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					Developing an R statistical simulation of the Ridenour
Ranch in NE Montana in order to ask questions about
optimum stocking rate, income, and expenses under
    uncertain economic and climactic conditions

                    Andrew Lord
            Ridenour Ranch Company
       111 Welliver Rd. Plentywood MT 59254

              Project Duration: 1 year
                  Budget: 27,000
Project Summary/Abstract:

    In this study, an R simulation of the Ridenour Ranch Company was written in order to ask
questions about how changes in the business model affect net income. This pilot study asked
two main questions. First, the simulation was used to assess the possibility of adding one full
time employee. Next, the simulation was used to assess the possibility of increasing the
stocking rate to replace income from the Conservation Reserve Program (CRP). This study
found that neither of these options are possible. The ranch does not generate enough net
income to pay an additional full time employee and does not produce enough forage to sustain
a large enough stocking rate to meet expenses without additional income. These results are
indicators that further research is needed. Studies needs to be conducted in order to assess
and increase the accuracy of the simulation, find ways to increase the efficiency of the existing
business, and assess the viability of additional income generating options to diversify and
increase net income.


    In this study, an R simulation (Appendix I & II) was created in order to ask questions about
changes in income and expenses at the Ridenour Ranch. The Ridenour Ranch Company is a
family owned beef cattle operation in NE Montana that is beginning the transition from third
to fourth generation ownership. The company is owned and operated by William and
Rosemarie Lord. Both are approaching retirement age. As Bill and Rose get older, rising prices
for hired labor, ranch inputs, medicine, and insurance increase the overall income needed to
meet those costs. When they retire from the business, the management will be turned over to
their children who will have to work together to run the ranch.
    Ranching is an increasingly complex job, requiring knowledge in many different fields, from
business to mechanics, rangeland ecology to veterinary science, law to politics. The Ridenour
Ranch faces the same situation as millions of other ranches in the United States. The 2007
U.S.D.A. Census of Agriculture found that the mean age of U.S. farm operators was 57.1 years
and the fastest growing age group were those 65 years and up (U.S.D.A. 2007). This means
that the U.S. faces a huge transfer of ownership and management of its millions of family
owned farms and ranches. Without open communication among family members, successful
transfer of the ranch can be difficult.
    In order to plan for the transfer, reasonable estimates are need for both the additional
expenses and additional income needed to cover those expenses. For this study an R statistical
model of the Ridenour Ranch Company was developed to simulate variation in stocking rate,
expenses, forage yield, and market prices, in order to calculate potential net income under
varying environmental and economic conditions. This program is used to simulate the stocking
rate needed to match the additional expenses levied by intergenerational transfer. This
program uses forage yield data from the local Sheridan County MT Natural Resource
Conservation Service. The forage yield data, along with actual expenses, market prices, and
average livestock weights, were used to calculate and compare the minimum income needed
to cover additional expenses with the maximum stocking rate that forage yield could
sustainably support.
    The overall goal of this study is to provide reasonable estimates that can be used to aid the
continuing success of the Ridenour Ranch Company for generations to come. This pilot study
used the R simulation to answer two questions.
    1. Can the Ridenour Ranch Company take on one additional full time employee?
    2. If the CRP program is ended at the Ridenour Ranch, can the company scale up the
         cow/calf enterprise to replace the CRP income?
   The simulation made it clear that the answer to both of these questions is “no.” Based on
the calculations of the simulation, the current stocking rate is the maximum stocking rate. The
current income is not enough to pay an additional full time employee, and there no extra
forage to increase the stocking rate. Second, if the CRP program comes to an end, the acres
that are in CRP do not have a high enough forage yield to raise enough cattle to replace the
income from CRP. Careful planning is thus needed to reduce the ranches vulnerability to
changes in the federal funding.
    In order to ensure reliability of the simulation, further research needs to be done to
increase the programs accuracy at representing the reality at the Ridenour Ranch. A study to
measure actual forage yields and precipitation patterns at the Ridenour Ranch will enable
much more accurate estimates of forage yield, livestock production capability, and possible
economic gains. A study focused on increasing the Ridenour Ranch Company’s efficiency and
effectiveness at making more income from less inputs is needed in order to create additional
income to pay for the increased hired help Bill and Rose will need as they get older. Additional
income generating enterprises will also need to be explored in order to ensure financial
stability should the CRP program be phased out and/or an additional full time employee
becomes a necessity.

