Farm-scale greenhouse gas balances, hotspots and uncertainties in smallholder crop-livestock systems in Central Kenya

Climate-smart approaches have gained momentum in tropical, agricultural development. However, to date, few studies have examined whole-farm greenhouse gas (GHG) balances in smallholder crop-livestock systems. This study aimed to quantify GHG balances at farm-scale, identify GHG hotspots and assess mitigation options in coffee-dairy farms undergoing agricultural intensification in Central Kenya. In recent decades, decreasing farm size has forced the shift from extensive practices to zero-grazing systems and higher nitrogen (N) inputs. We hypothesised that different farm strategies and intensification levels determine the farm's GHG balance. A farm typology was constructed through principal component analysis (PCA) and hierarchical clustering from 125 farms surveyed. Four farm types were identified ranging relatively from small to large farms, low to high livestock intensities, and low to high N input rates. Whole-farm GHG balances were estimated using an adapted version of the Cool Farm Tool (CFT). Farms were found to be net sources of GHG, averaging from 4.5 t CO2 eq ha−1 yr−1 in less intensive farms to 12.5 t CO2 eq ha−1 yr−1 in high intensive farms. Within the farm GHG hotspots identified, methane (CH4) from enteric fermentation processes accounted for 26–39% of total farm GHG emissions; nitrous oxide (N2O) and CH4 from manure management systems (MMS) for 26–38%; soil background and fertilizer induced N2O emissions for 24–29%; off-farm production of feeds and agrochemicals for 10–22%; and crop residue management (CRM) for the remaining 1–3%. Within the mitigation practices assessed, zero-grazing stalls already lowered the livestock maintenance energy requirements, reducing enteric fermentation emissions. Stall-feeding, however, brings the necessity-opportunity to manage the manure and our results showed that MMS can be a determining factor in the GHG balance. Increasing the frequency of manure collection from stalls in favour of solid storage systems can reduce N2O emissions by up to 75%. Furthermore, dry manure storage reduced the CH4 emissions of liquid slurry systems by more than 70%. Further benefits in terms of carbon (C) sequestration were identified along farm types from manure and crop residues applications in soils (with averages of −1.3 to −2.3 t CO2 eq ha−1 yr−1) and biomass growth in agroforestry systems (−1.2 to −2 t CO2 eq ha−1 yr−1). Together, soils and woody biomass offset 25–36% of farm emissions. We conclude that reduced farm size and increased livestock density lead to higher emissions per unit area, though this increase is smoothed by larger negative fluxes in soils (by higher C inputs) and woody biomass (by higher tree densities) until a steady state is reached. Average yield-scaled emissions, or product carbon footprints (CFs), resulted in 1.08 kg CO2 eq kg coffee berry−1, 0.64 kg CO2 eq kg maize−1 and 1.05 kg CO2 eq kg milk−1 on average. CFs did not always differ between farm types and intensification levels, meaning that increases in productivity were not higher than increases in GHG fluxes from intensification. This may be due to: 1) increases in productivity are the result of more processes other than N inputs; and/or 2) emissions from N inputs are overestimated by EFs and GHG calculators. Smallholders may benefit in the near future from climate initiatives and further field characterisation, models calibration and monitoring are required to overcome critical levels of uncertainty and provide more accurate estimations of GHG balances at farm-scale.

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Main Authors: Ortiz Gonzalo, Daniel, Vaast, Philippe, Oelofse, Myles, de Neergaard, Andreas, Albrecht, Alain, Rosenstock, Todd S.
