Environmental Dynamics in The Sumatran Coffee Landscapes: Opportunities and Challenges Through Spatial Perspectives
Abstract
The coffee industry in Indonesia, particularly in the Sumatran landscape, emerges as a vital contributor to the nation's economy, impacting regional growth. Nevertheless, this landscape faces ecological threats from rapid deforestation, resulting in a substantial loss of primary forest cover. This historical deforestation along with climate crisis presents challenges for coffee plantations. The study employs geospatial analysis to comprehensively outline challenges and opportunities for smallholder coffee farmers in Sumatra, particularly in the Arabica (Central Aceh) and Robusta (Tanggamus) landscapes. The study shows non-shade coffee plantations covered approximately 23,453 ha in Central Aceh and 43,991 ha in Tanggamus. Additionally, mixed agroforestry areas were prevalent, comprising about 132,569 ha in Tanggamus and 19,450 ha in Central Aceh. Tanggamus and Central Aceh have become favorable areas for Robusta coffee and Arabica coffee, respectively. One significant opportunity identified for coffee development in Central Aceh is that 86% of existing coffee farms already adhere to EUDR. Furthermore, 94% of existing coffee farms in Tanggamus meet EUDR standards, opening doors for more farmers to access the European market.
References
Camps-Valls G, Campos-Taberner M, Moreno-Martínez Á, Walther S, Duveiller G, Cescatti A, Mahecha MD, Muñoz-Marí J, García-Haro FJ, Guanter L, et al. 2021. A unified vegetation index for quantifying the terrestrial biosphere. Sci Adv. 7(9). doi:10.1126/sciadv.abc7447.
Cohen J. 1960. A Coefficient of Agreement for Nominal Scales. Educ Psychol Meas. doi:10.1177/001316446002000104.
Curtis PG, Slay CM, Harris NL, Tyukavina A, Hansen MC. 2018. Classifying drivers of global forest loss. Science (1979). 361(6407):1108–1111. doi:10.1126/science.aau3445.
Etter A, McAlpine C, Possingham H. 2008. Historical Patterns and Drivers of Landscape Change in Colombia Since 1500: A Regionalized Spatial Approach. Annals of the Association of American Geographers. 98(1):2–23. doi:10.1080/00045600701733911.
Gao B-C. 1996. NDWI - A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water From Space. Remote Sens Environ. 58(3):257–266. doi:10.1016/s0034-4257(96)00067-3.
Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R. 2017. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens Environ. 202:18–27. doi:10.1016/j.rse.2017.06.031. https://doi.org/10.1016/j.rse.2017.06.031.
Hansen MC, Potapov P V., Moore R, Hancher M, Turubanova SA, Tyukavina A, Thau D, Stehman S V., Goetz SJ, Loveland TR, et al. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science (1979). 342(6160):850–853. doi:10.1126/science.1244693.
Harvey CA, Pritts AA, Zwetsloot MJ, Jansen K, Pulleman MM, Armbrecht I, Avelino J, Barrera JF, Bunn C, García JH, et al. 2021. Transformation of coffee-growing landscapes across Latin America. A review. Agron Sustain Dev. 41(5):62. doi:10.1007/s13593-021-00712-0.
Huete A, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG. 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens Environ. doi:10.1016/S0034-4257(02)00096-2.
Huete AR. 1988. A soil-adjusted vegetation index (SAVI). Remote Sens Environ. doi:10.1016/0034-4257(88)90106-X.
Hung Anh N, Bokelmann W, Thi Nga D, Van Minh N. 2019. Toward Sustainability or Efficiency: The Case of Smallholder Coffee Farmers in Vietnam. Economies. 7(3):66. doi:10.3390/economies7030066.
Le QV, Cowal S, Jovanovic G, Le D-T. 2021. A Study of Regenerative Farming Practices and Sustainable Coffee of Ethnic Minorities Farmers in the Central Highlands of Vietnam. Front Sustain Food Syst. 5. doi:10.3389/fsufs.2021.712733.
Leroy B, Delsol R, Hugueny B, Meynard CN, Barhoumi C, Barbet-Massin M, Bellard C. 2018. Without quality presence–absence data, discrimination metrics such as TSS can be misleading measures of model performance. J Biogeogr. 45(9):1994–2002. doi:10.1111/jbi.13402.
Margono BA, Turubanova S, Zhuravleva I, Potapov P, Tyukavina A, Baccini A, Goetz S, Hansen MC. 2012. Mapping and monitoring deforestation and forest degradation in Sumatra (Indonesia) using Landsat time series data sets from 1990 to 2010. Environmental Research Letters. 7(3):2000–2010. doi:10.1088/1748-9326/7/3/034010.
MoA. 2011. Technical Guidance for Crop Suitability Analysis in Indonesia. [accessed 2023 Nov 23]. https://apps.worldagroforestry.org/sea/Publications/files/manual/MN0036-07.pdf.
Nandakishor TM, Gopi G, Champatan V, Sukesh A, Aravind P V. 2022. Agroforestry in Shade Coffee Plantations as an Emission Reduction Strategy for Tropical Regions: Public Acceptance and the Role of Tree Banking. Front Energy Res. 10. doi:10.3389/fenrg.2022.758372.
Poor EE, Frimpong E, Imron MA, Kelly MJ. 2019. Protected area effectiveness in a sea of palm oil: A Sumatran case study. Biol Conserv. 234(March):123–130. doi:10.1016/j.biocon.2019.03.018.
Putri A, Syahni R, Hasnah, Miko A. 2023. The effect of Arabica coffee farmers’ innovation on good agriculture practice in Solok. IOP Conf Ser Earth Environ Sci. 1160(1):012064. doi:10.1088/1755-1315/1160/1/012064.
Saragih JR. 2013. Socioeconomic and ecological dimension of certified and conventional arabica coffee production in North Sumatra, Indonesia. Asian Journal of Agriculture and Rural Development, 3(3): 1-15. doi: 10.22004/ag.econ.198103. https://ideas.repec.org/a/ags/ajosrd/198103.html
Sarvina Y, June T, Hadi Sutjahjo S, Nurmalina R, Surmaini E. 2021. The impacts of climate variability on coffee yield in five indonesian coffee production centers. Coffee Sci. 16:1–9. doi:10.25186/.v16i.1917.
Sujatmiko T, Ihsaniyati H. 2018. Implication of climate change on coffee farmers’ welfare in Indonesia. IOP Conf Ser Earth Environ Sci. 200:012054. doi:10.1088/1755-1315/200/1/012054.
[UNESCO] United Nations Educational, Scientific and Cultural Organization. 2023. Tropical Rainforest Heritage of Sumatra [accessed Dec 1, 2023]. https://whc.unesco.org/en/list/1167/
Yang L, Wang L, Abubakar GA, Huang J. 2021. High-Resolution Rice Mapping Based on SNIC Segmentation and Multi-Source Remote Sensing Images. Remote Sens (Basel). 13(6):1148. doi:10.3390/rs13061148.
Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).