   Literature Review:

Ranch Management and the Stocking Rate:
         Ranch management decisions are based on ranchers estimates of uncertainty in stock
handling capability, water availability, forage yield, expenses, market prices of cattle, hay and
fuel, legal issues like zoning and taxation, availability of government programs, and more.
Because of high uncertainty, profit maximizing can lead ranches into serious ecological
problems and large financial risk. On ranches, increased profits are associated with increased
risk, leading ranchers to adapt management strategies to their environment (Whitson 1975).
Ranchers business is to conserve and sustain rangeland ecosystems, which is both a social and
ecological process. Ranchers and their families are part of a local community, and the ranching
business is part of a national and global community made up of diverse social groups
(Huntisinger & Hopkins 1996). Ranchers are forced to balance the need to increase ranch
income to match rising expenses with the need to conserve enough forage to ensure long-term
range health (Torell et. al. 1991). The ecological and economic complexities of matching
stocking rate to the true grazing capacity of a pasture, or average number of animals a pasture
can sustain over time, can easily lead to rangeland degradation due to overgrazing (Galt et. al.).
Stocking rate is therefore considered the most important single factor in ranch management
decisions involving livestock management, rangeland health, wildlife diversity, and economic
returns (Torell et. al. 1991).

Ranch Transfer:
       Increasing the complexity of ranch decision-making is the transfer of control of ranch
business assets from one generation to the next in a way that increases the interpersonal and
economic well-being of the entire family. Early and open communication among family
members over decision-making is the most effective strategy to ensure a successful transfer
and continuation of the ranching operation (Fetsch 1999).

       Several complex ranch mathematical equations and simulations have been published.
Techniques include linear programming to optimize resource allocation (Bartlett et. al. 2007), a
dynamic optimal control model to calculate optimum stocking rate (Torell et. al. 1991),
simulated net income compared to real net income of a large ranch (Halter & Dean 1965), and
a stochastic dynamic model of reproduction paired with a economic simulation model to
evaluate the effect of cattle reproduction on net income (Werth et. al. 1991).


       This study uses an R simulation (Appendix 1 & 2) of the Ridenour Ranch to compare the
minimum stocking rate needed to cover expenses with the maximum stocking rate sustainable
without overgrazing, under varying economic and environmental conditions. The simulation
can be adjusted to answer different questions. For this pilot study, two questions have been
evaluated using the simulation.
   1. Can the Ridenour Ranch Company take on one additional full time employee?
   2. If the CRP program is ended at the Ridenour Ranch, can the company scale up the
       cow/calf enterprise to replace the CRP income?

        In order to answer these questions, estimates were gathered to calculate total
expenses, calf weights, cattle prices, and forage yields. To simulate uncertainty in income,
point estimates for forage yields and cattle prices were selected from one of three categories
(favorable, normal, and unfavorable) and used as inputs in the simulation. To simulate
uncertainty in expenses, hay prices were selected with the same method, and other expenses
were adjusted by hand. To select from normal, favorable, and unfavorable years, a binomial
number generator was used.
        Once the inputs are all selected, the simulator simulates 1,000 ten-year averages for
net income and net Animal Unit Equivalents (AUEs) (the total possible AUEs available minus the
total stocking rate AUEs). Histograms are generated for both net income (Fig. 3 & 5), and net
AUEs (Fig. 2 & 4). If net income is negative the ranch is losing money, and if net AUEs are
negative the ranch is overgrazing. Increasing the stocking rate and decreasing expenses are the
two ways to increase net income. Decreasing the stocking rate and increasing the number of
acres grazed are two ways to increase net AUEs. To pass the test of the simulator, a business
model has to have both a positive income and positive net forage yield for 100% of the trials.

Measurement Methods:

R Program Input Estimates:
AUEs: Animal Unit Equivalents were calculated according to Scarnecchia & Gaskins (1987)
using the harvest coefficient (forage grazing efficiency) of 25% (Galt et. al. 2000).

Forage Yield: Forage yield estimates by soil type were calculated by Monica Friedrich, the
District Conservationist at the USDA-NRCS in Plentywood Montana (Friedrich 2011).

Cattle Prices and Weights: Market price variability was estimated by using the average calf
weights (550 lb. steers/500 lb. heifers) and corresponding prices received by the Ridenour in
2010 and 2011. Bill lord estimated the 2011 cattle prices as favorable ($1.46 for 550lb. steers
and $1.36 for 500lb. heifers), the 2010 cattle prices as unfavorable ($0.92 for 550lb. steers and
$0.82 for 500lb. heifers), and the mean as normal ($1.19 for 550lb. steers and $1.09 for 500lb.

