Editing IPCC:AR6/WGIII/Chapter-7 (section)

=== Box 7.4 | Case Study: The Climate-smart Village Approach ===

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'''Summary'''

The climate-smart villages (CSV) approach aims to generate local knowledge, with the involvement of farmers, researchers, practitioners, and governments, on climate change adaptation and mitigation while improving productivity, food security, and farmers’ livelihoods ( [[#Aggarwal--2018|Aggarwal et al. 2018]] ). This knowledge feeds a global network that includes 36 climate-smart villages in South and South-East Asia, West and East Africa, and Latin America.

'''Background'''

It is expected that agricultural production systems across the world will change in response to climate change, posing significant challenges to the livelihoods and food security of millions of people ( [[#Kennedy--2014|Kennedy et al. 2014]] ). Maintaining agricultural growth while minimising climate shocks is crucial to building a resilient food production system and meeting sustainable development goals in vulnerable countries.

'''Case description'''

The CSV approach seeks an integrated vision so that sustainable rural development is the final goal for rural communities. At the same time, it fosters the understanding of climate change with the implementation of adaptation and mitigation actions, as much as possible. Rural communities and local stakeholders are the leaders of this process, where scientists facilitate their knowledge to be useful for the communities and learn at the same time about challenges but also the capacity those communities have built through time. The portfolio includes weather-smart activities, water-smart practices, seed/breed smart, carbon-/nutrient-smart practices, and institutional-/market-smart activities.

'''Interactions''' '''and limitations'''

The integration of technologies and services that are suitable for the local conditions resulted in many gains for food security and adaptation and for mitigation where appropriate. It was also shown that, in all regions, there is considerable yield advantage when a portfolio of technologies is used, rather than the isolated use of technologies ( [[#Govaerts--2005|Govaerts et al. 2005]] ; [[#Zougmoré--2014|Zougmoré et al. 2014]] ). Moreover, farmers are using research results to promote their products as climate-smart leading to increases in their income ( [[#Acosta-Alba--2019|Acosta-Alba et al. 2019]] ). However, climatic risk sites and socio-economic conditions together with a lack of resource availability are key issues constraining agriculture across all five regions.

'''Lessons'''

i. Understanding the priorities, context, challenges, capacity, and characteristics of the territory and the communities regarding climate, as well as the environmental and socio-economic dimensions, is the first step. Then, understanding climate vulnerability in their agricultural systems based on scientific data but also listening to their experience will set the pathway to identify climate-smart agriculture (CSA) options (practices and technologies) to reduce such vulnerability.

ii. Building capacity is also a critical element of the CSV approach, rural families learn about the practices and technologies in a neighbour’s house, and as part of the process, families commit to sharing their knowledge with other families, to start a scaling-out process within the communities. Understanding the relationship between climate and their crop is key, as well as the use of weather forecasts to plan their agricultural activities.

The assessment of the implementation of the CSA options should be done together with community leaders to understand changes in livelihoods and climate vulnerability. Also, knowledge appropriation by community leaders has led to farmer-to-farmer knowledge exchange within and outside the community (Ortega Fernandez and Martínez-Barón 2018).

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==== 7.4.3.7 Manure Management ====

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'''Activities, co-benefits, risks and implementation opportunities and barriers.''' Manure management measures aim to mitigate CH 4 and N 2 O emissions from manure storage and deposition. Mitigation of N 2 O considers both direct and indirect (i.e., conversion of ammonia and nitrate to N 2 O) sources. According to the SRCCL, measures may include (i) anaerobic digestion, (ii) applying nitrification or urease inhibitors to stored manure or urine patches, (iii) composting, (iv) improved storage and application practices, (v) grazing practices and (vi) alteration of livestock diets to reduce nitrogen excretion ( [[#Mbow--2019|Mbow et al. 2019]] ; [[#Jia--2019|Jia et al. 2019]] ). Implementation of manure management with other livestock and soil management measures can enhance system resilience, sustainability, food security and help prevent land degradation (Smith et al. 2014; [[#Mbow--2019|Mbow et al. 2019]] ; P. [[#Smith--2019|Smith et al. 2019]] a), while potentially benefiting the localised environment, for example, regarding water quality ( [[#Di--2016|Di and Cameron 2016]] ). Risks include increased N 2 O emission from the application of manure to poorly drained or wet soils, trade-offs between N 2 O and ammonia emissions and potential eco-toxicity associated with some measures.

'''Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC and SRCCL); mitigation potential, costs, and pathways.''' The AR5 reported manure measures to have high (&gt;10%) mitigation potential. The SRCCL estimated a technical global mitigation potential between 2020 and 2050 of 0.01–0.26 GtCO 2 -eq yr –1 , with the range depending on economic and sustainable capacity ( [[#Dickie--2014a|Dickie et al. 2014a]] ; [[#Herrero--2016|Herrero et al. 2016]] ) (SRCCL, Chapter 2). Conversion of estimates to native units is restricted as a mixture of GWP100 values was used in underlying studies. Measures considered were typically more suited to confined production systems ( [[#Jia--2019|Jia et al. 2019]] ; [[#Mbow--2019|Mbow et al. 2019]] ), while improved manure management is included within IAM emission pathways ( [[#Rogelj--2018b|Rogelj et al. 2018b]] ).

