CIFOR - Center for International Forestry Research IRSNB - Koninklijk Belgisch Instituut voor Natuurwetenschappen ANR - Agence Nationale de la Recherche IFS - International Foundation for Science
Adame, P., Brandeis, T.J., Uriarte, M., Diameter growth performance of tree functional groups in Puerto Rican secondary tropical forests. For. Syst. 23 (2014), 52–63, 10.5424/fs/2014231-03644.
Anderson, E.C., Winter, D.J., 2020. Simple Features for R. Package “sf” (version 0.9.2).
Antin, C., Pélissier, R., Vincent, G., Couteron, P., Crown allometries are less responsive than stem allometry to tree size and habitat variations in an Indian monsoon forest. Trees - Struct. Funct. 27 (2013), 1485–1495, 10.1007/s00468-013-0896-7.
Araujo, R.F., Chambers, J.Q., Celes, C.H.S., Muller-Landau, H.C., Santos, A.P.F., Emmert, F., Ribeiro, G.H.P.M., Gimenez, B.O., Lima, A.J.N., Campos, M.A.A., Higuchi, N., Integrating high resolution drone imagery and forest inventory to distinguish canopy and understory trees and quantify their contributions to forest structure and dynamics. PLoS One, 1–16, 2020, 10.1371/journal.pone.0243079.
Baker, T., Swaine, M., Burslem, D., Variation in tropical forest growth rates: combined effects of functional group composition and resource availability. Perspect. Plant Ecol. Evol. Syst. 6 (2003), 21–36, 10.1078/1433-8319-00040.
Ball, J.G.C., Hickman, S.H.M., Jackson, T.D., Koay, X.J., Hirst, J., Jay, W., Archer, M., Coomes, D.A., Accurate delineation of individual tree crowns in tropical forests from aerial RGB imagery using Mask R-CNN. Remote Sens. Ecol. Conserv., 1–14, 2023, 10.1002/rse2.332.
Barros de Oliveira, E.K., Rezende, A.V., Mazzei, L., Murta Júnior, L.S., Oliveira Castro, R.V., Neves d'Oliveira, M.V., Barros, Q.S., Competition indices after reduced impact logging in the Brazilian Amazon. J. Environ. Manage., 281, 2021, 10.1016/j.jenvman.2020.111898.
Bastin, J., Barbier, N., Réjou-Méchain, M., Fayolle, A., Gourlet-Fleury, S., Maniatis, D., de Haulleville, T., Baya, F., Beeckman, H., Beina, D., Couteron, P., Chuyong, G., Dauby, G., Doucet, J.-L., Droissart, V., Dufrêne, M., Ewango, C., Gillet, J.F., Gommadje, C.H., Hart, T., Kavali, T., Kenfack, D., Libalah, M., Malhi, Y., Makana, J.-R., Pélissier, R., Ploton, P., Serkx, A., Sonké, B., Stevart, T., Thomas, D.W., Cannière, C.D., Bogaert, J., Seeing Central African forests through their largest trees. Nat. Publ. Gr., 1–8, 2015, 10.1038/srep13156.
Bénédet, F., Doucet, J.-L., Fayolle, A., Gillet, J.-F., Gourlet-Fleury, S., Vincke, D., CoForTraits, base de données d'information sur les traits des espèces d'arbres africaines. Version, 1, 2013, 2018.
Biging, G.S., Evaluation of competition indices in individual tree growth models. For. Sci. 41 (1995), 360–377, 10.1093/forestscience/41.2.360.
Blanchard, E., Birnbaum, P., Ibanez, T., Boutreux, T., Antin, C., Ploton, P., Vincent, G., Pouteau, R., Vandrot, H., Hequet, V., Barbier, N., Droissart, V., Sonké, B., Texier, N., Kamdem, N.G., Zebaze, D., Libalah, M., Couteron, P., Contrasted allometries between stem diameter, crown area, and tree height in five tropical biogeographic areas. Trees-Struct. Funct. 30 (2016), 1953–1968, 10.1007/s00468-016-1424-3.
