A Move towards Developing Usable Climate Change Adaptation and Mitigation Services for the Agricultural Sector
Abstract
:1. Introduction
2. Methods
3. How to Develop Efficient and Usable Climate Services
3.1. Coproduction
3.2. Tailored/Context-Specific
3.3. Innovation
3.4. Demand-Driven
3.5. Timeliness
3.6. Applicability
3.7. Formatting
3.8. User Experience
3.9. Accessibility
3.10. Location-Specific
4. Climate Services Available for Farmers
4.1. Climate Services for Adaptation
4.2. Climate Services for Mitigation
4.3. Integrated Climate Services for Adaptation and Mitigation
Hypothetical Climate Service for Dryland Maize Production
5. Barriers to the Adoption of New Climate Services
- (a)
- Technological barriers: Introducing a climate service to users can be challenging with respect to technology. A new service will normally be qualitatively compared with existing tools, and farming communities need to see considerable advancement in order to change or incorporate the new technology into their decision-making process [13].
- (b)
- Financial barriers: Sometimes it is not feasible to conduct proper market research and follow fully cooperative principles because of limited financial resources [13]. There must be a cut-off in terms of how far some of the initial processes can go to ensure enough financial resources for the entire climate services project cycle. Many researchers are adamant that more financial resources are needed to move climate services from the category of being useful to being usable [13]. From the user’s perspective, a new product needs to provide value for the money or time spent using it. Policies and frameworks need to be developed to enhance climate services that are subsidized for resource-poor farmers in an effort to ensure productivity at the small-scale level. Ensuring that the services provided are cost-effective is an ingredient that will increase the likelihood of adoption and higher market share. Profits in primary agriculture are minimal and thus costing services for farmers need to be approached with care.
- (c)
- Organizational barriers: It is very important that a proposed climate service be aligned with how operations work in order to avoid rejection. This requirement might necessitate a detailed study by the developers and intermediaries to understand the industry so that the climate service can be adopted immediately. The decision-making process of farmers and the agricultural community is complicated and involves input from multiple factors. A clear value addition is required for the use of a new resource to have a chance in the decision-making process. A number of capacity-development sessions with the users are required to break this barrier as well as to establish a client support system after evaluating a climate service. Organizational boundaries can also be bridged through the development of policies at national and local levels that enhance issues like cross-agency collaborations on matters that are central to the functioning of a society [66]. Policies are also integral to ensuring the penetration of services for beneficiaries by establishing enablers along the value chain.
- (d)
- Psychological barriers: The conditioning of users of climate services varies as a function of their history, status, beliefs, religion, and financial situations. The adoption of a new service or product may be subjected to emotions of fear, anger, and disgust because of the potential of the new service to alter the routines of the end users [64]. In some cases, a fear that innovation will adversely affect the livelihoods of people can result in a lack of trust in the service. The attitudes of gatekeepers in some of the farming communities can play a role in the success or failure of a new service [63].
- (e)
- Functional barriers: Users who are not eager to change their way of thinking and thus introduce a new climate service that functions unfamiliarly can create challenges for developers. It is important that the functionality of the new service be aligned with their current capabilities and technologies to lower the barrier to adoption [64]. Something new is normally perceived as complex. Factors such as farmers’ profiles affect the adoption rate, and issues such as age and literacy can play a huge role [63]. This barrier can be lowered by dedicated client training and aftercare support.
- (f)
- Time barriers: The development of climate services is highly time-consuming, and at times it is not easy to fully explore all the possibilities [13]. It takes a lot of time to convince users to utilize a service. In some cases, users are not prepared to explore innovative solutions because of the initial learning curve.
6. New Climate Services Development Stages
- (a)
- Awareness stage: It is important to ensure that the climate service introduced into the market is visible at important information points. A summary of the product can be published in popular agricultural magazines or newsletters to increase its visibility. In most countries, there are several important agricultural shows during the year where the services of the new product can be presented. Strongly marketing the new service is paramount to market penetration and increases the chances of its being used. In the awareness stage, introducing capacity-building programs for farmers and other major stakeholders is key to improving adoption rates. Capacity-building initiatives need to be incorporated throughout the lifecycle of the climate service.