Operating Expenses: Expenses were calculated using the Ridenour Ranch 2010 Tax Return.
Operating expenses included wages, medical expenses, taxes, veterinary expenses, machinery
expense, fencing supplies, etc.

Hay Expenses: Haying Expenses were calculated using point estimates from Bill Lord.
Favorable year hay expenses were estimated at all hay costing $40/ton, normal as half $40/ton
half $70/ton, and unfavorable as half $40/ton half $100. Forty dollars per ton is the price per
ton for making the hay at the ranch. Seventy dollars per ton represents a normal hay price
when bought in the summer in preparation for winter and one hundred per ton is the price
paid in a drought year or late in the winter when hay is in high demand. On a favorable year all
hay can be made at the ranch. On a normal or unfavorable year, only half the hay can be made
on the ranch and the other half must be purchased.

Binomial Number Generator: Two rounds of a binomial number generator were used to chose
between normal, favorable, or unfavorable year forage yield and market prices. In the first
round, to select for normal or not normal, the number generator was set to a rate of 0.65
(normal), and if not normal, a binomial number generator was set at 0.5 to select from
favorable or unfavorable. Market price was selected the same way, but rate 0.5 was used for
both rounds. These rates were chosen by the researcher without a literature reference, and
will take further study to substantiate. The pregnancy rates were set at 0.85 in the binomial
generator to simulate calf yield and 0.5 for the male to female binomial generator. These
were the rates recorded at the Ridenour Ranch in 2011.

Statistical Methods:

    An R simulation was written in order to ask questions about future possibilities for the
Ridenour Ranch Company. A flowchart was then constructed to use as a guide for navigating
the R simulation (Fig. 1.). First, parameters are set and loaded into the simulation. Net income
and forage harvest are simulated and results are displayed as histograms (Fig. 2-6). Net income
is calculated by subtracting total expenses from gross income, and can either be positive or
negative. Simulated forage harvest data is used to calculate extra available AUEs by
subtracting stocking rate AUEs from the gross AUEs. If the histogram of leftover AUEs contains
only positive values, the parcels have not been overgrazed. If there are negative values on the
histogram, the parcels have been overgrazed by that quantity of AUEs (x-axis) at that frequency
(y-axis). Following the flowchart (Fig.1), positive income followed by no overgrazing leads to
optimizing the stocking rate (raising the stocking rate until just before overgrazing occurs) to
maximize profits without overgrazing. This ends the simulation. The maximized total net
income is then used to answer the question. The other branches of the decision tree lead to
adjusting, either stocking rate, area grazed, or expenses, before re-simulating.
    The answer to the first question became obvious while tuning the simulation to calculate
the net income and AUE potential with the current actual inputs from the Ridenour Ranch
Company. The histogram of net income has a low tail value of $5,000, which is not enough to
pay for another full time employee. The second question was answered by removing the CRP
income from the simulation and turning the parcels, formerly allocated to CRP, over to
simulated grazing. With the available forage yield, the ranch cannot stock enough animals to
provide a positive net income without overgrazing. The CRP payment is more income per acre
than raising cattle. In order for the Ridenour Ranch Company to function without the CRP,
additional income generating enterprises are needed.

Fig. 1. Flowchart for the use of the R simulation of the Ridenour Ranch.

Adequacy of Design/Results of Pilot Study:

   The first R simulation (Appendix I) was set to answer the question: Can the Ridenour Ranch
afford to take on an additional fulltime staff? Figure 2 is a histogram of net AUEs, which are
approaching but not crossing zero, and therefore approaching but not overgrazing (optimized
stocking rate). Figure 3 is a histogram of 10-year average net incomes at the ranch with the
2011 stocking rate over 1,000 trials. With a stocking rate of 164 AUEs on 3,585.8 acres of
pasture and 1,085.4 acres farmland contracted in the CRP program at $32/acre, it is clear that
there is not consistently enough income to pay an extra full time employee a living wage.

 Fig. 2. (Left) Net AUEs with a stocking rate of 164 AUEs on 3585.8 acres.

