Climate regulation processes are linked to the functional composition of plant communities in European forests, shrublands, and grasslands.
albedo
biodiversity change
climate change
climate-surface models
greenhouse gases
land use change
leaf economics spectrum
nature-based solutions
transpiration
Journal
Global change biology
ISSN: 1365-2486
Titre abrégé: Glob Chang Biol
Pays: England
ID NLM: 9888746
Informations de publication
Date de publication:
Feb 2024
Feb 2024
Historique:
revised:
05
01
2024
received:
22
08
2023
accepted:
10
01
2024
medline:
20
2
2024
pubmed:
20
2
2024
entrez:
20
2
2024
Statut:
ppublish
Résumé
Terrestrial ecosystems affect climate by reflecting solar irradiation, evaporative cooling, and carbon sequestration. Yet very little is known about how plant traits affect climate regulation processes (CRPs) in different habitat types. Here, we used linear and random forest models to relate the community-weighted mean and variance values of 19 plant traits (summarized into eight trait axes) to the climate-adjusted proportion of reflected solar irradiation, evapotranspiration, and net primary productivity across 36,630 grid cells at the European extent, classified into 10 types of forest, shrubland, and grassland habitats. We found that these trait axes were more tightly linked to log evapotranspiration (with an average of 6.2% explained variation) and the proportion of reflected solar irradiation (6.1%) than to net primary productivity (4.9%). The highest variation in CRPs was explained in forest and temperate shrubland habitats. Yet, the strength and direction of these relationships were strongly habitat-dependent. We conclude that any spatial upscaling of the effects of plant communities on CRPs must consider the relative contribution of different habitat types.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e17189Subventions
Organisme : Basque Government
ID : IT1487-22
Organisme : Agence Nationale de la Recherche
ID : ANR-20-EBI5-0001-05
Organisme : Deutsche Forschungsgemeinschaft
ID : DFG BR 1698/21-1
Organisme : Deutsche Forschungsgemeinschaft
ID : DFG HI 1538/16-1
Organisme : Slovenian Research Agency
ID : ARRS P1-0236
Organisme : Svensk Njurmedicinsk Förening
ID : 193907
Organisme : Technology Agency of the Czech Republic
ID : SS70010002
Organisme : Danish National Research Foundation
ID : DNRF173
Organisme : Slovak Research and Development Agency
ID : APVV 16-0431
Organisme : Villum Fonden
ID : 16549
Organisme : University of Latvia
ID : AAP2016/B041//Zd2016/AZ03
Organisme : Italian Ministry of University and Research
Informations de copyright
© 2024 The Authors. Global Change Biology published by John Wiley & Sons Ltd.
Références
Alibakhshi, S., Naimi, B., Hovi, A., Crowther, T. W., & Rautiainen, M. (2020). Quantitative analysis of the links between forest structure and land surface albedo on a global scale. Remote Sensing of Environment, 246, 111854. https://doi.org/10.1016/j.rse.2020.111854
Alkama, R., & Cescatti, A. (2016). Biophysical climate impacts of recent changes in global forest cover. Science, 351(6273), 600-604. https://doi.org/10.1126/science.aac8083
Alkama, R., Forzieri, G., Duveiller, G., Grassi, G., Liang, S., & Cescatti, A. (2022). Vegetation-based climate mitigation in a warmer and greener world. Nature Communications, 13(1), 606. https://doi.org/10.1038/s41467-022-28305-9
Anderson-Teixeira, K. J., Snyder, P. K., Twine, T. E., Cuadra, S. V., Costa, M. H., & DeLucia, E. H. (2012). Climate-regulation services of natural and agricultural ecoregions of the Americas. Nature Climate Change, 2(3), 177-181. https://doi.org/10.1038/nclimate1346
Archer, E. (2023). rfPermute: Estimate permutation p-values for random forest importance metrics. R package version 2.5.2.
