Philippa Kaur

Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, the NetherlandsAndrew K. Skidmore, Elnaz Neinavaz, Abebe Ali, Roshanak Darvishzadeh, Marcelle C. Lock & Tiejun WangDepartment of Earth and Environmental Science, Macquarie University, Sydney, New South Wales, AustraliaAndrew K. Skidmore & Marcelle C. LockDepartment of Forest Resources Management, University of British Columbia, Vancouver, British Columbia, CanadaNicholas C. CoopsDepartment of Geography and Environmental Studies, Wollo University, Dessie, EthiopiaAbebe AliRemote Sensing Laboratories, Department of Geography, University of Zurich, Zurich, SwitzerlandMichael E. SchaepmanEuropean Space Research Institute (ESRIN), European Space Agency, Frascati, ItalyMarc PaganiniInstitute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Amsterdam, the NetherlandsW. Daniel KisslingBiodiversity Centre, Finnish Environment Institute (SYKE), Helsinki, FinlandPetteri VihervaaraInstitute of Geographical Sciences, Freie Universität Berlin, Berlin, GermanyHannes FeilhauerRemote Sensing Center for Earth System Research, University of Leipzig, Leipzig, GermanyHannes FeilhauerNatureServe, Arlington, VA, USAMiguel FernandezGeorge Mason University, Fairfax, VA, USAMiguel FernandezGerman Centre for Integrative Biodiversity Research (iDiv), Leipzig, GermanyNéstor FernándezInstitute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale), GermanyNéstor FernándezGoogle, Zurich, SwitzerlandNoel GorelickTour du Valat, Arles, FranceIlse GeijzendorfferEarth Observation Center (EOC), Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, GermanyUta Heiden & Stefanie HolzwarthDepartment of Visitor Management and National Park Monitoring, Bavarian Forest National Park Administration, Grafenau, GermanyMarco HeurichAlbert Ludwigs University of Freiburg, Freiburg, GermanyMarco HeurichGBIF Secretariat, Copenhagen, DenmarkDonald HobernCollege of Marine Science, University of South Florida, St Petersburg, FL, USAFrank E. Muller-KargerFlemish Institute for Technological Research (VITO), Mol, BelgiumRuben Van De KerchoveComputational Landscape Ecology, Helmholtz Centre for Environmental Research (UFZ), Leipzig, GermanyAngela LauschGeography Department, Humboldt University of Berlin, Berlin, GermanyAngela LauschTechnische Universität Braunschweig, Braunschweig, GermanyPedro J. LeitãoHumboldt-Universität zu Berlin, Berlin, GermanyPedro J. LeitãoWageningen Environmental Research, Wageningen University & Research, Wageningen, the NetherlandsCaspar A. MücherUN Environment World Conservation Monitoring Centre, Cambridge, UKBrian O’ConnorDepartment of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, ItalyDuccio RocchiniDepartment of Applied Geoinformatics and Spatial Planning, Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech RepublicDuccio RocchiniEarth Science Division, NASA, Washington DC, USAWoody TurnerUnilever Europe B.V., Rotterdam, the NetherlandsJan Kees VisInstitute of Geography and Geology, University of Wuerzburg, Würzburg, GermanyMartin WegmannLand Systems and Sustainable Land Management, Geographisches Institut, Universität Bern, Bern, SwitzerlandVladimir Wingate More

Effects of the two planting systems on soil fungal diversityIn this study, 561,254 sequences were generated from 15 samples obtained from 5 treatments. Base sequences with a length of 201–300 bp accounted for 97.82% of all sequences (Table S1a,b). Rarefaction curves at a similarity level of 97% indicated that the number of sequences extracted from most samples tended to plateau above 10,000. The number of sequences extracted in the test exceeded 30,000, suggesting that the sequencing data were close to saturation, sequencing depth was reasonable, and the results reflected true sample conditions (Fig. 1). The coverage of all samples was above 99.84%. The range of reads in each sample was between 34,390 and 43,510. The range of Operational Taxonomic Units (OTUs) in each sample was between 145 and 318 (Table 1).Figure 1α-Diversity comparison. Rarefaction curves for OTUs were calculated using Mothur (v1.27.0) with reads normalized to more than 30,000 for each sample using a distance of 0.03 OTU.Full size imageTable 1 Comparison of α-diversity indices in TPP and VEE soil samples.Full size tableThe analysis of alpha diversity showed that with increasing planting time, soil fungal OTUs, the Chao index, and the ACE index in TPP-treated plots increased and then decreased with time. In the VEE-IPBP-treated plots, these 3 indexes increased with time and were 56.94%, 33.81%, and 32.50% higher than those in the TPP-treated plots, respectively, after 6 years of implementation (p  More

