Dynamic Stochastic Simulation Model Research Articles

Effects of extending dairy cow longevity by adjusted reproduction management decisions on partial net return and greenhouse gas emissions: A dynamic stochastic herd simulation study

Prolonging dairy cattle longevity is regarded as one of the options to contribute to more sustainable milk production. Because failure to conceive is one of the main reasons for culling, this study investigates how adjustments in reproduction management affect partial net return at herd level and greenhouse gas emissions per unit of milk, using a dynamic stochastic simulation model. The effects of reproduction decisions that extend cattle longevity on milk yield, calving interval and pregnancy rate were derived from actual performance of Dutch commercial dairy cows over multiple lactations. The model simulated lactations, calving, and health status events of individual cows for herds of 100 cows. Scenarios evaluated differed in the maximum number of consecutive AI attempts (4, 5, or 6 services), or the production threshold (20, 15, or 10 kg of milk/d) at which cows that failed to conceive are culled (reproductive culling). Annual partial net return was computed from revenues of sold milk, calves, and slaughtered cows, and the costs from feed consumption, rearing replacement heifers, AI services, and treatment for clinical mastitis and lameness. Greenhouse gas emissions were computed for feed production, enteric fermentation, and manure management, and were expressed as total CO2 equivalents (CO2-eq). Average age at culling increased with an increased maximum number of AI services. This increase was larger when going from a maximum of 4 to 5 AI attempts (108 d) than from a maximum of 5 to 6 attempts (47 d). Similarly, the average age at culling increased from 1,968 to 2,040 and 2,132 d when the threshold for reproductive culling decreased from 20, to 15 and 10 kg of milk/d, respectively. Average annual partial net return increased by 1.1% from €165,850 per 100 cows at a maximum of 4 AI to €167,670 per 100 cows at a maximum of 6 AI, and increased by 4.3% from €161,210 per 100 cows at a reproductive culling threshold of 10 kg/d to €168,190 per 100 cows at a threshold of 20 kg/d. Greenhouse gas emissions decreased by 1.2% from 0.926 to 0.915 kg CO2-eq per kg of fat- and protein-corrected milk (FPCM) with an increase in a maximum number of AI from 4 to 6 AI. Conversely, greenhouse gas emissions increased by 0.2% from 0.926 kg at a threshold of reproductive culling of 20 kg/d to 0.928 kg CO2-eq/kg FPCM at a threshold of 10 kg/d. Although lowering the threshold for reproductive culling has the potential to extend cattle longevity more than increasing the maximum number of AI services, only the increase in AI services benefits a farm's partial net return, while reducing greenhouse gas emissions.

Closing the gaps in the continuum of depression care for persons with HIV: modeling the impact on viral suppression in the United States.

Depression is prevalent among persons with HIV (PWH) and is associated with poorer adherence and lack of viral load suppression (VLS). When treated for depression, PWH are more likely to stay in HIV care and adhere to medications; however, for many PWH, depression is not adequately diagnosed or treated. We adapted Progression and Transmission of HIV (PATH 3.0), a U.S. agent-based dynamic stochastic simulation model, by incorporating a continuum of depression care and estimating the impact on VLS of an enhanced depression diagnosis and care scenario (EDC). We compared EDC - whereby every PWH is assessed for depression, gets treatment if diagnosed, and of those, half achieve remission - to a status quo scenario (SQ) on VLS. Based on published findings, assumptions for SQ were: 34.7% depressed, 45% diagnosed, 55.3% treated and 33% of treated achieving remission. Compared to PWH without depression, we assumed the probability of being non-virally suppressed increased by 1.57 times for PWH with depression (PWH-D), and by 0.95 times for PWH with remitted depression. There was an average increase of 14.6% (11.5-18.5) in the proportion of PWH-D who achieved VLS in EDC compared to SQ. Among all PWH, there was a 4.7% (3.4-6.0) increase in the proportion who achieved VLS in EDC compared to SQ. Fully diagnosing and adequately treating depression would improve health and quality of life for a substantial proportion of PWH-D and result in a nearly 5% increase in expected rates of VLS in the United States, supporting national prevention goals.