Atwoli, L., Baqui, A. H., Benfield, T., Bosurgi, R., Godlee, F., Hancocks, S., Horton, R., Laybourn-Langton, L., Monteiro, C. A., Norman, I., Patrick, K., Praities, N., Olde Rikkert, M. G. M., Rubin, E. J., Sahni, P., Smith, R., Talley, N., Turale, S., & Vázquez, D. (2021). Call for emergency action to limit global temperature increases, restore biodiversity, and protect health. The New England Journal of Medicine, 385(12), 1134-1137. https://doi.org/10.1056/NEJMe2113200
Bartoń, K. (2022). MuMIn: Multi-model inference. R package version 1.46.0.
Bruelheide, H., Dengler, J., Jiménez-Alfaro, B., Purschke, O., Hennekens, S. M., Chytrý, M., Pillar, V. D., Jansen, F., Kattge, J., Sandel, B., Aubin, I., Biurrun, I., Field, R., Haider, S., Jandt, U., Lenoir, J., Peet, R. K., Peyre, G., Sabatini, F. M., … Zverev, A. (2019). sPlot - A new tool for global vegetation analyses. Journal of Vegetation Science, 30(2), 161-186. https://doi.org/10.1111/jvs.12710
Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez-Alfaro, B., Hennekens, S. M., Botta-Dukát, Z., Chytrý, M., Field, R., Jansen, F., Kattge, J., Pillar, V. D., Schrodt, F., Mahecha, M. D., Peet, R. K., Sandel, B., van Bodegom, P., Altman, J., Alvarez-Dávila, E., … Jandt, U. (2018). Global trait-environment relationships of plant communities. Nature Ecology & Evolution, 2(12), 1906-1917. https://doi.org/10.1038/s41559-018-0699-8
Brun, P., Violle, C., Mouillot, D., Mouquet, N., Enquist, B. J., Munoz, F., Münkemüller, T., Ostling, A., Zimmermann, N. E., & Thuiller, W. (2022). Plant community impact on productivity: Trait diversity or key(stone) species effects? Ecology Letters, 25(4), 913-925. https://doi.org/10.1111/ele.13968
Brun, P., Zimmermann, N. E., Hari, C., Pellissier, L., & Karger, D. N. (2022). Global climate-related predictors at kilometre resolution for the past and future. Earth System Science Data, 24(12), 5573-5603. https://doi.org/10.5194/essd-14-5573-2022
Chapin, F. S., III, Randerson, J. T., McGuire, A. D., Foley, J. A., & Field, C. B. (2008). Changing feedbacks in the climate-biosphere system. Frontiers in Ecology and the Environment, 6(6), 313-320. https://doi.org/10.1890/080005
Chapin, F. S., III, Zavaleta, E. S., Eviner, V. T., Naylor, R. L., Vitousek, P. M., Reynolds, H. L., Hooper, D. U., Lavorel, S., Sala, O. E., Hobbie, S. E., Mack, M. C., & Díaz, S. (2000). Consequences of changing biodiversity. Nature, 405(6783), 234-242. https://doi.org/10.1038/35012241
Chytrý, M., Hennekens, S. M., Jiménez-Alfaro, B., Knollová, I., Dengler, J., Jansen, F., Landucci, F., Schaminée, J. H. J., Aćić, S., Agrillo, E., Ambarlı, D., Angelini, P., Apostolova, I., Attorre, F., Berg, C., Bergmeier, E., Biurrun, I., Botta-Dukát, Z., Brisse, H., … Yamalov, S. (2016). European Vegetation Archive (EVA): An integrated database of European vegetation plots. Applied Vegetation Science, 19(1), 173-180. https://doi.org/10.1111/avsc.12191