 Fig. 3. (Right) Net Income from cow calf operation with 164 AUEs on 3585.8
 acres,1085.4 acres contracted in the CRP program, paying one full time

   The second R simulation (Appendix II) was used to address the question: Is a cow/calf
operation a viable business on the Ridenour Ranch without income from the CRP program? All
farmland parcels formerly assigned to the CRP program were reassigned into the grazing
program, increasing the total grazing acreage by 1085 acres. At a stocking rate of 244 AUEs on
4,953.4 acres, overgrazing is beginning to occur (Fig. 4) while income is positive in very low
frequency (Fig. 5).

 Fig. 4. (Left) Net AUEs with a stocking rate of 244 AUEs on 4953.4 acres.

 Fig. 5. (Right) Net Income from cow/calf operation with 244 AUEs on 4953.4
 acres paying one full time employee.

Future Research:
   The results of this pilot study point to the need for further research in several areas:

    First, a study should be done to link forage yield to precipitation data and weather cycles at
the Ridenour Ranch. In this pilot study, precipitation and forage yield were linked by the
qualitative measures used by the Natural Resource Conservation Service (NRCS); favorable,
normal, and unfavorable. Normal (average) precipitation in NE Montana is 12 in./yr., while
favorable and unfavorable are not paired with inches of precipitation. There is no way to use
precipitation data to distinguish between a favorable year and normal year with high-normal
precipitation or between an unfavorable year and a normal year with low-normal precipitation.
For example, currently I have no way to tell if a year with 14 inches of precipitation is a normal
year with above average precipitation, or a favorable year? Also, instead of using weather
cycles, which last more than one year, qualitative measures were selected each year. For
example, a drought (unfavorable) usually last more than one year, but in my model, there is a
new round of selection each year, un-linked to the year before. In order to create a link
between precipitation, forage yield, and the qualitative measures used by the NRCS, a
minimum of a one year study is needed in order to measure actual forage yields on the
Ridenour Ranch, couple those with actual precipitation data for that year, and find where
those measures fall on the NRCS scale. Additionally, a literature study of past weather cycles
and their associated precipitation could be used to make predictions about summer forage
yield based on spring precipitation, and possibly next years forage yield based on this years
    Next, a study focused on increasing efficiency of the current cow/calf operation is needed.
Current pregnancy rates are below average. This is due to below average performance of the
bulls, which have been getting injured at an above average rate, lowering their ability to mate.
Reduction in pregnancy rate directly reduce net income. A study needs to be done in order to
find a better breeding system. Next, a study is needed to assess mechanical harvest efficiency.
 Mechanical harvest efficiency is measured as the percentage of total forage yield that can be
turned into hay bales and stored for winter feed. This measure is used to calculate the number
of animals that can be wintered without buying hay. Making hay on the ranch is much cheaper
than buying hay, and therefore reduces expenses. Another study is needed to explore
alternatives to feeding methods. One problem that should be addressed is forage lost to
trampling. Currently, bales are rolled out on the ground. Alternatives exist to reduce forage
loss during winter feeding, such as placing the bales into metal feeders, and should be
considered. Finally, a study needs to be done to address the date when calves are sold.
Currently, calves are sold in November when prices are at their lowest. Alternatives exist, such
as over-wintering calves and selling in the spring when prices are at their peak. This alternative
is a trade-off between increased in winter feeding expenses and higher spring market prices,
and therefore increased net income is not a sure thing. A study is needed to assess the
potential of this and other alternatives.
    Finally, a study is needed to assess the income potential of additional income generating
enterprises, which could be used to diversify and increase net income. Currently, Bill and Rose
have rental property in town, and this income has not been considered in this R program.
Other potential enterprises include opening a feed lot, sharecropping or leasing farmland to a
farmer (for wheat, barley, or lentil production), bee farming, tree breeding, small scale
vegetable production, hunting leases, wind farming, a micro-brewery, and tourism (bed and
   breakfast, camping, etc.), to name a few. Government conservation programs, such as the
   USDA Conservation Stewardship program, or USDA organic certification, are also potential
   income sources that need to be explored. In addition, possibilities of off farm enterprises, such
   as a Ridenour Ranch restaurant in Plentywood, serving organic grass-fed beef, could be a

   Timetable & Budget:

