Citation
Economic and ecological assessment of groundwater nitrogen pollution from North Florida dairy farm systems

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
Creator:
Cabrera, Victor E
Hildebrand, Peter E
University of Florida -- Food and Resource Economics Dept
Place of Publication:
Gainesville Fla
Publisher:
University of Florida, Institute of Food and Agricultural Sciences, Food and Resource Economics Department
Publication Date:
Language:
English
Physical Description:
15 p. : ill. ; 28 cm.

Subjects

Subjects / Keywords:
Dairy farming -- Economic aspects -- Florida ( lcsh )
Dairy farming -- Environmental aspects -- Florida ( lcsh )
Water -- Nitrogen content -- Florida ( lcsh )
Groundwater -- Pollution -- Florida -- Suwannee River ( lcsh )
Genre:
bibliography ( marcgt )
non-fiction ( marcgt )

Notes

Bibliography:
Includes bibliographical references (p. 14-15).
General Note:
Cover title.
General Note:
"August 2003."
Funding:
Florida Historical Agriculture and Rural Life
Statement of Responsibility:
by Victor E. Cabrera and Peter E. Hildebrand.

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Marston Science Library, George A. Smathers Libraries, University of Florida
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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
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The University of Florida George A. Smathers Libraries respect the intellectual property rights of others and do not claim any copyright interest in this item. This item may be protected by copyright but is made available here under a claim of fair use (17 U.S.C. §107) for non-profit research and educational purposes. Users of this work have responsibility for determining copyright status prior to reusing, publishing or reproducing this item for purposes other than what is allowed by fair use or other copyright exemptions. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder. The Smathers Libraries would like to learn more about this item and invite individuals or organizations to contact Digital Services (UFDC@uflib.ufl.edu) with any additional information they can provide.
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54394564 ( oclc )
APN4612 ( notis )

Full Text



SP 03-2





STAFF PAPER SERIES






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

Staff Paper SP 03-2 August 2003






U F














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"

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 15t 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 1-1 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' yeaf 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-' 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).




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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.



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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



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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).




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Rationality in the simulation models follows the logic of budgeting or accounting for the flows of N 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), withinsystem 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.





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MILK PRODU lON IV-, F~.fa.aMILK Ob.) MIL K N
FEEDSTOCK(Ibs 75595 2550
ON& N FEED NH3
333,31 31 bb NH3
CP% 17.5 - 763 Ib. FTROGE
HERD (units) 67,562
I NG1 MINGk2 MI,JNG 3 M[LKJNG 4
2 2T 2 25 NURSE (bs) LAGOON%
MLKING 5 ILlING 6 MILKING 7 MtING 8 FECES URINE NITROGEN l.I I 18 2n 88 277 S4,7b37s0
I MILRING 9DR MIJRNG_10 MAILIN511 I ,7.X~0.
DRY?2 T COWS MIRNG IYON
ocat< 425 REPRON IRR 1302
rc no 165 70Is .
N4 7 CROP SYSTEMS/ACRES 1
AREA INACRES 47.5 AREA IN ACRES 21 .
_________________________________________________ 1-Corn miage 17-Rye P.
ARFA iN ACRES 23 8 A ACRES 0
. .*** 2Rye, oat, or ryers. hj 13-Corn ilage berm.da
[3U us as ROGEI DM _N UPTAKEj
RUN LES TN AREK IN ACRES AREA IN ACRES 0
rtmbers 451 3 2154 11-Cor allge b rnude 2 rs orage son5*
.0 TIMES RUN


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



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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 DHIL

Lbs/day/cow
group Description milk DMI feces urine
I 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.




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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/1 997report/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



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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




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N is evenly applied to all sprayfields
a 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
B 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.

ico Nur ILEAC.ooD TOTALNLEACHED(5YEAR)





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,



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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. 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 0 7 1
8 17.50 07" 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 of N is expected to be



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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 of N 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 of N 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 of N would be leached during five years (compared to the control 62K lbs). 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.








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80% 70%
60%


40%



10%

R N Ci) W (P 1CD G CD R 0 4 Ci) ~ C CDR D 0
N C4 N 04 N N- N- 0 N Nl 0 M M ~ M)c) a) ~


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



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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.




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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 accountably: 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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