- (b)
- Research and discovery stage: End users need to have confidence in the climate services being offered [13]. This confidence can be bolstered by demonstrating that the service is an improvement over existing services or by introducing valuable information that is deemed useful by the stakeholders. Most climate services do not go past this stage, dying a natural death before being used by farmers. Ensuring that end users understand the value that a new climate service brings is important in the second stage of development. In this stage, any feedback mechanisms that can improve the usefulness of the product are encouraged. This stage involves much capacity-building among the users, with an important focus on major informants and potential early adopters who are influential in the agricultural sector.
- (c)
- Evaluation stage: This is a crucial step where users compare the proposed climate service with other products on the market. If there are no competing products, potential clients gauge the usefulness of the service and whether to use it. Its functionality and ease of use will encourage early adopters to take a chance with the product.
- (d)
- Trial stage: All users require a trial period to decide how well a product addresses their real-time challenges. It is important to provide as much time as possible for people to test a climate service. Increasing contact with potential end users and incorporating their views on how to improve the service is needed to sustain the service. It is important to ensure minimal barriers to adoption at this stage.
- (e)
- Adoption or rejection stage: The inevitable reality after some time has passed is that the new climate service will be adopted or rejected by the targeted group. The adoption of the service will be an indication that the initial marketing, functionality, and usefulness of the service were apparent to the users. It is important to further engage users in sustained use of the service. Continual upgrading of the services and support of the users is always crucial at the adoption stage. Thus, incorporating a monitoring and evaluation (M&E) procedure from the inception of the climate service project to the full deployment of the service is important. M&E needs to cover all aspects of the climate service. Any lapse can result in the defaulting of clients. It is important to ensure that the necessary financial support, human capital, and other resources that are needed to support the service are continually available.
7. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Vincent, K.; Dougill, A.J.; Dixon, J.L.; Stringer, L.C.; Cull, T. Identifying climate services needs for national planning: Insights from Malawi. Clim. Policy 2017, 17, 189–202. [Google Scholar] [CrossRef]
- Lourenço, T.C.; Swart, R.; Goosen, H.; Street, R. The rise of demand-driven climate services. Nat. Clim. Chang. 2016, 6, 13–14. [Google Scholar] [CrossRef]
- Alexander, M.; Dessai, S. What can climate services learn from the broader services literature? Clim. Chang. 2019, 157, 133–149. [Google Scholar] [CrossRef]
- Lemos, M.C.; Kirchhoff, C.J.; Ramprasad, V. Narrowing the climate information usability gap. Nat. Clim. Chang. 2012, 2, 789–794. [Google Scholar] [CrossRef]
- Dobardzic, S.; Dengel, C.; Gomes, A.M.; Hansen, J.; Bernardi, M.; Fujisawa, M.; Heureux, A.M.; Kanamaru, H.; Neretin, L.; Rojas, O.; et al. 2019 State of Climate Services: Agriculture and Food Security, vol. WMO-No 1242. World Meteorological Organization. 2020. Available online: https://library.wmo.int/records/item/56884-2019-state-of-climate-services-agriculture-and-food-security (accessed on 22 November 2023).
