool for representing real situations. It
runs in monthly steps, using monthly budgets, as opposed to the yearly approach of Van
Horn et al. (2001).

The DNFDM has the following modules: feedstock, cattle, milk production, waste
management system, and crop system. All these components interact among themselves
and have two common variables throughout: nitrogen and money. It runs on a monthly
basis for a desired number of years.

The model considers 11 classes of milking cows, from one-month to eleven months of
lactation; two classes of dry cows, one and two month dry cows; and 24 classes of young
stock: calves and heifers. At every monthly update, cattle classes increase their age by
one month. Then, cows of milking group # 1 will become cows of milking group # 2 and
three month-old calves will become four month-old calves, etc.

Culling rates apply to any month and the total culling rate for a specific farm is divided
among the cattle groups and applied at each update. At any point in time, different cow
groups require different diets, produce different milk quantities, require specific dairy
facilities, and recycle specific amounts of nitrogen.




























Figure 1 Dynamic North Florida Dairy Farm Model (DNFDM)


Dry matter intake (DMI) is calculated adapting research results in Tifton, Georgia of Van
Horn et al. (1998). It changes with the stage of cow production, from 25.20 to 55.92 lbs
per cow per day for dry cows to highest productive cows, respectively (Table 1). The
amount of crude protein in the diet varies from 15 to 17.5% and is a user choice option.
The amount of crude protein determines the quantity of nitrogen entering the system and
the flow of this nutrient in the system. According to Van Horn et al (1998) crude protein
does not affect milk production if the herd is well managed. Therefore, higher crude
protein concentrations may produce similar milk quantity, but increase environmental
risk and increased costs. Higher crude protein rations are believed beneficial for
production purposes and that is why dairymen like to use them in high levels.

Milking cows require different amounts and different qualities of feed and at the same
time they produce different amounts of manure (feces and urine) containing different
amounts of non-digested nitrogen according to the production of milk (Table 1, source
Van Horn et al., 1998). Milk production per group was estimated based on the Florida
average cow performance of 18,150 lbs per year per cow, obtained from the Dairy Herd
Improvement (DHI) data source (http://www.drms.org).

Manure time spent on concrete is the proportion of time milking cows stay inside
intensive facilities from which manure is collected (free barn stalls, walkways, and
milking parlor). Consequently time spent on concrete determines the quantity of manure
(and nitrogen) for recycling. Dry cow and young stock manure is not part of the recycling
program (i.e. their manure is deposited directly on pasture or it is managed in another
way) because quantities are much lower than the production group. Cattle flow on the
farm is greatly influenced by culling rates. Culling rates are farm-specific parameters for











adult and young stock that determine the proportion of cattle that leaves the herd (for any
reason) in time frames. Culling rates of 42% for the productive herd and 16% for the
young stock are acceptable for Florida dairies according to data from the DHI.

Lbs/day/cow
group Description milk DMI feces urine
1 milking open 50 39.38 76.97 48.54
2 milking open 100 55.92 126.31 66.02
3 milking open 90 52.61 116.44 62.53
4 milking open 70 46.00 96.71 55.53
5 milking pregnant 65 44.34 91.77 53.78
6 milking pregnant 60 42.69 86.84 52.04
7 milking pregnant 55 41.04 81.91 50.29
8 milking pregnant 50 39.38 76.97 48.54
9 milking pregnant 45 37.73 72.04 46.79
10 milking pregnant 40 36.07 67.10 45.04
11 milking pregnant 35 34.42 62.17 43.29
12 dry pregnant 25.20
13 dry pregnant 25.20
TOTAL MILK 18,150 lbs per COW/YEAR
Table 1 Milk production, dry matter intake and manure excreted by cattle groups

On north Florida dairy farms, the most common system used to handle manure is a liquid
manure system that encompasses a flushing system, a solid screening system, a treatment
lagoon, and a storage pond. The flushing system uses large amounts of water to wash the
manure from point of concentration to the treatment lagoon. Before reaching the lagoon a
system separates solids from the remaining liquid. Liquid manure passes through the
treatment lagoon, where some sedimentation is expected, and reaches the larger waste
storage pond, where it is kept for a variable time. Liquid manure from the storage pond is
used as fertilizer in the farm crop fields, usually applied to fields through sprinklers in
central pivot irrigation units. Solids separated from the liquid manure take only a little
more than 15% of the total N and it is usually composted for use on-farm or sold.

