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  • Perspective
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Priority science can accelerate agroforestry as a natural climate solution

Nature Climate Change volume 13, pages 1179–1190 (2023)Cite this article

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Abstract

The expansion of agroforestry could provide substantial climate change mitigation (up to 0.31 Pg C yr−1), comparable to other prominent natural climate solutions such as reforestation. Yet, climate-focused agroforestry efforts grapple with ambiguity about which agroforestry actions provide mitigation, uncertainty about the magnitude of that mitigation and inability to reliably track progress. In this Perspective, we define agroforestry as a natural climate solution, discuss current understanding of the controls on farm-scale mitigation potential and highlight recent innovation on emergent, high-resolution remote sensing methods to enable detection, measurement and monitoring. We also assess the status of agroforestry in the context of global climate ambitions, highlighting regions of underappreciated expansion opportunity and identifying priorities for policy and praxis.

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Fig. 1: Land-use change and carbon outcomes determine whether agroforestry is an NCS.
Fig. 2: Carbon stock changes after agroforestry adoption vary within and across practices.
Fig. 3: Global comparison between remote sensing of agroforestry and site locations gathered from literature.
Fig. 4: Importance of spatial precision, spatial resolution and temporal dynamics in remote sensing of agroforestry.
Fig. 5: Variation in current and potential additional agroforestry carbon storage.

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Data availability

All data used in this study are publicly available from their original providers via the supplementary materials and/or requests to the corresponding authors of the originating peer-reviewed publications, except the summary data we gathered about previous agroforestry meta-analyses and the agroforestry site geographic coordinate data that we collected from the primary literature. We have made all data available in our GitHub repository (http://github.com/naturalclimatesolutions/AF_as_NCS; https://doi.org/10.5281/zenodo.8209212).

Code availability

All code used for this study is provided at http://github.com/naturalclimatesolutions/AF_as_NCS (https://doi.org/10.5281/zenodo.8209212).

References

  1. Lentz, D. L. & Hockaday, B. Tikal timbers and temples: ancient Maya agroforestry and the end of time. J. Archaeol. Sci. 36, 1342–1353 (2009).

    Article  Google Scholar 

  2. Eichhorn, M. P. et al. Silvoarable systems in Europe—past, present and future prospects. Agrofor. Syst. 67, 29–50 (2006).

    Article  Google Scholar 

  3. Nair, P. K. R. State-of-the-art of agroforestry systems. For. Ecol. Manage. 45, 5–29 (1991).

    Article  Google Scholar 

  4. Wolz, K. J. & DeLucia, E. H. Black walnut alley cropping is economically competitive with row crops in the Midwest USA. Ecol. Appl. 29, e01829 (2019).

    Article  Google Scholar 

  5. Castle, S. E., Miller, D. C., Ordonez, P. J., Baylis, K. & Hughes, K. The impacts of agroforestry interventions on agricultural productivity, ecosystem services, and human well‐being in low‐ and middle‐income countries: a systematic review. Campbell Syst. Rev. 17, e1167 (2021).

    Article  Google Scholar 

  6. Beillouin, D., Ben-Ari, T. & Makowski, D. Evidence map of crop diversification strategies at the global scale. Environ. Res. Lett. 14 123001 (2019); erratum 15, 019601 (2020).

  7. Beillouin, D., Ben‐Ari, T., Malézieux, E., Seufert, V. & Makowski, D. Positive but variable effects of crop diversification on biodiversity and ecosystem services. Glob. Change Biol. 27, 4697–4710 (2021).

    Article  CAS  Google Scholar 

  8. Griscom, B. W. et al. Natural climate solutions. Proc. Natl Acad. Sci. USA 114, 11645–11650 (2017).

    Article  CAS  Google Scholar 

  9. Roe, S. et al. Land‐based measures to mitigate climate change: potential and feasibility by country. Glob. Change Biol. 27, 6025–6058 (2021).

    Article  CAS  Google Scholar 

  10. Rosenstock, T. S. et al. Making trees count: measurement and reporting of agroforestry in UNFCCC national communications of non-Annex I countries. Agric. Ecosyst. Environ. 284, 106569 (2019).

    Article  Google Scholar 

  11. Chapman, M. et al. Large climate mitigation potential from adding trees to agricultural lands. Glob. Change Biol. 26, 4357–4365 (2020).