Chytrý, M., Tichý, L., Hennekens, S. M., Knollová, I., Janssen, J. A. M., Rodwell, J. S., Peterka, T., Marcenò, C., Landucci, F., Danihelka, J., Hájek, M., Dengler, J., Novák, P., Zukal, D., Jiménez-Alfaro, B., Mucina, L., Abdulhak, S., Aćić, S., Agrillo, E., … Schaminée, J. H. J. (2020). EUNIS habitat classification: Expert system, characteristic species combinations and distribution maps of European habitats. Applied Vegetation Science, 23(4), 648-675. https://doi.org/10.1111/avsc.12519
Chytrý, M., Tichý, L., Hennekens, S. M., Knollová, I., Janssen, J. A. M., Rodwell, J. S., Peterka, T., Marcenò, C., Landucci, F., Danihelka, J., Hájek, M., Dengler, J., Novák, P., Zukal, D., Jiménez-Alfaro, B., Mucina, L., Abdulhak, S., Aćić, S., Agrillo, E., … Schaminée, J. H. J. (2021). EUNIS-ESy. Version 2021-06-01. https://doi.org/10.5281/zenodo.4812736
Díaz, S., Kattge, J., Cornelissen, J. H. C., Wright, I. J., Lavorel, S., Dray, S., Reu, B., Kleyer, M., Wirth, C., Colin Prentice, I., Garnier, E., Bönisch, G., Westoby, M., Poorter, H., Reich, P. B., Moles, A. T., Dickie, J., Gillison, A. N., Zanne, A. E., … Gorné, L. D. (2016). The global spectrum of plant form and function. Nature, 529(7585), 167-171. https://doi.org/10.1038/nature16489
Díaz, S. M., Settele, J., Brondízio, E., Ngo, H., Guèze, M., Agard, J., Arneth, A., Balvanera, P., Brauman, K. A., Butchart, S. H. M., Chan, K. M. A., Garibaldi, L. A., Ichii, K., Liu, J., Subramanian, S. M., Midgley, G. F., Miloslavich, P., Molnár, Z., Obura, D., … Zayas, C. N. (2019). The global assessment report on biodiversity and ecosystem services: Summary for policy makers: Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. https://ri.conicet.gov.ar/handle/11336/116171
Doughty, C. E., Santos-Andrade, P. E., Shenkin, A., Goldsmith, G. R., Bentley, L. P., Blonder, B., Díaz, S., Salinas, N., Enquist, B. J., Martin, R. E., Asner, G. P., & Malhi, Y. (2018). Tropical forest leaves may darken in response to climate change. Nature Ecology & Evolution, 2(12), 1918-1924. https://doi.org/10.1038/s41559-018-0716-y
Enquist, B. J., Norberg, J., Bonser, S. P., Violle, C., Webb, C. T., Henderson, A., Sloat, L., & Savage, V. (2015). Scaling from traits to ecosystems: Developing a general trait driver theory via integrating trait-based and metabolic scaling theories. Advances in Ecological Research, 52, 249-318.
Fisher, R. A., Koven, C. D., Anderegg, W. R. L., Christoffersen, B. O., Dietze, M. C., Farrior, C. E., Holm, J. A., Hurtt, G. C., Knox, R. G., Lawrence, P. J., Lichstein, J. W., Longo, M., Matheny, A. M., Medvigy, D., Muller-Landau, H. C., Powell, T. L., Serbin, S. P., Sato, H., Shuman, J. K., … Moorcroft, P. R. (2018). Vegetation demographics in earth system models: A review of progress and priorities. Global Change Biology, 24(1), 35-54. https://doi.org/10.1111/gcb.13910
Gardner, C. J., Struebig, M. J., & Davies, Z. G. (2020). Conservation must capitalise on climate's moment. Nature Communications, 11(1), 109. https://doi.org/10.1038/s41467-019-13964-y
Garnier, E., Navas, M.-L., & Grigulis, K. (2016). Plant functional diversity. Organism traits, community structure, and ecosystem properties (1st ed.). Oxford University Press.