Format: article biblioteca
Language:eng
Subjects:F08 - Systèmes et modes de culture, L01 - Élevage - Considérations générales, P40 - Météorologie et climatologie, système agropastoral, petite exploitation agricole, exploitation agricole familiale, effet de serre, changement climatique, gaz à effet de serre, mesure (activité), intensification, pastoralisme, http://aims.fao.org/aos/agrovoc/c_16112, http://aims.fao.org/aos/agrovoc/c_7113, http://aims.fao.org/aos/agrovoc/c_2787, http://aims.fao.org/aos/agrovoc/c_15585, http://aims.fao.org/aos/agrovoc/c_1666, http://aims.fao.org/aos/agrovoc/c_34841, http://aims.fao.org/aos/agrovoc/c_4668, http://aims.fao.org/aos/agrovoc/c_33485, http://aims.fao.org/aos/agrovoc/c_16144, http://aims.fao.org/aos/agrovoc/c_4086,
Online Access:http://agritrop.cirad.fr/585505/
http://agritrop.cirad.fr/585505/1/1-s2.0-S016788091730244X-main.pdf
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id dig-cirad-fr-585505
record_format koha
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic F08 - Systèmes et modes de culture
L01 - Élevage - Considérations générales
P40 - Météorologie et climatologie
système agropastoral
petite exploitation agricole
exploitation agricole familiale
effet de serre
changement climatique
gaz à effet de serre
mesure (activité)
intensification
pastoralisme
http://aims.fao.org/aos/agrovoc/c_16112
http://aims.fao.org/aos/agrovoc/c_7113
http://aims.fao.org/aos/agrovoc/c_2787
http://aims.fao.org/aos/agrovoc/c_15585
http://aims.fao.org/aos/agrovoc/c_1666
http://aims.fao.org/aos/agrovoc/c_34841
http://aims.fao.org/aos/agrovoc/c_4668
http://aims.fao.org/aos/agrovoc/c_33485
http://aims.fao.org/aos/agrovoc/c_16144
http://aims.fao.org/aos/agrovoc/c_4086
F08 - Systèmes et modes de culture
L01 - Élevage - Considérations générales
P40 - Météorologie et climatologie
système agropastoral
petite exploitation agricole
exploitation agricole familiale
effet de serre
changement climatique
gaz à effet de serre
mesure (activité)
intensification
pastoralisme
http://aims.fao.org/aos/agrovoc/c_16112
http://aims.fao.org/aos/agrovoc/c_7113
http://aims.fao.org/aos/agrovoc/c_2787
http://aims.fao.org/aos/agrovoc/c_15585
http://aims.fao.org/aos/agrovoc/c_1666
http://aims.fao.org/aos/agrovoc/c_34841
http://aims.fao.org/aos/agrovoc/c_4668
http://aims.fao.org/aos/agrovoc/c_33485
http://aims.fao.org/aos/agrovoc/c_16144
http://aims.fao.org/aos/agrovoc/c_4086
spellingShingle F08 - Systèmes et modes de culture
L01 - Élevage - Considérations générales
P40 - Météorologie et climatologie
système agropastoral
petite exploitation agricole
exploitation agricole familiale
effet de serre
changement climatique
gaz à effet de serre
mesure (activité)
intensification
pastoralisme
http://aims.fao.org/aos/agrovoc/c_16112
http://aims.fao.org/aos/agrovoc/c_7113
http://aims.fao.org/aos/agrovoc/c_2787
http://aims.fao.org/aos/agrovoc/c_15585
http://aims.fao.org/aos/agrovoc/c_1666
http://aims.fao.org/aos/agrovoc/c_34841
http://aims.fao.org/aos/agrovoc/c_4668
http://aims.fao.org/aos/agrovoc/c_33485
http://aims.fao.org/aos/agrovoc/c_16144
http://aims.fao.org/aos/agrovoc/c_4086
F08 - Systèmes et modes de culture
L01 - Élevage - Considérations générales
P40 - Météorologie et climatologie
système agropastoral
petite exploitation agricole
exploitation agricole familiale
effet de serre
changement climatique
gaz à effet de serre
mesure (activité)
intensification
pastoralisme
http://aims.fao.org/aos/agrovoc/c_16112
http://aims.fao.org/aos/agrovoc/c_7113
http://aims.fao.org/aos/agrovoc/c_2787
http://aims.fao.org/aos/agrovoc/c_15585
http://aims.fao.org/aos/agrovoc/c_1666
http://aims.fao.org/aos/agrovoc/c_34841
http://aims.fao.org/aos/agrovoc/c_4668
http://aims.fao.org/aos/agrovoc/c_33485
http://aims.fao.org/aos/agrovoc/c_16144
http://aims.fao.org/aos/agrovoc/c_4086
Ortiz Gonzalo, Daniel
Vaast, Philippe
Oelofse, Myles
de Neergaard, Andreas
Albrecht, Alain
Rosenstock, Todd S.
