Unforeseen plant phenotypic diversity in a dry and grazed world

ABSTRACT Earth harbours an extraordinary plant phenotypic diversity1 that is at risk from ongoing global changes2,3. However, it remains unknown how increasing aridity and livestock grazing

pressure—two major drivers of global change4,5,6—shape the trait covariation that underlies plant phenotypic diversity1,7. Here we assessed how covariation among 20 chemical and

morphological traits responds to aridity and grazing pressure within global drylands. Our analysis involved 133,769 trait measurements spanning 1,347 observations of 301 perennial plant

species surveyed across 326 plots from 6 continents. Crossing an aridity threshold of approximately 0.7 (close to the transition between semi-arid and arid zones) led to an unexpected 88%

increase in trait diversity. This threshold appeared in the presence of grazers, and moved toward lower aridity levels with increasing grazing pressure. Moreover, 57% of observed trait

diversity occurred only in the most arid and grazed drylands, highlighting the phenotypic uniqueness of these extreme environments. Our work indicates that drylands act as a global reservoir

of plant phenotypic diversity and challenge the pervasive view that harsh environmental conditions reduce plant trait diversity8,9,10. They also highlight that many alternative strategies

may enable plants to cope with increases in environmental stress induced by climate change and land-use intensification. Access through your institution Buy or subscribe This is a preview of

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* Log in * Learn about institutional subscriptions * Read our FAQs * Contact customer support SIMILAR CONTENT BEING VIEWED BY OTHERS PLANT TRAIT AND VEGETATION DATA ALONG A 1314 M ELEVATION

GRADIENT WITH FIRE HISTORY IN PUNA GRASSLANDS, PERÚ Article Open access 21 February 2024 PLANT TRAITS AND VEGETATION DATA FROM CLIMATE WARMING EXPERIMENTS ALONG AN 1100 M ELEVATION GRADIENT

IN GONGGA MOUNTAINS, CHINA Article Open access 19 June 2020 CONSISTENT TRAIT–ENVIRONMENT RELATIONSHIPS WITHIN AND ACROSS TUNDRA PLANT COMMUNITIES Article 25 February 2021 DATA AVAILABILITY

All processed datasets generated during the current study are available in the open source repository at https://doi.org/10.57745/SFCXOO. CODE AVAILABILITY The R code used to analyse the

data is available in the open source repository at https://doi.org/10.57745/SFCXOO. CHANGE HISTORY * _ 12 AUGUST 2024 In the version of this article initially published, an incorrect email

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S. Undrakhbold, M. Uuganbayar, B. Byambatsogt, S. Khaliun, S. Solongo, B. Batchuluun, M. Sloan, S. Spann, J. Spence, E. Geiger, I. Souza, R. Onoo, T. Araújo, M. Mabaso, P. M. Lunga, L.

Eloff, J. Sebei, J. J. Jordaan, E. Mudongo, V. Mokoka, B. Mokhou, T. Maphanga, D. Thompson, A. S. K. Frank, R. Matjea, F. Hoffmann, C. Goebel, B. Semple, B. Tamayo, R. Peters, A. L. Piña, R.

Ledezma, E. Vidal, F. Perona, J. M. Alcántara, A. Howell, R. Reibold, N. Melone, M. Starbuck, E. Geiger, Bush Heritage Australia, the University of Limpopo, Comunidad Agricola Quebrada de

Talca, Conaf Chile and South African Environmental Observation Network (SAEON) for assistance with field work and plant identification, the South African Military for assistance with field

work and/or granting access to their properties, and the Scientific Services Kruger National Park. This research was funded by the European Research Council (ERC Grant agreement 647038 1004

[BIODESERT]) and Generalitat Valenciana (CIDEGENT/2018/041). N.G. was supported by CAP 20–25 (16-IDEX-0001) and the AgreenSkills+ fellowship programme which has received funding from the

European Union’s Seventh Framework Programme under grant agreement FP7-609398 (AgreenSkills+ contract). F.T.M. acknowledges support from the King Abdullah University of Science and

Technology (KAUST), the KAUST Climate and Livability Initiative, the University of Alicante (UADIF22-74 and VIGROB22-350), the Spanish Ministry of Science and Innovation

(PID2020-116578RB-I00), and the Synthesis Center (sDiv) of the German Centre for Integrative Biodiversity Research Halle–Jena–Leipzig (iDiv). Y.L.B.-P. was supported by a Marie