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Sampling, preparation and treatment of modern reference materialA total of 53 modern wood samples were analyzed. The modern reference samples were collected in 2014 during the annual archaeological field mission, from 36 individuals (Table S1). For some trees, two wood samples of different diameters were collected in order to take into account anatomical variability within individual.The collected individuals showed different conditions of growth described in the introduction section and detailed in the Table 1. With the agreement of the Tifigit inhabitants and local authorities, wood sampling was achieved but samples were not collected from trunks, to avoid injuring trees of major symbolic, ecological and economic importance. Only section samples with perfect axial symmetry were retained to avoid any impact of biomechanical constraints (formation of reaction wood) on wood characters.Once collected, the samples were air-dried during a month at the laboratory. The samples were separately wrapped in tin foil and buried in the sand and then charred without oxygen, at 450 °C for 15 to 20 min depending on the size of the sample. As a result, samples were enriched in carbon (content  > 90%)20,26, reached their maximal shrinkage27, and thus are considered to become morphologically comparable to charcoal produced in medieval fires27,28,29,30,31. The minimum and the maximum diameter of wood samples were measured (mm) using a digital measuring calliper before and after carbonization. The diameter used in the following analyses is the mean of the two measurements carried out before carbonization.Archaeological materialTwenty archaeological charcoal fragments of Argan tree identified during a previous analysis session13 were included in this study (Table S2). All the Argan charcoal fragments were collected in the medieval archaeological deposits of Îgîlîz13. They come from various contexts, for the most part from living units, and belong to the period of highest human activity at the site, between the late 11th and early thirteenth centuries.Quantitative eco-anatomical analysis of wood applied to the Argan treeThe approach consists in measuring constitutive elements of wood and aims to understand variations according to intrinsic (inferred by the branch diameter mainly age of tree18, linked to the existence of growth rings that are often difficult to distinguish) and environmental parameters affecting the cambial activity and thus, rate of growth and wood development20,28,29,30. This high resolution analysis of wood structure, particularly of conductive elements, allows addressing numerous questions that have been successfully solved in the case of the olive tree and the grapevine, such as phenology, ecology, climate, impact of human activities and agricultural practices20,24,25,31,32,33.Argania spinosa wood is diffuse-porous with a dendritic and diagonal arrangement of vessel elements in transversal section34. The axial parenchyma bands are in tangential alignment and composed of multicellular strands. In radial alignment, woody rays are 1–3 cells wide and of heterocellular composition (Fig. 6).Figure 6Wood anatomical features of the Argan tree (in blue) and measured anatomical characters (in red).Full size imageTo apply a quantitative eco-anatomy approach to the Argan tree, both modern charred samples and archaeological charcoal are broken manually in transverse anatomical section. The following wood constitutive elements and anatomical characters related to sap conduction and reserve storage are observed and measured under a reflected-light microscope connected with an image analysis system (DFC300 FX Leica camera and LAS Leica software) (Fig. 6): (1) vessel density (DVS—number of vessels / mm2), (2) vessel surface area (SVS, µm2), (3) ray density (DRA—number of