    Article  Google Scholar 

  12. Lesiv, M. et al. Global forest management data for 2015 at a 100 m resolution. Sci. Data 9, 199 (2022).

    Article  Google Scholar 

  13. Aboveground Live Woody Biomass Density (Global Forest Watch, 2021); https://www.globalforestwatch.org/map/?mapMenu=eyJtZW51U2VjdGlvbiI6ImRhdGFzZXRzIiwiZGF0YXNldENhdGVnb3J5IjoiY2xpbWF0ZSJ9&modalMeta=aboveground_biomass

  14. Zarin, D. J. et al. Can carbon emissions from tropical deforestation drop by 50% in 5 years? Glob. Change Biol. 22, 1336–1347 (2016).

    Article  Google Scholar 

  15. Zomer, R. J. et al. Global tree cover and biomass carbon on agricultural land: the contribution of agroforestry to global and national carbon budgets. Sci. Rep. 6, 29987 (2016).

    Article  CAS  Google Scholar 

  16. Zomer, R. J. et al. Global carbon sequestration potential of agroforestry and increased tree cover on agricultural land. Circ. Agric Syst. 2, 3 (2022).

    Google Scholar 

  17. Cardinael, R. et al. Revisiting IPCC Tier 1 coefficients for soil organic and biomass carbon storage in agroforestry systems. Environ. Res. Lett. 13, 124020 (2018).

    Article  Google Scholar 

  18. DeStefano, A. & Jacobson, M. G. Soil carbon sequestration in agroforestry systems: a meta-analysis. Agrofor. Syst. 92, 285–299 (2018).

    Google Scholar 

  19. Kim, D.-G., Kirschbaum, M. U. F. & Beedy, T. L. Carbon sequestration and net emissions of CH4 and N2O under agroforestry: synthesizing available data and suggestions for future studies. Agric. Ecosyst. Environ. 226, 65–78 (2016).

    Article  CAS  Google Scholar 

  20. Drexler, S., Gensior, A. & Don, A. Carbon sequestration in hedgerow biomass and soil in the temperate climate zone. Reg. Environ. Change 21, 74 (2021).

    Article  Google Scholar 

  21. Hübner, R. et al. Soil carbon sequestration by agroforestry systems in China: a meta-analysis. Agric. Ecosyst. Environ. 315, 107437 (2021).

    Article  Google Scholar 

  22. Shi, L., Feng, W., Xu, J. & Kuzyakov, Y. Agroforestry systems: meta‐analysis of soil carbon stocks, sequestration processes, and future potentials. Land Degrad. Dev. 29, 3886–3897 (2018).

    Article  Google Scholar 

  23. Mayer, S. et al. Soil organic carbon sequestration in temperate agroforestry systems—a meta-analysis. Agric. Ecosyst. Environ. 323, 107689 (2022).

    Article  CAS  Google Scholar 

  24. Kuyah, S. et al. Agroforestry delivers a win–win solution for ecosystem services in sub-Saharan Africa: a meta-analysis. Agron. Sustain. Dev. 39, 47 (2019).

    Article  CAS  Google Scholar 

  25. Chatterjee, N., Nair, P. K. R., Chakraborty, S. & Nair, V. D. Changes in soil carbon stocks across the forest–agroforest–agriculture/pasture continuum in various agroecological regions: a meta-analysis. Agric. Ecosyst. Environ. 266, 55–67 (2018).

    Article  Google Scholar 

  26. Muchane, M. N. et al. Agroforestry boosts soil health in the humid and sub-humid tropics: a meta-analysis. Agric. Ecosyst. Environ. 295, 106899 (2020).

    Article  CAS  Google Scholar 

  27. Feliciano, D., Ledo, A., Hillier, J. & Nayak, D. R. Which agroforestry options give the greatest soil and above ground carbon benefits in different world regions? Agric. Ecosyst. Environ. 254, 117–129 (2018).

    Article  Google Scholar 

  28. Udawatta, R. P. & Jose, S. Agroforestry strategies to sequester carbon in temperate North America. Agrofor. Syst. 86, 225–242 (2012).