Garnier, E., Stahl, U., Laporte, M.-A., Kattge, J., Mougenot, I., Kühn, I., Laporte, B., Amiaud, B., Ahrestani, F. S., Bönisch, G., Bunker, D. E., Cornelissen, J. H. C., Díaz, S., Enquist, B. J., Gachet, S., Jaureguiberry, P., Kleyer, M., Lavorel, S., Maicher, L., … Klotz, S. (2017). Towards a thesaurus of plant characteristics: An ecological contribution. Journal of Ecology, 105(2), 298-309. https://doi.org/10.1111/1365-2745.12698
Gates, D. M., & Hanks, R. J. (1967). Plant factors affecting evapotranspiration. In R. M. Hagan, H. R. Haise, & T. W. Edminster (Eds.), Irrigation of agricultural lands (pp. 506-521). American Society of Agronomy (Agronomy Monographs).
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18-27. https://doi.org/10.1016/j.rse.2017.06.031
Grant, R. H., Heisler, G. M., Gao, W., & Jenks, M. (2003). Ultraviolet leaf reflectance of common urban trees and the prediction of reflectance from leaf surface characteristics. Agricultural and Forest Meteorology, 120(1-4), 127-139. https://doi.org/10.1016/j.agrformet.2003.08.025
Grime, J. P. (1998). Benefits of plant diversity to ecosystems: Immediate, filter and founder effects. Journal of Ecology, 86(6), 902-910. https://doi.org/10.1046/j.1365-2745.1998.00306.x
Griscom, B. W., Adams, J., Ellis, P. W., Houghton, R. A., Lomax, G., Miteva, D. A., Schlesinger, W. H., Shoch, D., Siikamäki, J. V., Smith, P., Woodbury, P., Zganjar, C., Blackman, A., Campari, J., Conant, R. T., Delgado, C., Elias, P., Gopalakrishna, T., Hamsik, M. R., … Fargione, J. (2017). Natural climate solutions. Proceedings of the National Academy of Sciences of the United States of America, 114(44), 11645-11650. https://doi.org/10.1073/pnas.1710465114
Halim, M. A., Chen, H. Y. H., & Thomas, S. C. (2019). Stand age and species composition effects on surface albedo in a mixedwood boreal forest. Biogeosciences, 16(22), 4357-4375. https://doi.org/10.5194/bg-16-4357-2019
Harding, R. J., & Pomeroy, J. W. (1996). The energy balance of the winter boreal landscape. Journal of Climate, 9(11), 2778-2787. https://doi.org/10.1175/1520-0442(1996)009<2778:TEBOTW>2.0.CO;2
Harper, A. B., Cox, P. M., Friedlingstein, P., Wiltshire, A. J., Jones, C. D., Sitch, S., Mercado, L. M., Groenendijk, M., Robertson, E., Kattge, J., Bönisch, G., Atkin, O. K., Bahn, M., Cornelissen, J., Niinemets, Ü., Onipchenko, V., Peñuelas, J., Poorter, L., Reich, P. B., … Bodegom, P. V. (2016). Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait information. Geoscientific Model Development, 9(7), 2415-2440. https://doi.org/10.5194/gmd-9-2415-2016
He, N., Yan, P., Liu, C., Xu, L., Li, M., van Meerbeek, K., Zhou, G., Zhou, G., Liu, S., Zhou, X., Li, S., Niu, S., Han, X., Buckley, T. N., Sack, L., & Yu, G. (2023). Predicting ecosystem productivity based on plant community traits. Trends in Plant Science, 28(1), 43-53. https://doi.org/10.1016/j.tplants.2022.08.015
Hinojo-Hinojo, C., & Goulden, M. L. (2020). Plant traits help explain the tight relationship between vegetation indices and gross primary production. Remote Sensing, 12(9), 1405. https://doi.org/10.3390/rs12091405
Hollinger, D. Y., Ollinger, S. V., Richardson, A. D., Meyers, T. P., Dail, D. B., Martin, M. E., Scott, N. A., Arkebauer, T. J., Baldocchi, D. D., Clark, K. L., Curtis, P. S., Davis, K. J., Desai, A. R., Dragoni, D., Goulden, M. L., Gu, L., Katul, G. G., Pallardy, S. G., Paw, K. T., … Verma, S. B. (2010). Albedo estimates for land surface models and support for a new paradigm based on foliage nitrogen concentration. Global Change Biology, 16(2), 696-710. https://doi.org/10.1111/j.1365-2486.2009.02028.x
Holmes, M. G., & Keiller, D. R. (2002). Effects of pubescence and waxes on the reflectance of leaves in the ultraviolet and photosynthetic wavebands: A comparison of a range of species. Plant, Cell & Environment, 25(1), 85-93. https://doi.org/10.1046/j.1365-3040.2002.00779.x
IUCN. (2020). Global standard for nature-based solutions: A user-friendly framework for the verification, design and scaling up of NbS (1st ed.). International Union for Conservation of Nature.