- Bremer, S.; Wardekker, A.; Dessai, S.; Sobolowski, S.; Slaattelid, R.; van der Sluijs, J. Toward a multi-faceted conception of co-production of climate services. Clim. Serv. 2019, 13, 42–50. [Google Scholar] [CrossRef]
- Jacobs, K.L.; Street, R.B. The next generation of climate services. Clim. Serv. 2020, 20, 100199. [Google Scholar] [CrossRef]
- Vaughan, C.; Hansen, J.; Roudier, P.; Watkiss, P.; Carr, E. Evaluating agricultural weather and climate services in Africa: Evidence, methods, and a learning agenda. Wiley Interdiscip. Rev. Clim. Change 2019, 10, e586. [Google Scholar] [CrossRef]
- Haigh, T.; Koundinya, V.; Hart, C.; Klink, J.; Lemos, M.; Mase, A.S.; Prokopy, L.; Singh, A.; Todey, D.; Widhalm, M. Provision of Climate Services for Agriculture: Public and Private Pathways to Farm Decision-Making. Bull. Am. Meteorol. Soc. 2018, 99, 1781–1790. [Google Scholar] [CrossRef]
- Vollstedt, B.; Koerth, J.; Tsakiris, M.; Nieskens, N.; Vafeidis, A.T. Co-production of climate services: A story map for future coastal flooding for the city of Flensburg. Clim. Serv. 2021, 22, 100225. [Google Scholar] [CrossRef]
- Thinklocalactpersonal, ‘Co-Production—In More Detail’. Available online: https://www.thinklocalactpersonal.org.uk/co-production-in-commissioning-tool/co-production/In-more-detail/ (accessed on 16 December 2023).
- Buontempo, C.; Hanlon, H.M.; Soares, M.B.; Christel, I.; Soubeyroux, J.-M.; Viel, C.; Calmanti, S.; Bosi, L.; Falloon, P.; Palin, E.J.; et al. What have we learnt from EUPORIAS climate service prototypes? Clim. Serv. 2018, 9, 21–32. [Google Scholar] [CrossRef]
- Hermansen, E.A.; Sillmann, J.; Vigo, I.; Whittlesey, S. The EU needs a demand-driven innovation policy for climate services. Clim. Serv. 2021, 24, 100270. [Google Scholar] [CrossRef]
- Hansen, J.W.; Vaughan, C.; Kagabo, D.M.; Dinku, T.; Carr, E.R.; Körner, J.; Zougmoré, R.B. Climate Services Can Support African Farmers’ Context-Specific Adaptation Needs at Scale. Front. Sustain. Food Syst. 2019, 3, 21. [Google Scholar] [CrossRef]
- Zuma-Netshiukhwi, G.N.; Stigter, K.C.; Walker, S. Improving agricultural decision making using weather and climate information for farmers, south-western Free State, South Africa. Net J. Agric. Sci. 2016, 4, 67–77. [Google Scholar]
- Antwi-Agyei, P.; Abalo, E.M.; Dougill, A.J.; Baffour-Ata, F. Motivations, enablers and barriers to the adoption of climate-smart agricultural practices by smallholder farmers: Evidence from the transitional and savannah agroecological zones of Ghana. Reg. Sustain. 2021, 2, 375–386. [Google Scholar] [CrossRef]
- Ouedraogo, A.; Egyir, I.S.; Ouedraogo, M.; Jatoe, J.B.D. Farmers’ Demand for Climate Information Services: A Systematic Review. Sustainability 2022, 14, 9025. [Google Scholar] [CrossRef]
- Collins, J.; Lazier, B. Beyond Entrepreneurship 2.0: Turning Your Business into an Enduring Great Company; Penguin Random House: New York, NY, USA, 2020. [Google Scholar]
- Simon, W.J.; Krupnik, T.J.; Aguilar-Gallegos, N.; Halbherr, L.; Groot, J.C. Putting social networks to practical use: Improving last-mile dissemination systems for climate and market information services in developing countries. Clim. Serv. 2021, 23, 100248. [Google Scholar] [CrossRef]
- Masupha, T.E.; Moeletsi, M.E.; Tsubo, M. Utilizing innovative technologies to enhance drought prediction and management for South Africa’s agriculture. In Proceedings of the 24th WaterNet/WARFSA/GWP-SA Symposium, Zanzibar, Tanzania, 25–27 October 2023. [Google Scholar]
- Moeletsi, M.; Mellaart, E.; Mpandeli, N.; Hamandawana, H. The Use of Rainfall Forecasts as a Decision Guide for Small-scale Farming in Limpopo Province, South Africa. J. Agric. Educ. Ext. 2013, 19, 133–145. [Google Scholar] [CrossRef]
- Arulnathan, V.; Heidari, M.D.; Doyon, M.; Li, E.; Pelletier, N. Farm-level decision support tools: A review of methodological choices and their consistency with principles of sustainability assessment. J. Clean. Prod. 2020, 256, 120410. [Google Scholar] [CrossRef]
- Moeletsi, M.E.; Moopisa, S.G.; Walker, S.; Tsubo, M. Development of an agroclimatological risk tool for dryland maize production in the Free State Province of South Africa. Comput. Electron. Agric. 2013, 95, 108–121. [Google Scholar] [CrossRef]
- Zain, B. Shift from UI Design to UX Design by Basit Zain How and what Made the Shift from the User Interface Design to the User Experience Design? 2023. Available online: https://www.linkedin.com/pulse/how-what-made-shift-from-user-interface-design-experience-basit-zain/ (accessed on 16 December 2023).