Economic impact of highly pathogenic avian influenza outbreaks in Western Java smallholder broiler farms

Highly Pathogenic Avian Influenza (HPAI) H5N1 is considered endemic in most parts of Indonesia and constitutes an important risk for broiler production, especially in Western Java which has the highest poultry population in the country. Most broiler farms in Western Java are smallholder farms that operate under different business types: independent (i.e., revenues based on market price and live bird weight), price-contract (i.e., revenues based on a contract selling price and live bird weight) or makloon (i.e., revenues based on a management fee per sold bird). Many studies focus on the epidemiological impacts of HPAI at the regional level, and insights into the economic impact at the farm level are scarce, especially in the Indonesian context. Meanwhile, a single HPAI outbreak could disrupt smallholder broiler farmers’ primary source of income. Therefore, this study aimed to evaluate the economic impact of HPAI outbreaks under different response scenarios (i.e., no action, stamping out, and early selling) on typical Western Java smallholder broiler farms. Furthermore, the effect of different farm business types and the existence of a sick-bird market on the economic effects of HPAI outbreaks were evaluated. We developed a dynamic stochastic bio-economic simulation model to simulate epidemiological and economic impacts of HPAI outbreaks on a typical Western Java smallholder broiler farm during one production round. Our results show that the economic consequences of HPAI outbreaks for independent and price-contract farms are considerable, ranging from, on average, 1.2–62.7 million Indonesian Rupiah (IDR) losses (€76.9 to €3919), depending on the moment of and response to infection, compared to an expected gross margin of 5.3 million IDR (€331) under normal circumstances. The economic loss for makloon farms was substantially lower than for other business types, reducing their incentive to implement biosecurity. The economic impacts were sensitive to changes in a diverse set of parameters, including disease transmission rate, detection threshold, and stamping-out compensation. The losses in a scenario with stamping out were higher than in other scenarios, especially when stamping out happened near the end of the production round. Moreover, reacting to an outbreak by selling chickens early gave the lowest economic losses, incentivizing farmers to engage in behavior with a high disease transmission risk. Therefore, the results of this study suggest that it is important to consider the economic perspective of individual farmers when designing HPAI mitigation programs. Financial incentives for farmers to control HPAI differ largely between farm business types.

Perspectives on exploration and extraction of seafloor massive sulfide deposits in Norwegian waters

Abstract We present a stochastic dynamic simulation model for exploration and extraction of seafloor massive sulfide (SMS) mineral deposits on the Norwegian Continental Shelf (NCS). The model is developed based on selected industry knowledge, expectations, and perceptions elicited through a participatory systems mapping session with 82 participants and 20 in-depth interviews with experts from industry, academia, and the public policy sector. Using the model, we simulate the expected ranges of resource- and economic potential. The simulation results indicate an expected commercial resource base of 1.8 to 3 million tons of copper, zinc, and cobalt, in which copper makes out the most significant part. Relating to the expected commercial resource base, we highlight a discrepancy between academic and industrial expectations, in which the academic expectations are more conservative than the industrial expectations. The corresponding net present values lie in the range of a net present loss of 970 million USD up to a net present gain of 2.53 billion USD, in which the academic expectations are projected to yield a negative net present value, while the industrial expectations are projected to yield a positive net present value. Closer investigation of the results reveals that one of the main challenges regarding SMS exploration and extraction is the initial exploration costs associated with coring operations. These costs are expected to be high with today’s exploration technology. Moreover, they occur relatively early in time compared to revenue-generating activity, which has a significant negative impact on the net present value of the industry due to discounting. Thus, a key focus of the industry should be to find ways to reduce the costs associated with coring operations and/or the time it takes from initial exploration to extraction and generation of revenue.