    Article  Google Scholar 

  29. Ma, Z., Chen, H. Y. H., Bork, E. W., Carlyle, C. N. & Chang, S. X. Carbon accumulation in agroforestry systems is affected by tree species diversity, age and regional climate: a global meta‐analysis. Glob. Ecol. Biogeogr. 29, 1817–1828 (2020).

    Article  Google Scholar 

  30. Ziegler, A. D. et al. Carbon outcomes of major land‐cover transitions in SE Asia: great uncertainties and REDD+ policy implications. Glob. Change Biol. 18, 3087–3099 (2012).

    Article  Google Scholar 

  31. Shrestha, B. M., Chang, S. X., Bork, E. W. & Carlyle, C. N. Enrichment planting and soil amendments enhance carbon sequestration and reduce greenhouse gas emissions in agroforestry systems: a review. Forests 9, 369 (2018).

    Article  Google Scholar 

  32. Obeng, E. A. & Aguilar, F. X. Marginal effects on biodiversity, carbon sequestration and nutrient cycling of transitions from tropical forests to cacao farming systems. Agrofor. Syst. 89, 19–35 (2015).

    Article  Google Scholar 

  33. Nath, A. J. et al. Quantifying carbon stocks and sequestration potential in agroforestry systems under divergent management scenarios relevant to India’s Nationally Determined Contribution. J. Clean. Prod. 281, 124831 (2021).

    Article  CAS  Google Scholar 

  34. Ivezić, V., Lorenz, K. & Lal, R. Soil organic carbon in alley cropping systems: a meta-analysis. Sustainability 14, 1296 (2022).

    Article  Google Scholar 

  35. Baah-Acheamfour, M., Chang, S. X., Bork, E. W. & Carlyle, C. N. The potential of agroforestry to reduce atmospheric greenhouse gases in Canada: insight from pairwise comparisons with traditional agriculture, data gaps and future research. For. Chron. 93, 180–189 (2017).

    Article  Google Scholar 

  36. Ahirwal, J. et al. Patterns and driving factors of biomass carbon and soil organic carbon stock in the Indian Himalayan region. Sci. Total Environ. 770, 145292 (2021).

    Article  CAS  Google Scholar 

  37. Miller, D. C. et al. The impacts of agroforestry on agricultural productivity, ecosystem services, and human well‐being in low‐ and middle‐income countries: an evidence and gap map. Campbell Syst. Rev. 16, e1066 (2020).

    Article  Google Scholar 

  38. IPCC Climate Change 2022: Mitigation of Climate Change (eds Shukla, P. R. et al.) (Cambridge Univ. Press, 2022).

  39. Verchot, L. V. et al. Climate change: linking adaptation and mitigation through agroforestry. Mitig. Adapt. Strateg. Glob. Change 12, 901–918 (2007).

    Article  Google Scholar 

  40. Nair, P. K. R., Kumar, B. M. & Nair, V. D. Agroforestry as a strategy for carbon sequestration. J. Plant Nutr. Soil Sci. 172, 10–23 (2009).

    Article  CAS  Google Scholar 

  41. Nair, P. K. R. Carbon sequestration studies in agroforestry systems: a reality-check. Agrofor. Syst. 86, 243–253 (2012).

    Article  Google Scholar 

  42. Montagnini, F. & Nair, P. K. R. Carbon sequestration: an underexploited environmental benefit of agroforestry systems. Adv. Agrofor. https://doi.org/10.1007/978-94-017-2424-1_20 (2004).

  43. Albrecht, A. & Kandji, S. T. Carbon sequestration in tropical agroforestry systems. Agric. Ecosyst. Environ. 99, 15–27 (2003).

    Article  CAS  Google Scholar 

  44. Nair, P. K. R. Classification of agroforestry systems. Agrofor. Syst. 3, 97–128 (1985).

    Article  Google Scholar 

  45. West, T. A. P., Börner, J., Sills, E. O. & Kontoleon, A. Overstated carbon emission reductions from voluntary REDD+ projects in the Brazilian Amazon. Proc. Natl Acad. Sci. USA 117, 24188–24194 (2020).

    Article  CAS  Google Scholar 

  46. Ollinaho, O. I. & Kröger, M. Agroforestry transitions: the good, the bad and the ugly. J. Rural Stud. 82, 210–221 (2021).