- Yang, B.; Liu, Y.; Liang, Y.; Tang, M. Exploiting user experience from online customer reviews for product design. Int. J. Inf. Manag. 2019, 46, 173–186. [Google Scholar] [CrossRef]
- Hart, J.; Sutcliffe, A. Is it all about the Apps or the Device? User experience and technology acceptance among iPad users. Int. J. Hum.-Comput. Stud. 2019, 130, 93–112. [Google Scholar] [CrossRef]
- Jin, J.; Ji, P.; Kwong, C. What makes consumers unsatisfied with your products: Review analysis at a fine-grained level. Eng. Appl. Artif. Intell. 2016, 47, 38–48. [Google Scholar] [CrossRef]
- Nanja, D.H. Dissemination of Climate Information to Small-Holder Farmers: A Case Study for Mujika Area, Zambia. Ph.D. Thesis, University of the Free State, Bloemfontein, South Africa, 2010. Available online: https://scholar.ufs.ac.za/server/api/core/bitstreams/72f38297-48ed-4113-999b-7da0afe41d0b/content (accessed on 13 December 2023).
- Walker, S. Development of Tailored Early Warning Agromet Advisories for Farmers in Zambia, Indonesia, and South Africa. Front. Clim. 2021, 3, 710625. [Google Scholar] [CrossRef]
- Khan, S.; Umer, R.; Umer, S.; Naqvi, S. Antecedents of trust in using social media for E-government services: An empirical study in Pakistan. Technol. Soc. 2021, 64, 101400. [Google Scholar] [CrossRef]
- Walker, S. Value-added weather advisories for small-scale farmers in South Africa delivered via mobile apps. Irrig. Drain. 2021, 70, 505–511. [Google Scholar] [CrossRef]
- Campbell, B.M.; Vermeulen, S.J.; Aggarwal, P.K.; Corner-Dolloff, C.; Girvetz, E.; Loboguerrero, A.M.; Ramirez-Villegas, J.; Rosenstock, T.; Sebastian, L.; Thornton, P.K.; et al. Reducing risks to food security from climate change. Glob. Food Secur. 2016, 11, 34–43. [Google Scholar] [CrossRef]
- Stigter, C. From basic agrometeorological science to agrometeorological services and information for agricultural decision makers: A simple conceptual and diagnostic framework. Agric. For. Meteorol. 2007, 142, 91–95. [Google Scholar] [CrossRef]
- My Climate View. Available online: https://myclimateview.com.au/ (accessed on 16 December 2023).
- Fraisse, C.; Andreis, J.H.; Borba, T.; Cerbaro, V.; Gelcer, E.; Pavan, W.; Pequeno, D.; Perondi, D.; Shen, X.; Staub, C.; et al. AgroClimate—Tools for managing climate risk in agriculture. Agrometeoros 2016, 24, 121–129. [Google Scholar]
- CLIMTAG. Climate Services for Agriculture. Available online: https://climtag.vito.be/en (accessed on 21 February 2024).