Sklodowska-Curie Actions Individual Fellowship (MSCA-1018 IF) within the European Program Horizon 2020 (DRYFUN Project 656035). H.S. is supported by a María Zambrano fellowship funded by the

Ministry of Universities and European Union-Next Generation plan. L.W. acknowledges support from the US National Science Foundation (EAR 1554894). G.M.W. acknowledges support from the

Australian Research Council (DP210102593) and TERN. M.B is supported by a Ramón y Cajal grant from Spanish Ministry of Science (RYC2021-031797-I). L.v.d.B. and K.T. were supported by the

German Research Foundation (DFG) Priority Program SPP-1803 (TI388/14-1). A.F. acknowledges the financial support from ANID PIA/BASAL FB210006 and Millenium Science Initiative Program

NCN2021-050. A.J. was supported by the Bavarian Research Alliance for travel and field work (BayIntAn UBT 2017 61). A.L. and L.K. acknowledge support from the German Research Foundation, DFG

(grant CRC TRR228) and German Federal Government for Science and Education, BMBF (grants 01LL1802C and 01LC1821A). B.B. and S.U. were supported by the Taylor Family-Asia Foundation Endowed

Chair in Ecology and Conservation Biology. P.J.R. and A.J.M. acknowledge support from Fondo Europeo de Desarrollo Regional through the FEDER Andalucía operative programme, FEDER-UJA 1261180

project. E.M.-J. and C.P. acknowledge support from the Spanish Ministry of Science and Innovation (PID2020-116578RB-I00). D.J.E. was supported by the Hermon Slade Foundation. J.D. and

A.Rodríguez acknowledge support from the FCT (2020.03670.CEECIND and SFRH/BDP/108913/2015, respectively), as well as from the MCTES, FSE, UE and the CFE (UIDB/04004/2021) research unit

financed by FCT/MCTES through national funds (PIDDAC). S.C.R. acknowledges support from the US Department of Energy (DE-SC-0008168), US Department of Defense (RC18-1322), and the US

Geological Survey Ecosystems Mission Area. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US government. E.H.-S. acknowledges

support from Mexican National Science and Technology Council (CONACYT PN 5036 and 319059). A.N. and C. Branquinho. acknowledge the support from FCT—Fundação para a Ciência e a Tecnologia

(CEECIND/02453/2018/CP1534/CT0001, PTDC/ASP-SIL/7743/ 2020, UIDB/00329/2020), from AdaptForGrazing project (PRR-C05-i03-I-000035) and from LTsER Montado platform (LTER_EU_PT_001). Field work

of G.P. and J.M.Z. was supported by UNRN (PI 40-C-873). AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Université Clermont Auvergne, INRAE, VetAgro Sup, Unité Mixte de Recherche Ecosystème

Prairial, Clermont-Ferrand, France Nicolas Gross, Raphaël Martin & Franck Jabot * Environmental Sciences and Engineering, Biological and Environmental Science and Engineering Division,

King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia Fernando T. Maestre * Botany Department, State Museum of Natural History Stuttgart, Stuttgart, Germany

Pierre Liancourt * Plant Ecology Group, University of Tübingen, Tübingen, Germany Pierre Liancourt, Liesbeth van den Brink, Rafaella Canessa, Jan C. Ruppert & Katja Tielbörger *

Departamento de Biodiversidad, Ecología y Evolución, Facultad de Ciencias Biológicas, Universidad Complutense de Madrid, Madrid, Spain Miguel Berdugo, Enrique Valencia, Juan G. Rubalcaba 

& Alberto L. Teixido * Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland Miguel Berdugo * Instituto Multidisciplinar para el Estudio del Medio “Ramon

Margalef”, Universidad de Alicante, Alicante, Spain Beatriz Gozalo, Victoria Ochoa, Santiago Soliveres, Emilio Guirado, Sergio Asensio, Jaime Martínez-Valderrama & Ivan Santaolaria

Pijuan * Laboratorio de Biodiversidad y Funcionamiento Ecosistémico. Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), CSIC, Sevilla, Spain Manuel Delgado-Baquerizo *

Département des Sciences de l’Environnement, Université du Québec à Trois-Rivières, Trois Rivières, Quebec, Canada Vincent Maire * Departamento de Ciencias Agrarias y Medio Natural, Escuela