    Article  Google Scholar 

  47. Straaten van, O. et al. Conversion of lowland tropical forests to tree cash crop plantations loses up to one-half of stored soil organic carbon. Proc. Natl Acad. Sci. USA 112, 9956–9960 (2015).

    Article  Google Scholar 

  48. Martin, D. A. et al. Land‐use history determines ecosystem services and conservation value in tropical agroforestry. Conserv. Lett. 13, e12740 (2020).

    Article  Google Scholar 

  49. Griscom, B., Shoch, D., Stanley, B., Cortez, R. & Virgilio, N. Sensitivity of amounts and distribution of tropical forest carbon credits depending on baseline rules. Environ. Sci. Policy 12, 897–911 (2009).

    Article  Google Scholar 

  50. Kumar, B. M. & Takeuchi, K. Agroforestry in the Western Ghats of peninsular India and the satoyama landscapes of Japan: a comparison of two sustainable land use systems. Sustain. Sci. 4, 215–232 (2009).

    Article  Google Scholar 

  51. Seruni, A. P., Aguilar, F. X., Cai, Z., Gold, M. A. & Roshetko, J. M. Parcelized cut-and-carry agroforestry systems for confined livestock. Small Scale For. 20, 119–143 (2021).

    Article  Google Scholar 

  52. Ickowitz, A. et al. Transforming food systems with trees and forests. Lancet Planet. Health 6, e632–e639 (2022).

    Article  Google Scholar 

  53. Dhyani, S. K., Ram, A. & Dev, I. Potential of agroforestry systems in carbon sequestration in India. Indian J. Agric. Sci. 86, 1103–1112 (2016).

    CAS  Google Scholar 

  54. Cardinael, R. et al. Impact of alley cropping agroforestry on stocks, forms and spatial distribution of soil organic carbon—a case study in a Mediterranean context. Geoderma 259, 288–299 (2015).

    Article  Google Scholar 

  55. Sharrow, S. H. & Ismail, S. Carbon and nitrogen storage in agroforests, tree plantations, and pastures in western Oregon, USA. Agrofor. Syst. 60, 123–130 (2004).

    Article  Google Scholar 

  56. Makumba, W., Akinnifesi, F. K., Janssen, B. & Oenema, O. Long-term impact of a gliricidia–maize intercropping system on carbon sequestration in southern Malawi. Agric. Ecosyst. Environ. 118, 237–243 (2007).

    Article  CAS  Google Scholar 

  57. Kraft, P. et al. Modelling agroforestry’s contributions to people—a review of available models. Agronomy 11, 2106 (2021).

    Article  CAS  Google Scholar 

  58. Paustian, K. M. et al. in Precision Conservation: Geospatial Techniques for Agricultural and Natural Resources Conservation 361–384 (ASA and SSSA, 2018).

  59. Vezy, R. et al. DynACof: a process-based model to study growth, yield and ecosystem services of coffee agroforestry systems. Environ. Modell. Softw. 124, 104609 (2020).

    Article  Google Scholar 

  60. Masera, O. R. et al. Modeling carbon sequestration in afforestation, agroforestry and forest management projects: the CO2FIX V.2 approach. Ecol. Modell. 164, 177–199 (2003).

    Article  CAS  Google Scholar 

  61. Nair, P. R. & Nair, V. D. ‘Solid–fluid–gas’: the state of knowledge on carbon-sequestration potential of agroforestry systems in Africa. Curr. Opin. Environ. Sust. 6, 22–27 (2014).

    Article  Google Scholar 

  62. Beillouin, D. et al. A global overview of studies about land management, land‐use change, and climate change effects on soil organic carbon. Glob. Change Biol. 28, 1690–1702 (2022).

    Article  CAS  Google Scholar 

  63. Santoro, M. et al. The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations. Earth Syst. Sci. Data 13, 3927–3950 (2021).

    Article  Google Scholar 

  64. Blagodatsky, S., Xu, J. & Cadisch, G. Carbon balance of rubber (Hevea brasiliensis) plantations: a review of uncertainties at plot, landscape and production level. Agric. Ecosyst. Environ. 221, 8–19 (2016).