- Tubiello, F.N.; Salvatore, M.; Rossi, S.; Ferrara, A.; Fitton, N.; Smith, P. The FAOSTAT database of greenhouse gas emissions from agriculture. Environ. Res. Lett. 2013, 8, 015009. [Google Scholar] [CrossRef]
- Hillier, J.; Walter, C.; Malin, D.; Garcia-Suarez, T.; Mila-I-Canals, L.; Smith, P. A farm-focused calculator for emissions from crop and livestock production. Environ. Model. Softw. 2011, 26, 1070–1078. [Google Scholar] [CrossRef]
- Crippa, M.; Solazzo, E.; Guizzardi, D.; Monforti-Ferrario, F.; Tubiello, F.N.; Leip, A. Food systems are responsible for a third of global anthropogenic GHG emissions. Nat. Food 2021, 2, 198–209. [Google Scholar] [CrossRef] [PubMed]
- Carlson, K.M.; Gerber, J.S.; Mueller, N.D.; Herrero, M.; MacDonald, G.K.; Brauman, K.A.; Havlik, P.; O’Connell, C.S.; Johnson, J.A.; Saatchi, S.; et al. Greenhouse gas emissions intensity of global croplands. Nat. Clim. Chang. 2017, 7, 63–68. [Google Scholar] [CrossRef]
- Parker, R.W.R.; Blanchard, J.L.; Gardner, C.; Green, B.S.; Hartmann, K.; Tyedmers, P.H.; Watson, R.A. Fuel use and greenhouse gas emissions of world fisheries. Nat. Clim. Chang. 2018, 8, 333–337. [Google Scholar] [CrossRef]
- Patra, A.K. Trends and Projected Estimates of GHG Emissions from Indian Livestock in Comparisons with GHG Emissions from World and Developing Countries. Asian-Australas. J. Anim. Sci. 2014, 27, 592–599. [Google Scholar] [CrossRef] [PubMed]
- Alemu, A.; Ominski, K.H.; Kebreab, E. Estimation of enteric methane emissions trends (1990–2008) from Manitoba beef cattle using empirical and mechanistic models. Can. J. Anim. Sci. 2011, 91, 305–321. [Google Scholar] [CrossRef]
- Jahan, S.; Azad, A.K. Estimation of Greenhouse Gas Emission from the Livestock Sector of Bangladesh. Int. J. Sci. Res. 2013, 4, 1148–1155. [Google Scholar]
- Moeletsi, M.E.; Tongwane, M.I.; Tsubo, M. Enteric Methane Emissions Estimate for Livestock in South Africa for 1990–2014. Atmosphere 2017, 8, 69. [Google Scholar] [CrossRef]
- Tongwane, M.I.; Moeletsi, M.E. Provincial cattle carbon emissions from enteric fermentation and manure management in South Africa. Environ. Res. 2021, 195, 110833. [Google Scholar] [CrossRef]
- Tongwane, M.I.; Moeletsi, M.E.; Tsubo, M. Trends of carbon emissions from applications of nitrogen fertiliser and crop residues to agricultural soils in South Africa. J. Environ. Manag. 2020, 272, 111056. [Google Scholar] [CrossRef]
- Whittaker, C.; McManus, M.C.; Smith, P. A comparison of carbon accounting tools for arable crops in the United Kingdom. Environ. Model. Softw. 2013, 46, 228–239. [Google Scholar] [CrossRef]
- Kayatz, B.; Baroni, G.; Hillier, J.; Lüdtke, S.; Heathcote, R.; Malin, D.; van Tonder, C.; Kuster, B.; Freese, D.; Hüttl, R.; et al. Cool Farm Tool Water: A global on-line tool to assess water use in crop production. J. Clean. Prod. 2019, 207, 1163–1179. [Google Scholar] [CrossRef]
- Hillier, J. The Cool Farm Tool. 2013. Available online: https://www.ipcinfo.org/fileadmin/user_upload/epic/docs/workshops/Technical_consultation/Presentations/CFT_intro.pdf (accessed on 24 November 2023).
- Little, S.; Lindeman, J.; Maclean, K.; Janzen, H. Holos: A Tool to Estimate and Reduce Greenhouse Gases from Farms. Agriculture and Agri-Food Canada. 2008. Available online: https://publications.gc.ca/collections/collection_2009/agr/A52-136-2008E.pdf (accessed on 4 December 2023).