Politécnica Superior, Instituto Universitario de Investigación en Ciencias Ambientales de Aragón (IUCA), Universidad de Zaragoza, Huesca, Spain Hugo Saiz * Departamento de Ecología,

Universidad de Alicante, Alicante, Spain Santiago Soliveres * Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New

South Wales, Australia David J. Eldridge * Instituto Nacional de Tecnología Agropecuaria (INTA), Instituto de Suelos-CNIA, Buenos Aires, Argentina Juan J. Gaitán * Departamento de

Tecnología, Universidad Nacional de Luján, Luján, Argentina Juan J. Gaitán * Consejo Nacional de Investigaciones Científicas y Técnicas de Argentina (CONICET), Buenos Aires, Argentina Juan

J. Gaitán & Guadalupe Peter * Departamento de Ingeniería y Morfología del Terreno, Escuela Técnica Superior de Ingenieros de Caminos, Canales y Puertos, Universidad Politécnica de

Madrid, Madrid, Spain Miguel García-Gómez * Instituto de Ciencias Agrarias, Consejo Superior de Investigaciones Científicas, Madrid, Spain Paloma Martínez & César Plaza * Departamento de

Biología y Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, Móstoles, Spain Betty J. Mendoza & David S. Pescador * Department of Agricultural and Food Chemistry,

Faculty of Sciences, Universidad Autónoma de Madrid, Madrid, Spain Eduardo Moreno-Jiménez * Departamento de Farmacología, Farmacognosia y Botánica, Facultad de Farmacia, Universidad

Complutense de Madrid, Madrid, Spain David S. Pescador * Department of Range Management, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor, Iran Mehdi Abedi 

& Khadijeh Bahalkeh * Estación Experimental Agropecuaria Catamarca, Instituto Nacional de Tecnología Agropecuaria, Catamarca, Argentina Rodrigo J. Ahumada & R. Emiliano Quiroga *

Laboratoire de Recherche: Biodiversité, Biotechnologie, Environnement et Développement Durable (BioDev), Faculté des Sciences, Université M’hamed Bougara de Boumerdès, Boumerdès, Algérie

Fateh Amghar * Instituto Pirenaico de Ecología (IPE CSIC), Zaragoza, Spain Antonio I. Arroyo & Yolanda Pueyo * Center for Ecosystem Science and Society, Northern Arizona University,

Flagstaff, AZ, USA Lydia Bailey & Matthew A. Bowker * Laboratory of Pastoral Ecosystems and Promotion of Spontaneous Plants and Associated Micro-Organisms, Institut des Régions Arides

(IRA) Médenine, University of Gabes, Zrig Eddakhlania, Tunisia Farah Ben Salem * Plant Ecology and Nature Conservation, University of Potsdam, Potsdam, Germany Niels Blaum & Florian

Jeltsch * Department of Biology, School of Arts and Sciences, National University of Mongolia, Ulaanbaatar, Mongolia Bazartseren Boldgiv & Sainbileg Undrakhbold * School of Forestry,

Northern Arizona University, Flagstaff, AZ, USA Matthew A. Bowker * cE3c — Centre for Ecology, Evolution and Environmental Changes and CHANGE — Global Change and Sustainability Institute,

Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal Cristina Branquinho & Alice Nunes * ECOBIOSIS, Departmento of Botánica, Universidad de Concepción, Concepción, Chile

Liesbeth van den Brink * Institute of Soil and Water Conservation, Northwest A&F University, Yangling, China Chongfeng Bu & Mengchen Ju * Institute of Soil and Water Conservation,

Chinese Academy of Sciences and Ministry of Water Resources, Yangling, China Chongfeng Bu & Mengchen Ju * German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig,

Leipzig, Germany Rafaella Canessa * Institut für Biologie, Martin-Luther-University Halle-Wittenberg, Halle, Germany Rafaella Canessa * Departamento de Biología, Escuela Politécnica

Nacional, Quito, Ecuador Andrea del P. Castillo-Monroy & David A. Donoso * Department of Life Sciences, Centre for Functional Ecology, University of Coimbra, Coimbra, Portugal Helena

Castro * Facultad de Ciencias Agropecuarias, Carrera de Ingeniería Agronómica, Grupo de Agroforestería, Manejo y Conservación del Paisaje, Universidad de Cuenca, Cuenca, Ecuador Patricio