Using the Van Horn et al. (2001) nutrient flow approach, the amount of nitrogen that
reaches the waste system is the difference between the amounts of nitrogen input in the
feed less the digested proportion of it plus the weight gained by cows plus the amount of
nitrogen used for reproduction (new calves):
N(waste) = N(feeding) [N(digested) + N(weight) + N(reproduction)]
Part of the nitrogen is lost to the air as gaseous forms during flushing, storage, and
spraying. While losses during flushing and spraying are difficult to control, the loss of
nitrogen during storage can vary greatly according to management. In the DNFDM,
storage time determines the quantity of nitrogen available for applying to crops. Storage
time is a user choice. The greater the time in storage, the lower the nitrogen quantity
available for recycling. Estimations of nitrogen losses to the air were adapted from Van
Horn et al. (1998) on a monthly basis.










Dairy farms have many crop options for their land. Many times options are narrowed by
trying for the most efficient use of nutrients from manure. There are many crops
cultivated in north Florida dairy farm systems. Some are corn, rye, oat, ryegrass, peanut,
alfalfa, bermudagrass, and sorghum. These are usually planted from seed or sod planted
in rotations according to season. Some of them can be planted for different dairy
purposes as for example the case of the bermudagrass that can be used as hay or as
pasture. Crops are assumed to be well managed and with all their required nutritive
demands to accomplish maximum dry matter accumulation. Biomass produced by crops
is entirely used by the farm cattle, closing in this way the nutritive cycle.

Uptake by crops of nitrogen applied to the soil was estimated and adapted monthly based
on Van Horn et al., 2001 (Table 4: Nitrogen removals by different crop rotations). The
DNFDM allows choosing up to 6 different field sizes with the 13 most common crop
rotations for north Florida. Following rationality of many dairy farmers, total nitrogen
available to apply is evenly distributed to all sprayfields. Different crops under different
environmental conditions in different seasons with different areas applied with liquid
manure (sprayfields) will uptake different amounts of nitrogen. In some circumstances
the quantity of applied nitrogen will be lower than the quantity required by the crop, a
situation in which extra fertilization of nitrogen would be justified. But other times the
quantity of nitrogen applied is greater than the uptake capacity of the present crops. In
this case, extra nitrogen in the soil will be lost out of the farm boundaries (leaching below
one meter soil depth) and may constitute an environmental hazard for groundwater
resources. The DNFDF estimates in monthly steps the amounts of nitrogen outgoing from
the farm.

Income to the dairy farm comes basically from selling milk and male calves. Male calves
are sold at $30 per head one day after they are born and milk price is a stochastic function
based on historical milk prices collected for the last five years from the USDA Website
(http://www.nass.usda.gov/fl). The milk price contains an independent stochastic function
that generates monthly milk prices based on the ranges of variation observed in the last
five years as seen in Table 2. Farm expenses are only based on feed protein purchased
after using all dry matter produced on farm evaluated at the market price of $290 per TM
(http://coopworth.org.nz/coopbul8.html). The cost of a pound of feed varies according to
the chosen protein amount as a function of the following form:
1.2 x [%crudeprotein]- 0.07, which is an equation adapted from Van Horn et al. (1998)
with information on prices obtained from the Louisiana State University Agricultural
Center (http://www.lsuagcenter.com/dairy/pdfs/1997report/feed%20cost.pdf).

Assessment of quantities of nitrogen lost as well as economic performance are calculated
on a monthly basis, so comparisons of environmental and economic outcomes can be
achieved in monthly time frames or be accumulated for long term analyses. The DNFDM
is a user-friendly, interactive model that allows input and output data directly from the
model. Color codes indicate properties of cells with respect to inputting or outputting data
in cells. Light green cells indicate cells that are input and output cells: users can introduce











data in those cells by overwriting them; results will be displayed in the same cells. Light
blue cells (including scrolling boxes) indicate cells that allow the user to change
parameters of the model before running; these cells will not change values during
simulation. Yellow cells are output cells that display the internal model calculation
results.

