Improve Animal Management
System: Dairy Cattle
Mainly applicable for: Herds with sub-optimal animal health and reproduction, and/or short life span
Description
Improving animal health and productive life span by improving animal nutrition and housing, health management (incl. veterinary services), reproductive management, and genetic selection for traits that promote longevity (e.g. health, fertility). The improvements in cow and young stock management will reduce involuntary culling, mortality and morbidity rates, and reduce age at first calving. This will extend the productive life of cows, improve lifetime productivity, and reduce the number of replacements heifers needed. Effects on greenhouse gas emissions have been reported for various animal health disorders, including infectious diseases (such as BVD, Paratuberculosis, and IBR), metabolic disorders (such as subclinical ketosis), and production diseases (such as lameness, mastitis and claw diseases).
Mechanism of effect
Improving animal health and extending productive life span reduce greenhouse gas emissions by minimizing milk losses and lowering the number of replacements animals. A healthier herd shows higher milk yields, better fertility, less mortality, better growth of heifers, and less milk is discarded (e.g., due to mastitis); leading to lower GHG emissions per kg of milk and meat produced. Since replacement stock contributes significantly to the whole-herd emissions, fewer replacements and earlier calving further cut emissions. Disease-related issues often trigger involuntary culling or death, so better health and fertility enhance productive lifespan and reduce the need for additional replacements. Older cows also tend to produce more milk per unit of feed consumed, which further lowers emissions. However, it should be noted that from a broader food system perspective, increasing life span may reduce beef output from dairy systems, potentially shifting emissions to specialized beef production (Vellinga and De Vries, 2018).
Reference situation
Average farm
Legend
| ● – Small effect (<5%) | o – No effect |
| ●● – Medium effect (5-20%) | ● – Unfavourable effect |
| ●●● – Large effect (>20%) | ● – ● – Variable effect (depending on farm characteristics or way/level of implementation) |
Effect on total greenhouse gas (GHG) emissions
| Mean effect and range in kg CO2-equivalents | per kg product | per farm | |||
| Mean | Min-Max | Mean | Min-Max | Level of evidence | |
| Reduce animal health disorders | ● | ● – ●● | ● | ●–●● | Medium |
| Reduce age at first calving | ● | ● – ●● | ● | ●–●● | Medium |
| Increase longevity (life span) | ●● | ● – ●● | ●● | ●–●● | Medium |
Effect per emission source
| Mean effect on emission from | Manure | Animal | Feed and forage production | Barn & farm inputs | |||
| CH4 | N2O | CH4 | CO2 | N2O | LUC | CO2 | |
| Reduce animal health disorders | ● | ● | ●● | ● | ● | ● | ● |
| Reduce age at first calving | ● | ● | ●● | ● | ● | ● | ● |
| Increase longevity (life span) | ● | ● | ●● | ● | ● | ● | ● |
*risk of an adverse effect (see ’cause of variable or unfavourable effect’)
Explanation of variable effect
Reduce animal health disorders
The effect depends on the number of affected animals in the reference and new situation, the type and impact of the disease, such as changes in productivity, mortality, replacement rate and milk loss. Also, the effect may depend on the way the improvements are realized. For example, if realized through changes in the feed ration or housing system, the effect depends on the carbon footprint of the feed ration or type of housing in the old and new situation.
Reduce age at first calving
The effect depends on the extend of reduction in age of calving, and the way it is realized. For example, if realized through changes in the feed ration, the effect depends on the carbon footprint of the feed ration in the old and new situation. Most other interventions (e.g. calf care (incl. colostrum), hygiene, vaccinations, heat detection) will solely have beneficial effects.
Increase longevity (life span)
The effect depends on extend of improvement in life span of animals, reduction in the number of young stock, and the way improvement is realized. For example, if realized through changes in the feed ration, the effect depends on the carbon footprint of the feed ration in the old and new situation. Most other interventions, such as improved animal health care or genetic selection for increased longevity, will solely have beneficial effects.
| Literature references | Reduce animal health disorders |
|---|---|
| Capper and Williams, 2023 | Investing in health to improve the sustainability of cattle production in the United Kingdom: A narrative review |
| Mostert, 2014 | The impact of diseases in dairy cows on greenhouse gas emissions and economic performance (dissertation) |
| Mostert et al., 2019 | Estimating the impact of clinical mastitis in dairy cows on greenhouse gas emissions using a dynamic stochastic simulation model: a case study |
| Chen et al., 2016 | The effect of lameness on the environmental performance of milk production by rotational grazing |
| Özkan Gülzari et al., 2017 | Impact of subclinical mastitis on greenhouse gas emissions intensity and profitability of dairy cows in Norway |
| Reduce age at first calving | |
|---|---|
| Dall-Orsoletta et al., 2019 | A quantitative description of the effect of breed, first calving age and feeding strategy on dairy systems enteric methane emission |
| Sorley et al., 2024 | Factors influencing the carbon footprint of milk production on dairy farms with different feeding strategies in western Europe |
| Dall-Orsoletta et al., 2019 | A quantitative description of the effect of breed, first calving age and feeding strategy on dairy systems enteric methane emissions |
| Sommerseth et al., 2024 | How increased heifer growth rate and reduced dairy cow replacement rate can improve farm economy and reduce greenhouse gas emissions – a win to win situation? |
| Knapp et al., 2014 | Invited review: Enteric methane in dairy cattle production: Quantifying the opportunities and impact of reducing emissions |
| Increase longevity (life span) | |
|---|---|
| Vellinga and De Vries, 2018 | Effectiveness of climate change mitigation options considering the amount of meat produced in dairy systems |
| Kok et al., 2017 | Effects of dry period length on production, cash flows and greenhouse gas emissions of the dairy herd: A dynamic stochastic simulation model |
| Van Middelaar et al., 2014 | Methods to determine the relative value of genetic traits in dairy cows to reduce greenhouse gas emissions along the chain |
| Grandl et al., 2019 | Impact of longevity on greenhouse gas emissions and profitability of individual dairy cows analysed with different system boundaries |
| Sommerseth et al., 2024 | How increased heifer growth rate and reduced dairy cow replacement rate can improve farm economy and reduce greenhouse gas emissions – a win to win situation? |
| Dall-Orsoletta et al., 2019 | A quantitative description of the effect of breed, first calving age and feeding strategy on dairy systems enteric methane emission |
| Han et al. 2024 | 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 |
| Vellinga et al., 2009 | Implementation of GHG mitigation on intensive dairy farms: Farmers’ preferences and variation in cost effectiveness |