Hijmans, R. J.: terra: Spatial Data Analysis, r package version 1.7-55,
https://CRAN.R-project.org/package=terra (last access: 17 March 2024), 2023. a
Hijmans, R. J., Barbosa, M., Ghosh, A., and Mandel, A.: geodata: Download Geographic Data, r package version 0.5-9,
https://CRAN.R-project.org/package=geodata (last access: 17 March 2024), 2023. a
Jung, M., Schwalm, C., Migliavacca, M., Walther, S., Camps-Valls, G., Koirala, S., Anthoni, P., Besnard, S., Bodesheim, P., Carvalhais, N., Chevallier, F., Gans, F., Goll, D. S., Haverd, V., Köhler, P., Ichii, K., Jain, A. K., Liu, J., Lombardozzi, D., Nabel, J. E. M. S., Nelson, J. A., O'Sullivan, M., Pallandt, M., Papale, D., Peters, W., Pongratz, J., Rödenbeck, C., Sitch, S., Tramontana, G., Walker, A., Weber, U., and Reichstein, M.: Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach, Biogeosciences, 17, 1343–1365,
https://doi.org/10.5194/bg-17-1343-2020, 2020.
a
Leroy, B., Meynard, C. N., Bellard, C., and Courchamp, F.: virtualspecies, an R package to generate virtual species distributions, Ecography, 39, 599–607,
https://doi.org/10.1111/ecog.01388, 2016.
a,
b,
c,
d
Liaw, A. and Wiener, M.: Classification and Regression by randomForest, The R Journal, 2, 18–22,
https://CRAN.R-project.org/doc/Rnews/ (last access: 17 March 2024), 2002.
a,
b
Linnenbrink, J., Milà, C., Ludwig, M., and Meyer, H.: kNNDM CV: k-fold nearest-neighbour distance matching cross-validation for map accuracy estimation, Geosci. Model Dev., 17, 5897–5912,
https://doi.org/10.5194/gmd-17-5897-2024, 2024.
a,
b
Lopez-Gonzalez, G., Lewis, S. L., Burkitt, M., and Phillips, O. L.: ForestPlots.net: a web application and research tool to manage and analyse tropical forest plot data, Journal of Vegetation Science, 22, 610–613,
https://doi.org/10.1111/j.1654-1103.2011.01312.x, 2011.
a
Ludwig, M., Moreno-Martinez, A., Hölzel, N., Pebesma, E., and Meyer, H.: Assessing and improving the transferability of current global spatial prediction models, Global Ecology and Biogeography, 32, 356–368,
https://doi.org/10.1111/geb.13635, 2023.
a
Meyer, H. and Pebesma, E.: Predicting into unknown space? Estimating the area of applicability of spatial prediction models, Methods in Ecology and Evolution, 12, 1620–1633,
https://doi.org/10.1111/2041-210X.13650, 2021.
a,
b,
c,
d,
e,
f,
g,
h,
i,
j,
k,
l,
m,
n
Meyer, H., Reudenbach, C., Hengl, T., Katurji, M., and Nauss, T.: Improving performance of spatio-temporal machine learning models using forward feature selection and target-oriented validation, Environmental Modelling & Software, 101, 1–9,
https://doi.org/10.1016/j.envsoft.2017.12.001, 2018.
a
Meyer, H., Ludwig, M., Milà, C., Linnenbrink, J., and Schumacher, F.: The CAST package for training and assessment of spatial prediction models in R,
https://hannameyer.github.io/CAST (last access: 17 March 2024), 2024a. a
Meyer, H., Milà, C., Ludwig, M., Linnenbrink, J., and Schumacher, F.: CAST: “caret” Applications for Spatial-Temporal Models, r package version 1.0.2,
https://CRAN.R-project.org/package=CAST (last access: 17 March 2024), 2024b.
a,
b,
c
Meyer, H., Milà, C., Ludwig, M., Schumacher, F., Linnenbrink, J., Reudenbach, C., Jakub, Pebesma, E., Bahlmann, J., Görgen, D., Bell, K., Bouasria, A., and Schratz, P.: HannaMeyer/CAST: CAST 1.0.2, Zenodo [code],
https://doi.org/10.5281/zenodo.14362793, 2024c.
a
Milà, C., Mateu, J., Pebesma, E., and Meyer, H.: Nearest neighbour distance matching Leave-One-Out Cross-Validation for map validation, Methods in Ecology and Evolution, 13, 1304–1316,
https://doi.org/10.1111/2041-210X.13851, 2022.
a,
b
Pauchard, A., Fuentes, N., Jiménez, A., Bustamante, R., and Marticorena, A.: Alien Plants Homogenise Protected Areas: Evidence from the Landscape and Regional Scales in South Central Chile, Springer Netherlands, Dordrecht, 191–208, ISBN 978-94-007-7749-1,
https://doi.org/10.1007/978-94-007-7750-7_10, 2013.
a
Peyre, G., Balslev, H., Martí, D., Sklenář, P., Ramsay, P., Lozano, P., Cuello, N., Bussmann, R., Cabrera, O., and Font, X.: VegPáramo, a flora and vegetation database for the Andean páramo, Phytocoenologia, 45, 195–201,
https://doi.org/10.1127/phyto/2015/0045, 2015.