'''Developments since AR5 and IPCC Special Reports (SR1.5, SROCC and SRCCL).''' Research published since SRCCL broadly focuses on measures relevant to intensive or confined systems (e.g., ( [[#Hunt--2019|Hunt et al. 2019]] ; [[#Kavanagh--2019|Kavanagh et al. 2019]] ; Sokolov et al. 2020; [[#Im--2020|Im et al. 2020]] ; [[#Adghim--2020|Adghim et al. 2020]] ; [[#Mostafa--2020|Mostafa et al. 2020]] ), highlighting co-benefits and risks. For example, measures may enhance nutrient recovery, fertiliser value ( [[#Sefeedpari--2019|Sefeedpari et al. 2019]] ; [[#Ba--2020|Ba et al. 2020]] ; [[#Yao--2020|Yao et al. 2020]] ) and secondary processes such as biogas production ( [[#Shin--2019|Shin et al. 2019]] ). However, the potential antagonistic relationship between GHG and ammonia mitigation and need for appropriate management is emphasised ( [[#Aguirre-Villegas--2019|Aguirre-Villegas et al. 2019]] ; [[#Grossi--2019|Grossi et al. 2019]] ; [[#Kupper--2020|Kupper et al. 2020]] ; [[#Ba--2020|Ba et al. 2020]] ). In some circumstances, fugitive emissions may reduce the potential mitigation benefits of biogas production ( [[#Scheutz--2019|Scheutz and Fredenslund 2019]] ; [[#Bakkaloglu--2021|Bakkaloglu et al. 2021]] ), while high implementation cost is identified as an adoption barrier, notably of anaerobic digestion ( [[#Liu--2018|Liu and Liu 2018]] ; [[#Niles--2019|Niles and Wiltshire 2019]] ; [[#Ndambi--2019|Ndambi et al. 2019]] ; [[#Ackrill--2020|Ackrill and Abdo 2020]] ; [[#Adghim--2020|Adghim et al. 2020]] ). Nitrification inhibitors have been found to be effective at reducing N 2 O emissions from pasture deposited urine (López-Aizpún et al. 2020), although the use of nitrification inhibitors is restricted in some jurisdictions due to concerns regarding residues in food products ( [[#Di--2016|Di and Cameron 2016]] ; [[#Eckard--2020|Eckard and Clark 2020]] ) while ''limited evidence'' suggests eco-toxicity risk under certain circumstances ( [[#Kösler--2019|Kösler et al. 2019]] ). Some forage crops may naturally contain inhibitory substances ( [[#Simon--2019|Simon et al. 2019]] , 2020; [[#de%20Klein--2020|de Klein et al. 2020]] ), though this warrants further research ( [[#Podolyan--2020|Podolyan et al. 2020]] ; [[#Gardiner--2020|Gardiner et al. 2020]] ).

Country specific studies provide insight into regionally applicable measures, with emphasis on small-scale anaerobic digestion (e.g., dome digesters), solid manure coverage and daily manure spreading in Asia and the Pacific, and Africa ( [[#Hasegawa--2012|Hasegawa and Matsuoka 2012]] ; [[#Hoa--2014|Hoa et al. 2014]] ; [[#Jilani--2015|Jilani et al. 2015]] ; [[#Hasegawa--2016|Hasegawa et al. 2016]] ; [[#Pradhan--2017|Pradhan et al. 2017]] ; [[#Ericksen--2018|Ericksen and Crane 2018]] ; [[#Pradhan--2019|Pradhan et al. 2019]] ; [[#Kiggundu--2019|Kiggundu et al. 2019]] ; [[#Dioha--2020|Dioha and Kumar 2020]] ). Tank/lagoon covers, large-scale anaerobic digestion, improved application timing, nitrogen inhibitor application to urine patches, soil-liquid separation, reduced livestock nitrogen intake, trailing shoe, band or injection slurry spreading and acidification are emphasised in Developed Countries ( [[#Kaparaju--2011|Kaparaju and Rintala 2011]] ; [[#Eory--2015|Eory et al. 2015]] ; Pape et al. 2016; [[#Jayasundara--2016|Jayasundara et al. 2016]] ; [[#Pellerin--2017|Pellerin et al. 2017]] ; [[#Liu--2018|Liu and Liu 2018]] ; [[#Lanigan--2018|Lanigan et al. 2018]] ; [[#Carroll--2019|Carroll and Daigneault 2019]] ; [[#Eckard--2020|Eckard and Clark 2020]] ). Using IPCC AR4 GWP100 values for CH 4 and N 2 O, a recent assessment finds 69% (63.4 MtCO 2 -eq yr –1 ) of economic potential (up to USD100 tCO 2 -eq –1 ) between 2020–2050, to be in Developed Countries ( [[#Roe--2021|Roe et al. 2021]] ).

'''Critical assessment and conclusion.''' There is ''medium confidence'' that manure management measures have a global technical potential of 0.3 (0.1–0.5) GtCO 2 -eq yr –1 , (using a range of IPCC GWP100 values for CH 4 and N 2 O), of which 0.1 (0.09–0.1) GtCO 2 -eq yr –1 is available at up to USD100 tCO 2 -eq –1 (Figure 7.11). As with other non-CO 2 GHG mitigation estimates, values may slightly differ depending upon which IPCC GWP100 values were used. There is ''robust evidence'' and ''high agreement'' that there are measures that can be applied in all regions, but greatest mitigation potential is estimated in Developed Countries in more intensive and confined production systems.

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