Farm-scale greenhouse gas balances, hotspots and uncertainties in smallholder crop-livestock systems in Central Kenya
description Climate-smart approaches have gained momentum in tropical, agricultural development. However, to date, few studies have examined whole-farm greenhouse gas (GHG) balances in smallholder crop-livestock systems. This study aimed to quantify GHG balances at farm-scale, identify GHG hotspots and assess mitigation options in coffee-dairy farms undergoing agricultural intensification in Central Kenya. In recent decades, decreasing farm size has forced the shift from extensive practices to zero-grazing systems and higher nitrogen (N) inputs. We hypothesised that different farm strategies and intensification levels determine the farm's GHG balance. A farm typology was constructed through principal component analysis (PCA) and hierarchical clustering from 125 farms surveyed. Four farm types were identified ranging relatively from small to large farms, low to high livestock intensities, and low to high N input rates. Whole-farm GHG balances were estimated using an adapted version of the Cool Farm Tool (CFT). Farms were found to be net sources of GHG, averaging from 4.5 t CO2 eq ha−1 yr−1 in less intensive farms to 12.5 t CO2 eq ha−1 yr−1 in high intensive farms. Within the farm GHG hotspots identified, methane (CH4) from enteric fermentation processes accounted for 26–39% of total farm GHG emissions; nitrous oxide (N2O) and CH4 from manure management systems (MMS) for 26–38%; soil background and fertilizer induced N2O emissions for 24–29%; off-farm production of feeds and agrochemicals for 10–22%; and crop residue management (CRM) for the remaining 1–3%. Within the mitigation practices assessed, zero-grazing stalls already lowered the livestock maintenance energy requirements, reducing enteric fermentation emissions. Stall-feeding, however, brings the necessity-opportunity to manage the manure and our results showed that MMS can be a determining factor in the GHG balance. Increasing the frequency of manure collection from stalls in favour of solid storage systems can reduce N2O emissions by up to 75%. Furthermore, dry manure storage reduced the CH4 emissions of liquid slurry systems by more than 70%. Further benefits in terms of carbon (C) sequestration were identified along farm types from manure and crop residues applications in soils (with averages of −1.3 to −2.3 t CO2 eq ha−1 yr−1) and biomass growth in agroforestry systems (−1.2 to −2 t CO2 eq ha−1 yr−1). Together, soils and woody biomass offset 25–36% of farm emissions. We conclude that reduced farm size and increased livestock density lead to higher emissions per unit area, though this increase is smoothed by larger negative fluxes in soils (by higher C inputs) and woody biomass (by higher tree densities) until a steady state is reached. Average yield-scaled emissions, or product carbon footprints (CFs), resulted in 1.08 kg CO2 eq kg coffee berry−1, 0.64 kg CO2 eq kg maize−1 and 1.05 kg CO2 eq kg milk−1 on average. CFs did not always differ between farm types and intensification levels, meaning that increases in productivity were not higher than increases in GHG fluxes from intensification. This may be due to: 1) increases in productivity are the result of more processes other than N inputs; and/or 2) emissions from N inputs are overestimated by EFs and GHG calculators. Smallholders may benefit in the near future from climate initiatives and further field characterisation, models calibration and monitoring are required to overcome critical levels of uncertainty and provide more accurate estimations of GHG balances at farm-scale.
format article
topic_facet F08 - Systèmes et modes de culture
L01 - Élevage - Considérations générales
P40 - Météorologie et climatologie
système agropastoral
petite exploitation agricole
exploitation agricole familiale
effet de serre
changement climatique
gaz à effet de serre
mesure (activité)
intensification
pastoralisme
http://aims.fao.org/aos/agrovoc/c_16112
http://aims.fao.org/aos/agrovoc/c_7113
http://aims.fao.org/aos/agrovoc/c_2787
http://aims.fao.org/aos/agrovoc/c_15585
http://aims.fao.org/aos/agrovoc/c_1666
http://aims.fao.org/aos/agrovoc/c_34841
http://aims.fao.org/aos/agrovoc/c_4668
http://aims.fao.org/aos/agrovoc/c_33485
http://aims.fao.org/aos/agrovoc/c_16144
http://aims.fao.org/aos/agrovoc/c_4086
author Ortiz Gonzalo, Daniel
Vaast, Philippe
Oelofse, Myles
de Neergaard, Andreas
Albrecht, Alain
Rosenstock, Todd S.
author_facet Ortiz Gonzalo, Daniel
Vaast, Philippe
Oelofse, Myles
de Neergaard, Andreas
Albrecht, Alain
Rosenstock, Todd S.
