Appendix A — References

Archibald, S., & Bond, W. J. (2003). Growing tall vs. Growing wide: Tree architecture and allometry of acacia karroo in forest, savanna, and arid environments. Oikos (Copenhagen, Denmark), 102(1), 3–14. https://doi.org/10.1034/j.1600-0706.2003.12181.x

Armstrong, J. S. (1978). Long-range forecasting: From crystal ball to computer (2nd ed.). Wiley.

ART. (2021). The REDD+ environmental excellence standard (2.0 ed.). https://www.artredd.org/wp-content/uploads/2021/12/TREES-2.0-August-2021-Clean.pdf

Baillie, R., & Wagstaff, S. S. (1980). Lucas pseudoprimes. Mathematics of Computation, 35(152), 1391–1417.

Ballantyne, A., Andres, R., Houghton, R., Stocker, B., Wanninkhof, R., Anderegg, W., Cooper, L., DeGrandpre, M., Tans, P., Miller, J., & al., et. (2015). Audit of the global carbon budget: Estimate errors and their impact on uptake uncertainty. Biogeosciences (Online), 12(8), 2565–2584.

Bohlman, S., & O’Brien, S. (2006). Allometry, adult stature and regeneration requirement of 65 tree species on barro colorado island, panama. Journal of Tropical Ecology, 22(2), 123–136.

Brown, S. (1997). Estimating biomass and biomass change of tropical forests: A primer. Food and agriculture organization of the united nations.

Butler, B. J., Sass, E. M., Gamarra, J. G., Campbell, J. L., Wayson, C., Olguıń, M., Carrillo, O., & Yanai, R. D. (2024). Uncertainty in REDD+ carbon accounting: A survey of experts involved in REDD+ reporting. Carbon Balance and Management, 19(1), 22.

Camara, G., Simoes, R., Souza, F., Menino, F., Pelletier, C., Andrade, P. R., Ferreira, K., & Queiroz, G. (2024). Uncertainty and active learning analysis. In Satellite time series on earth observation data cubes. https://e-sensing.github.io/sitsbook/uncertainty-and-active-learning.html#uncertainty-and-active-learning

Cao, S., Yu, Q., & Zhang, J. (2012). Automatic division for pure/mixed pixels based on probabilities entropy and spatial heterogeneity. 2012 First International Conference on Agro-Geoinformatics (Agro-Geoinformatics), 1–4.

Chave, J., Coomes, D., Jansen, S., Lewis, S. L., Swenson, N. G., & Zanne, A. E. (2009). Towards a worldwide wood economics spectrum. Ecology Letters, 12(4), 351–366.

Chave, J., Réjou-Méchain, M., Búrquez, A., Chidumayo, E., Colgan, M. S., Delitti, W. B., Duque, A., Eid, T., Fearnside, P. M., Goodman, R. C., & al., et. (2014). Improved allometric models to estimate the aboveground biomass of tropical trees. Global Change Biology, 20(10), 3177–3190.

Crawford, M. M., Tuia, D., & Yang, H. L. (2013). Active learning: Any value for classification of remotely sensed data? Proceedings of the IEEE, 101(3), 593–608.

Dietze, M. C., Wolosin, M. S., & Clark, J. S. (2008). Capturing diversity and interspecific variability in allometries: A hierarchical approach. Forest Ecology and Management, 256(11), 1939–1948.

Duncanson, L., Disney, M., Armston, J., Nickeson, J., Minor, D., & Camacho, F. (2021). Aboveground woody biomass product validation good practices protocol. https://doi.org/10.5067/DOC/CEOSWGCV/LPV/AGB.001

Enquist, B. J., West, G. B., Charnov, E. L., & Brown, J. H. (1999). Allometric scaling of production and life-history variation in vascular plants. Nature, 401(6756), 907–911.

Feldpausch, T. R., Banin, L., Phillips, O. L., Baker, T. R., Lewis, S. L., Quesada, C. A., Affum-Baffoe, K., Arets, E. J., Berry, N. J., Bird, M., & al., et. (2011). Height-diameter allometry of tropical forest trees. Biogeosciences (Online), 8(5), 1081–1106.

Frénay, B., & Verleysen, M. (2013). Classification in the presence of label noise: A survey. IEEE Transactions on Neural Networks and Learning Systems, 25(5), 845–869.

Gonzalez-Akre, E., Piponiot, C., Lepore, M., & Anderson-Teixeira, K. (2025). Allodb: Tree biomass estimation at extra-tropical forest plots.

