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A stochastic, individual animal systems simulation model describing U.S. beef cow–calf production was developed and parameterized to match typical U.S. Angus genetics under cow–calf production conditions in the Kansas Flint Hills. Model simulation results were compared to available actual, multivariate U.S. cow–calf production data reported according to beef cow–calf standardized performance analysis (SPA) methodology through North Dakota State University’s CHAPS program to assess model validity. Individual animal nutrition, reproduction, growth, and health characteristics, as well as production state are determined on a daily time step. Any number of days can be simulated. These capabilities allow for decision analysis and assessment of long-run outcomes of various genetic, management, and economic scenarios regarding multiple metrics simultaneously. Parameterizing the model to match Kansas Flint Hills production conditions for the years 1995 through 2018, 32 different genetic combinations for mature cow weight and peak lactation potential were simulated with 100 iterations each. Sire mature cow weight genetics ranged from 454 to 771 kg in 45 to 46 kg increments. Sire peak lactation genetics were considered at 6.8, 9, 11.3, and 13.6 kg/d for all eight mature cow weights. Utilizing model results for the years 2000 to 2018, raw model results were assessed against actual historical cow–calf production data. Exploratory factor analysis was applied to interpret the underlying factor scores of model output relative to actual cow–calf production data. Comparing modeled herd output with CHAPS herd data, median average calf weaning age, average cow age, percent pregnant per cow exposed, and percent calf mortality per calf born of model output was 3.4 d greater, 0.2 yr greater, 1 percentage point less, and 1.7 percentage points greater, respectively. Subtracting the median CHAPS pre-weaning average daily gain from the median modeled pre-weaning average daily gain for each of the eight respective mature cow weight genetics categories, and then calculating the median of the eight values, the median difference was −0.21 kg/d. Performing the same calculation for birth weight and adjusted 205 d weaning weight, the modeled data was 4.9 and 48.6 kg lighter than the CHAPS data, respectively. Management and genetic details underlying the CHAPS data were unknown.

The sustainability of the beef industry has become a point of national interest, particularly the investment of land and water resources. Our objective was to estimate how much land and irrigation water are required to maintain a simulated Angus cow-calf operation in the North Central Great Plains (NCGP) for an average year. A stochastic model was used, which enabled consideration of biological variation. The model computed 100 iterations of a 24-year timeframe (1995–2018). The simulated herd had 100 breeding females with replacement heifers being retained annually. The nutrients required to maintain a body condition score 5 for each individual animal, adjusting for temperature and physiological state, were calculated. A stocking rate of 3.3 hectares (ha) per cow-calf pair and mature cow weight of 600 kg was set, which is representative of the NCGP. Replacement heifers were assumed to be 65% of mature cow weight and allotted 1.22 ha. Bred heifers were assumed to be 85% of mature cow weight and allotted 1.81 ha. The herd was assumed to be grazing from May 1 to October 31. A supplemented ration of 60% alfalfa and 40% corn was provided if an individual’s nutritional needs were not met. Animals were assumed to be delivered a base ration from November 1 to April 30, which consisted of 73% alfalfa, 19% wheat straw, and 8% corn. The amount of irrigation necessary to grow feed was determined by estimating evapotranspiration of each crop then subtracting the amount of precipitation during the growing season. Average crop yield was determined using county level data from the UDSA NASS to estimate how much land would be needed for feed production. Sustaining a 100 head cow-calf herd in the NCGP for an average year requires 103.5 million liters for irrigation, 1288.5 ha for crop production, 357 ha grazing land.

The objective of the project was to create an economic risk analysis tool for user-defined embryo transfer (ET) programs as an aid in decision-making. Distributions defining the biological uncertainty for many reproductive outcomes are estimated through extensive literature review and limited industry sources. Applying the Latin hypercube variation of Monte Carlo simulation, a sample value from the descriptive distribution associated with each stochastic variable is included in each iteration of the simulation. Through large numbers of iterations with dynamic combinations of variable values, the process culminates in a distribution of possible values for the net present value, annuity equivalent net present value, and return on investment associated with the modeled embryo production scenario. Two options for embryo production, multiple ovulation embryo transfer (MOET) and in vitro embryo production (IVP) from aspirated oocytes, are modeled. Within both MOET and IVP, the use of unsorted or sex-sorted semen is considered, as well as the exception or inclusion of follicular synchronization and/or stimulation before ovum pick-up in IVP procedures. Pretransfer embryo selection through embryo biopsy can also be accounted for when considering in vivo derived embryos. Ample opportunity exists for the commercial application of in-depth, alternative ET scenario assessment afforded through stochastic simulation methodology that the ET industry has not yet fully exploited.