author_sort Ortiz Gonzalo, Daniel
title Farm-scale greenhouse gas balances, hotspots and uncertainties in smallholder crop-livestock systems in Central Kenya
title_short Farm-scale greenhouse gas balances, hotspots and uncertainties in smallholder crop-livestock systems in Central Kenya
title_full Farm-scale greenhouse gas balances, hotspots and uncertainties in smallholder crop-livestock systems in Central Kenya
title_fullStr Farm-scale greenhouse gas balances, hotspots and uncertainties in smallholder crop-livestock systems in Central Kenya
title_full_unstemmed Farm-scale greenhouse gas balances, hotspots and uncertainties in smallholder crop-livestock systems in Central Kenya
title_sort farm-scale greenhouse gas balances, hotspots and uncertainties in smallholder crop-livestock systems in central kenya
url http://agritrop.cirad.fr/585505/
http://agritrop.cirad.fr/585505/1/1-s2.0-S016788091730244X-main.pdf
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spelling dig-cirad-fr-5855052024-01-29T00:31:40Z http://agritrop.cirad.fr/585505/ http://agritrop.cirad.fr/585505/ Farm-scale greenhouse gas balances, hotspots and uncertainties in smallholder crop-livestock systems in Central Kenya. Ortiz Gonzalo Daniel, Vaast Philippe, Oelofse Myles, de Neergaard Andreas, Albrecht Alain, Rosenstock Todd S.. 2017. Agriculture, Ecosystems and Environment, 248 : 58-70.https://doi.org/10.1016/j.agee.2017.06.002 <https://doi.org/10.1016/j.agee.2017.06.002> Farm-scale greenhouse gas balances, hotspots and uncertainties in smallholder crop-livestock systems in Central Kenya Ortiz Gonzalo, Daniel Vaast, Philippe Oelofse, Myles de Neergaard, Andreas Albrecht, Alain Rosenstock, Todd S. eng 2017 Agriculture, Ecosystems and Environment F08 - Systèmes et modes de culture L01 - Élevage - Considérations générales P40 - Météorologie et climatologie système agropastoral petite exploitation agricole exploitation agricole familiale effet de serre changement climatique gaz à effet de serre mesure (activité) intensification pastoralisme http://aims.fao.org/aos/agrovoc/c_16112 http://aims.fao.org/aos/agrovoc/c_7113 http://aims.fao.org/aos/agrovoc/c_2787 http://aims.fao.org/aos/agrovoc/c_15585 http://aims.fao.org/aos/agrovoc/c_1666 http://aims.fao.org/aos/agrovoc/c_34841 http://aims.fao.org/aos/agrovoc/c_4668 http://aims.fao.org/aos/agrovoc/c_33485 http://aims.fao.org/aos/agrovoc/c_16144 Kenya http://aims.fao.org/aos/agrovoc/c_4086 Climate-smart approaches have gained momentum in tropical, agricultural development. However, to date, few studies have examined whole-farm greenhouse gas (GHG) balances in smallholder crop-livestock systems. This study aimed to quantify GHG balances at farm-scale, identify GHG hotspots and assess mitigation options in coffee-dairy farms undergoing agricultural intensification in Central Kenya. In recent decades, decreasing farm size has forced the shift from extensive practices to zero-grazing systems and higher nitrogen (N) inputs. We hypothesised that different farm strategies and intensification levels determine the farm's GHG balance. A farm typology was constructed through principal component analysis (PCA) and hierarchical clustering from 125 farms surveyed. Four farm types were identified ranging relatively from small to large farms, low to high livestock intensities, and low to high N input rates. Whole-farm GHG balances were estimated using an adapted version of the Cool Farm Tool (CFT). Farms were found to be net sources of GHG, averaging from 4.5 t CO2 eq ha−1 yr−1 in less intensive farms to 12.5 t CO2 eq ha−1 yr−1 in high intensive farms. Within the farm GHG hotspots identified, methane (CH4) from enteric fermentation processes accounted for 26–39% of total farm GHG emissions; nitrous oxide (N2O) and CH4 from manure management systems (MMS) for 26–38%; soil background and fertilizer induced N2O emissions for 24–29%; off-farm production of feeds and agrochemicals for 10–22%; and crop residue management (CRM) for the remaining 1–3%. Within the mitigation practices assessed, zero-grazing stalls already lowered the livestock maintenance energy requirements, reducing enteric fermentation emissions. Stall-feeding, however, brings the necessity-opportunity to manage the manure and our results showed that MMS can be a determining factor in the GHG balance. Increasing the frequency of manure collection from stalls in favour of solid storage systems can reduce N2O emissions by up to 75%. Furthermore, dry manure storage reduced the CH4 emissions of liquid slurry systems by more than 70%. Further benefits in terms of carbon (C) sequestration were identified along farm types from manure and crop residues applications in soils (with averages of −1.3 to −2.3 t CO2 eq ha−1 yr−1) and biomass growth in agroforestry systems (−1.2 to −2 t CO2 eq ha−1 yr−1). Together, soils and woody biomass offset 25–36% of farm emissions. We conclude that reduced farm size and increased livestock density lead to higher emissions per unit area, though this increase is smoothed by larger negative fluxes in soils (by higher C inputs) and woody biomass (by higher tree densities) until a steady state is reached. Average yield-scaled emissions, or product carbon footprints (CFs), resulted in 1.08 kg CO2 eq kg coffee berry−1, 0.64 kg CO2 eq kg maize−1 and 1.05 kg CO2 eq kg milk−1 on average. CFs did not always differ between farm types and intensification levels, meaning that increases in productivity were not higher than increases in GHG fluxes from intensification. This may be due to: 1) increases in productivity are the result of more processes other than N inputs; and/or 2) emissions from N inputs are overestimated by EFs and GHG calculators. Smallholders may benefit in the near future from climate initiatives and further field characterisation, models calibration and monitoring are required to overcome critical levels of uncertainty and provide more accurate estimations of GHG balances at farm-scale. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/585505/1/1-s2.0-S016788091730244X-main.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1016/j.agee.2017.06.002 10.1016/j.agee.2017.06.002 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.agee.2017.06.002 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1016/j.agee.2017.06.002 info:eu-repo/grantAgreement/EC/////