RANGE OF
MONTH MIN MAX AVG VARIATION
JAN 12.00 17.99 15.86 5.99
FEB 11.80 15.95 14.75 4.15
MAR 11.90 16.65 14.84 4.75
APR 11.90 17.44 14.35 5.54
MAY 12.10 18.21 14.59 6.11
JUN 12.30 18.99 14.88 6.69
JUL 12.60 19.34 15.12 6.74
AUG 12.50 19.40 15.35 6.90
SEP 13.00 19.56 15.51 6.56
OCT 12.60 19.93 15.30 7.33
NOV 12.30 19.76 14.82 7.46
DEC 13.10 15.98 14.51 2.88
Table 2 US$ price per cwt (100 lbs) of liquid milk in Florida

The DNFDM can run in different modes. It can run showing "number" results which
appear in cells. The "number" simulation is intended to show the friendliness of the
model to stakeholders, especially to dairy farmers to gain their interest; additionally four
boxes indicate graphically the monthly and accumulated values of N (red) and money
(green). The DNFDM can also be run in a "graph" mode which shows the big picture of
the main variables (profit, N leached (temporal and total), and cattle flow) during the time
frame of simulation. "Graph" outputs are intended for analysis purposes, after several
simulations. In either mode, "number" or "graph," there is the option to run a "stepwise"
simulation, which stops the running every month to provide time to analyze the evolution
of the variables. Simulations of main variables are also stored in an independent
spreadsheet as an organized table for analysis purposes. Additionally, a "run 10 times"
button is conveniently located to allow the user to run the model 10 times with chosen
parameters and save results in an independent table. Experiments analyzed in this study
were accomplished using this useful function.

5. Limitations of the DNFDM

Some current limitations of the model need to be recognized in order to improve it for
further versions. These are:
Cows get pregnant at the same time; monthly groups are assumed to be exactly the
same age
Costs and incomes only include variable costs related to the parameters in the study.
For example initial cost of waste management facilities were ignored
Production of milk is not seasonally corrected, it is only cow stage dependent










* N is evenly applied to all sprayfields
The same crop rotations are present for the whole simulation time
Milk production concentration in winter, which may be a management strategy in
some north Florida dairy farms, was not included
The value of manure solids are not yet incorporated in the model.

6. General Results of Simulations

A simulation was set up for the cattle module to reach a "steady state" after a number of
years of simulation. Analyses were done after the herd reached this steady state, in which
there were about 300 adult cows (88% of them as milking cows) and about 270 young
stock. This simulated dairy farm had additionally 94.6 acres of sprayfields with three
crops: 47.5 acres of corn silage, 21.6 acres of rye pasture, and 24.8 acres of oat haylage.
Also, this farm was assumed to use a 17.5% crude protein diet for milking cows, have
their milking cows 80% of the time confined on concrete, and applying the liquid manure
after seven days of storage. The simulation was run for five-year periods. Profit varies
every run because of the stochastic price variability. Figure 2a shows for this specific
arrangement of parameters, that August is the most profitable month because more feed is
produced on farm in that month. The opposite is also true; November and April are least
profitable months because of the purchase of maximum quantities of feed because there
is no on-farm production.

o PROF LEACHED TOTAL N LEACHED(5YEAR)




Iainfis ffie gi'i< I A
Figure 2 a) Monthly changes of profitability, b) N leached by month, and c) Cumulated N
leached in five-year period

Nitrogen leached into the subsoil is highly related to crop nitrogen uptake, and to profit.
It changes completely according to the area planted and crop rotations. Using 47.5 acres
of corn silage, 21.6 acres of rye pasture, and 24.6 acres oat haylage, the nitrogen leached
changes seasonally as seen in Figure 2b. Figure 2b shows that with these 93.9 acres
planted, there will be considerable N lost in most months. Negative numbers indicate no
N leaching is expected. Those months are May, June and July. Figure 2c shows the
cumulative N leached during a five-year period.