Castro & Oswaldo Jadan * Laboratory of Eremology and Combating Desertification, Institut des Régions Arides (IRA) Médenine, University of Gabes, Zrig Eddakhlania, Tunisia Roukaya Chibani

* Departamento de Ciências Biológicas, Universidade Estadual de Feira de Santana, Feira de Santana, Brasil Abel Augusto Conceição & Frederic Mendes Hughes * Department of Biological

Sciences, University of Texas at El Paso, El Paso, TX, USA Anthony Darrouzet-Nardi * Faculty of Science, University of Technology Sydney, Sydney, New South Wales, Australia Yvonne C. Davila

* Lendület Seed Ecology Research Group, Institute of Ecology and Botany, Centre for Ecological Research, Vácrátót, Hungary Balázs Deák & Orsolya Valkó * Misión Biolóxica de Galicia,

CSIC, Pontevedra, Spain Jorge Durán & Alexandra Rodríguez * Departamento de Ciencias Biológicas y Agropecuarias, Universidad Técnica Particular de Loja, Loja, Ecuador Carlos Espinosa 

& Elizabeth Gusman-Montalvan * Instituto de Investigación Interdisciplinaria (I3), Universidad de Talca, Talca, Chile Alex Fajardo & Juan P. Mora * Instituto de Ecología y

Biodiversidad (IEB), Santiago, Chile Alex Fajardo * Limits of Life (LiLi), Instituto Milenio, Valdivia, Chile Alex Fajardo * Department of Range and Watershed Management, Faculty of Natural

Resources and Environment, Ferdowsi University of Mashhad, Mashhad, Iran Mohammad Farzam * Instituto Nacional de Tecnología Agropecuaria EEA Santa Cruz, Río Gallegos, Argentina Daniela

Ferrante & Gabriel Oliva * Universidad Nacional de la Patagonia Austral, Río Gallegos, Argentina Daniela Ferrante & Gabriel Oliva * Instituto de Investigaciones en Biodiversidad y

Medioambiente, Consejo Nacional de Investigaciones Científicas y Técnicas–Universidad Nacional del Comahue, Neuquen, Argentina Jorgelina Franzese & Sofía Gonzalez * Department of Natural

Resource Science, Thompson Rivers University, Kamloops, British Columbia, Canada Lauchlan Fraser & Colton Stephens * Instituto de Estudios Científicos y Tecnológicos (IDECYT); Centro de

Estudios de Agroecología Tropical (CEDAT), Universidad Nacional Experimental Simón Rodríguez (UNESR), Miranda, Venezuela Rosa Mary Hernández-Hernández * Institute of Landscape Ecology,

University of Münster, Münster, Germany Norbert Hölzel & Frederike Velbert * Instituto Potosino de Investigación Científica y Tecnológica, San Luis Potosí, México Elisabeth

Huber-Sannwald * Department of Disturbance Ecology, Bayreuth Center of Ecology and Environmental Research BayCEER, University of Bayreuth, Bayreuth, Germany Anke Jentsch & Peter Wolff *

Earth Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA Kudzai F. Kaseke * Biodiversity Research, Systematic Botany Group, Institute of Biochemistry and

Biology, University of Potsdam, Potsdam, Germany Liana Kindermann & Anja Linstädter * Department of Plant and Soil Sciences, University of Pretoria, Pretoria, South Africa Peter le Roux 

& Michelle A. Louw * Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany Anja Linstädter * Department of Biochemistry, Genetics and Microbiology,

DSI/NRF SARChI in Marine Microbiomics, University of Pretoria, Pretoria, South Africa Mancha Mabaso * Gobabeb, Namib Research Institute, Walvis Bay, Namibia Gillian Maggs-Kölling & 

Eugene Marais * Department of Microbiology, Faculty of Science, Stellenbosch University, Stellenbosch, South Africa Thulani P. Makhalanyane * Institut d’Écologie et des Sciences de

l’Environnement de Paris (iEES-Paris), Sorbonne Université, IRD, CNRS, INRAE, Université Paris Est Creteil, Université de Paris, Centre IRD de France Nord, Bondy, France Oumarou Malam Issa *