    Article  Google Scholar 

  65. Feng, Y. et al. Multispecies forest plantations outyield monocultures across a broad range of conditions. Science 376, 865–868 (2022).

    Article  CAS  Google Scholar 

  66. Kuyah, S. et al. Allometric equations for estimating biomass in agricultural landscapes: I. Aboveground biomass. Agric. Ecosyst. Environ. 158, 216–224 (2012).

    Article  Google Scholar 

  67. Zhou, X. et al. Analyzing the uncertainties in use of forest-derived biomass equations for open-grown trees in agricultural land. For. Sci. 61, 144–161 (2015).

    Article  Google Scholar 

  68. Kuyah, S. et al. Allometric equations for estimating biomass in agricultural landscapes: II. Belowground biomass. Agric. Ecosyst. Environ. 158, 225–234 (2012).

    Article  Google Scholar 

  69. Annighöfer, P. et al. Examination of aboveground attributes to predict belowground biomass of young trees. For. Ecol. Manage. 505, 119942 (2022).

    Article  Google Scholar 

  70. Axe, M. S., Grange, I. D. & Conway, J. S. Carbon storage in hedge biomass—a case study of actively managed hedges in England. Agric. Ecosyst. Environ. 250, 81–88 (2017).

    Article  Google Scholar 

  71. Cardinael, R. et al. Competition with winter crops induces deeper rooting of walnut trees in a Mediterranean alley cropping agroforestry system. Plant Soil 391, 219–235 (2015).

    Article  CAS  Google Scholar 

  72. Lian, X. et al. Biomass calculations of individual trees based on unmanned aerial vehicle multispectral imagery and laser scanning combined with terrestrial laser scanning in complex stands. Remote Sens. 14, 4715 (2022).

    Article  Google Scholar 

  73. Calders, K. et al. Laser scanning reveals potential underestimation of biomass carbon in temperate forest. Ecol. Solut. Évid. 3, e12197 (2022).

    Article  Google Scholar 

  74. Mugabowindekwe, M. et al. Nation-wide mapping of tree-level aboveground carbon stocks in Rwanda. Nat. Clim. Change https://doi.org/10.1038/s41558-022-01544-w (2022).

  75. Bambrick, A. D. et al. Spatial heterogeneity of soil organic carbon in tree-based intercropping systems in Quebec and Ontario, Canada. Agrofor. Syst. 79, 343–353 (2010).

    Article  Google Scholar 

  76. Cardinael, R. et al. High organic inputs explain shallow and deep SOC storage in a long-term agroforestry system—combining experimental and modeling approaches. Biogeosciences 15, 297–317 (2018).

    Article  CAS  Google Scholar 

  77. Wendt, J. W. & Hauser, S. An equivalent soil mass procedure for monitoring soil organic carbon in multiple soil layers. Eur. J. Soil Sci. 64, 58–65 (2013).

    Article  CAS  Google Scholar 

  78. Guenet, B. et al. Can N2O emissions offset the benefits from soil organic carbon storage? Glob. Change Biol. 27, 237–256 (2021).

    Article  CAS  Google Scholar 

  79. Iiyama, M. et al. The potential of agroforestry in the provision of sustainable woodfuel in sub-Saharan Africa. Curr. Opin. Environ. Sust. 6, 138–147 (2014).

    Article  Google Scholar 

  80. Williams, C. A., Gu, H. & Jiao, T. Climate impacts of U.S. forest loss span net warming to net cooling. Sci. Adv. 7, eaax8859 (2021).

    Article  CAS  Google Scholar 

  81. Rohatyn, S., Yakir, D., Rotenberg, E. & Carmel, Y. Limited climate change mitigation potential through forestation of the vast dryland regions. Science 377, 1436–1439 (2022).

    Article  CAS  Google Scholar 

  82. Oldfield, E. E. et al. Crediting agricultural soil carbon sequestration. Science 375, 1222–1225 (2022).

    Article  CAS  Google Scholar 

  83. Badgley, G. et al. California’s forest carbon offsets buffer pool is severely undercapitalized. Front. For. Glob. Change https://doi.org/10.3389/ffgc.2022.930426 (2022).

  84. Anderegg, W. R. L. et al. Climate-driven risks to the climate mitigation potential of forests. Science 368, eaaz7005 (2020).