Bry, X., Trottier, C., Verron, T., Mortier, F., Supervised component generalized linear regression using a PLS-extension of the Fisher scoring algorithm. J. Multivar. Anal. 119 (2013), 47–60, 10.1016/j.jmva.2013.03.013.
Burkhart, H.E., Tomé, M., 2012. Modeling forest trees and stands. Model. For. Trees Stands 9789048131, 1–457. doi: 10.1007/978-90-481-3170-9.
Caha, J., 2023. Qgis: An extension of package “qgisprocess” providing direct R functions for QGIS functions. Version 0.0.0.9000.
Carrillo, G., 2015. vec2dtransf: 2D Cartesian Coordinate Transformation. R package version 1.1. doi: https://CRAN.R-project.org/package=vec2dtransf.
Charbonnier, F., Roupsard, O., Maire, G., Guillemot, J., Casanoves, F., Lacointe, A., Vaast, P., Allinne, C., Audebert, L., Cambou, A., Clément-vidal, A., Defrenet, E., Duursma, R.A., 2017. Increased light-use efficiency sustains net primary productivity of shaded coffee plants in agroforestry system 1592–1608. doi: 10.1111/pce.12964.
Cole, W.G., Lorimer, C.G., Predicting tree growth from crown variables in managed northern hardwood stands. For. Ecol. Manage. 67 (1994), 159–175, 10.1016/0378-1127(94)90014-0.
Dandois, J.P., Ellis, E.C., High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision. Remote Sens. Environ. 136 (2013), 259–276, 10.1016/j.rse.2013.04.005.
Davies, S.J., Tree Mortality and Growth in 11 Sympatric Macaranga Species in Borneo. Ecology, 82, 2001, 920, 10.2307/2679892.
Dawkins, H.C., 1958. The management of natural tropical high- forests with special reference to Uganda. Imperial Forestry Institute, University of Oxford. Institute Paper 34, p. 155.
del Rio, M., Condés, S., Pretzsch, H., Analyzing size-symmetric vs. size-asymmetric and intra-vs. inter-specific competition in beech (Fagus sylvatica L.) mixed stands. For. Ecol. Manage. 325 (2014), 90–98, 10.1016/j.foreco.2014.03.047.
Dos Santos, A.A., Marcato Junior, J., Araújo, M.S., Di Martini, D.R., Tetila, E.C., Siqueira, H.L., Aoki, C., Eltner, A., Matsubara, E.T., Pistori, H., Feitosa, R.Q., Liesenberg, V., Gonçalves, W.N., Assessment of CNN-based methods for individual tree detection on images captured by RGB cameras attached to UAVS. Sensors (switzerland) 19 (2019), 1–11, 10.3390/s19163595.
Fayolle, A., Swaine, M.D., Bastin, J.F., Bourland, N., Comiskey, J.A., Dauby, G., Doucet, J.L., Gillet, J.F., Gourlet-Fleury, S., Hardy, O.J., Kirunda, B., Kouamé, F.N., Plumptre, A.J., Patterns of tree species composition across tropical African forests. J. Biogeogr. 41 (2014), 2320–2331, 10.1111/jbi.12382.
Filipescu, C.N., Groot, A., Maclsaac, D.A., Cruickshank, M.G., Stewart, J.D., Prediction of diameter using height and crown attributes: a case study. West. J. Appl. for. 27 (2012), 30–35, 10.1093/wjaf/27.1.30.
Foli, E.G., Alder, D., Miller, H.G., Swaine, M.D., Modelling growing space requirements for some tropical forest tree species. For. Ecol. Manage. 173 (2003), 79–88.
Franc, A., Gourlet-Fleury, S., Picard, N., Une introduction à la modélisation des forêts hétérogènes. ENGREF. ed., 2000, Nancy, France.