Gonzalez-Akre, E., Piponiot, C., Lepore, M., Herrmann, V., Lutz, J. A., Baltzer, J. L., Dick, C. W., Gilbert, G. S., He, F., Heym, M., & al., et. (2022). Allodb: An r package for biomass estimation at globally distributed extratropical forest plots. Methods in Ecology and Evolution, 13(2), 330–338.

Gould, S. J. (1966). Allometry and size in ontogeny and phylogeny. Biological Reviews, 41(4), 587–638.

Gould, S. J. (1971). Geometric similarity in allometric growth: A contribution to the problem of scaling in the evolution of size. The American Naturalist, 105(942), 113–136.

Hijmans, R. J. (2025). Terra: Spatial data analysis. https://CRAN.R-project.org/package=terra

Huxley, J. S. (1924). Constant differential growth-ratios and their significance. Nature, 114(2877), 895–896.

IPCC. (n.d.). 2013 revised supplementary methods and good practice guidance arising from the kyoto protocol.

IPCC. (2012). Report of the conference of the parties serving as the meeting of the parties to the kyoto protocol on its seventh session,. FCCC/KP/CMP/2011/10(Durban Meeting November 28th to December 11th, 2011), 824.

IPCC. (2019a). 2019 refinement to the 2006 IPCC guidelines for national greenhouse gas inventories (Agriculture, Forestry and Other Land Use, Vol. 4). Intergovernmental Panel on Climate Change. https://www.ipcc-nggip.iges.or.jp/public/2019rf/vol4.html

IPCC. (2019b). Chapter 2: Generic methodologies applicable to multiple land-use categories. In 2019 refinement to the 2006 IPCC guidelines for national greenhouse gas inventories (Agriculture, Forestry and Other Land Use, Vol. 4). Intergovernmental Panel on Climate Change. https://www.ipcc-nggip.iges.or.jp/public/2019rf/pdf/4_Volume4/19R_V4_Ch02_Generic%20Methods.pdf

Jansen, J. J., Sevenster, J., & Faber, J. and. (1996). Opbrengsttabellen voor belangrijke boomsoorten in nederland. IBN-DLO.

Jenkins, J. C. (2004). Comprehensive database of diameter-based biomass regressions for north american tree species. United States Department of Agriculture, Forest Service, Northeastern ….

King, D. A. (1996). Allometry and life history of tropical trees. Journal of Tropical Ecology, 12(1), 25–44.

King, D. A., & Clark, D. A. (2011). Allometry of emergent tree species from saplings to above-canopy adults in a costa rican rain forest. Journal of Tropical Ecology, 27(6), 573–579.

Köhler, P., & Huth, A. (2010). Towards ground-truthing of spaceborne estimates of above-ground life biomass and leaf area index in tropical rain forests. Biogeosciences (Online), 7(8), 2531–2543.

Komiyama, A., Ong, J. E., & Poungparn, S. (2008). Allometry, biomass, and productivity of mangrove forests: A review. Aquatic Botany, 89(2), 128–137. https://doi.org/10.1016/j.aquabot.2007.12.006

Komiyama, A., Poungparn, S., & Kato, S. (2005). Common allometric equations for estimating the tree weight of mangroves. Journal of Tropical Ecology, 21(4), 471–477.

Kuhn, M. (2011). The caret package.

Maxwell, A. E., Warner, T. A., & Fang, F. (2018). Implementation of machine-learning classification in remote sensing: An applied review. International Journal of Remote Sensing, 39(9), 2784–2817.

Metropolis, N., & Ulam, S. (1949). The monte carlo method. Journal of the American Statistical Association, 44(247), 335–341.

Muller-Landau, H. C., Condit, R. S., Chave, J., Thomas, S. C., Bohlman, S. A., Bunyavejchewin, S., Davies, S., Foster, R., Gunatilleke, S., Gunatilleke, N., & al., et. (2006). Testing metabolic ecology theory for allometric scaling of tree size, growth and mortality in tropical forests. Ecology Letters, 9(5), 575–588.

Murray, S. H. (2003). The schreier-sims algorithm. Essay Submitted to the Department of Mathematics of the Australian National University.

Paul, K. I., Roxburgh, S. H., & Larmour, J. S. (2017). Moisture content correction: Implications of measurement errors on tree-and site-based estimates of biomass. Forest Ecology and Management, 392, 164–175.

Pelletier, J., Martin, D., & Potvin, C. (2013). REDD+ emissions estimation and reporting: Dealing with uncertainty. Environmental Research Letters, 8(3), 034009.