7. Five-year Management Strategies

Ten different management strategies were experimented with using the DNFDM model.
These are summarized in Table 3. The control management strategy was based on the
same farm parameters shown in section 4: 17.5% crude protein for feeding milking cows,










* N is evenly applied to all sprayfields
The same crop rotations are present for the whole simulation time
Milk production concentration in winter, which may be a management strategy in
some north Florida dairy farms, was not included
The value of manure solids are not yet incorporated in the model.

6. General Results of Simulations

A simulation was set up for the cattle module to reach a "steady state" after a number of
years of simulation. Analyses were done after the herd reached this steady state, in which
there were about 300 adult cows (88% of them as milking cows) and about 270 young
stock. This simulated dairy farm had additionally 94.6 acres of sprayfields with three
crops: 47.5 acres of corn silage, 21.6 acres of rye pasture, and 24.8 acres of oat haylage.
Also, this farm was assumed to use a 17.5% crude protein diet for milking cows, have
their milking cows 80% of the time confined on concrete, and applying the liquid manure
after seven days of storage. The simulation was run for five-year periods. Profit varies
every run because of the stochastic price variability. Figure 2a shows for this specific
arrangement of parameters, that August is the most profitable month because more feed is
produced on farm in that month. The opposite is also true; November and April are least
profitable months because of the purchase of maximum quantities of feed because there
is no on-farm production.

o PROF LEACHED TOTAL N LEACHED(5YEAR)




Iainfis ffie gi'i< I A
Figure 2 a) Monthly changes of profitability, b) N leached by month, and c) Cumulated N
leached in five-year period

Nitrogen leached into the subsoil is highly related to crop nitrogen uptake, and to profit.
It changes completely according to the area planted and crop rotations. Using 47.5 acres
of corn silage, 21.6 acres of rye pasture, and 24.6 acres oat haylage, the nitrogen leached
changes seasonally as seen in Figure 2b. Figure 2b shows that with these 93.9 acres
planted, there will be considerable N lost in most months. Negative numbers indicate no
N leaching is expected. Those months are May, June and July. Figure 2c shows the
cumulative N leached during a five-year period.

7. Five-year Management Strategies

Ten different management strategies were experimented with using the DNFDM model.
These are summarized in Table 3. The control management strategy was based on the
same farm parameters shown in section 4: 17.5% crude protein for feeding milking cows,











milking cows spend 80% of the time in confined areas, liquid manure is applied after
seven days in the waste storage pond, and there are 93.90 acres of sprayfields to apply
manure.

Experiments one to four tested the output changes with respect to changes in crude
protein content in the diet of milking cows. Experiments five and six tested different
lengths of storage of liquid manure in the storage pond. Experiments seven and eight
tested the possible decrease of time spent in confined areas by milking cows. Experiment
nine changed the crop of the largest field of 47.5 acres to a rotation (crop rotation # 2) of
corn silage, forage sorghum, and rye silage. The last experiment, number ten, was similar
to number nine for crop rotations, but crude protein in the diet was reduced to 15%. For
each experiment, five years of simulation time was run, from January 2004 to December
2008, and two main variables were monitored: profit and nitrogen leaching. Every
experiment was run ten times to observe the distribution of results for the profit that has
stochastic price functions. Results are summarized in Figure 4. The baseline, or control
treatment has the following outputs: 90% chance of getting at least $2.02 million of
profit, 50% chance of getting at least $2.12 million of profit and 100% of chance of
getting less than $2.18 million. There is an estimated N loss of 62K lbs of N during this
five-year period.

Crude Time Days in Crop
Experiment Protein Concrete Lagoon Rotation
CONTROL 17.50 80% 7 1
1 1 7.00 80% 7 1
2 16.50 80% 7 1
3 16.00 80% 7 1
4 15.00 80% 7 1
5 17.50 80% 14 1
6 17.50 80% 28 1
7 17.50 60% 7 1
8 17.50 50% 7 1
9 17.50 80% 7 2
10 15.00 80% 7 2
Table 3 Control and "experiments" with DNFDM for a 5-year period

Van Horn et al. (1998) indicate that some diet control over N excretion is possible.
Decreasing crude protein may decrease the amount of N in the manure still maintaining
optimum animal performance and milk production. These authors tested two different
diet formulations proposed by the National Research Council (NRC): high and low. The
high diet requires more crude protein to assure requirements are met and the low diet
minimizes dietary N. These levels, high and low, were estimated to be 17.5 and 15.0 %
of crude protein on diet by local dairy farmers. These ranges along with numbers
provided by Van Horn et al. were used as functions in the DNFDM.