rays / mm2), (4) axial parenchyma density (DPA, number of bands / mm2), (5) Density of wood fenestrated zones bordered on one side by the radial alignment of axial parenchyma cells and on the other side, tangentially, by rays (DWF—number of fenestrated zones / mm2).These anatomical features were measured several times (see ‘Statistical analyses’ section) following radial lines from the cambium inwards the sample and crossing a small number of growth rings (i.e. functional rings from a sap conduction point of view). Moreover, the hydraulic conductivity or vascular conductivity (CD) was assessed using the following formula: CD = (SVS/π)2/DVS (after32,35,36,37). Finally, the ratio ‘Conductive surface / total wood area’ (SC) was calculated.Statistical analysesIn order to determine the number of measurements required for an optimal assessment of anatomical features, a rarefaction method was carried out from the analysis of test wood samples. For each one, repeated measurements of anatomical characters (Surface vessel area (SVS), Density of vessels (DVS), Ray density (DRA), Axial parenchyma density (DPA) and Density of wood fenestrated zones (DWF)) were performed following the aforementioned method and the cumulative mean value was then calculated for each character20,29. For each test sample and anatomical character, the number of measurements of a character required for an optimal assessment was quantified as the minimum number of measurements required to stabilize the mean value (rarefaction curve or cumulative mean curve).Furthermore, different measurement sessions were carried out with the aim of testing possible errors and reproducibility of measurements taken by one or various observers, respectively. The data sets produced were tested using the PCA performed to evaluate the Argan anatomical variability. The ARG8-2 sample was used as test sample. In addition to the initial measurements. The ARG8-2 sample was analyzed 4 times: twice by one operator (ARG8-2 (1-OP1) and ARG8-2 (2-OP1)) and twice by another (ARG8-2 (3-OP2) and ARG8-2 (3-OP2)) at different times. The additional data were incorporated into the PCA as additional individuals for comparison with initial anatomical features of ARG8-2.After showing that measurement errors have no impact on the validity of results and the measurements are reproducible, quantitative eco-anatomical data were processed using a principal component analysis (PCA) in order to evaluate anatomical plasticity in the reference modern material, to appreciate relationships between characters and wood sample caliber and to confront archaeological data to the reference model. PCA was applied on 53 reference modern samples and 7 quantitative variables (anatomical characters) to: (1) validate the hypothesis that there is a significant relationship between the size of the branch and anatomy, as previously demonstrated by analyses of wood development and structure18,20,38 and dendrochronology39; (2) identify the anatomical characters most affected by the age of the branch and, in that case, model the ‘anatomical characters—caliber of the branch’ relationship; (3) develop predictive model that might estimate the minimum branch caliber from eco-anatomical data of archaeological charcoal.Finally, data from analysis of the 20 archaeological charcoal fragments were included in PCA as additional statistical samples. They do not contribute to the development of the reference model, but are compared to the modern reference samples in order to infer the ecological conditions under which Argan trees grew during the Middle Ages. More

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Study area and parcel selectionThe study was conducted in Castro Verde Special Protection Area (SPA), located in southern Portugal (Fig. 1). The climate is Mediterranean, with hot summers (30–35 °C on average in July) and mild winters (averaging 5–8 °C in January), and over 75% of annual rainfall (500–600 mm) concentrated in October–March. The landscape is flat or gently undulating (100–300 m), mainly dominated by open areas used for rainfed pastures (ca. 60%) and annual crops (ca. 25%), and to a less extent by open woodlands (ca. 7%)15.Figure 1(a) Location of the study area within the Castro Verde Special