    Article  CAS  Google Scholar 

  85. Damianidis, C. et al. Agroforestry as a sustainable land use option to reduce wildfires risk in European Mediterranean areas. Agrofor. Syst. 95, 919–929 (2021).

    Article  Google Scholar 

  86. Ndayambaje, J. D. & Mohren, G. M. J. Fuelwood demand and supply in Rwanda and the role of agroforestry. Agrofor. Syst. 83, 303–320 (2011).

    Article  Google Scholar 

  87. Villa, P. M. et al. Policy forum: shifting cultivation and agroforestry in the Amazon: premises for REDD. For. Policy Econ. 118, 102217 (2020).

    Article  Google Scholar 

  88. Ford, S. A. et al. Deforestation leakage undermines conservation value of tropical and subtropical forest protected areas. Glob. Ecol. Biogeogr. 29, 2014–2024 (2020).

    Article  Google Scholar 

  89. IPCC Special Report on Land Use, Land-Use Change and Forestry (eds Watson, R. T. et al.) 375 (Cambridge Univ. Press, 2000).

  90. Zomer, R. J. et al. Trees on Farms: An Update and Reanalysis of Agroforestry’s Global Extent and Socio-ecological Characteristics Working Paper 179 (ICRAF, 2014); https://doi.org/10.5716/wp14064.pdf

  91. Skole, D. L., Mbow, C., Mugabowindekwe, M., Brandt, M. S. & Samek, J. H. Trees outside of forests as natural climate solutions. Nat. Clim. Change 11, 1013–1016 (2021).

    Article  Google Scholar 

  92. Brandt, M. et al. An unexpectedly large count of trees in the West African Sahara and Sahel. Nature 587, 78–82 (2020).

    Article  Google Scholar 

  93. Thomas, N. et al. Trees outside forests are an underestimated resource in a country with low forest cover. Sci. Rep. 11, 7919 (2021).

    Article  CAS  Google Scholar 

  94. Brandt, J. & Stolle, F. A global method to identify trees outside of closed-canopy forests with medium-resolution satellite imagery. Int. J. Remote Sens. 42, 1713–1737 (2020).

    Article  Google Scholar 

  95. Sarti, M., Ciolfi, M., Lauteri, M., Paris, P. & Chiocchini, F. Trees outside forest in Italian agroforestry landscapes: detection and mapping using Sentinel-2 imagery. Eur. J. Remote Sens. 54, 610–624 (2021).

    Article  Google Scholar 

  96. Meneguzzo, D. M., Liknes, G. C. & Nelson, M. D. Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object-based classification approaches. Environ. Monit. Assess. 185, 6261–6275 (2013).

    Article  Google Scholar 

  97. Liknes, G. C., Meneguzzo, D. M. & Kellerman, T. A. Shape indexes for semi-automated detection of windbreaks in thematic tree cover maps from the central United States. Int. J. Appl. Earth Obs. 59, 167–174 (2017).

    Google Scholar 

  98. Batista, J. E. et al. Optical time series for the separation of land cover types with similar spectral signatures: cocoa agroforest and forest. Int. J. Remote Sens. 43, 3298–3319 (2022).

    Article  Google Scholar 

  99. Numbisi, F. N., Coillie, F. M. B. V. & Wulf, R. D. Delineation of cocoa agroforests using multiseason Sentinel-1 SAR images: a low grey level range reduces uncertainties in GLCM texture-based mapping. ISPRS Int. J. Geo inf. 8, 179 (2019).

    Article  Google Scholar 

  100. Kalischek, N. et al. Satellite-based high-resolution maps of cocoa planted area for Côte d’Ivoire and Ghana. Preprint at https://doi.org/10.48550/arXiv.2206.06119 (2022).

  101. Hunt, D. A. et al. Review of remote sensing methods to map coffee production systems. Remote Sens. 12, 2041 (2020).

    Article  Google Scholar 

  102. Xiao, J. et al. Remote sensing of the terrestrial carbon cycle: a review of advances over 50 years. Remote Sens. Environ. 233, 111383 (2019).

    Article  Google Scholar 

  103. Csillik, O., Kumar, P., Mascaro, J., O’Shea, T. & Asner, G. P. Monitoring tropical forest carbon stocks and emissions using Planet satellite data. Sci. Rep. 9, 17831 (2019).