Getzin, S., Wiegand, K., Schöning, I., Assessing biodiversity in forests using very high-resolution images and unmanned aerial vehicles. Methods Ecol. Evol. 3 (2012), 397–404, 10.1111/j.2041-210X.2011.00158.x.
Gourlet-Fleury, S.G.-, Rossi, V., Forni, E., Fayolle, A., Allah-, G.L.F., Fidèle, B., Fabrice, B., Boyemba, F., Cornu, G., Doucet, L., Gillet, J.-F., Mazengue, M., Mbasi, M., Hoef, Y. Van, Zombo, I., Freycon, V., 2023. Competition and site weakly explain tree growth variability in undisturbed Central African moist forests. J. Ecol. 00, 1–18. doi: 10.1111/1365-2745.14152.
Gourlet-Fleury, S., Houllier, F., Modelling diameter increment in a lowland evergreen rain forest in French Guiana. For. Ecol. Manage. 131 (2000), 269–289, 10.1016/S0378-1127(99)00212-1.
Guerra-Hernández, J., González-Ferreiro, E., Monleón, V.J., Faias, S.P., Tomé, M., Díaz-Varela, R.A., Use of multi-temporal UAV-derived imagery for estimating individual tree growth in Pinus pinea stands. Forests 8 (2017), 1–19, 10.3390/f8080300.
Hijmans, R.J., Etten, J. van, Sumner, M., Cheng, J., Bevan, A., Bevan, R., Busetto, L., Canty, M., Forrest, D., Ghosh, A., Golicher, D., Gray, J., Greenberg, J.A., 2020. Raster : Geographic Data Analysis and Modeling (version 3.5-2). Cran 1–249.
Hofierka, J., Suri, M., 2002. The Solar Radiation model for Open Source GIS: implementation and applications, in: Proceedings of the Open Source GIS - GRASS Users Conference 2002. Trento, Italy, p. 20.
Järnstedt, J., Pekkarinen, A., Tuominen, S., Ginzler, C., Holopainen, M., Viitala, R., Forest variable estimation using a high-resolution digital surface model. ISPRS J. Photogramm. Remote Sens. 74 (2012), 78–84, 10.1016/j.isprsjprs.2012.08.006.
Kattenborn, T., Eichel, J., Fassnacht, F.E., Convolutional Neural Networks enable efficient, accurate and fine- grained segmentation of plant species and communities from high-resolution UAV imagery. Sci. Rep., 1–10, 2019, 10.1038/s41598-019-53797-9.
Laurans, M., Hérault, B., Vieilledent, G., Vincent, G., Vertical stratification reduces competition for light in dense tropical forests. For. Ecol. Manage. 329 (2014), 79–88, 10.1016/j.foreco.2014.05.059.
Ligot, G., Gourlet-fleury, S., Dainou, K., Gillet, J., Rossi, V., Mazengu, M., Nna, S., Serge, Y., Zombo, I., Forni, E., Doucet, J., Tree growth and mortality of 42 timber species in central Africa. For. Ecol. Manage., 505, 2022, 13, 10.1016/j.foreco.2021.119889.
Lisein, J., Linchant, J., Lejeune, P., 2013. Aerial surveys using an Unmanned Aerial System (UAS): comparison of different methods for estimating the surface area of sampling strips 6, 506–520.
Loubota Panzou, G.J., Ligot, G., Gourlet-Fleury, S., Doucet, J.L., Forni, E., Loumeto, J.J., Fayolle, A., Architectural differences associated with functional traits among 45 coexisting tree species in Central Africa. Funct. Ecol., 1–11, 2018, 10.1111/1365-2435.13198.
Ma, Q., Su, Y., Tao, S., Guo, Q., Quantifying individual tree growth and tree competition using bi-temporal airborne laser scanning data: a case study in the Sierra Nevada Mountains. California. Int. J. Digit. Earth 11 (2018), 485–503, 10.1080/17538947.2017.1336578.