Protected Area (SPA), southern Portugal. (b) Distribution of the 27 sheep (dark grey polygons) and 23 cattle (light grey polygons) grazing parcels and (c) Sampling scheme applied to each parcel surveyed. Bird counts were done at the centroid of the parcel (white dot) whereas vegetation sampling was performed at the indicated 10 points (black dots). The area covered with pastures and annual crops (derived from CORINE land cover 2018—https://land.copernicus.eu/pan-european/corine-land-cover/clc2018) is shown in yellow. The map was done using the version 3.10.0 of QGIS—https://qgis.org/en/site/index.html.Full size imageSince 1995, part of the study area has benefited from a CAP agri-environment aiming to protect the traditional farming system16. This scheme provides financial support to farmers for agricultural practices considered favourable to conservation, including the traditional rotation of cereals and fallows, the maintenance of low stocking rates (usually related with sheep grazing systems), and sowing of crops benefiting grassland birds16. However, in recent years the traditional farming system has been declining, with many farmers converting to specialized livestock systems, mainly, cattle grazing systems, with an increase of stocking rates7,15.Parcel selection started by identifying grasslands grazed by either sheep or cattle, based on parcel-level statistical information from 2010 provided by the Portuguese Ministry of Agriculture7. To minimize potentially confounding effects of adjacent land uses (edge effects) and other non-crop elements within parcels on bird assemblages, we excluded parcels less than 100 m from shrubland or forested areas, with shrub and tree cover  > 5% and with a minimum size of 10 ha. In January 2019 we visited 100 pre-selected parcels which were grazed by either sheep or cattle in 2010 in order to confirm the parcel land use in the agricultural year of 2018/2019, aiming to sample a balanced proportion of 50 sheep and cattle grazed parcels. Additional livestock information for the agricultural year of 2018/2019 was obtained during systematic visits to targeted parcels (see “Grazing Regime” section from Methods). We ended up with 23 cattle parcels and 27 sheep parcels (Fig. 1).Bird and vegetation dataBreeding birds were sampled twice in each parcel during 7–16 April and 1–15 May 2019 respectively, always by the same observer (R.F.R). This was done to take into account species-specific breeding phenology in the area (early and late breeders)17 and minimize bias due to other factors (like weather or disturbance). Sampling was conducted using standardized 10 min point counts18 carried out at the central point of the parcel (Fig. 1). As the open terrain allowed for high visibility, a large detection radius was used, and all birds detected within 100 m of the central point were identified and counted. This radius is roughly similar to the one previously used for characterizing bird populations in the region19. All counts were carried out in the first four hours after sunrise and in the last two hours before sunset, with none in heavy or persistent rain, or in strong wind conditions. To estimate bird species richness and occurrences in each parcel, we pooled the data from the two counts. Species-level analyses focused on the six most common species, which occurred in  > 30% of the parcels (see Supplementary Table S1). In addition to presence/absence, we also estimated population densities, using the count which yielded the highest estimate of density for each species (assuming this is the best indicator of population density, given the potential phenology and detectability biases above mentioned). Bird densities were based on the number of males simultaneously detected and expressed as breeding pairs/10 ha or males/10 ha (in the case of Little Bustard Tetrax tetrax and Common Quail Coturnix coturnix). Categorization to the genus level was made for the Crested and Thekla larks (Galerida cristata and G. theklae) due to difficulties in correctly identifying all individuals of these two very similar species in the field.Vegetation height and cover were measured once in each parcel, between April 22 and May 6. Vegetation height was estimated in a set of ten 3 m radius plots