a
R Core Team: R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria,
https://www.R-project.org/, last access: 3 December 2023. a
Sabatini, F. M., Lenoir, J., Hattab, T., Arnst, E. A., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S. M., Jandt, U., Jansen, F., Jiménez-Alfaro, B., Kattge, J., Levesley, A., Pillar, V. D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A. T. R., Agrillo, E., Alvarez, M., Apostolova, I., Arfin Khan, M. A. S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A. D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., de Gasper, A. L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El-Sheikh, M. A. E.-R. M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán-de Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I. G., Grytnes, J.-A., Guerin, G. R., Gutiérrez, A. G., Haider, S., Hatim, M. Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J. A. M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D. N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H. S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D. V., Liu, H., Lysenko, T., Mahecha, M. D., Marcenò, C., Martynenko, V., Moeslund, J. E., Monteagudo Mendoza, A., Mucina, L., Müller, J. V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G. E., Pärtel, M., Pauchard, A., Peet, R. K., Peñuelas, J., Pérez-Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O. L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas-Torres, G., Rodwell, J. S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Z., Sparrow, B., Sperandii, M. G., Stančić, Z., Svenning, J.-C., Tang, Z., Tang, C. Q., Tsiripidis, I., Vanselow, K. A., Vásquez Martínez, R., Vassilev, K., Vélez-Martin, E., Venanzoni, R., Vibrans, A. C., Violle, C., Virtanen, R., von Wehrden, H., Wagner, V., Walker, D. A., Waller, D. M., Wang, H.-F., Wesche, K., Whitfeld, T. J. S., Willner, W., Wiser, S. K., Wohlgemuth, T., Yamalov, S., Zobel, M., and Bruelheide, H.: sPlotOpen – An environmentally balanced, open-access, global dataset of vegetation plots, Global Ecology and Biogeography, 30, 1740–1764,
https://doi.org/10.1111/geb.13346, 2021.
a
Sabatini, F. M., Jiménez-Alfaro, B., Jandt, U., Chytrý, M., Field, R., Kessler, M., Lenoir, J., Schrodt, F., Wiser, S. K., Arfin Khan, M. A. S., Attorre, F., Cayuela, L., De Sanctis, M., Dengler, J., Haider, S., Hatim, M. Z., Indreica, A., Jansen, F., Pauchard, A., Peet, R. K., Petřík, P., Pillar, V. D., Sandel, B., Schmidt, M., Tang, Z., Van Bodegom, P., Vassilev, K., Violle, C., Alvarez-Davila, E., Davidar, P., Dolezal, J., Hérault, B., Galán-de Mera, A., Jiménez, J., Kambach, S., Kepfer-Rojas, S., Kreft, H., Lezama, F., Linares-Palomino, R., Monteagudo Mendoza, A., N’Dja, J. K., Phillips, O. L., Rivas-Torres, G., Sklenář, P., Speziale, K., Strohbach, B. J., Vásquez Martínez, R., Wang, H.-F., Wesche, K., and Bruelheide, H.: Global patterns of vascular plant alpha diversity, Nature Communications, 13, 4683,
https://doi.org/10.1038/s41467-022-32063-z, 2022.
a
Sievert, C.: Interactive Web-Based Data Visualization with R, plotly, and shiny, Chapman and Hall/CRC, ISBN 9781138331457,
https://plotly-r.com (last access: 17 March 2024), 2020. a
van den Hoogen, J., Geisen, S., Routh, D., Ferris, H., Traunspurger, W., Wardle, D. A., de Goede, R. G. M., Adams, B. J., Ahmad, W., Andriuzzi, W. S., Bardgett, R. D., Bonkowski, M., Campos-Herrera, R., Cares, J. E., Caruso, T., de Brito Caixeta, L., Chen, X., Costa, S. R., Creamer, R., Mauro da Cunha Castro, J., Dam, M., Djigal, D., Escuer, M., Griffiths, B. S., Gutiérrez, C., Hohberg, K., Kalinkina, D., Kardol, P., Kergunteuil, A., Korthals, G., Krashevska, V., Kudrin, A. A., Li, Q., Liang, W., Magilton, M., Marais, M., Martín, J. A. R., Matveeva, E., Mayad, E. H., Mulder, C., Mullin, P., Neilson, R., Nguyen, T. A. D., Nielsen, U. N., Okada, H., Rius, J. E. P., Pan, K., Peneva, V., Pellissier, L., Carlos Pereira da Silva, J., Pitteloud, C., Powers, T. O., Powers, K., Quist, C. W., Rasmann, S., Moreno, S. S., Scheu, S., Setälä, H., Sushchuk, A., Tiunov, A. V., Trap, J., van der Putten, W., Vestergård, M., Villenave, C., Waeyenberge, L., Wall, D. H., Wilschut, R., Wright, D. G., Yang, J.-I., and Crowther, T. W.: Soil nematode abundance and functional group composition at a global scale, Nature, 572, 194–198,
https://doi.org/10.1038/s41586-019-1418-6, 2019.
a
van den Hoogen, J., Robmann, N., Routh, D., Lauber, T., van Tiel, N., Danylo, O., and Crowther, T. W.: A geospatial mapping pipeline for ecologists, bioRxiv [preprint],
https://doi.org/10.1101/2021.07.07.451145, 2021.
a
Vibrans, A. C., Gasper, A. L. D., Moser, P., Oliveira, L. Z., Lingner, D. V., and Sevegnani, L.: Insights from a large-scale inventory in the southern Brazilian Atlantic Forest, Scientia Agricola, 77, e20180036,
https://doi.org/10.1590/1678-992x-2018-0036, 2020.
a
Wickham, H.: ggplot2: Elegant Graphics for Data Analysis, Springer-Verlag New York, ISBN 978-3-319-24277-4,
https://ggplot2.tidyverse.org (last access: 17 March 2024), 2016. a
Wright, M. N. and Ziegler, A.: ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R, Journal of Statistical Software, 77, 1–17,
https://doi.org/10.18637/jss.v077.i01, 2017.
a
