Identifying farm-level hotspots to target greenhouse gas measurements in smallholder crop-livestock systems. [P27]

In sub-Saharan Africa, data quantifying greenhouse gas (GHG) emissions and removals from smallholder's production systems are available for only a limited set of farm activities and agroecosystems. Due to this scarcity of data, IPCC Tier 1 emission factors are typically used to calculate farm emissions despite the fact that they are based on external estimates. To overcome the degree of uncertainty when using generalized emission factors for heterogeneous and multi-functional sub-Saharan smallholder crop-livestock systems, we wished to test if we could predict hotspots to guide GHG measurements. We believe that by identifying hotspots we achieve a key step in order to: 1) Guide measurements to save efforts and resources; 2) Determine the accuracy or inaccuracy of current estimations; 3) Reduce the risk of increasing errors thorough the running of models or scaling fluxes to larger spatial scales; 4) Target factors with higher contribution to the GHG balances; 5) Identify options with major potential of mitigation. We developed guidelines to identify hotspots based on systems deconstruction from what is already known about nutrient stocks and GHG fluxes. We hypothesized that we can derive hotspots and target our measurements toward the systems' nutrient pools changes. The method is tested with data from the highlands of Kenya, in Murang'a and Nyeri districts. This involved calculation of farm-level GHG balances and an assessment of the major fluxes. Then a sensitivity analysis provided the quantification of uncertainty that informs about the spatial and temporal measuring requirements to guide sampling. Finally we discussed barriers to mitigation practices based on a full system analysis that considers realistic biophysical and socioeconomic constraints. (Texte intégral)

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Main Authors: Ortiz Gonzalo, Daniel, Rosenstock, Todd S., Vaast, Philippe, Oelofse, Myles, de Neergaard, Andreas, Albrecht, Alain
Format: conference_item biblioteca
Language:eng
Published: CIRAD
Subjects:P01 - Conservation de la nature et ressources foncières, L01 - Élevage - Considérations générales, F01 - Culture des plantes, U30 - Méthodes de recherche,
Online Access:http://agritrop.cirad.fr/576494/
http://agritrop.cirad.fr/576494/1/P43%20de%20L1%20Regional%20Dimensions%281%29.pdf
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spelling dig-cirad-fr-5764942022-02-15T07:32:07Z http://agritrop.cirad.fr/576494/ http://agritrop.cirad.fr/576494/ Identifying farm-level hotspots to target greenhouse gas measurements in smallholder crop-livestock systems. [P27]. Ortiz Gonzalo Daniel, Rosenstock Todd S., Vaast Philippe, Oelofse Myles, de Neergaard Andreas, Albrecht Alain. 2015. In : Building tomorrow’s research agenda and bridging the science-policy gap. CIRAD, INRA, IRD, Agropolis International, Wageningen UR, CGIAR, UCDAVIS, FAO, Agreenium, GFAR. Montpellier : CIRAD, Résumé, 108. Climate-Smart Agriculture 2015 : Global Science Conference. 3, Montpellier, France, 16 Mars 2015/18 Mars 2015.http://csa2015.cirad.fr/var/csa2015/storage/fckeditor/file/L1%20Regional%20Dimensions(1).pdf <http://csa2015.cirad.fr/var/csa2015/storage/fckeditor/file/L1%20Regional%20Dimensions(1).pdf> Researchers Identifying farm-level hotspots to target greenhouse gas measurements in smallholder crop-livestock systems. [P27] Ortiz Gonzalo, Daniel Rosenstock, Todd S. Vaast, Philippe Oelofse, Myles de Neergaard, Andreas Albrecht, Alain eng 2015 CIRAD Building tomorrow’s research agenda and bridging the science-policy gap P01 - Conservation de la nature et ressources foncières L01 - Élevage - Considérations générales F01 - Culture des plantes U30 - Méthodes de recherche In sub-Saharan Africa, data quantifying greenhouse gas (GHG) emissions and removals from smallholder's production systems are available for only a limited set of farm activities and agroecosystems. Due to this scarcity of data, IPCC Tier 1 emission factors are typically used to calculate farm emissions despite the fact that they are based on external estimates. To overcome the degree of uncertainty when using generalized emission factors for heterogeneous and multi-functional sub-Saharan smallholder crop-livestock systems, we wished to test if we could predict hotspots to guide GHG measurements. We believe that by identifying hotspots we achieve a key step in order to: 1) Guide measurements to save efforts and resources; 2) Determine the accuracy or inaccuracy of current estimations; 3) Reduce the risk of increasing errors thorough the running of models or scaling fluxes to larger spatial scales; 4) Target factors with higher contribution to the GHG balances; 5) Identify options with major potential of mitigation. We developed guidelines to identify hotspots based on systems deconstruction from what is already known about nutrient stocks and GHG fluxes. We hypothesized that we can derive hotspots and target our measurements toward the systems' nutrient pools changes. The method