Budget Justification:               Activity                             Cost

   Jan-May 2012                     - Full-time student MSU enrolled     $9,300
                                    in relevant courses with research
                                    credits ( NRSM 235 Range and
                                    Pasture Monitoring, BIOB 318
                                    Biometry, GPHY 284 Introduction
                                    to GIS Science and Cartography)
                                    - Create more sophisticated          10hrs*16 weeks*$10 = $1,600
                                    simulation and prepare for data
   May-Aug 2012                     Gather forage and precipitation   Travel: $1,000
                                    data at the Ridenour Ranch        Salary: $4,000
                                                                      Equipment: $200
   Aug-Dec 2010                     Full-time student MSU enrolled in $9,300
                                    relevant courses with research
                                    credits (NRSM 353 Grazing
                                    Ecology and Management, STATS
                                    217 Intermediate Statistical
                                    Concepts, AGEC 345 Agricultural
                                    Finance and Credit Analysis)
                                    - Improve R simulation, data      10hrs*16 weeks*$10 = $1,600
                                    analysis, Complete and submit

                                                                 Total: 27,000

Andrew Lord

Bachelor of Science in Plant Biotechnology (2011)
        Montana State University-Bozeman U.S.A.
Teaching English to Speakers of Other Languages (TESOL)
         I.N.T.E.S.O.L. 120hr Certificate/AYC Thailand/1 year experience
S.C.U.B.A. Diving Instructor: P.A.D.I. –I.D.C. with S.S.I. crossover (MSDT EFRI /DCSI,)
        Certification: 83 Logged Dives: 405
D.A.N. O2 Provider (03/09)
A.S.S.E.T Diving Industry Service Technician
        Member No. T871/22-Sept.-2010
B.S.A.C. Boat Handler and Diver Coxswain

Work History:

       Cattle Rancher: The Ridenour Ranch, South West of Plentywood Montana
Dec 2007-Present
       Freelance SCUBA Diving and Emergency First Response Instructor
       Building Construction, Finish and Design: Spain, Montana, Alaska, Guatemala
       Cleaning and organizing businesses, properties and houses.
July 2009-Aug 2010
       English Camp Director and Assistant Projects Manager: AYC Intercultural Thailand
2007 March-May
       Substitute Public School Teacher K-12: Plentywood School, Plentywood Montana USA
2006 March-June
       Outdoor Education Instructor: Camp Killoqua, Washington USA
2004-2005 Nov-Mar
       Assistant Manager and Baker: Hotel Aaculaax, San Marcos la Laguna, Guatemala.
2003 Jan-May
       Assistant Manager: Big Sky Ski Resort Outside Condo Housekeeping Department
       Plant Science Research: MSU-Bozeman. For Nina Zidack on sugarbeet systems.
       Sales, Management, and Recruiting: Private Contractor For Southwestern Company
Literature Cited:

Bartlett, E., G. Evans, R. Bement. 1974. A Serial Optimization Model for Ranch
Management. Journal of Range Management. 27(3), 233-239.

Galt, D., F. Molinar, J. Navarro, J. Joseph, J. Holechek. 2000. Grazing Capacity and Stocking Rate.
Rangelands. 229(6), 7-11.

Scarnecchia, D., C. Gaskins. 1987. Modeling animal-unit-equivalents for beef cattle. Agricultural
Systems. 23(1), 19-26.

Fetsch, R., 1999. “Some Do's and Don'ts for Successful Farm and Ranch Family Estate
Transfers,” Journal of Extension 37(3).

Friedrich, M. Sheridan County Natural Resources Conservation Service, United States
Department of Agriculture. Web Soil Survey. Available online at Accessed [Sept/10/2011].

Galt, D., F. Molinar, J. Navarro, J. Joseph, J. Holechek. 2000. Grazing Capacity and Stocking Rate.
Rangelands. 22(6) 7-11.

Halter, A. and G. Dean. 1965. Use of Simulation in Evaluating Management Policies Under
Uncertainty: Application to a Large Scale Ranch. Journal of Farm Economics. 47(3), 557-573.

Huntsinger, L. & P. Hopkinson. 1996. Viewpoint: Sustaining Rangeland Landscapes: A Social and
Ecological Process. Journal of Range Management. 49(2), 167-173.

Torell, A., K. Lyon, B. Godfrey. 1991. Long-Run versus Short-Run Planning Horizons and the
Rangeland Stocking Rate Decision. American Journal of Agricultural Economics. 73(3), 795-807.

U.S.D.A. Census of Agriculture 2007. Farmers by age. Downloaded from web: on 11-27-2011.

Werth, L., S. Azzam, M. Nielsen and J. Kinder. 1991. Use of a simulation model to evaluate the
influence of reproductive performance and management decisions on net income in beef
production. Journal of Animal Science. 69, 4710-4721.

Whitson, R. 1975. Ranch Decision-Making under Uncertainty: An Illustration
Journal of Range Management. 28(4) 267-270.

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