Messinger, M., Asner, G.P., Silman, M., Rapid Assessments of Amazon Forest Structure and Biomass Using Small Unmanned Aerial Systems. Remote Sens. 8 (2016), 1–15, 10.3390/rs8080615.
Michez, A., Piégay, H., Lisein, J., Claessens, H., Lejeune, P., Classification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system. Environ. Monit. Assess., 2016, 10.1007/s10661-015-4996-2.
Morales, G., Kemper, G., Sevillano, G., Arteaga, D., Ortega, I., Telles, J., Automatic segmentation of Mauritia flexuosa in unmanned aerial vehicle (UAV) imagery using deep learning. Forests, 9, 2018, 10.3390/f9120736.
Moravie, M.-A., Durand, M., Houllier, F., Ecological meaning and predictive ability of social status, vigour and competition indices in a tropical rain forest (India). For. Ecol. Manage. 117 (1999), 221–240, 10.1016/S0378-1127(98)00480-0.
Mortier, F., Chauvet, J., Trottier, C., Cornu, G., Bry, X., 2017. La régression linéaire généralisée sur composantes supervisées et ses extensions. p. 21.
Ndamiyehe, N.J.B., Lejeune, P., Gourlet-Fleury, S., Fayolle, A., Mianda-Bungi, L.N., Ligot, G., Quantifier les dimensions des houppiers à l'aide d'images aériennes à haute résolution pour estimer l'accroissement diamétrique des arbres dans les forêts d'Afrique centrale. Bois Forets Des Trop. 343 (2020), 67–81, 10.19182/bft2020.343.a31848.
Ocer, N.E., Kaplan, G., Erdem, F., Matci, D.K., Tree extraction from multi-scale UAV images using Mask R-CNN with FPN. Remote Sens. Lett. 11 (2020), 847–856, 10.1080/2150704X.2020.1784491.
Olpenda, A.S., Sterenczak, K., Bedkowski, K., Modeling Solar Radiation in the Forest Using Remote Sensing Data : A Review of Approaches and Opportunities. Remote Sens., 10, 2018, 22, 10.3390/rs10050694.
Paneque-gálvez, J., Mccall, M.K., Napoletano, B.M., Wich, S.A., Koh, L.P., Small Drones for Community-Based Forest Monitoring: An Assessment of Their Feasibility and Potential in Tropical Areas. Forests 5 (2014), 1481–1507, 10.3390/f5061481.
PhotoScan, 2015. Agisoft PhotoScan Manuel de l'utilisateur. Profes- sional Edition, version 1.1.
Picard, N., Gourlet-Fleury, S., 2008. Manuel de référence pour l'installation de dispositifs permanents en forêt de production dans le Bassin du Congo. CIRAD-COMIFAC.
Picard, N., Boyemba, F., Rossi, V., Reducing the error in biomass estimates strongly depends on model selection. Ann. for. Sci. 72 (2015), 811–823, 10.1007/s13595-014-0434-9.
Popescu, S.C., Wynne, R.H., Nelson, R.F., 2003. Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass 29, 564–577.
Prévosto, B., Les indices de compétition en for esterie : exemples d'utilisation, intérêts et limites. Rev. for. Fr. LVII, 2005, 413–430.
Price, B., Waser, L.T., Wang, Z., Marty, M., Ginzler, C., Zellweger, F., Predicting biomass dynamics at the national extent from digital aerial photogrammetry. Int. J. Appl. Earth Obs. Geoinf., 90, 2020, 102116, 10.1016/j.jag.2020.102116.
Purves, D., Pacala, S., 2013. Predictive Models of Forest Dynamics. Science (80-.). 342, 776–776. doi: 10.1126/science.342.6160.776-d.
QGIS Development Team, 2020. QGIS Geographic Information System. Open Source Geospatial Foundation.