Total nitrogen lost during the five-year period varies considerably with different protein
diets as seen in Figure 3. If crude protein is 17.5%, 62,000 lbs ofN is expected to be










leached, but if the crude protein is only 15% it is expected to leach about 46,000 lbs of N.
Profit changes inversely; while with 17.5% crude protein the profit would be less than
$2.2 million, with 15% crude protein there is 90% chance that the profit could be greater
than $3.0 million. Inputting less crude protein saves important feeding costs and
decreases the risk ofN overflows.

Time of liquid manure storage in the waste pond affects the results in the following way:
the N leaching amounts would decrease from 62K to 38K lbs when the manure is stored
14 days instead of 7 days, and it could even decrease to 22K lbs when it is stored 28 days;
the profit increases to $2.5 million (90% chance) when it is 14 days instead of 7 days, and
decreases again to original levels when it is stored 28 days. Less nitrogen leached will be
expected with more stored time because large amounts of ammonia nitrogen are expected
to be lost to the air during storage time; this decreases the risk of N groundwater
pollution, but it increases the risk of air pollution and it requires larger facilities. Time of
liquid manure storage in the pond is part of the nutrient management plan and it could be
controlled by the regulatory agencies. It is also expected that in the future, N pollution to
the air could be measured and regulated. On the other hand, by not recycling maximum
amounts of N on the farm there is a negative economic impact because of the lost value
of N as crop fertilizer.

Time that milking cows spend on concrete has a direct relationship with the amount of N
produced as waste for the system to handle. With 60% or 50% of the time on concrete
(versus 80% in the control) the amount of N leached would decrease from 62K to 37K
and 30K respectively. The profit will also be affected by these changes because mainly
the N as fertilizer has a value and produces biomass as feeding for the milking cows.
With both treatments (60% and 50%) larger profit margins than the control are expected.
With the 60% level, profits greater than the 50% level are expected because greater
utilization ofN as fertilizer is expected.

Changing the main field (47.5 acres) crop has a relevant effect on the results. Changing
the corn silage to a rotation that includes forage sorghum, corn silage in summer, and rye
silage in winter implies first, that the field will be cultivated longer in time, and second, it
will have greater rates of N up take at any point in time. That is why with this rotation
only about 9K lbs ofN would be leached during five years (compared to the control 62K
Ibs). Besides the low rate of N leached, a much greater profit is expected because of the
use of the N as fertilizer: with this new rotation at least $3.062 million profit is expected
(90% chance) and at most $3.21 million. Profit of this treatment is quite similar to that
from crude protein at 15% as can be seen in Figure 3, although the levels of N leached
are quite different.


























o N Ct 1 U0 CD G- CO C> 0 4 CM C C C0 I- CO 0V
N C4 N4 04 N % N N N 04 o C (m V ) M) c') c')


Figure 3 Profit and Nitrogen Lost with Different Treatments
Note of abbreviations: CP is crude protein, DL is days in storage lagoon, TC is time in
concrete, and CR is crop rotation.

A final treatment combined the most encouraging previous results: crude protein at 15%
and a crop rotation of sorghum, corn, and rye in the largest field. The results were quite
revealing. First, no N is expected to be leached out of the farm, the entire N produced is
recycled on farm. Second, the profit levels are far above the previous ones: it would be at
least $3.66 million (90%) and at most $3.87 million. There is less risk of N lost in the
system because the low protein in the diet and the high up-take capabilities of the crops.
Higher profits are expected because of maximum use of the N as fertilizer and greater
biomass accumulation.