defined inside the 100 m buffer (Fig. 1). In each plot, ten measurements of vegetation height were taken at random locations, for a total of 100 measurements per parcel. Vegetation height was measured using a 50 cm ruler and was defined as the highest point of vegetation projection within 3 cm of the ruler20. All values were estimated to the nearest half centimeter. When no vegetation was present (bare soil, soil litter, rocks or animal dung) the height was set to zero (0) but these measurements were not considered to estimate the mean height of the sward. Vegetation cover was measured inside a 50 × 50 cm quadrat placed at each of the ten grid points, by visual estimation to the nearest 5% of the percentage of the quadrat area covered by vegetation21 (Fig. 1). Vegetation height and cover measurements were averaged within each parcel.Grazing regimeThe number and type of livestock in each parcel as well as the extent of the grazing period since the start of the year (2019) were gathered from interviews (Supplementary Information S1) to land managers during 1–15 May 2019. This information was further validated, and corrected in a few cases, through field checks during regular visits (made at two-week intervals) to the parcels (see “Bird and vegetation data” section from Methods). Three grazing regime indicators were estimated for the whole period (January–May 2019): livestock type (either sheep or cattle), animal density, and grazing pressure. The animal density in each parcel was calculated as the average density (animals per hectare) of any species (regardless of being sheep or cattle) that grazed the parcel during the 5-months period. Stocking Rate translated animal density into livestock unit (LU) per hectare (LU/ha), between January and May, according to the following criteria: one adult bovine = 1 LU; bovine aged  More

German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstrasse 4, 04103, Leipzig, GermanyHelen R. P. Phillips, Joanne M. Bennett, Rémy Beugnon, Olga Ferlian, Carlos A. Guerra, Birgitta König-Ries, Julia J. Krebs, Ulrich Brose & Nico EisenhauerInstitute of Biology, Leipzig University, Puschstrasse 4, 04103, Leipzig, GermanyHelen R. P. Phillips, Rémy Beugnon, Olga Ferlian, Julia J. Krebs & Nico EisenhauerDepartment of Environmental Science, Saint Mary’s University, Halifax, Nova Scotia, CanadaHelen R. P. Phillips & Erin K. CameronGlobal Soil Biodiversity Initiative and School of Global Environmental Sustainability, Colorado State University, Fort Collins, CO, 80523, USAElizabeth M. Bach & Diana H. WallDepartment of Biology, Colorado State University, Fort Collins, CO, 80523, USAElizabeth M. Bach & Diana H. WallUniversidade Positivo, Rua Prof. Pedro Viriato Parigot de Souza, 5300, Curitiba, PR, 81280-330, BrazilMarie L. C. BartzCenter of Functional Ecology, Department of Life Sciences, University of Coimbra, Calçada Martins de Freitas, 3000-456, Coimbra, PortugalMarie L. C. BartzInstitute of Biology, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, 06108, Halle (Saale), GermanyJoanne M. Bennett & Carlos A. GuerraCentre for Applied Water Science, Institute for Applied Ecology, Faculty of Science and Technology, University of Canberra, Canberra, AustraliaJoanne M. BennettDepartamento de Ecología y Biología Animal, Universidad de Vigo, 36310, Vigo, SpainMaria J. I. BrionesEmbrapa Forestry, Estrada da Ribeira, km. 111, C.P. 231, Colombo, PR, 83411-000, BrazilGeorge G. BrownA.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Leninsky pr., 33, Moscow, 119071, RussiaKonstantin B. Gongalsky & Iurii M. LebedevM.V. Lomonosov Moscow State University, Leninskie Gory, 1, Moscow, 119991, RussiaKonstantin B. Gongalsky & Iurii M. LebedevInstitute of Computer Science, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743, Jena, GermanyBirgitta König-RiesEuropean Commission, Joint Research Centre (JRC), Ispra, ItalyAlberto OrgiazziDepartment of Terrestrial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), 6700, Wageningen, AB, The NetherlandsKelly S. Ramirez, Wim H. van der Putten & Madhav P. ThakurSenckenberg Museum for Natural History Görlitz, Department of Soil Zoology, 02826, Görlitz, GermanyDavid J. RussellBiometry and Environmental System Analysis, University of Freiburg, Tennenbacher