R Core Team, R: A Language and Environment for Statistical Computing (Version 4.1.1). 2021, R Foundation for Statistical Computing, Vienna, Austria.
Rasmussen, C.R., Weiner, J., Modelling the effect of size-asymmetric competition on size inequality: Simple models with two plants. Ecol. Modell. 343 (2017), 101–108, 10.1016/j.ecolmodel.2016.10.011.
Réjou-Méchain, M., Mortier, F., Bastin, J.F., Cornu, G., Barbier, N., Bayol, N., Bénédet, F., Bry, X., Dauby, G., Deblauwe, V., Doucet, J.L., Doumenge, C., Fayolle, A., Garcia, C., Kibambe Lubamba, J.P., Loumeto, J.J., Ngomanda, A., Ploton, P., Sonké, B., Trottier, C., Vimal, R., Yongo, O., Pélissier, R., Gourlet-Fleury, S., Unveiling African rainforest composition and vulnerability to global change. Nature 593 (2021), 90–94, 10.1038/s41586-021-03483-6.
Rozendaal, D.M.A., Phillips, O.L., Lewis, S.L., Affum-Baffoe, K., Alvarez-Davila, E., Andrade, A., Aragão, L.E.O.C., Araujo-Murakami, A., Baker, T.R., Bánki, O., Brienen, R.J.W., Camargo, J.L.C., Comiskey, J.A., Djuikouo Kamdem, M.N., Fauset, S., Feldpausch, T.R., Killeen, T.J., Laurance, W.F., Laurance, S.G.W., Lovejoy, T., Malhi, Y., Marimon, B.S., Marimon Junior, B.H., Marshall, A.R., Neill, D.A., Núñez Vargas, P., Pitman, N.C.A., Poorter, L., Reitsma, J., Silveira, M., Sonké, B., Sunderland, T., Taedoumg, H., ter Steege, H., Terborgh, J.W., Umetsu, R.K., van der Heijden, G.M.F., Vilanova, E., Vos, V., White, L.J.T., Willcock, S., Zemagho, L., Vanderwel, M.C., Competition influences tree growth, but not mortality, across environmental gradients in Amazonia and tropical Africa. Ecology 101 (2020), 1–11, 10.1002/ecy.3052.
Rüger, N., Berger, U., Hubbell, S.P., Vieilledent, G., Condit, R., Growth strategies of tropical tree species: Disentangling light and size effects. PLoS One, 6, 2011, 10.1371/journal.pone.0025330.
Rutishauser, E., Wagner, F., Herault, B., Nicolini, E.A., Blanc, L., Contrasting above-ground biomass balance in a Neotropical rain forest. J. Veg. Sci. 21 (2010), 672–682, 10.1111/j.1654-1103.2010.01175.x.
Rutishauser, E., Barthélémy, D., Blanc, L., Eric-André, N., Crown fragmentation assessment in tropical trees: Method, insights and perspectives. For. Ecol. Manage. 261 (2011), 400–407, 10.1016/j.foreco.2010.10.025.
Schiefer, F., Kattenborn, T., Frick, A., Frey, J., Schall, P., Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks. ISPRS J. Photogramm. Remote Sens. 170 (2020), 205–215, 10.1016/j.isprsjprs.2020.10.015.
Schomaker, M.E., Zarnoch, S.J., Bechtold, W.A., Latelle, D.J., Burkman, W.G., Cox, S.M., 2007. Crown-Condition Classification : A Guide to Data Collection and Analysis.