8. Conclusions

* Seasonality and monthly nutrient balances make a difference compared with the
traditional one-year nutrient budgeting
Crude protein and kind of nitrogen as a feed supplement have a great impact on
outputs, but experimental data are required to support and tune up interactions with N
flow
Crops are the best way of N recycling on farm. Dairy farms have to complement
livestock activity with crop activity. If crops are well managed they can provide a
good feed source to livestock and they can recycle large amounts of N
Increasing the time of liquid manure storage would not be practical in real situations
because facilities are designed for a specific holding time according to the herd size.
Besides trying to lose N to the air intentionally (in order to decrease soil N lost) could
be a bad economic decision and another environmental hazard










Changing the time milking cows spend on concrete facilities is highly dependent on
climatic conditions. Milking cows will be grazed only when weather is cool enough
not to affect milk production because of heat stress. Therefore, options on trying to
change time spent in confined facilities should be combined with changes in the herd
breed (breeds with heat tolerance, for example) or providing shade in grazing areas.
In practical and real situations, it seems that dairy farmers try to graze as much as
they possibly can.

9. References

Adams, A. L. 1998. Dietary fat effects on rumen fermentation, milk production, and
reproduction of dairy cattle, and economic implications for dairy production. PhD
Thesis, University of Florida.
Andrew, W.J. 1994. Nitrate in ground water and spring water near four dairy farms in
north Florida, 1990-1993. U.S. Geological Survey, Water-Resources Investigations
Report 94-4162.
Fraisse, C. W., K. L. Campbell, J. W. Jones, and W. G. Boggess. 1996. GIDM: A
GIS-based model for dairy waste management analysis. American Water Resource
Association Symposium on GIS and Water Resources, Sept 22-26, 1996, Ft.
Lauderdale, FL.
Giesy, R., A. de Vries, and D. Bray. 2002. Florida dairy farm situation 2002.
Cooperative Extension Service, IFAS, University of Florida.
Katz, B. 2000. Sources of nitrate contamination of spring waters, Suwannee River basin,
Florida. Florida Springs Conference Abstracts.
Katz, B., D. Hornsby, F. Bohlke, M. Mokray. 1999. Sources and chronology of nitrate
contamination in spring waters, Suwannee River Basin, Florida. USGS, Water
Resources Report 99-4252.
Kelly, T. C. 1995. A bioeconomic systems approach to sustainability analysis at the farm
level. PhD Dissertation, University of Florida.
Lanyon, L. E. 1994. Dairy manure and plant nutrient management issues affecting water
quality and the dairy industry. Journal of Dairy Science 77: 1999-2007.
Ondersteijn C.J.M., A.C.G. Beldmanb, C.H.G. Daatselaar, G.W.J. Giesen, and
R.B.M. Huirne. 2002. The Dutch mineral accounting system and the European
nitrate directive: implications for N and P management and farm performance.
Agriculture Ecosystems & Environment: 92:283-296.
Pittman, J.R., H. H. Hatzell, and E. T. Oaksford. 1997. Spring contributions to water
quantity and nitrate loads in the Suwannee River during base flow in July 1995. U.S.
Geological Survey, Water-Resources Investigations Report 97-4152. 12p.
Staples C. R., R. S. Tervola, and E. C. French. 1997. Forage Production Practices by
Dairy Producers in the Suwannee Valley. Cooperative Extension Service, IFAS,
University of Florida.
Twatchtmann, D. 1990. Regulation of dairies in Suwannee River basin. Memorandum.
Florida Department of Environmental Regulation.










Van Horn, H.H. 1997. Manure Issues: Identifying nutrient overload, odor research
report. Department of Dairy and Poultry Sciences, University of Florida.
Van Horn, H.H., G.L. Newton, G. Kidder, K.R. Woodard, and E.C. Nordstedt.
2001. Managing dairy manure accountable: worksheets for nutrient management
planning. Cooperative Extension Service, Circular 1196. IFAS, University of Florida.
Van Horn, H.H., G. L. Newton, E. C. Nordstedt, E. C. French, G. Kidder, D. A.
Graetz, and C. F. Chambliss. 1998. Dairy manure management: strategies for
recycling nutrients to recover fertilizer value and avoid environmental pollution.
Cooperative Extension Service, Circular 1016. IFAS, University of Florida.




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