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Updated: Jun 3, 2025

The Hawaii Protocol for Scientific Monitoring of Coffee Berry Borer: a Model for Coffee Agroecosystems Worldwide
Published on: March 19, 2018
Comparing carbon agronomic footprint and sequestration in Central American coffee agroforestry systems and assessing
Conor Walsh1, Jeremy Haggar1, Stefania Cerretelli1
1Natural Resources Institute, University of Greenwich, Central Avenue, Chatham Maritime, Kent ME4 4TB, UK.
Abstract:
Agricultural systems are both emitters of greenhouse gases and have the potential to sequester carbon, especially agroforestry systems. Coffee agroforestry systems offer a wide range of intensities of use of agricultural inputs and densities and management of shade trees. We assessed the agronomic carbon footprint (up to farm gate) and modelled the carbon sequestration of a range of coffee agroforestry systems across 180 farms in Costa Rica and Guatemala. The agronomic carbon footprint included upstream, direct and indirect processes associated with chemical and organic fertiliser use and energy consumption (excluding processing of cherries). Carbon sequestration was modelled using the CAF2021 model a processed based model of the C, N and water dynamics specifically designed for coffee agroforestry systems. The carbon footprint per kg of coffee cherries was significantly and positively related to the level of nitrogen inputs. Modelled changes in C stocks i.e. carbon sequestration was significantly and positively related to the Leaf Area Index (LAI) of the trees, and the levels of nitrogen inputs. Increasing nitrogen inputs per hectare was positively associated with emission per kg as nitrogen efficiency varied significantly across the sample. The net carbon balance, defined as sequestration minus CO2e emissions was also positively related to shade tree LAI but negatively with yield and N application. Carbon positive farms were characterized by shade cover over 60 %, but low yields and low net income. However, farms that were close to carbon neutral had higher yields and higher net income, with shade levels of about 50 % cover, while carbon negative farms which had shade cover averaging 40 %. Nevertheless, farms showed a large variation in performance with all combinations of positive and negative for carbon balance and net income. However, among the farms with a positive net income, those with a positive carbon balance had a significantly lower net income than those that were carbon negative (i.e. net emitters). This confirms the economic trade-off for farmers seeking to maximise these two goals. If farmers are expected to generate positive carbon balances and potentially to offset emissions higher in the supply chain, then they should receive economic support to compensate continued on-farm carbon accumulation.
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