- Newlands, N.K. GHGFARM: A Software Tool to Estimate and Reduce Net-Greenhouse Gas Emission from Farms in Canada. 2007. Available online: https://www.researchgate.net/publication/234789193 (accessed on 16 December 2023).
- Kröbel, R.; Bolinder, M.; Janzen, H.; Little, S.; Vandenbygaart, A.; Kätterer, T. Canadian farm-level soil carbon change assessment by merging the greenhouse gas model Holos with the Introductory Carbon Balance Model (ICBM). Agric. Syst. 2016, 143, 76–85. [Google Scholar] [CrossRef]
- Little, S.M.; Benchaar, C.; Janzen, H.H.; Kröbel, R.; McGeough, E.J.; Beauchemin, K.A. Demonstrating the Effect of Forage Source on the Carbon Footprint of a Canadian Dairy Farm Using Whole-Systems Analysis and the Holos Model: Alfalfa Silage vs. Corn Silage. Climate 2017, 5, 87. [Google Scholar] [CrossRef]
- Kröbel, R.; Moore, J.; Ni, Y.Z.; McPherson, A.; Poppy, L.; Soolanayakanahally, R.Y.; Amichev, B.Y.; Ward, T.; Laroque, C.P.; Van Rees, K.C.J.; et al. Demonstration and Testing of the Improved Shelterbelt Component in the Holos Model. Front. Environ. Sci. 2020, 8, 149. [Google Scholar] [CrossRef]
- Fouli, Y.; Hurlbert, M.; Kröbel, R. Greenhouse Gas Emissions from Canadian Agriculture: Estimates and Measurements the Simpson Centre for Agricultural and Food Innovation and Public Education. 2021. Available online: https://ssrn.com/abstract=4042259 (accessed on 16 December 2023).
- Alemu, A.W.; Amiro, B.D.; Bittman, S.; MacDonald, D.; Ominski, K.H. Greenhouse gas emission of Canadian cow-calf operations: A whole-farm assessment of 295 farms. Agric. Syst. 2017, 151, 73–83. [Google Scholar] [CrossRef]
- Legesse, G.; Beauchemin, K.A.; Ominski, K.H.; McGeough, E.J.; Kroebel, R.; MacDonald, D.; Little, S.M.; McAllister, T.A. Greenhouse gas emissions of Canadian beef production in 1981 as compared with 2011. Anim. Prod. Sci. 2016, 56, 153–168. [Google Scholar] [CrossRef]
- Kroebel, R.; Alemu, A.; Pogue, S.; McPherson, A. 169 Estimating the Environmental Impact of Livestock Operations Using the Canadian Whole-farm Model Holos Developed for Canadian Farmers. J. Anim. Sci. 2021, 99, 90. [Google Scholar] [CrossRef]
- Kpogo, A.L.; Jose, J.; Panisson, J.; Predicala, B.; Alvarado, A.; Agnew, J.; Sprenger, C.; Beaulieu, D.A. 27 Greenhouse Gas Emissions and a Partial Life Cycle Assessment When Growing Pigs Are Fed High Wheat Millrun Diets. J. Anim. Sci. 2021, 99, 24–25. [Google Scholar] [CrossRef]
- Farm Carbon Toolkit. About Us—Farm Carbon Toolkit. Available online: https://farmcarbontoolkit.org.uk/ (accessed on 21 February 2024).
- Parker, L.; Smith, J. Methodology of the Farm Carbon Calculator. 2023. Available online: https://farmcarbontoolkit.org.uk/wp-content/uploads/2022/09/Methodology-of-the-Farm-Carbon-Calculator-Final-Version-160821.pdf (accessed on 16 December 2023).