The effect of claw disorders on the locomotion activity of dairy cows

Article Details: Received: 2020-10-26 | Accepted: 2020-11-27 | Available online: 2021-01-31 https://doi.org/10.15414/afz.2021.24.mi-prap.135-139 The purpose of the work was aimed at determining changes in locomotion activity of dairy cows with healthy claws, as opposed to cows suffering from claw disorders. To achieve this goal, Heatime RuminAct technical equipment was used. Data gathering took place at the dairy farm of University of Agriculture in Nitra, where locomotion activity was measured via Heatime RuminAct hardware with DataFlowTMII software. This data came from 87 dairy cows, whose locomotion activity was monitored during a period of 21 days. This period consisted of 10 days of monitoring before the claw trimming, monitoring during the day of the trimming, and afterwards, another 10 days of monitoring after the trimming was complete. Units of locomotion activity in 24 hours (u.24h -1 ) were used to formulate the locomotion activity of the dairy cows. Health conditions of claws of the dairy cows were recorded and based on the presence of claw disorders, the cows were divided into two groups - cows with observed claw disorders formed a group of 33 cows, and cows exhibiting no claw disorder related symptoms formed a group of 54 cows. Conclusions based on results from the data gathered confirm a crucial difference in locomotion activity between healthy cows and cows afflicted by claw disorders. Keywords: dairy cow, Heatime RuminAct, locomotion activity, claw health, claw disorders References Anil, L. et al. (2005). Pain detection and amelioration in animals on the farm: issues and options. Journal of Applied Animal Welfare Science , 8, 261-278. https://doi.org/10.1207/s15327604jaws0804_3 Beer, G. et al. (2016). Use of extended characteristics of locomotion and feeding behavior for automated identification of lame dairy cows. PLoS One , 11, e0155796. https://doi.org/10.1371/journal.pone.0155796 Bruijnis, M. R. et al. H. (2010). Assessing economic consequences of foot disorders in dairy cattle using a dynamic stochastic simulation model. Journal of Dairy Scienc e, 93(6), 2419-2432. https://doi.org/10.3168/jds.2009-2721 Flower, F. C. et al.(2006). Effect of hoof pathologies on subjective assessments of dairy cow gait. Journal of Dairy Science , 89, 139-146. https://doi.org/10.3168/jds.S0022-0302(06)72077-X Hudson, C. et al. (2008) H. Recognition and management of pain in cattle. In Practice, 30, 126-134. https://doi.org/ 10.1136/inpract.30.3.126 King, M. T. M. et al. (2017). Cow-level associations of lameness, behavior, and milk yield of cows milked in automated systems. Journal of Dairy Science , 100(6), 4818-4828. https://doi.org/10.3168/jds.2016-12281 Nechanitzky, K. et al. (2016). Analysis of behavioral changes in dairy cows associated with claw horn lesions. Journal of Dairy Science , 99(4), 2904-2914. https://doi.org/10.3168/jds.2015-10109 O'Callaghan, K. A. et al. (2003). Subjective and objective assessment of pain and discomfort due to lameness in dairy cattle. Animal Welfare , 12, 605-610. O'Leary, N. W. et al. (2020). Invited review: Cattle lameness detection with accelerometers. Journal of Dairy Science , 103(5), 3895-3911. https://doi.org/10.3168/jds.2019-17123 Shepley, E. et al. (2017). Validation of the ability of a 3D pedometer to accurately determine the number of steps taken by dairy cows when housed in tie-stalls. Agriculture (Basel), 7, 53. https://doi.org/10.3390/agriculture7070053 Stoddard, G. C. and Cramer, G. (2017). A Review of the Relationship Between Hoof Trimming and Dairy Cattle Welfare. Veterinary Clinics of North America: Food Animal Practice , 33(2), 365-375. https://doi.org/10.1016/j.cvfa.2017.02.012 Strapak, P. et al. (2013). Cattle Breeding . Nitra: Slovak University of Agriculture. In Slovak. Thorup, V. M. et al. (2015). Lameness detection via leg-mounted accelerometers on dairy cows on four commercial farms. Animal , 9, 1704-1712. https://doi.org/10.1017/S1751731115000890 Weigele, H. C. et al. (2018). Moderate lameness leads to marked behavioral changes in dairy cows. Journal of Dairy Science , 101(3), 2370-2382. https://doi.org/10.3168/jds.2017-13120

Infectious Diseases, Livestock, and Climate: A Vicious Cycle?

Ruminant livestock are a significant contributor to global methane emissions. Infectious diseases have the potential to exacerbate these contributions by elevating methane outputs associated with animal production. With the increasing spread of many infectious diseases, the emergence of a vicious climate–livestock–disease cycle is a looming threat.

Estimating the combined costs of clinical and subclinical ketosis in dairy cows.