Slik, J.W.F., Arroyo-Rodriguez, V., Aiba, S.-I., Alvarez-Loayza, P., Alves, L.F., Ashton, P., Balvanera, P., Bastian, M.L., Bellingham, P.J., van den Berg, E., Bernacci, L., da Conceicao Bispo, P., Blanc, L., Bohning-Gaese, K., Boeckx, P., Bongers, F., Boyle, B., Bradford, M., Brearley, F.Q., Breuer-Ndoundou Hockemba, M., Bunyavejchewin, S., Calderado Leal Matos, D., Castillo-Santiago, M., Catharino, E.L.M., Chai, S.-L., Chen, Y., Colwell, R.K., Robin, C.L., Clark, C., Clark, D.B., Clark, D. a., Culmsee, H., Damas, K., Dattaraja, H.S., Dauby, G., Davidar, P., DeWalt, S.J., Doucet, J.-L., Duque, A., Durigan, G., Eichhorn, K. a. O., Eisenlohr, P. V., Eler, E., Ewango, C., Farwig, N., Feeley, K.J., Ferreira, L., Field, R., de Oliveira Filho, A.T., Fletcher, C., Forshed, O., Franco, G., Fredriksson, G., Gillespie, T., Gillet, J.-F., Amarnath, G., Griffith, D.M., Grogan, J., Gunatilleke, N., Harris, D., Harrison, R., Hector, A., Homeier, J., Imai, N., Itoh, A., Jansen, P. a., Joly, C. a., de Jong, B.H.J., Kartawinata, K., Kearsley, E., Kelly, D.L., Kenfack, D., Kessler, M., Kitayama, K., Kooyman, R., Larney, E., Laumonier, Y., Laurance, S., Laurance, W.F., Lawes, M.J., Amaral, I.L. Do, Letcher, S.G., Lindsell, J., Lu, X., Mansor, A., Marjokorpi, A., Martin, E.H., Meilby, H., Melo, F.P.L., Metcalfe, D.J., Medjibe, V.P., Metzger, J.P., Millet, J., Mohandass, D., Montero, J.C., de Morisson Valeriano, M., Mugerwa, B., Nagamasu, H., Nilus, R., Ochoa-Gaona, S., Onrizal, Page, N., Parolin, P., Parren, M., Parthasarathy, N., Paudel, E., Permana, A., Piedade, M.T.F., Pitman, N.C. a., Poorter, L., Poulsen, A.D., Poulsen, J., Powers, J., Prasad, R.C., Puyravaud, J.-P., Razafimahaimodison, J.-C., Reitsma, J., dos Santos, J.R., Roberto Spironello, W., Romero-Saltos, H., Rovero, F., Rozak, A.H., Ruokolainen, K., Rutishauser, E., Saiter, F., Saner, P., Santos, B. a., Santos, F., Sarker, S.K., Satdichanh, M., Schmitt, C.B., Schongart, J., Schulze, M., Suganuma, M.S., Sheil, D., da Silva Pinheiro, E., Sist, P., Stevart, T., Sukumar, R., Sun, I.-F., Sunderand, T., Suresh, H.S., Suzuki, E., Tabarelli, M., Tang, J., Targhetta, N., Theilade, I., Thomas, D.W., Tchouto, P., Hurtado, J., Valencia, R., van Valkenburg, J.L.C.H., Van Do, T., Vasquez, R., Verbeeck, H., Adekunle, V., Vieira, S. a., Webb, C.O., Whitfeld, T., Wich, S. a., Williams, J., Wittmann, F., Woll, H., Yang, X., Adou Yao, C.Y., Yap, S.L., Yoneda, T., Zahawi, R. a., Zakaria, R., Zang, R., de Assis, R.L., Garcia Luize, B., Venticinque, E.M., 2015. An estimate of the number of tropical tree species. Pnas 112, 7472–7477. doi: 10.1073/pnas.1423147112.
Slik, J.W.F., Paoli, G., Mcguire, K., Amaral, I., Barroso, J., Bastian, M., Blanc, L., Bongers, F., Boundja, P., Clark, C., Large trees drive forest aboveground biomass variation in moist lowland forests across the tropics. Glob. Ecol. Biogeogr. 22 (2013), 1261–1271, 10.1111/geb.12092.
Stăncioiu, P.T., Șerbescu, A.A., Dutcă, I., Live crown ratio as an indicator for tree vigor and stability of turkey oak (Quercus cerris l.): A case study. Forests 12 (2021), 1–12, 10.3390/f12121763.