Picard, N., Saint-Andre, L., & Henry, M. (2012). Manual for building tree volume and biomass allometric equations: From field measurement to prediction. Food and agriculture organization of the united nations, centre de cooperation internationale en recherche agronomique pour le developpement.

Rahman, M. S., Donoghue, D. N., Bracken, L. J., & Mahmood, H. (2021). Biomass estimation in mangrove forests: A comparison of allometric models incorporating species and structural information. Environmental Research Letters, 16(12), 124002.

Réjou-Méchain, M., Tanguy, A., Piponiot, C., Chave, J., & Herault, B. (2017a). BIOMASS : An r package for estimating above-ground biomass and its uncertainty in tropical forests. 8. https://doi.org/10.1111/2041-210X.12753

Réjou-Méchain, M., Tanguy, A., Piponiot, C., Chave, J., & Herault, B. (2017b). BIOMASS : An r package for estimating above-ground biomass and its uncertainty in tropical forests. 8. https://doi.org/10.1111/2041-210X.12753

Réjou-Méchain, M., Tanguy, A., Piponiot, C., Chave, J., & Hérault, B. (2017). Biomass: An r package for estimating above-ground biomass and its uncertainty in tropical forests. Methods in Ecology and Evolution, 8(9), 1163–1167.

Rocha de Souza Pereira, F., Kampel, M., Gomes Soares, M. L., Estrada, G. C. D., Bentz, C., & Vincent, G. (2018). Reducing uncertainty in mapping of mangrove aboveground biomass using airborne discrete return lidar data. Remote Sensing, 10(4), 637.

Roxburgh, S., Paul, K., Clifford, D., England, J., & Raison, R. (2015). Guidelines for constructing allometric models for the prediction of woody biomass: How many individuals to harvest? Ecosphere (Washington, D.C), 6(3), 1–27.

Rutishauser, E., Noor’an, F., Laumonier, Y., Halperin, J., Hergoualc’h, K., Verchot, L., et al. (2013). Generic allometric models including height best estimate forest biomass and carbon stocks in indonesia. Forest Ecology and Management, 307, 219–225.

Schrodt, F., Beck, M., Estopinan, J., Bowler, D. E., Fontaine, C., Gaüzère, P., Goury, R., Grenié, M., Martins, I. S., Morueta-Holme, N., & al., et. (2025). Advancing causal inference in ecology: Pathways for biodiversity change detection and attribution. Methods in Ecology and Evolution, 16(10), 2276–2304.

Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379–423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x

Sheynin, O. B. (1989). AA markov’s work on probability. Archive for History of Exact Sciences, 39(4), 337–377.

Shinozaki, K., Yoda, K., Hozumi, K., & Kira, T. (1964). A quantitative analysis of plant form-the pipe model theory: I. Basic analyses. Japanese Journal of Ecology, 14(3), 97–105.

Simoes, R., Camara, G., Queiroz, G., Souza, F., Andrade, P. R., Santos, L., Carvalho, A., & Ferreira, K. (2021). Satellite image time series analysis for big earth observation data. Remote Sensing, 13(13), 2428.

Solovay, R., & Strassen, V. (1977). A fast monte-carlo test for primality. SIAM Journal on Computing, 6(1), 84–85.

Sornette, D. (2006). Critical phenomena in natural sciences: Chaos, fractals, selforganization and disorder: Concepts and tools. Springer.

Tarazona Coronel, Y., Zabala, A., Pons, X., Broquetas, A., Nowosad, J., & A. Zurqani, H. (2021). Fusing landsat and SAR data for mapping tropical deforestation through machine learning classification and the PVts-β non-seasonal detection approach. https://doi.org/10.1080/07038992.2021.1941823

UNFCCC, C. (2010). Report of the conference of the parties on its fifteenth session, held in copenhagen from 7 to 19 december 2009. FCCC/CP/2009/11/Add. 1.

Valbuena, R., Heiskanen, J., Aynekulu, E., Pitkänen, S., & Packalen, P. (2016). Sensitivity of above-ground biomass estimates to height-diameter modelling in mixed-species west african woodlands. PloS One, 11(7), e0158198.

Vieilledent, G., Fischer, F. J., Chave, J., Guibal, D., Langbour, P., & Gérard, J. (2018). New formula and conversion factor to compute basic wood density of tree species using a global wood technology database. American Journal of Botany, 105(10), 1653–1661.

West, G. B., Brown, J. H., & Enquist, B. J. (1997). A general model for the origin of allometric scaling laws in biology. Science, 276(5309), 122–126.

Zianis, D., & Mencuccini, M. (2004). On simplifying allometric analyses of forest biomass. Forest Ecology and Management, 187(2-3), 311–332.