Clinical ketosis (CK) and subclinical ketosis (SCK) are associated with lower milk production, lower reproductive performance, an increased culling of cows and an increased probability of other disorders. Quantifying the costs related to ketosis will enable veterinarians and farmers to make more informed decisions regarding the prevention and treatment of the disease. The overall aim of this study was to estimate the combined costs of CK and SCK using assumptions and input variables from a typical Dutch context. A herd level dynamic stochastic simulation model was developed, simulating 385 herds with 130 cows each. In the default scenario there was a CK probability of almost 1% and a SCK probability of 11%. The herds under the no risk scenario had no CK and SCK, while the herds under the high-risk scenario had a doubled probability of CK and SCK compared to the default scenario. The results from the simulation model were used to estimate the annual cash flows of the herds, including the costs related to milk production losses, treatment, displaced abomasum, mastitis, calf management, culling and feed, as well as the returns from sales of milk and calves. The difference between the annual net cash flows of farms in the no risk scenario and the default scenario provides the estimate of the herd level costs of ketosis. Average herd level costs of ketosis (CK and SCK combined) were €3,613 per year for a default farm and €7,371 per year for a high-risk farm. The costs for a single CK case were on average €709 (with 5 and 95 percentiles of €64 and €1,196, respectively), while the costs for a single SCK case were on average €150 (with 5 and 95 percentiles of €18 and €422, respectively) for the default farms. The differences in costs between cases occurred due to differences between cases (e.g., cow culled vs cow not culled, getting another disease vs not getting another disease).

Economics of reducing antibiotic usage for clinical mastitis and metritis through genomic selection

Antibiotics use (ABU) in animal agriculture has been implicated in the emergence of antibiotic resistance, a global public health threat. Economically justifiable antibiotic reduction strategies can motivate farmers to reduce ABU for clinical mastitis (CM) and metritis, the most common reasons for ABU on dairy farms. Our objective was to quantify the reduction in incidence of CM, metritis, and ABU, and the herd performance of a representative US herd that uses genomic selection for Lifetime Net Merit 2018 (NM$) selection index, compared with genetic selection based only on the mastitis (MAST) or metritis resistance (METR) trait or a health trait subindex (HTH$). A stochastic dynamic simulation model of a 1,000-cow herd with multi-trait genetics for 19 correlated traits included in the NM$ affected the performance of animals. The incidence of CM and metritis for each animal was affected by the genetic and environmental components of the MAST or METR, along with a standard phenotypic function that calculated the daily underlying herd probability to contract CM or metritis. Selection decisions were made based on genomic estimated breeding values of the traits of interest. A strategy named AI-NM$ based decisions on the NM$ trait so that the correlated genetic trends in MAST and METR are improved. Three other strategies named AI-MAST, AI-METR, and AI-HTH$ maximized respectively MAST, METR, and HTH$ genetic merit, but with a tradeoff in NM$ genetic merit. The cumulative true breeding values (TBV) of NM$ for 15 yr showed a difference of $4,947 per cow between the AI-NM$ (best strategy for NM$) and AI-METR (worst strategy for NM$). However, the 15-yr cumulative TBV of MAST was 26.50 percentage points (PP) higher in AI-MAST, and 18.5 PP higher for METR in AI-METR, compared with AI-NM$. As a result, the 15-yr cumulative phenotypic CM and metritis incidence was respectively 94.03 PP and 58 PP lower in AI-MAST and AI-METR compared with AI-NM$. Therefore the corresponding 15-yr cumulative ABU decreased by 42% in AI-MAST and by 53% in AI-METR. We found that AI-MAST had the lowest CM incidence across the 15 yr, whereas AI-METR had the lowest incidence of metritis and the smallest total ABU for 15 yr. To achieve the lowest incidence of CM, metritis, and ABU strategies AI-MAST, AI-METR, and AI-HTH$ had to incur 15-yr discounted cumulative losses per cow of $1,486, $1,434, and $1,130, respectively, compared with AI-NM$. Hence, AI-NM$ had the best financial performance, despite having slightly higher incidence of CM, metritis, and ABU.

