Soil fungal abundance and plant functional traits drive fertile island formation in global drylands

Dryland vegetation is characterized by discrete plant patches that accumulate and capture soil resources under their canopies. These “fertile islands” are major drivers of dryland ecosystem structure and functioning, yet we lack an integrated understanding of the factors controlling their magnitude and variability at the global scale.EEA BarilocheFil: Ochoa-Hueso, Raúl. Universidad Autónoma de Madrid. Department of Ecology; EspañaFil: Eldridge, David J. University of New South Wales. School of Biological, Earth and Environmental Sciences; AustraliaFil: Delgado-Baquerizo, Manuel. University of Colorado. Cooperative Institute for Research in Environmental Sciences; Estados Unidos. Universidad Rey Juan Carlos. Escuela Superior de Ciencias Experimentales y Tecnología. Departamento de Biología y Geología, Física y Química Inorgánica; EspañaFil: Soliveres, Santiago. University of Bern. Institute of Plant Sciences; SuizaFil: Bowker, Matthew A. Northern Arizona University. School of Forestry; Estados UnidosFil: Gross, Nicolás. Universidad Rey Juan Carlos. Escuela Superior de Ciencias Experimentales y Tecnología. Departamento de Biología y Geología, Física y Química Inorgánica; España. Institut Nationale de la Recherche Agronomique; Francia. Université La Rochelle. Centre d’étude biologique de Chizé; FranciaFil: Le Bagousse-Pinguet, Yoann. Universidad Rey Juan Carlos. Escuela Superior de Ciencias Experimentales y Tecnología. Departamento de Biología y Geología, Física y Química Inorgánica; EspañaFil: Quero, José L. Universidad de Córdoba. Escuela Técnica Superior de Ingeniería Agronómica y de Montes. Departamento de Ingeniería Forestal: EspañaFil: García-Gómez, Miguel. Universidad Rey Juan Carlos. Escuela Superior de Ciencias Experimentales y Tecnología. Departamento de Biología y Geología, Física y Química Inorgánica; EspañaFil: Valencia, Enrique. Universidad Rey Juan Carlos. Escuela Superior de Ciencias Experimentales y Tecnología. Departamento de Biología y Geología, Física y Química Inorgánica; EspañaFil: Arredondo, Tulio. Instituto Potosino de Investigación Científica y Tecnológica. División de Ciencias Ambientales; MéxicoFil: Beinticinco, Laura. Universidad Nacional de La Pampa. Facultad de Agronomía; ArgentinaFil: Bran, Donaldo Eduardo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; ArgentinaFil: Cea, Alex. Universidad de La Serena. Departamento de Biología; ChileFil: Coaguila, Daniel. Instituto de Ensino Superior de Rio Verde; BrasilFil: Dougill, Andrew J. University of Leeds. School of Earth and Environment; Gran BretañaFil: Espinosa, Carlos I. Universidad Técnica Particular de Loja. Departamento de Ciencias Naturales; EcuadorFil: Gaitan, Juan Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Guuroh, Reginald T. University of Cologne. Botanical Institute. Range Ecology and Range Management Group; Alemania. CSIR-Forestry Research Institute of Ghana; GhanaFil: Guzmán, Elizabeth. Universidad Técnica Particular de Loja. Departamento de Ciencias Naturales; EcuadorFil: Gutiérrez, Julio R.. Universidad de La Serena. Departamento de Biología; Chile. Centro de Estudios Avanzados en Zonas Áridas (CEAZA); Chile. Instituto de Ecología y Biodiversidad; ChileFil: Hernández, Rosa M. Universidad Experimental Simón Rodríguez. Centro de Agroecología Tropical. Laboratorio de Biogeoquímica; VenezuelaFil: Huber-Sannwald, Elisabeth. Instituto Potosino de Investigación Científica y Tecnológica. División de Ciencias Ambientales; MéxicoFil: Jeffries, Thomas. Western Sydney University. Hawkesbury Institute for the Environment; AustraliaFil: Linstädter, Anja. University of Cologne. Botanical Institute. Range Ecology and Range Management Group; AlemaniaFil: Mau, Rebecca L. Northern Arizona University. Center for Ecosystem Science and Society: Estados UnidosFil: Monerris, Jorge. Université du Québec à Montréal. Pavillon des Sciences Biologiques. Département des Sciences Biologiques; CanadáFil: Prina, Anibal. Universidad Nacional de La Pampa. Facultad de Agronomía; ArgentinaFil: Pucheta, Eduardo. Universidad Nacional de San Juan. Facultad de Ciencias Exactas, Físicas y Naturales. Departamento de Biología; ArgentinaFil: Stavi, Ilan. Dead Sea and Arava Science Center, IsraelFil: Thomas, Andrew. Aberystwyth University. Department of Geography and Earth Sciences; Gran BretañaFil: Zaady, Eli. Agricultural Research Organization. Gilat Research Center. Natural Resources; IsraelFil: Singh, Brajesh K. Western Sydney University. Hawkesbury Institute for the Environment; Australia. Western Sydney University. Global Centre for Land-Based Innovation; AustraliaFil: Maestre, Fernando T. Universidad Rey Juan Carlos. Escuela Superior de Ciencias Experimentales y Tecnología. Departamento de Biología y Geología, Física y Química Inorgánica; Españ

Soil fungal abundance and plant functional traits drive fertile island formation in global drylands