Kambach, S., Sabatini, F. M., Attorre, F., Biurrun, I., Boenisch, G., Bonari, G., Čarni, A., Carranza, M. L., Chiarucci, A., Chytrý, M., Dengler, J., Garbolino, E., Golub, V., Güler, B., Jandt, U., Jansen, J., Jašková, A., Jiménez-Alfaro, B., Karger, D. N., … Bruelheide, H. (2023). Climate-trait relationships exhibit strong habitat specificity in plant communities across Europe. Nature Communications, 14(1), 712. https://doi.org/10.1038/s41467-023-36240-6
Kannenberg, S. A., Guo, J. S., Novick, K. A., Anderegg, W. R. L., Feng, X., Kennedy, D., Konings, A. G., Martínez-Vilalta, J., & Matheny, A. M. (2022). Opportunities, challenges and pitfalls in characterizing plant water-use strategies. Functional Ecology, 36(1), 24-37. https://doi.org/10.1111/1365-2435.13945
Karger, D., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., Zimmermann, N. E., Linder, H. P., & Kessler, M. (2017). Climatologies at high resolution for the earth's land surface areas. Scientific Data, 4, 170122. https://doi.org/10.1038/sdata.2017.122
Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., Zimmermann, N. E., Linder, H. P., & Kessler, M. (2018). Data from: Climatologies at high resolution for the earth's land surface areas [Dataset]. Dryad. https://doi.org/10.5061/dryad.kd1d4
Kattge, J., Bönisch, G., Díaz, S., Lavorel, S., Prentice, I. C., Leadley, P., Tautenhahn, S., Werner, G. D. A., Aakala, T., Abedi, M., Acosta, A. T. R., Adamidis, G. C., Adamson, K., Aiba, M., Albert, C. H., Alcántara, J. M., Carolina Alcázar, C., Aleixo, I., Ali, H., … Wirth, C. (2020). TRY plant trait database - Enhanced coverage and open access. Global Change Biology, 26(1), 119-188. https://doi.org/10.1111/gcb.14904
Lavorel, S., & Garnier, E. (2002). Predicting changes in community composition and ecosystem functioning from plant traits: Revisiting the holy grail. Functional Ecology, 16(5), 545-556. https://doi.org/10.1046/j.1365-2435.2002.00664.x
Lê, S., Josse, J., & Husson, F. (2008). FactoMineR: An R package for multivariate analysis. Journal of Statistical Software, 25(1), 1-18. https://doi.org/10.18637/jss.v025.i01
Leonardi, S., Magnani, F., Nolè, A., van Noije, T., & Borghetti, M. (2015). A global assessment of forest surface albedo and its relationships with climate and atmospheric nitrogen deposition. Global Change Biology, 21(1), 287-298. https://doi.org/10.1111/gcb.12681
Liaw, A., & Wiener, M. (2002). Classification and regression by randomForest. R News, 2(3), 18-22.