Estimating the impact of clinical mastitis in dairy cows on greenhouse gas emissions using a dynamic stochastic simulation model: a case study

The increasing attention for global warming is likely to contribute to the introduction of policies or other incentives to reduce greenhouse gas (GHG) emissions related to livestock production, including dairy. The dairy sector is an important contributor to GHG emissions. Clinical mastitis (CM), an intramammary infection, results in reduced milk production and fertility, increases culling and mortality of cows and, therefore, has a negative impact on the efficiency (output/input) of milk production. This may increase GHG emissions per unit of product. Our objective was to estimate the impact of CM in dairy cows on GHG emissions of milk production for the Dutch situation. A dynamic stochastic simulation model was developed to simulate the dynamics and losses of CM for individual lactations. Cows receive a parity (1 to 5+), a milk production and a calving interval (CI). Based on the parity, cows have a risk of CM, with a maximum of three cases in a lactation. Pathogens causing CM were classified as gram-positive bacteria, gram-negative bacteria, or other. Based on the parity and pathogen combinations, cows had a reduced milk production, discarded milk, prolonged CI and a risk of removal (culling and mortality) that reduce productivity of dairy cows and therefore increase GHG emissions per unit of product. Using life cycle assessment, emissions of GHGs were estimated from cradle to farm gate for processes along the milk production chain that are affected by CM. Processes included were feed production, enteric fermentation, and manure management. Emissions of GHGs were expressed as kg CO2 equivalents per ton of fat-and-protein-corrected milk (kg CO2e/t FPCM). Emissions of cows with CM increased on average by 57.5 (6.2%) kg CO2e/t FPCM compared with cows without CM. This increase was caused by removal (39%), discarded milk (38%), reduced milk production (17%) and prolonged CI (6%). The GHG emissions increased by 48 kg CO2e/t FPCM for cows with one case of CM, by 69 kg CO2e/t FPCM for cows with two cases of CM and by 92 kg CO2e/t FPCM for cows with three cases of CM compared with cows without CM. Preventing CM can be an effective strategy for farmers to reduce GHG emissions and can contribute to sustainable development of the dairy sector, because this also can improve the income of farmers and the welfare of cows. The impact of CM on GHG emissions, however, will vary between farms due to environmental conditions and management practices.

The impact of foot lesions in dairy cows on greenhouse gas emissions of milk production

The dairy sector is an important contributor to greenhouse gas (GHG) emissions. Foot lesions in dairy cows result in production losses and, therefore, might increase GHG emissions per kg milk. The objective of this study was to estimate the impact of foot lesions in dairy cows on GHG emissions. A dynamic stochastic simulation model was developed to estimate dynamics of digital dermatitis (DD), white line disease (WLD), and sole ulcer (SU), and associated production losses within one lactation. Production losses included were reduced milk production, prolonged calving interval (CI), and culling. Subsequently, a life cycle assessment was performed to estimate the impact of foot lesions on GHG emissions per ton of fat-and-protein-corrected milk (kg CO2e/t FPCM). GHG emissions increased on average by 14 (1.5%) kg CO2e/t FPCM per case of foot lesions (i.e. DD, WLD, and SU combined), ranging from 17 kg CO2e/t FPCM in parity 1, to 7 kg CO2e/t FPCM in parity 5. Emissions of GHGs increased on average by 4 (0.4%) kg CO2e/t FPCM per case of DD, by 39 (4.3%) kg CO2e/t FPCM per case of WLD, and by 33 (3.6%) kg CO2e/t FPCM per case of SU. A prolonged CI explained the majority of the increase in GHG emissions for cows with DD, whereas culling was most important for cows with WLD or SU. DD had the lowest impact on GHG emissions, but the highest prevalence, and, therefore, contributed most to the average impact of foot lesions. This study showed that preventing different types of foot lesions can reduce GHG emissions from the dairy sector. The increasing attention for global warming and possible policies to reduce GHG emissions from agriculture might give dairy farmers another incentive to prevent foot lesions. The impact of foot lesions on GHG emissions, however, can vary among dairy farms, because of differences in prevalence of foot lesions and associated production losses, and in farm management.

Correction: Effects of dry period length on production, cash flows and greenhouse gas emissions of the dairy herd: A dynamic stochastic simulation model.

[This corrects the article DOI: 10.1371/journal.pone.0187101.].

