Limitations of using simple indicators for evaluating agricultural emission reductions at farm level — evidence from Kenyan smallholder dairy production

National-scale carbon footprints of livestock production are commonly computed from a set of production system characteristics that serve as inputs for greenhouse gas (GHG) emission models. We evaluated the feasibility of using such equations at a finer scale to derive a simple farm-scale indicator...

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Main Authors: Luedeling, Eike, Whitney, Cory W., Wilkes, Andreas, Aynekulu, Ermias, Rosenstock, Todd S.
Format: Journal Article
Language:Inglés
Published: OAE Publishing Inc. 2022
Subjects:
Online Access:https://hdl.handle.net/10568/127070
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author Luedeling, Eike
Whitney, Cory W.
Wilkes, Andreas
Aynekulu, Ermias
Rosenstock, Todd S.
author_browse Aynekulu, Ermias
Luedeling, Eike
Rosenstock, Todd S.
Whitney, Cory W.
Wilkes, Andreas
author_facet Luedeling, Eike
Whitney, Cory W.
Wilkes, Andreas
Aynekulu, Ermias
Rosenstock, Todd S.
author_sort Luedeling, Eike
collection Repository of Agricultural Research Outputs (CGSpace)
description National-scale carbon footprints of livestock production are commonly computed from a set of production system characteristics that serve as inputs for greenhouse gas (GHG) emission models. We evaluated the feasibility of using such equations at a finer scale to derive a simple farm-scale indicator of emission intensity (milk yield per head). Using probabilistic simulations, we quantified the impact of input variable uncertainty on emission estimates for smallholder dairy farms in Kenya. We simulated emissions for farm-scale scenarios generated from a survey of 414 households and published or expert-estimated uncertainty bounds. We simulated the impacts of five interventions: changing breeds, retiring unproductive males, keeping fewer replacement males, feeding forage supplements, and balancing animal diets. Impacts were assessed against a true counterfactual and against a more realistic scenario affected by random effects. We estimated errors incurred in classifying farms into adopters and non-adopters of the innovations based on changes in milk yield per animal. Given the current uncertainty, such classification would either miss a large percentage of adopters or misclassify many non-adopters as adopters. As a critical uncertainty, we identified the milk yield of dairy cows. Added precision on this metric reduced but did not eliminate classification errors. We remain cautiously optimistic about using milk yield per head to proxy emission intensity, but its effective use will require further reduction of critical uncertainties. Replacing generic recommendations of parameter uncertainties with context-specific error estimates might lead to a more efficient quantification of the carbon footprint of milk production on smallholder farms.
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spelling CGSpace1270702025-12-08T09:54:28Z Limitations of using simple indicators for evaluating agricultural emission reductions at farm level — evidence from Kenyan smallholder dairy production Luedeling, Eike Whitney, Cory W. Wilkes, Andreas Aynekulu, Ermias Rosenstock, Todd S. livestock monitoring and evaluation mitigation ganado seguimiento y evaluación mitigación National-scale carbon footprints of livestock production are commonly computed from a set of production system characteristics that serve as inputs for greenhouse gas (GHG) emission models. We evaluated the feasibility of using such equations at a finer scale to derive a simple farm-scale indicator of emission intensity (milk yield per head). Using probabilistic simulations, we quantified the impact of input variable uncertainty on emission estimates for smallholder dairy farms in Kenya. We simulated emissions for farm-scale scenarios generated from a survey of 414 households and published or expert-estimated uncertainty bounds. We simulated the impacts of five interventions: changing breeds, retiring unproductive males, keeping fewer replacement males, feeding forage supplements, and balancing animal diets. Impacts were assessed against a true counterfactual and against a more realistic scenario affected by random effects. We estimated errors incurred in classifying farms into adopters and non-adopters of the innovations based on changes in milk yield per animal. Given the current uncertainty, such classification would either miss a large percentage of adopters or misclassify many non-adopters as adopters. As a critical uncertainty, we identified the milk yield of dairy cows. Added precision on this metric reduced but did not eliminate classification errors. We remain cautiously optimistic about using milk yield per head to proxy emission intensity, but its effective use will require further reduction of critical uncertainties. Replacing generic recommendations of parameter uncertainties with context-specific error estimates might lead to a more efficient quantification of the carbon footprint of milk production on smallholder farms. 2022-09-08 2023-01-13T15:20:39Z 2023-01-13T15:20:39Z Journal Article https://hdl.handle.net/10568/127070 en Open Access application/pdf OAE Publishing Inc. Luedeling, E.; Whitney, C.; Wilkes, A.; Aynekulu, E.; Rosenstock, T.S. (2022) Limitations of using simple indicators for evaluating agricultural emission reductions at farm level — evidence from Kenyan smallholder dairy production. Carbon Footprints 1(9) 21 p. ISSN: 2831-932X
spellingShingle livestock
monitoring and evaluation
mitigation
ganado
seguimiento y evaluación
mitigación
Luedeling, Eike
Whitney, Cory W.
Wilkes, Andreas
Aynekulu, Ermias
Rosenstock, Todd S.
Limitations of using simple indicators for evaluating agricultural emission reductions at farm level — evidence from Kenyan smallholder dairy production
title Limitations of using simple indicators for evaluating agricultural emission reductions at farm level — evidence from Kenyan smallholder dairy production
title_full Limitations of using simple indicators for evaluating agricultural emission reductions at farm level — evidence from Kenyan smallholder dairy production
title_fullStr Limitations of using simple indicators for evaluating agricultural emission reductions at farm level — evidence from Kenyan smallholder dairy production
title_full_unstemmed Limitations of using simple indicators for evaluating agricultural emission reductions at farm level — evidence from Kenyan smallholder dairy production
title_short Limitations of using simple indicators for evaluating agricultural emission reductions at farm level — evidence from Kenyan smallholder dairy production
title_sort limitations of using simple indicators for evaluating agricultural emission reductions at farm level evidence from kenyan smallholder dairy production
topic livestock
monitoring and evaluation
mitigation
ganado
seguimiento y evaluación
mitigación
url https://hdl.handle.net/10568/127070
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