    Article  Google Scholar 

  104. Tucker, C. et al. Sub-continental-scale carbon stocks of individual trees in African drylands. Nature 615, 80–86 (2023).

    Article  CAS  Google Scholar 

  105. Li, S. et al. Deep learning enables image-based tree counting, crown segmentation and height prediction at national scale. PNAS Nexus 2, pgad076 (2023).

    Article  Google Scholar 

  106. Durgun, Y. Ö., Gobin, A., Duveiller, G. & Tychon, B. A study on trade-offs between spatial resolution and temporal sampling density for wheat yield estimation using both thermal and calendar time. Int. J. Appl. Earth Obs. 86, 101988 (2020).

    Google Scholar 

  107. Zeng, Y. et al. Optical vegetation indices for monitoring terrestrial ecosystems globally. Nat. Rev. Earth Environ. https://doi.org/10.1038/s43017-022-00298-5 (2022).

  108. Bégué, A. et al. Remote sensing and cropping practices: a review. Remote Sens. 10, 99 (2018).

    Article  Google Scholar 

  109. Winkler, K., Fuchs, R., Rounsevell, M. & Herold, M. Global land use changes are four times greater than previously estimated. Nat. Commun. 12, 2501 (2021).

    Article  CAS  Google Scholar 

  110. Forest Monitoring Designed for Action (Global Forest Watch, 2002); http://www.globalforestwatch.org

  111. Increasing Ambition and Action in NDCs Through Forest Landscape Restoration (International Union for Conservation of Nature, 2018); https://www.iucn.org/theme/forests/our-work/forest-landscape-restoration/increasing-ambition-action-ndcs-through-flr

  112. Human Development Index (HDI) (United Nations Development Program, 2022); https://hdr.undp.org/en/indicators/137506

  113. Nair, P. R. The coming of age of agroforestry. J. Sci. Food Agr. 87, 1613–1619 (2007).

    Article  CAS  Google Scholar 

  114. Chrobak, U. Corporate climate pledges pile up—will it matter? Engineering 7, 1044–1046 (2021).

    Article  Google Scholar 

  115. Climate-Smart Agriculture and Forestry (CSAF) Mitigation Activities List FY 2023 (US Department of Agriculture Natural Resources Conservation Service, 2023); https://www.nrcs.usda.gov/sites/default/files/2023-01/CSAF%20Mitigation%20Activities_2023.pdf

  116. Proposal for a Regulation of the European Parliament and of the Council Establishing a Union Certification Framework for Carbon Removals (European Commission, 2022); https://climate.ec.europa.eu/system/files/2022-11/Proposal_for_a_Regulation_establishing_a_Union_certification_framework_for_carbon_removals.pdf

  117. Simonet, G. et al. ID-RECCO, International Database on REDD+ Projects and Programs: Linking Economics, Carbon and Communities v.4.2 (CIFOR, CEC, CIRAD, IFRI, 2020); https://www.reddprojectsdatabase.org

  118. Programa Jurisdicional de REDD+ do Acre do Sistema de Incentivos ao Serviço Ambiental do Carbono (ISA Carbono) (Instituto de Mudanças Climáticas e Regulação de Serviços Ambientais, 2018); http://repositorio.enap.gov.br/handle/1/3616

  119. Mansourian, S. et al. Putting the pieces together: integration for forest landscape restoration implementation. Land Degrad. Dev. 31, 419–429 (2020).

    Article  Google Scholar 

  120. Bettles, J. et al. Agroforestry and non-state actors: a review. For. Policy Econ. 130, 102538 (2021).

    Article  Google Scholar 

  121. Schulte, I., Eggers, J., Nielsen, J. Ø. & Fuss, S. What influences the implementation of natural climate solutions? A systematic map and review of the evidence. Environ. Res. Lett. 17, 013002 (2022).

    Article  Google Scholar 

  122. Rois-Díaz, M. et al. Farmers’ reasoning behind the uptake of agroforestry practices: evidence from multiple case-studies across Europe. Agrofor. Syst. 92, 811–828 (2018).

    Article  Google Scholar 

  123. Shyamsundar, P. et al. Scaling smallholder tree cover restoration across the tropics. Glob. Environ. Change 76, 102591 (2022).