is tested with data from the highlands of Kenya, in Murang'a and Nyeri districts. This involved calculation of farm-level GHG balances and an assessment of the major fluxes. Then a sensitivity analysis provided the quantification of uncertainty that informs about the spatial and temporal measuring requirements to guide sampling. Finally we discussed barriers to mitigation practices based on a full system analysis that considers realistic biophysical and socioeconomic constraints. (Texte intégral) conference_item info:eu-repo/semantics/conferenceObject Conference info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/576494/1/P43%20de%20L1%20Regional%20Dimensions%281%29.pdf text Cirad license info:eu-repo/semantics/openAccess https://agritrop.cirad.fr/mention_legale.html http://csa2015.cirad.fr/var/csa2015/storage/fckeditor/file/L1%20Regional%20Dimensions(1).pdf info:eu-repo/semantics/altIdentifier/purl/http://csa2015.cirad.fr/var/csa2015/storage/fckeditor/file/L1%20Regional%20Dimensions(1).pdf
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 P01 - Conservation de la nature et ressources foncières
L01 - Élevage - Considérations générales
F01 - Culture des plantes
U30 - Méthodes de recherche
P01 - Conservation de la nature et ressources foncières
L01 - Élevage - Considérations générales
F01 - Culture des plantes
U30 - Méthodes de recherche
spellingShingle P01 - Conservation de la nature et ressources foncières
L01 - Élevage - Considérations générales
F01 - Culture des plantes
U30 - Méthodes de recherche
P01 - Conservation de la nature et ressources foncières
L01 - Élevage - Considérations générales
F01 - Culture des plantes
U30 - Méthodes de recherche
Ortiz Gonzalo, Daniel
Rosenstock, Todd S.
Vaast, Philippe
Oelofse, Myles
de Neergaard, Andreas
Albrecht, Alain
Identifying farm-level hotspots to target greenhouse gas measurements in smallholder crop-livestock systems. [P27]
description In sub-Saharan Africa, data quantifying greenhouse gas (GHG) emissions and removals from smallholder's production systems are available for only a limited set of farm activities and agroecosystems. Due to this scarcity of data, IPCC Tier 1 emission factors are typically used to calculate farm emissions despite the fact that they are based on external estimates. To overcome the degree of uncertainty when using generalized emission factors for heterogeneous and multi-functional sub-Saharan smallholder crop-livestock systems, we wished to test if we could predict hotspots to guide GHG measurements. We believe that by identifying hotspots we achieve a key step in order to: 1) Guide measurements to save efforts and resources; 2) Determine the accuracy or inaccuracy of current estimations; 3) Reduce the risk of increasing errors thorough the running of models or scaling fluxes to larger spatial scales; 4) Target factors with higher contribution to the GHG balances; 5) Identify options with major potential of mitigation. We developed guidelines to identify hotspots based on systems deconstruction from what is already known about nutrient stocks and GHG fluxes. We hypothesized that we can derive hotspots and target our measurements toward the systems' nutrient pools changes. The method is tested with data from the highlands of Kenya, in Murang'a and Nyeri districts. This involved calculation of farm-level GHG balances and an assessment of the major fluxes. Then a sensitivity analysis provided the quantification of uncertainty that informs about the spatial and temporal measuring requirements to guide sampling. Finally we discussed barriers to mitigation practices based on a full system analysis that considers realistic biophysical and socioeconomic constraints. (Texte intégral)
format conference_item
topic_facet P01 - Conservation de la nature et ressources foncières
L01 - Élevage - Considérations générales
F01 - Culture des plantes
U30 - Méthodes de recherche
author Ortiz Gonzalo, Daniel
Rosenstock, Todd S.
Vaast, Philippe
Oelofse, Myles
de Neergaard, Andreas
Albrecht, Alain
author_facet Ortiz Gonzalo, Daniel
Rosenstock, Todd S.
Vaast, Philippe
Oelofse, Myles
de Neergaard, Andreas
Albrecht, Alain
author_sort Ortiz Gonzalo, Daniel
title Identifying farm-level hotspots to target greenhouse gas measurements in smallholder crop-livestock systems. [P27]
title_short Identifying farm-level hotspots to target greenhouse gas measurements in smallholder crop-livestock systems. [P27]
title_full Identifying farm-level hotspots to target greenhouse gas measurements in smallholder crop-livestock systems. [P27]
title_fullStr Identifying farm-level hotspots to target greenhouse gas measurements in smallholder crop-livestock systems. [P27]
title_full_unstemmed Identifying farm-level hotspots to target greenhouse gas measurements in smallholder crop-livestock systems. [P27]
title_sort identifying farm-level hotspots to target greenhouse gas measurements in smallholder crop-livestock systems. [p27]
publisher CIRAD
url http://agritrop.cirad.fr/576494/
http://agritrop.cirad.fr/576494/1/P43%20de%20L1%20Regional%20Dimensions%281%29.pdf
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