Limberger, O., Homeier, J., Farwig, N., Pucha-Cofrep, F., Fries, A., Leuschner, C., Trachte, K., & Bendix, J. (2021). Classification of tree functional types in a megadiverse tropical mountain forest from leaf optical metrics and functional traits for two related ecosystem functions. Forests, 12(5), 649. https://doi.org/10.3390/f12050649
Lüdecke, D. (2018). Ggeffects: Tidy data frames of marginal effects from regression models. Journal of Open Source Software, 3(26), 772. https://doi.org/10.21105/joss.00772
Mahecha, M. D., Bastos, A., Bohn, F. J., Eisenhauer, N., Feilhauer, H., Hartmann, H., Hickler, T., Kalesse-Los, H., Migliavacca, M., Otto, F. E. L., Peng, J., Quaas, J., Tegen, I., Weigelt, A., Wendisch, M., & Wirth, C. (2022). Biodiversity loss and climate extremes - Study the feedbacks. Nature, 612(7938), 30-32. https://doi.org/10.1038/d41586-022-04152-y
Matheny, A. M., Mirfenderesgi, G., & Bohrer, G. (2017). Trait-based representation of hydrological functional properties of plants in weather and ecosystem models. Plant Diversity, 39(1), 1-12. https://doi.org/10.1016/j.pld.2016.10.001
Oehri, J., Schaepman-Strub, G., Kim, J.-S., Grysko, R., Kropp, H., Grünberg, I., Zemlianskii, V., Sonnentag, O., Euskirchen, E. S., Reji Chacko, M., Muscari, G., Blanken, P. D., Dean, J. F., di Sarra, A., Harding, R. J., Sobota, I., Kutzbach, L., Plekhanova, E., Riihelä, A., … Chambers, S. D. (2022). Vegetation type is an important predictor of the arctic summer land surface energy budget. Nature Communications, 13(1), 6379. https://doi.org/10.1038/s41467-022-34049-3
Pekel, J.-F., Cottam, A., Gorelick, N., & Belward, A. S. (2016). High-resolution mapping of global surface water and its long-term changes. Nature, 540(7633), 418-422. https://doi.org/10.1038/nature20584
Pfeifroth, U., Kothe, S., Trentmann, J., Hollmann, R., Fuchs, P., Kaiser, J., & Werscheck, M. (2019). Surface Radiation Data Set - Heliosat (SARAH) - Edition 2.1. Satellite Application Facility on Climate Monitoring.
Pielke, R. A., Avissar, R. I., Raupach, M., Dolman, A. J., Zeng, X., & Denning, A. S. (1998). Interactions between the atmosphere and terrestrial ecosystems: Influence on weather and climate. Global Change Biology, 4(5), 461-475. https://doi.org/10.1046/j.1365-2486.1998.t01-1-00176.x
R Core Team. (2022). R: A language and environment for statistical computing. Version 4.2.2. R Foundation for Statistical Computing.
Ridgwell, A., Singarayer, J. S., Hetherington, A. M., & Valdes, P. J. (2009). Tackling regional climate change by leaf albedo bio-geoengineering. Current Biology, 19(2), 146-150. https://doi.org/10.1016/j.cub.2008.12.025
Running, S., Mu, Q., Zhao, M., & Moreno, A. (2021). MODIS/Terra net evapotranspiration gap-filled yearly L4 global 500 m SIN grid V061.
Running, S., & Zhao, M. (2019). MOD17A3HGF MODIS/Terra net primary production gap-filled yearly L4 global 500 m SIN grid V006.
Schaaf, C., & Wang, Z. (2015). MCD43A3 MODIS/Terra+Aqua BRDF/Albedo daily L3 global - 500 m V006.