Estimating the economic impact of subclinical ketosis in dairy cattle using a dynamic stochastic simulation model

The objective of this study was to estimate the economic impact of subclinical ketosis (SCK) in dairy cows. This metabolic disorder occurs in the period around calving and is associated with an increased risk of other diseases. Therefore, SCK affects farm productivity and profitability. Estimating the economic impact of SCK may make farmers more aware of this problem, and can improve their decision-making regarding interventions to reduce SCK. We developed a dynamic stochastic simulation model that enables estimating the economic impact of SCK and related diseases (i.e. mastitis, metritis, displaced abomasum, lameness and clinical ketosis) occurring during the first 30 days after calving. This model, which was applied to a typical Dutch dairy herd, groups cows according to their parity (1 to 5+), and simulates the dynamics of SCK and related diseases, and milk production per cow during one lactation. The economic impact of SCK and related diseases resulted from a reduced milk production, discarded milk, treatment costs, costs from a prolonged calving interval and removal (culling or dying) of cows. The total costs of SCK were €130 per case per year, with a range between €39 and €348 (5 to 95 percentiles). The total costs of SCK per case per year, moreover, increased from €83 per year in parity 1 to €175 in parity 3. Most cows with SCK, however, had SCK only (61%), and costs were €58 per case per year. Total costs of SCK per case per year resulted for 36% from a prolonged calving interval, 24% from reduced milk production, 19% from treatment, 14% from discarded milk and 6% from removal. Results of the sensitivity analysis showed that the disease incidence, removal risk, relations of SCK with other diseases and prices of milk resulted in a high variation of costs of SCK. The costs of SCK, therefore, might differ per farm because of farm-specific circumstances. Improving data collection on the incidence of SCK and related diseases, and on consequences of diseases can further improve economic estimations.

Effects of dry period length on production, cash flows and greenhouse gas emissions of the dairy herd: A dynamic stochastic simulation model.

Shortening or omitting the dry period of dairy cows improves metabolic health in early lactation and reduces management transitions for dairy cows. The success of implementation of these strategies depends on their impact on milk yield and farm profitability. Insight in these impacts is valuable for informed decision-making by farmers. The aim of this study was to investigate how shortening or omitting the dry period of dairy cows affects production and cash flows at the herd level, and greenhouse gas emissions per unit of milk, using a dynamic stochastic simulation model. The effects of dry period length on milk yield and calving interval assumed in this model were derived from actual performance of commercial dairy cows over multiple lactations. The model simulated lactations, and calving and culling events of individual cows for herds of 100 cows. Herds were simulated for 5 years with a dry period of 56 (conventional), 28 or 0 days (n = 50 herds each). Partial cash flows were computed from revenues from sold milk, calves, and culled cows, and costs from feed and rearing youngstock. Greenhouse gas emissions were computed using a life cycle approach. A dry period of 28 days reduced milk production of the herd by 3.0% in years 2 through 5, compared with a dry period of 56 days. A dry period of 0 days reduced milk production by 3.5% in years 3 through 5, after a dip in milk production of 6.9% in year 2. On average, dry periods of 28 and 0 days reduced partial cash flows by €1,249 and €1,632 per herd per year, and increased greenhouse gas emissions by 0.7% and 0.5%, respectively. Considering the potential for enhancing cow welfare, these negative impacts of shortening or omitting the dry period seem justifiable, and they might even be offset by improved health.

The impact of subclinical ketosis in dairy cows on greenhouse gas emissions of milk production

The dairy sector is an important contributor to greenhouse gas (GHG) emissions. Subclinical ketosis (SCK), a metabolic disorder in dairy cows, increases the risk of other diseases. SCK can increase GHG emissions per kg of milk produced by reducing production efficiency of dairy herds. With an expected increase in milk consumption, and potential new policies to reduce GHG emissions from agriculture, producing efficiently and reducing GHG emissions becomes increasingly important. The objective of this study was to estimate the impact of SCK and related diseases (i.e. mastitis, metritis, displaced abomasum, lameness, and clinical ketosis) on GHG emissions of milk production. To this end, a dynamic stochastic simulation model was developed and combined with life cycle assessment (LCA). This model simulates the dynamics of SCK and related diseases, and the associated production losses (reduced milk production, discarded milk, a prolonged calving interval, and removal (culling or dying on the farm) per cow during one lactation. Subsequently, an LCA was performed to quantify the impact of SCK and related diseases on GHG emissions per ton fat-and-protein-corrected milk (kg CO2equivalents/t FPCM) from cradle to farm gate. The emissions of GHGs increased on average by 20.9 kg CO2e/t FPCM per case of SCK, with a range between 6.8 and 48.0 (5–95 percentiles). This increase in emissions was caused by a prolonged calving interval (31%), discarded milk (30%), reduced milk production (19%), and removal of cows (20%). Most cows had SCK only (61%); for these cows emissions increased by 7.9 kg CO2e/t FPCM, whereas emissions of cows that died on farm increased by 463.0 kg CO2e/t FPCM. Sensitivity analysis showed that the disease incidence, removal risk, relations of SCK with other diseases, and emission factors related to feed production, enteric fermentation, and manure resulted in a high variation of GHG emissions. This study is the first study that estimated the impact of SCK on GHG emissions and showed the relation between cow health and GHG emissions of milk production.