    Article  Google Scholar 

  124. Kay, S. et al. Agroforestry is paying off—economic evaluation of ecosystem services in European landscapes with and without agroforestry systems. Ecosyst. Serv. 36, 100896 (2019).

    Article  Google Scholar 

  125. Sinclair, F. & Coe, R. The options by context approach: a paradigm shift in agronomy. Exp. Agric. 55, 1–13 (2019).

    Article  Google Scholar 

Download references

Acknowledgements

We thank the Bezos Earth Fund for their generous grant to the Nature Conservancy, which funded the time of D.E.T.H., M.A., S.Y., S.W. and S.C.C.-P. We also thank all attendees of the Nature Conservancy’s 2021 workshop ‘Agroforestry as a Natural Climate Solution: Cultivating the Science’, for their engagement and eager contributions to the discussion and debate that developed into this work. We thank N. Wolff, L. Marx, P. Alava and others for their reading and feedback on earlier drafts. We thank V. Reed at Vin Design for his detailed and persistent work in finalizing Fig. 1. T.S.R. was supported by the One CGIAR Livestock and Climate Initiative. B.T. was partly supported by the University of Missouri Center for Agroforestry and the US Department of Agriculture, Agricultural Research Service, under agreement no. 58-6020-0-007; any opinions, findings, conclusion or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the US Department of Agriculture.

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Authors and Affiliations

  1. The Nature Conservancy, Arlington, VA, USA

    Drew E. Terasaki Hart, Samantha Yeo, Maya Almaraz, Stephen Wood & Susan C. Cook-Patton

  2. High Meadows Environmental Institute, Princeton University, Princeton, NJ, USA

    Maya Almaraz

  3. CIRAD, UPR HortSys, Le Lamentin, Martinique, France

    Damien Beillouin

  4. HortSys, Université Montpellier, Montpellier, France

    Damien Beillouin

  5. AIDA, Université Montpellier, CIRAD, Montpellier, France

    Rémi Cardinael

  6. CIRAD, UPR AIDA, Harare, Zimbabwe

    Rémi Cardinael

  7. Department of Plant Production Sciences and Technologies, University of Zimbabwe, Harare, Zimbabwe

    Rémi Cardinael

  8. The Nature Conservancy, Brasilia, Brazil

    Edenise Garcia

  9. Agricultural Landscape and Biodiversity Group, Agroscope, Zurich, Switzerland

    Sonja Kay

  10. Center for Agroforestry, University of Missouri, Columbia, MO, USA

    Sarah Taylor Lovell & Bhuwan Thapa

  11. Lovell Farm & Ranch, LLC, Milton, TN, USA

    Sarah Taylor Lovell

  12. Alliance of Bioversity International and International Center for Tropical Agriculture (Bioversity-CIAT), Montpellier, France

    Todd S. Rosenstock

  13. Conservation International, Arlington, VA, USA

    Starry Sprenkle-Hyppolite

  14. World Resources Institute, Washington, DC, USA

    Fred Stolle

  15. World Agroforestry (ICRAF) as part of CIFOR-ICRAF, Lima, Peru

    Marta Suber

  16. Yale School of the Environment, New Haven, CT, USA

    Stephen Wood

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  1. Drew E. Terasaki Hart
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Contributions

D.E.T.H., S.C.C.-P., S.Y., M.A., D.B., R.C., S.K., T.S.R., S.S.-H., F.S., M.S., B.T. and S.W. conceived the study and analyses. D.E.T.H., S.C.C.-P., S.Y., R.C., T.S.R., M.S. and B.T. gathered the data. D.E.T.H. analysed the data and prepared the figures, with input from all authors. D.E.T.H. and S.C.C.-P. wrote the manuscript, with contributions from all authors.

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Correspondence to Drew E. Terasaki Hart.

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Nature Climate Change thanks Martin Brandt, Manoj Jhariya and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Figs. 1–5, Table 1 and Methods.

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Terasaki Hart, D.E., Yeo, S., Almaraz, M. et al. Priority science can accelerate agroforestry as a natural climate solution. Nat. Clim. Chang. 13, 1179–1190 (2023). https://doi.org/10.1038/s41558-023-01810-5

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