Departamento Biología Animal, Biología Vegetal y Ecología, Universidad de Jaén, Jaén, Spain Antonio J. Manzaneda * Normandie Universite, UNIROUEN, INRAE, ECODIV, Rouen, France Pierre

Margerie * Programa de Pós-Graduação em Zoologia and Conselho de Curadores das Coleções Científicas, Universidade Estadual de Santa Cruz, Ilhéus, Brazil Frederic Mendes Hughes * Programa de

Pós-Graduação em Bioinformática, Universidade Federal de Minas Gerais, Pampulha, Brazil Frederic Mendes Hughes * Biology Department and Ecology Program, The Pennsylvania State University,

University Park, PA, USA João Vitor S. Messeder * Forestry School, INDEHESA, Universidad de Extremadura, Plasencia, Spain Gerardo Moreno & Victor Rolo * Southwest Biological Science

Center, US Geological Survey, Flagstaff, AZ, USA Seth M. Munson * Cátedra de Ecología, Facultad de Agronomía Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la

Agricultura (IFEVA-CONICET), Universidad de Buenos Aires, Buenos Aires, Argentina Gaston R. Oñatibia & Laura Yahdjian * CEANPa, Universidad Nacional de Río Negro, Sede Atlántica, Río

Negro, Argentina Guadalupe Peter & Juan Manuel Zeberio * Cátedra de Manejo de Pastizales Naturales, Facultad de Ciencias Agrarias, Universidad Nacional de Catamarca, Catamarca, Argentina

R. Emiliano Quiroga * Universidad Estatal Amazónica (UEA), Puyo-Ecuador, Ecuador Elizabeth Ramírez-Iglesias * US Geological Survey, Southwest Biological Science Center, Moab, UT, USA Sasha

C. Reed * Instituto Interuniversitario de Investigación del Sistema Tierra de Andalucía, Universidad de Jaén, Jaén, Spain Pedro J. Rey * Institute of Ecology, Environment and Sustainability

Network, Chihuahua, Mexico Víctor M. Reyes Gómez * Global Drylands Center,School of Life Sciences and School of Sustainability, Arizona State University, Tempe, AZ, USA Osvaldo Sala * Al

Quds University, Jerusalem, Palestine Ayman Salah * Mara Research Station, Limpopo Department of Agriculture and Rural Development, Polokwane, South Africa Phokgedi Julius Sebei * Dead Sea

and Arava Science Center, Yotvata, Israel Ilan Stavi * Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, UK Andrew D. Thomas * School of Earth and Space

Exploration, Arizona State University, Tempe, AZ, USA Heather L. Throop * School of Life Sciences, Arizona State University, Tempe, AZ, USA Heather L. Throop * Department of Planning and

Environment, Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia Samantha Travers & 

James Val * Zoology Department, National Museums of Kenya, Nairobi, Kenya Wanyoike Wamiti * Department of Earth and Environmental Sciences, Indiana University Indianapolis (IUI),

Indianapolis, IN, USA Lixin Wang * Key Laboratory of Vegetation Ecology of the Ministry of Education, Jilin Songnen Grassland Ecosystem National Observation and Research Station, Institute

of Grassland Science, Northeast Normal University, Changchun, China Deli Wang * Desert Ecology Research Group, School of Life and Environmental Sciences, The University of Sydney, Sydney,

New South Wales, Australia Glenda M. Wardle * Forest and Rangeland Research Department, Khorasan Razavi Agricultural and Natural Resources Research and Education Center, AREEO, Mashhad, Iran

Reza Yari * Gilat Research Center, Department of Natural Resources, Institute of Plant Sciences, Agricultural Research Organization, Rishon LeZion, Israel Eli Zaady * State Key Laboratory

of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Beijing,

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F.T.M. and Y.L.B.-P. conceived this study. F.T.M., N.G. and Y.L.B.-P. designed and coordinated the global field survey. N.G., P.L. and Y.L.B.-P. developed the original idea of the analyses

presented in the manuscript, with inputs from F.T.M., M.B., R.M., M.D.-B., V.M., E.M.-J., H.S., S.S. and E.V. F. Jabot. developed the theoretical model on plant cover. Fieldwork was done by

all co-authors with the assistance of M.G.-G. for field site assessments. Laboratory analyses were done by V.O., B.G., S.A., C.P., M.G.-G. and I.S.P. The trait database was built by N.G.,

R.M. and Y.L.B.-P. Data and code handling, curation and verification were done by N.G., R.M., V.O., B.G., I.S.P. and Y.L.B.-P. Statistical analyses were performed by N.G., M.B., and R.M.