International audience1.Dryland vegetation is characterised by discrete plant patches that accumulate and capture soil resources under their canopies. These “fertile islands” are major drivers of dryland ecosystem structure and functioning, yet we lack an integrated understanding of the factors controlling their magnitude and variability at the global scale.2.We conducted a standardized field survey across two hundred and thirty-six drylands from five continents. At each site, we measured the composition, diversity and cover of perennial plants. Fertile island effects were estimated at each site by comparing composite soil samples obtained under the canopy of the dominant plants and in open areas devoid of perennial vegetation. For each sample, we measured fifteen soil variables (functions) associated with carbon, nitrogen and phosphorus cycling and used the Relative Interaction Index to quantify the magnitude of the fertile island effect for each function. In eighty sites, we also measured fungal and bacterial abundance (quantitative PCR) and diversity (Illumina MiSeq).3.The most fertile islands, i.e. those where a higher number of functions were simultaneously enhanced, were found at lower-elevation sites with greater soil pH values and sand content under semiarid climates, particularly at locations where the presence of tall woody species with a low specific leaf area increased fungal abundance beneath plant canopies, the main direct biotic controller of the fertile island effect in the drylands studied. Positive effects of fungal abundance were particularly associated with greater nutrient contents and microbial activity (soil extracellular enzymes) under plant canopies.4.Synthesis. Our results show that the formation of fertile islands in global drylands largely depends on: (i) local climatic, topographic and edaphic characteristics, (ii) the structure and traits of local plant communities and (iii) soil microbial communities. Our study also has broad implications for the management and restoration of dryland ecosystems worldwide, where woody plants are commonly used as nurse plants to enhance the establishment and survival of beneficiary species. Finally, our results suggest that forecasted increases in aridity may enhance the formation of fertile islands in drylands worldwide

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Hotspots of biogeochemical activity linked to aridity and plant traits across global drylands

14 páginas.- 4 figuras.- 67 referencias.- The online version contains supplementary material available at https://doi.org/10.1038/s41477-024-01670-7Perennial plants create productive and biodiverse hotspots, known as fertile islands, beneath their canopies. These hotspots largely determine the structure and functioning of drylands worldwide. Despite their ubiquity, the factors controlling fertile islands under conditions of contrasting grazing by livestock, the most prevalent land use in drylands, remain virtually unknown. Here we evaluated the relative importance of grazing pressure and herbivore type, climate and plant functional traits on 24 soil physical and chemical attributes that represent proxies of key ecosystem services related to decomposition, soil fertility, and soil and water conservation. To do this, we conducted a standardized global survey of 288 plots at 88 sites in 25 countries worldwide. We show that aridity and plant traits are the major factors associated with the magnitude of plant effects on fertile islands in grazed drylands worldwide. Grazing pressure had little influence on the capacity of plants to support fertile islands. Taller and wider shrubs and grasses supported stronger island effects. Stable and functional soils tended to be linked to species-rich sites with taller plants. Together, our findings dispel the notion that grazing pressure or herbivore type are linked to the formation or intensification of fertile islands in drylands. Rather, our study suggests that changes in aridity, and processes that alter island identity and therefore plant traits, will have marked effects on how perennial plants support and maintain the functioning of drylands in a more arid and grazed world.This research was supported by the European Research Council (ERC grant 647038 (BIODESERT) awarded to F.T.M.) and Generalitat Valenciana (CIDEGENT/2018/041). D.J.E. was supported by the Hermon Slade Foundation (HSF21040). J. Ding was supported by the National Natural Science Foundation of China Project (41991232) and the Fundamental Research Funds for the Central Universities of China. M.D.-B. acknowledges support from TED2021-130908B-C41/AEI/10.13039/501100011033/Unión Europea Next Generation EU/PRTR and the Spanish Ministry of Science and Innovation for the I + D + i project PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033. O.S. was supported by US National Science Foundation (Grants DEB 1754106, 20-25166), and Y.L.B.-P. by a Marie Sklodowska-Curie Actions Individual Fellowship (MSCA-1018 IF) within the European Program Horizon 2020 (DRYFUN Project 656035). K.G. and N.B. acknowledge support from the German Federal Ministry of Education and Research (BMBF) SPACES projects OPTIMASS (FKZ: 01LL1302A) and ORYCS (FKZ: FKZ01LL1804A). B.B. was supported by the Taylor Family-Asia Foundation Endowed Chair in Ecology and Conservation Biology, and M. Bowker by funding from the School of Forestry, Northern Arizona University. C.B. acknowledges funding from the National Natural Science Foundation of China (41971131). D.B. acknowledges support from the Hungarian Research, Development and Innovation Office (NKFI KKP 144096), and A. Fajardo support from ANID PIA/BASAL FB 210006 and the Millennium Science Initiative Program NCN2021-050. M.F. and H.E. received funding from Ferdowsi University of Mashhad (grant 39843). A.N. and M.K. acknowledge support from FCT (CEECIND/02453/2018/CP1534/CT0001, SFRH/BD/130274/2017, PTDC/ASP-SIL/7743/2020, UIDB/00329/2020), EEA (10/CALL#5), AdaptForGrazing (PRR-C05-i03-I-000035) and LTsER Montado platform (LTER_EU_PT_001) grants. O.V. acknowledges support from the Hungarian Research, Development and Innovation Office (NKFI KKP 144096). L.W. was supported by the US National Science Foundation (EAR 1554894). Y.Z. and X.Z. were supported by the National Natural Science Foundation of China (U2003214). H.S. is supported by a María Zambrano fellowship funded by the Ministry of Universities and European Union-Next Generation plan. The use of any trade, firm or product names does not imply endorsement by any agency, institution or government. Finally, we thank the many people who assisted with field work and the landowners, corporations and national bodies that allowed us access to their land.Peer reviewe