Stochastic bio—economic modeling of mastitis in Ethiopian dairy farms

Mastitis is an inflammation of the mammary gland that is considered to be one of the most frequent and costly diseases in the dairy industry. Also in Ethiopia, bovine mastitis is one of the most frequently encountered diseases of dairy cows. However, there was no study, so far, regarding the costs of clinical mastitis and only two studies were reported on costs of subclinical mastitis. Presenting an appropriate and complete study of the costs of mastitis will help farmers in making management decisions for mastitis control. The objective of this study was to estimate the economic effects of mastitis on Ethiopian market-oriented dairy farms. Market-oriented dairy farming is driven by making profits through selling milk in the market on a regular basis. A dynamic stochastic Monte-Carlo simulation model (bio-economic model) was developed taking into account both clinical and subclinical mastitis. Production losses, culling, veterinarian costs, treatment, discarded milk, and labour were the main cost factors which were modeled in this study. The annual incidence of clinical mastitis varied from 0 to 50% with a mean annual incidence of 21.6%, whereas the mean annual incidence of subclinical mastitis was 36.2% which varied between 0 and 75%. The total costs due to mastitis for a default farm size of 8 lactating cows were 6,709 ETB per year (838 ETB per cow per year). The costs varied considerably, with 5th and 95th percentiles of 109 ETB and 22,009 ETB, respectively. The factor most contributing to the total annual cost of mastitis was culling. On average a clinical case costs 3,631 ETB, varying from 0 to 12,401, whereas a sub clinical case costs 147 ETB, varying from 0 to 412. The sensitivity analysis showed that the total costs at the farm level were most sensitive for variation in the probability of occurrence of clinical mastitis and the probability of culling. This study helps farmers to raise awareness about the actual costs of mastitis and motivate them to timely treat and/or take preventive measures. As a results, the dairy industry will improve.

Performance of Input- and Output-based Payments for the Conservation of Mobile Species

A conceptual model is presented for the comparison of input-based payments (where conservation measures are rewarded) and output-based payments (where conservation outcomes are rewarded) in a spatially structured landscape. The landscape consists of a grid of land parcels, each managed by a land user. The objective of the conservation agency is the survival of an endangered mobile species in the landscape. The comparison of the two payment schemes is made with regard to cost-effectiveness (maximizing species survival for given total conservation costs) and budget-effectiveness (maximizing species survival for given conservation budget). The model is a grid-based dynamic stochastic ecological-economic simulation model. In the model analysis it is found that within the considered model parameter ranges the output-based payment outperforms the input-based payment, except for the cases of risk-averse land users and spatial spill-overs. The comparative advantage of the output-based payment increases with increasing viability and decreasing dispersal range of the species, and with decreasing spatial variation of the conservation costs. In the light of these results, output-based payments appear as a promising policy option even for mobile species where the local outcome (presence of the species in the land parcel) of a local conservation measure is uncertain.

Stochastic dynamic simulation modeling including multitrait genetics to estimate genetic, technical, and financial consequences of dairy farm reproduction and selection strategies.