Str. 4, 79106, Freiburg, GermanyBenjamin SchwarzInstitute of Biodiversity, Friedrich Schiller University Jena, Dornburger-Str. 159, 07743, Jena, GermanyUlrich BroseCEFE, Univ Montpellier, CNRS, EPHE, IRD, Univ Paul Valéry Montpellier 3, Montpellier, FranceThibaud DecaënsSorbonne Université, Institut d’Ecologie et des Sciences de l’Environnement, 75005, Paris, FrancePatrick LavelleCentre for Biodiversity Theory and Modelling, Theoretical and Experimental Ecology Station, CNRS, 09200, Moulis, FranceMichel LoreauSorbonne Université, Institute of Ecology and Environmental Sciences of Paris (UMR 7618 IEES-Paris, CNRS, INRA, UPMC, IRD, UPEC), 4 place Jussieu, 75000, Paris, FranceJérôme MathieuINRA, IRD, Institut d’Ecologie et des Sciences de l’Environnement de Paris, F-75005, Paris, FranceJérôme MathieuDepartment of Biological, Geological and Environmental Sciences, University of Catania, Via Androne 81, 95124, Catania, ItalyChristian MulderLaboratory of Nematology, Wageningen University, PO Box 8123, 6700, Wageningen, ES, The NetherlandsWim H. van der PuttenInstitute of Biology, Freie Universität Berlin, 14195, Berlin, GermanyMatthias C. Rillig & Daniel R. LammelInstitute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The NetherlandsFranciska T. de VriesAsian School of the Environment, Nanyang Technological University, Singapore, 639798, SingaporeDavid A. WardleCentre of Biodiversity and Sustainable Landuse, University of Göttingen, Büsgenweg 1, Göttingen, GermanyChristian AmmerSilviculture and Forest Ecology of the Temperate Zones, University of Göttingen, Büsgenweg 1, Göttingen, GermanyChristian AmmerForest Sciences and Forest Ecology, University of Göttingen, Büsgenweg 1, Göttingen, GermanySabine AmmerInstitute for Agro-Environmental Sciences, National Agriculture and Food Research Organization, 3-1-3 Kan-nondai, Tsukuba, Ibaraki, JapanMiwa AraiLand Resource Management and Agricultural Technology, University of Nairobi, Kapenguria Road, Off Naivasha Road, P.O Box 29053, Nairobi, KenyaFredrick O. AyukeRwanda Institute for Conservation Agriculture, KG 541, Kigali, RwandaFredrick O. AyukeHealth & Biosecurity, CSIRO, PO Box 1700, Canberra, AustraliaGeoff H. BakerDepartment of Animal Science, Santa Catarina State University, Chapecó, SC, 89815-630, BrazilDilmar BarettaExperimental Infrastructure Platform (EIP), Leibniz Centre for Agricultural Landscape Research, Eberswalder Str. 84, Müncheberg, GermanyDietmar Barkusky & Monika JoschkoDépartment de biologie, Université de Sherbrooke, Sherbrooke, Québec, CanadaRobin Beauséjour & Robert L. BradleyGeology Department, FCEFQyN, ICBIA-CONICET (National Scientific and Technical Research Council), National University of Rio Cuarto, Ruta 36 Km, 601, Río Cuarto, ArgentinaJose C. Bedano & Anahí DomínguezDepartment of Ecology, Brandenburg University of Technology, Konrad-Wachsmann-Allee 6, Cottbus, GermanyKlaus BirkhoferEco&Sols, Univ Montpellier, IRD, INRAE, CIRAD, Institut Agro, Montpellier, FranceEric Blanchart & Michel BrossardNatural Resources, Cornell University, Ithaca, NY, USABernd BlosseyEarth Institute, University College Dublin, Belfield, Dublin, 4, IrelandThomas BolgerSchool of Biology and Environmental Science, University College Dublin, Belfield, Dublin, IrelandThomas BolgerDepartment of Entomology, Cornell University, 3132, Comstock Hall, Ithaca, NY, USAJames C. BurtisEMMAH, UMR 1114, INRA, Site Agroparc, Avignon, FranceYvan CapowiezThe School of Agriculture, Food and Wine, The Waite Research Institute, The University of Adelaide, PMB 1, Glen Osmond, AustraliaTimothy R. CavagnaroFaculty of Forestry, University of Toronto, 33 Willcocks Street, Toronto, CanadaAmy Choi & Sandy M. 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CrumseyDepartment of Biological Sciencies, SUNY Cortland, 1215 Bowers Hall, Cortland, USAAndrea DávalosBiodiversity, Ecology and Evolution, Faculty of Biology, University Complutense of Madrid, José Antonio Novais, 12, Madrid, SpainDarío J. Díaz Cosín, Mónica Gutiérrez López, Juan B. Jesús, Marta Novo & Dolores TrigoYale School of the Environment, Yale University, 370 Prospect St, New Haven, CT, USAAnnise M. DobsonDepartamento de Ciencias Básicas, Universidad Nacional de Luján, Argentina – INEDES (Universidad Nacional de Luján – CONICET), Luján, ArgentinaAndrés Esteban DuhourLouis Bolk Institute, Kosterijland 3-5, Bunnik, The NetherlandsNick van EekerenDepartment of Soil Science, University of Trier, Campus II, Behringstraße 21, Trier, GermanyChristoph EmmerlingDepartamento de Ciencias Básicas, Instituto de Ecología y Desarrollo Sustentable, Universidad Nacional de Luján, Av. Constitución y Ruta 5, Luján, ArgentinaLiliana B. 