Stephenson, N.L., Das, A.J., Condit, R., Russo, S.E., Baker, P.J., Beckman, N.G., Coomes, D. a, Lines, E.R., Morris, W.K., Rüger, N., Alvarez, E., Blundo, C., Bunyavejchewin, S., Chuyong, G., Davies, S.J., Duque, A., Ewango, C.N., Flores, O., Franklin, J.F., Grau, H.R., Hao, Z., Harmon, M.E., Hubbell, S.P., Kenfack, D., Lin, Y., Makana, J.-R., Malizia, A., Malizia, L.R., Pabst, R.J., Pongpattananurak, N., Su, S.-H., Sun, I.-F., Tan, S., Thomas, D., van Mantgem, P.J., Wang, X., Wiser, S.K., Zavala, M.A., 2014. Rate of tree carbon accumulation increases continuously with tree size. Nature 507, 90–3. doi: 10.1038/nature12914.
Sun, S., Cao, Q.V., Cao, T., Evaluation of distance-independent competition indices in predicting tree survival and diameter growth. Can. J. for. Res. 49 (2019), 440–446, 10.1139/cjfr-2018-0344.
Tomaschek, F., Hendrix, P., Baayen, R.H., Strategies for addressing collinearity in multivariate linguistic data. J. Phon. 71 (2018), 249–267, 10.1016/j.wocn.2018.09.004.
Tompalski, P., Coops, N.C., White, J.C., Goodbody, T.R.H., Hennigar, C.R., Wulder, M.A., Socha, J., Woods, M.E., Estimating Changes in Forest Attributes and Enhancing Growth Projections: a Review of Existing Approaches and Future Directions Using Airborne 3D Point Cloud Data. Curr. for. Reports 7 (2021), 25–30, 10.1007/s40725-021-00139-6.
Uriarte, M., Canham, C.D., Thompson, J., Zimmerman, J.K., A neighborhood analysis of tree growth and survival in a hurricane-driven tropical forest. Ecol. Monogr. 74 (2004), 591–614, 10.1890/03-4031.
Venables, B., Ripley, B., Bates, D.M., Hornik, K., Gebhardt, A., Firth, D., 2002. Package ‘MASS’ (version 7.3-54). Mod. Appl. Stat. with S.
West, P.W., Quantifying effects on tree growth rates of symmetric and asymmetric inter - tree competition in even - aged, monoculture Eucalyptus pilularis forests. Trees 37 (2023), 239–254, 10.1007/s00468-022-02341-w.
West, P.W., Ratkowsky, D.A., Problems with models assessing influences of tree size and inter-tree competitive processes on individual tree growth: a cautionary tale. J. for. Res., 2021, 10.1007/s11676-021-01395-9.
Wyckoff, P.H., Clark, J.S., Tree growth prediction using size and exposed crown area. Can. J. for. Res. 35 (2005), 13–20, 10.1139/x04-142.
Yu, K., Hao, Z., Post, C.J., Mikhailova, E.A., Lin, L., Zhao, G., Tian, S., Liu, J., 2022. Comparison of Classical Methods and Mask R-CNN for Automatic Tree Detection and Mapping Using UAV Imagery. Remote Sens. 14, 17. doi: doi.org/10.3390/rs14020295.
Zambrano, J., Fagan, W.F., Worthy, S.J., Thompson, J., Uriarte, M., Zimmerman, J.K., Umaña, M.N., Swenson, N.G., Tree crown overlap improves predictions of the functional neighbourhood effects on tree survival and growth. J. Ecol. 107 (2019), 887–900, 10.1111/1365-2745.13075.
Zarnoch, S.J., Bechtold, W.A., Stolte, K.W., Using crown condition variables as indicators of forest health. Can. J. for. Res. 34 (2004), 1057–1070, 10.1139/x03-277.