The objective of this study was to develop a daily stochastic dynamic dairy simulation model that included multitrait genetics and to evaluate the effects of reduced genetic models and various reproduction and selection strategies on the genetic, technical, and financial performance of a dairy herd. The 12 correlated genetic traits included in the 2014 lifetime net merit (NM$) index were modeled for each animal. For each animal, a true breeding value (TBV) for each trait was calculated as the average of the sire's and dam's TBV, plus a fraction of the inbreeding and Mendelian sampling variability. Similarly, an environmental component for each trait was calculated and was partitioned into a permanent and a daily (temporary) effect. The combined TBV and environmental effects were converted into the phenotypic performance of each animal. Hence, genetics and phenotypic performances were associated. Estimated breeding values (EBV) were also simulated. Genetic trends for each trait for the service sire were based on expected trends in US Holsteins. Surplus heifers were culled based on various ranking criteria to maintain a herd size of 1,000 milking cows. In the first 8 scenarios, culling of surplus heifers was either random or based on the EBV of NM$. Four different genetic models, depending on the presence or absence of genetic trends or genetic and environmental correlations, or both, were evaluated to measure the effect of excluding multitrait genetics on animal performance. In the last 5 scenarios, the full genetic model was used and culling of surplus heifers was either random or based on the EBV of NM$ or the EBV of milk. Sexed semen use and reliability of the EBV were also varied. Each scenario was simulated for 15yr into the future. Results showed that genetic models without all 12 genetic trends and genetic and environmental correlations provided biased estimates of the genetic, technical, and financial performance of the dairy herd. Average TBV of NM$ of all cows in the herd was $263 greater in yr 15 in a scenario that combined sexed semen use in heifers and culling of surplus heifers with the lowest EBV of NM$, compared with a scenario that used only conventional semen and surplus heifers were culled randomly. The average TBV of daughter pregnancy rate of all cows in the herd was 1.25 percentage points greater in yr 15 in a scenario that combined using sexed semen in heifers as well as culling of surplus heifers ranked by EBV of NM$, compared with a scenario using conventional semen only as well as culling surplus heifers ranked by EBV of milk. In conclusion, the multitrait genetics model resulted in improved estimates of genetic, technical, and financial effects and appears useful to evaluate consequences of various reproduction and selection strategies within a dairy farm.

Stochastic Dynamic Simulation Model Applied to Public Lawyers Using Petri Nets

The aim of this article is to present a method of assignment of defence lawyers to causes, using tools Petri nets, decision trees and Monte Carlo method. It presents a simulation model of assignment applied to law activities, specifically to defender lawyers contracted by tender, using Petri Nets, Montecarlo and decision trees. The main difficulty of this assignment task is how to distribute equally the workload along the year between two kinds of lawyers: defender lawyers’ staff and external (tendered) defender lawyer. The system utilized for analyzing task assignment is stochastic, parallel, concurrent and dynamic.

Stochastic 3D modeling of Ostwald ripening at ultra-high volume fractions of the coarsening phase

We present a (dynamic) stochastic simulation model for 3D grain morphologies undergoing a grain coarsening phenomenon known as Ostwald ripening. For low volume fractions of the coarsening phase, the classical LSW theory predicts a power-law evolution of the mean particle size and convergence toward self-similarity of the particle size distribution; experiments suggest that this behavior holds also for high volume fractions. In the present work, we have analyzed 3D images that were recorded in situ over time in semisolid Al–Cu alloys manifesting ultra-high volume fractions of the coarsening (solid) phase. Using this information we developed a stochastic simulation model for the 3D morphology of the coarsening grains at arbitrary time steps. Our stochastic model is based on random Laguerre tessellations and is by definition self-similar—i.e. it depends only on the mean particle diameter, which in turn can be estimated at each point in time. For a given mean diameter, the stochastic model requires only three additional scalar parameters, which influence the distribution of particle sizes and their shapes. An evaluation shows that even with this minimal information the stochastic model yields an excellent representation of the statistical properties of the experimental data.

Optimal Integrated Strategies to Control an Invasive Weed

Although there have been numerous studies on the economics of weed control in agriculture, relatively few studies have focused on weeds in natural ecosystems. A stochastic dynamic simulation model and a stochastic dynamic programming model are developed to: (A) identify the combination of control options that is optimal for blackberry (Rubus anglocandicans) in Australian natural ecosystems, (B) assess whether an integrated control strategy is superior to chemical‐only strategies, (C) evaluate the net benefits of biological control (a rust and grazing by goats), and (D) determine how changes in model parameters affect the optimal control strategy. The results indicate that, while an integrated strategy combining chemical and nonchemical control methods may be optimal in certain circumstances, it is not necessarily superior to a chemical‐dominant strategy in all cases. The results show that grazing goats for control of blackberry can be optimal despite uncertainty about its effectiveness. Policy makers need to be aware of the trade‐offs between choosing more effective control options that may impose environmental and health risks versus less effective control strategies that are safer to the environment and human health.