N.G., Y.L.B.-P. and F.T.M. wrote the first manuscript draft and all authors worked on the final version. CORRESPONDING AUTHORS Correspondence to Nicolas Gross, Fernando T. Maestre or Yoann

Le Bagousse-Pinguet. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Nature_ thanks Stéphane Dray and the other,

anonymous, reviewer(s) for their contribution to the peer review of this work. Peer review reports are available. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with

regard to jurisdictional claims in published maps and institutional affiliations. EXTENDED DATA FIGURES AND TABLES EXTENDED DATA FIG. 1 THE TRAIT SPACE OF GLOBAL DRYLAND RANGELANDS. A-C

represent the probabilistic species distributions in the space defined by a Principal Component Analysis (PCA) on whole-plant and leaf size, and on leaf chemical traits. A shows the

dimensions related to plant size and leaf C-economy. B-C show the additional, but independent dimensions related to the plant elementome characterized by the concentration of 14 elements in

plant leaves: C, N, P, Mg, Mn, Ca, Cu, Al, Ba, Fe, K, Na, S, and Zn. The dryland trait space displayed five major dimensions (Principal Components PC1 to PC5), accounting for 66.7 % of the

total trait variation. In A, Leaf traits related to leaf C-economy (PC1) and plant size (PC3) varied along two orthogonal dimensions and accounted for a total of 28.2% of trait variation. In

B-C, the plant elementome accounted for 55.5% of trait variation. While a dimension of the plant elementome covaried with the leaf C-economy dimension27 (N-P-K on PC1), it also added three

other orthogonal dimensions that were associated with important macro- and micronutrients (PC2, PC4, PC5). These findings show that a large fraction of trait diversity found across global

drylands is not captured by plant size and leaf C-economy alone, but by the plant elementome (see Supplementary Fig. 5 for an additional description of the elementome; Supplementary Fig. 8

for the PCA ran without the gap-filling of the data; Supplementary Fig. 7 for pictures of dryland plant species). The color gradient depicts the different species densities in the trait

space (high and low density in red and fading yellow, respectively). The arrow length is proportional to the trait loadings. Each point represents the location of a species within the

five-dimensional trait space for all the species surveyed (_n_ = 1347). Abbreviations: maximum plant height, H; Lateral spread, LS; Leaf length, LL; leaf area, LA; specific leaf area, SLA;

leaf dry matter content, LDMC. See also Supplementary Table 4 for detailed results. EXTENDED DATA FIG. 2 ARIDITY RESHUFFLES THE TRAIT SPACE OF GLOBAL DRYLAND RANGELANDS. We show how trait

covariation changes along the aridity gradient using Principal Component Analysis (PCA) conducted for sites with aridity values located below and above the aridity threshold of ~0.7 (Low

aridity _n_ = 338; high aridity _n_ = 1009). The arrow length is proportional to the loadings of the traits considered. In A-B, four principal components were selected at aridity values <

 0.7 while in C-E five components were selected at aridity values > 0.7. See Extended Data Fig. 1 for trait abbreviations and Supplementary Table 4 for detailed results. EXTENDED DATA

FIG. 3 PRESENCE OF GRAZERS MODULATES THE TRAIT SPACE OF GLOBAL DRYLAND RANGELANDS. We show how trait covariation changes with increasing grazing pressure using Principal Component analysis

(High Grazing _n_ = 382; Medium Grazing _n_ = 410; Low Grazing _n_ = 389; Ungrazed _n_ = 166). The arrow length is proportional to the loadings of the traits considered. In A-I, five

principal components were significantly selected in low, medium, and high grazing pressures. In J-K, four principal components were significantly selected in ungrazed plots. See Extended

Data Fig. 1 for trait abbreviations and Supplementary Table 6 for detailed results. Low = low grazing pressure, Med = medium grazing pressure, and High = high grazing pressure. EXTENDED DATA

FIG. 4 REPRESENTATION OF THE TRAIT HYPERVOLUME BEFORE AND AFTER CROSSING THE ~ 0.7 ARIDITY THRESHOLD. We show the 2D projection of the hypervolume for each pair of PCA dimensions shown in