Schrodt, F., Kattge, J., Shan, H., Fazayeli, F., Joswig, J., Banerjee, A., Reichstein, M., Bönisch, G., Díaz, S., Dickie, J., Gillison, A., Karpatne, A., Lavorel, S., Leadley, P., Wirth, C. B., Wright, I. J., Wright, S. J., & Reich, P. B. (2015). BHPMF - A hierarchical Bayesian approach to gap-filling and trait prediction for macroecology and functional biogeography. Global Ecology and Biogeography, 24(12), 1510-1521. https://doi.org/10.1111/geb.12335
Seddon, N., Chausson, A., Berry, P., Girardin, C. A. J., Smith, A., & Turner, B. (2020). Understanding the value and limits of nature-based solutions to climate change and other global challenges. Philosophical Transactions of the Royal Society B, 375(1794), 20190120. https://doi.org/10.1098/rstb.2019.0120
Serna-Chavez, H. M., Kissling, W. D., Veen, L. E., Swenson, N. G., & van Bodegom, P. M. (2018). Spatial scale dependence of factors driving climate regulation services in the Americas. Global Ecology and Biogeography, 27(7), 828-838. https://doi.org/10.1111/geb.12743
Serna-Chavez, H. M., Swenson, N. G., Weiser, M. D., van Loon, E. E., Bouten, W., Davidson, M. D., & van Bodegom, P. M. (2017). Strong biotic influences on regional patterns of climate regulation services. Global Biogeochemical Cycles, 31(5), 787-803. https://doi.org/10.1002/2017GB005627
Shan, H., Kattge, J., Reich, P. B., Banerjee, A., Schrodt, F., & Reichstein, M. (2012). Gap filling in the plant kingdom-Trait prediction using hierarchical probabilistic matrix factorization. Proceedings of the 29th International Conference on Machine Learning. Edinburgh, Scotland, UK.
Steffen, W., Richardson, K., Rockström, J., Cornell, S. E., Fetzer, I., Bennett, E. M., Biggs, R., Carpenter, S. R., de Vries, W., de Wit Cynthia, A., Folke, C., Gerten, D., Heinke, J., Mace, G. M., Persson, L. M., Ramanathan, V., Reyers, B., & Sörlin, S. (2015). Planetary boundaries: Guiding human development on a changing planet. Science, 347(6223), 1259855.
Stocker, T. F., Dahe, Q., Plattner, G.-K., Tignor, M. M. B., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., & Midgley, P. M. (Eds.). (2014). Climate change 2013. The physical science basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. WMO IPCC. https://boris.unibe.ch/71453
Sullivan, F. B., Ollinger, S. V., Martin, M. E., Ducey, M. J., Lepine, L. C., & Wicklein, H. F. (2013). Foliar nitrogen in relation to plant traits and reflectance properties of New Hampshire forests. Canadian Journal of Forest Research, 43(1), 18-27. https://doi.org/10.1139/cjfr-2012-0324
Thomas, G., & Rowntree, P. R. (1992). The boreal forests and climate. Quarterly Journal of the Royal Meteorological Society, 118(505), 469-497. https://doi.org/10.1002/qj.49711850505
Weigelt, A., Mommer, L., Andraczek, K., Iversen, C. M., Bergmann, J., Bruelheide, H., Fan, Y., Freschet, G. T., Guerrero-Ramírez, N. R., Kattge, J., Kuyper, T. W., Laughlin, D. C., Meier, I. C., van der Plas, F., Poorter, H., Roumet, C., van Ruijven, J., Sabatini, F. M., Semchenko, M., … McCormack, M. L. (2021). An integrated framework of plant form and function: The belowground perspective. New Phytologist, 232(1), 42-59. https://doi.org/10.1111/nph.17590
Wickham, H. (2016). ggplot2: Elegant graphics for data analysis. Springer-Verlag.
World Resources Institute. (2005). Ecosystem and human well-being - Biodiversity synthesis. https://wedocs.unep.org/handle/20.500.11822/8755
Zachary, M. J., & Linder, F. (2017). edarf: Exploratory data analysis using random forests. R package version 1.1.1.