- Perosa, B.; Newton, P.; Carrer, M.J. Access to information affects the adoption of integrated systems by farmers in Brazil. Land Use Policy 2021, 106, 105459. [Google Scholar] [CrossRef]
- Mani, Z.; Chouk, I. Consumer Resistance to Innovation in Services: Challenges and Barriers in the Internet of Things Era. J. Prod. Innov. Manag. 2018, 35, 780–807. [Google Scholar] [CrossRef]
- Amor, R.H. Succeeding with New Technology: Breaking Down Adoption Barriers. Available online: https://www.redhat.com/en/blog/succeeding-new-technology-breaking-down-adoption-barriers (accessed on 11 December 2023).
- Vogel, J.; Letson, D.; Herrick, C. A framework for climate services evaluation and its application to the Caribbean Agrometeorological Initiative. Clim. Serv. 2017, 6, 65–76. [Google Scholar] [CrossRef]
- Arifalo, E.N. Product Adoption Barriers and How to Overcome Them. Available online: https://mambo.io/blog/product-adoption-barriers-and-how-to-overcome-them (accessed on 11 December 2023).
- Alchemer. The Five Stages of Product Adoption. 2022. Available online: https://www.alchemer.com/resources/blog/the-five-stages-of-product-adoption/ (accessed on 11 December 2023).
Climate Service | Basic Functionalities | Applicability |
---|---|---|
Agroclimate (http://agroclimate.org, accessed on 16 December 2023) | - This tool can be used by farmers to manage climate risk, and it utilizes climate forecasts as well as recorded climate data to provide agricultural stakeholders with valuable information [35]. - The tool has the functionality to monitor different parameters important to growers, like growing degree days, chill units, and heat stress. - It can also help farmers with ENSO climatology and forecasting. - It also has subsidiary tools for pests and diseases for selected crops. | Selected areas in the United States of America |
CLIMTAG (https://climtag.vito.be/en, accessed on 16 December 2023) | - The tool equips agricultural stakeholders with climate information to help build climate-resilient agricultural systems [36]. - The tool uses rainfall and other climate parameters from reanalysis data (ERA5) and climate projection data (CMIP5) to estimate a variety of agrometeorology indicators. | Africa |
Climate Service | Basic Functionalities | Applicability |
---|---|---|
Cool farm tool (https://coolfarm.org/the-tool/, accessed on 16 December 2023) Started in 2008 | - It estimates farm emissions from both livestock and crop production using already established models from the Inter-governmental Panel on Climate Change (IPCC) national greenhouse gas inventory guidelines, independent research, and corporate greenhouse gas protocols [48]. - Input data include area planted, types of crops, amount and type of fertilizer applied, type and amount of pesticides and herbicides applied, amount of electricity and other energy sources used, livestock population and type, and amount of feed and manure management systems. | Worldwide |
Farm carbon Toolkit (https://farmcarbontoolkit.org.uk, accessed on 16 December 2023) Started in 2008 [61] | The tool can be used by farmers and agricultural stakeholders for all the major agricultural commodities, including livestock production, crop and horticulture production. - The calculator covers scope 1, 2, and 3 calculations with a customized boundary, which can be (1) to the farm gate only; (2) farm and distribution, and (3) farm and distribution to the final customer [62]. - The tool uses IPCC guidelines and other resources to estimate most of the greenhouse gas sources. | United Kingdom |
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Moeletsi, M.E.; Tsubo, M. A Move towards Developing Usable Climate Change Adaptation and Mitigation Services for the Agricultural Sector. Climate 2024, 12, 46. https://doi.org/10.3390/cli12030046
Moeletsi ME, Tsubo M. A Move towards Developing Usable Climate Change Adaptation and Mitigation Services for the Agricultural Sector. Climate. 2024; 12(3):46. https://doi.org/10.3390/cli12030046
Chicago/Turabian StyleMoeletsi, Mokhele E., and Mitsuru Tsubo. 2024. "A Move towards Developing Usable Climate Change Adaptation and Mitigation Services for the Agricultural Sector" Climate 12, no. 3: 46. https://doi.org/10.3390/cli12030046
APA StyleMoeletsi, M. E., & Tsubo, M. (2024). A Move towards Developing Usable Climate Change Adaptation and Mitigation Services for the Agricultural Sector. Climate, 12(3), 46. https://doi.org/10.3390/cli12030046