Extended Data Fig. 1 (n-dimensions = 5, from PC1 to PC5). Colored dots represent the locations of each measured species within the trait space. The blue and the red large bright dots

represented the centroids of each hypervolume before and after an aridity value of 0.7 (low aridity _n_ = 189; high aridity _n_ = 696). Colored lines show the 0.95 confidence intervals of

the hypervolume before and after this aridity value. EXTENDED DATA FIG. 5 RESPONSE OF ELEMENTAL CONCENTRATION IN SOILS (THE SOIL ELEMENTOME) TO ARIDITY. Soil elements covary across the 326

sampled plots along a unique Principal Component axis (PC1) that account for 65.8 % of soil total variation (see Methods). A shows responses of the soil elementome, illustrated using the

soil PC 1, to aridity. PC1 shows a quadratic response to aridity with non-linear decrease occurring only in the most arid areas, i.e., those with aridity values > 0.8. Grazing did not

modify this response. B shows how the soil elementome responded to aridity using a sliding windows analysis (see methods). We first ordered the 326 plots according to their aridity level. We

then defined an aridity window that represented 10% of the global aridity gradient and selected all plots within this aridity range (n > 30 plots in each window). We finally examined how

the bootstrapped covariation of soil elements across plots changed as aridity increased. We found that aridity further increased the covariation of soil elements in the most arid rangelands

surveyed. See Supplementary Table 7 for detailed results of model selections evaluating the response of the soil elementome to aridity. Error band shows the 0.95 confidence interval in A

and B. EXTENDED DATA FIG. 6 GLOBAL DECREASE IN PLANT COVER DRIVEN BY ARIDITY AND GRAZING. A shows the averaged model parameters (± 0.95 confidence interval) for different predictors (i.e.

aridity, grazing, soil, and geographical variables) on plant cover (n = 326 plots). Significant predictors do not cross the vertical dotted line. Aridity and grazing were the main drivers of

plant cover. B illustrates the effects of aridity on plant cover. Vertical dashed and dotted lines represent the mean location of the threshold and its 0.95 confidence interval,

respectively. Error band shows the 0.95 confidence interval. C shows grazing effect on plant cover (High Grazing _n_ = 98; Medium Grazing _n_ = 97; Low Grazing _n_ = 88; Ungrazed _n_ = 43).

Data are represented as boxplots where the middle line is the median, the lower and upper hinges correspond to the first and third quartiles, the upper and lower lines show the 0.95

confidence interval. Data beyond the confidence interval are outlying points that are plotted individually. We tested whether different grazing pressure levels showed significant differences

using a generalized least squares model (p < 0.001). Letters show results of a post-hoc test based on bootstrapped pairwise comparisons between grazing pressure levels. Different letters

indicate significant differences among grazing pressure levels. Plant cover decreased non-linearly at aridity ~0.7 and was the lowest under high grazing pressure. EXTENDED DATA FIG. 7 PLANT

COVER MEDIATES THE EFFECT OF ARIDITY AND GRAZING PRESSURE ON TRAIT DIVERSITY ACROSS GLOBAL DRYLAND RANGELANDS. A-B show the response of trait diversity (hypervolume and trait covariation

respectively) to plant cover using a sliding window procedure (see Methods). Increasing plant cover decreased hypervolume and increased trait covariations, with a significant threshold value

occurring at a plant cover value close to 50% ± CI (vertical dashed lines, the dotted lines show its 0.95 percentile Confidence Interval, CI). See Supplementary Table 8 for detailed results

of model selection evaluating the response of the plant elementome to plant cover. Error band shows the 0.95 confidence interval in A and B. SUPPLEMENTARY INFORMATION SUPPLEMENTARY

INFORMATION Supplementary Figs. 1–16, Supplementary Table 1 and 3–9 and Supplementary Text 1–3. REPORTING SUMMARY PEER REVIEW FILE SUPPLEMENTARY TABLE 2 Role of the elementome for plant

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and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Gross, N., Maestre, F.T., Liancourt, P. _et al._ Unforeseen plant phenotypic diversity in a dry and grazed world. _Nature_ 632, 808–814

(2024). https://doi.org/10.1038/s41586-024-07731-3 Download citation * Received: 22 June 2023 * Accepted: 18 June 2024 * Published: 07 August 2024 * Issue Date: 22 August 2024 * DOI:

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