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GeraskinaRazi University, Kermanshah, IranShaieste Gholami & Ehsan SayadUnited States Department of Agriculture, Forest Service, International Institute of Tropical Forestry, 1201 Ceiba Street, San Juan, Puerto RicoGrizelle GonzálezDepartment of Forest Ecology and Management, Swedish University of Agricultural Sciences, Skogsmarksgrand 17, 901 83, Umeå, SwedenMichael J. GundaleDepartment of Biology, University of Osijek, Cara Hadrijana 8 A, Osijek, CroatiaBranimir K. Hackenberger & Davorka K. HackenbergerAgriculture engineering, Agroecology Postgraduate Program, Maranhão State University, Avenida Lourenço Vieira da Silva 1000, São Luis, BrazilLuis M. Hernández & Guillaume X. RousseauDepartment of Jobs, Precincts and Regions, Agriculture Victoria, Chiltern Valley Road, Rutherglen, AustraliaJeff R. HirthFaculty of Agriculture, Kyushu University, 394 Tsubakuro, Sasaguri, Fukuoka, 811-2415, JapanTakuo HishiMinnesota Pollution Control Agency, 520 Lafayette Road, St Paul, MN, USAAndrew R. HoldsworthDepartment of Bioscience, Aarhus University, Vejlsøvej 25, Aarhus, DenmarkMartin HolmstrupDepartment of Biological Science, Northern Kentucky University, 1 Nunn Drive, Highland Heights, KY, USAKristine N. HopfenspergerAgricultura Sociedad y Ambiente, El Colegio de la Frontera Sur, Av. Polígono s/n Cd. Industrial Lerma, Campeche, Campeche, MexicoEsperanza Huerta LwangaSoil Physics and Land Management Group, Wageningen University & Research, Droevendaalsteeg 4, Wageningen, The NetherlandsEsperanza Huerta Lwanga & Loes van SchaikDept. of Biological and Environmental Sciences, University of Jyväskylä, Box 35, Jyväskylä, FinlandVeikko HuhtaCollege of Agriculture, Environmental and Human Sciences, Lincoln University of Missouri, Jefferson City, MO, 65101, USATunsisa T. HurissoSchool of Forest Resources and Conservation, University of Florida, Gainesville, USABasil V. Iannone IIISustainable Development and Environmental Engineering, University of Agricultural Sciences and Veterinary Medicine of Banat “King Michael the 1st of Romania” from Timisoara, Calea Aradului 119, Timisoara, RomaniaMadalina IordacheInstitute for Ecosystem Research, University of Kiel, Olshausenstrasse 40, 24098, Kiel, GermanyUlrich IrmlerTartu College, Tallinn University of Technology, Puiestee 78, Tartu, EstoniaMari IvaskDepartment of Soil and Water Systems, University of Idaho, 875 Perimeter Drive MS, 2340, Moscow, USAJodi L. Johnson-MaynardFaculty of Food and Agricultural Sciences, Fukushima University, Kanayagawa 1, Fukushima, JapanNobuhiro KanekoDepartment of Environment, Faculty of Natural Sciences, Matej Bel University, Tajovského 40, Banská Bystrica, SlovakiaRadoslava KanianskaUK Centre for Ecology & Hydrology, Library Avenue, Bailrigg, Lancaster, United KingdomAidan M. KeithLand Use and Governance, Leibniz Centre for Agricultural Landscape Research, Eberswalder Str. 84, Müncheberg, GermanyMaria L. KerneckerUFR Sciences de la Nature, UR Gestion Durable des Sols, Université Nangui Abrogoua, Abidjan, Côte d’IvoireArmand W. KonéFaculty of Natural Resources and Marine Sciences, Tarbiat Modares University, 46417-76489, Noor, Mazandaran, IranYahya KoochProduction Systems, Natural Resources Institute Finland, Survontie 9 A, Jyväskylä, FinlandSanna T. KukkonenDepartment of Zoology, Pachhunga University College, Aizawl, Mizoram, IndiaH. LalthanzaraSkolkovo Institute of Science and Technology, 30-1 Bolshoy Boulevard, Moscow, 121205, RussiaIurii M. LebedevSAS, INRAE, Institut Agro, 35042, Rennes, FranceEdith Le CadreTropical Plant and Soil Sciences, College of Tropical Agriculture and Human Resources, University of Hawai’i at Manoa, 3190 Maile Way, St. John 102, Honolulu, USANoa K. LincolnEcologia Aplicada, Instituto de Zoologia y Ecologia Tropical, Universidad Central de Venezuela, Los Chaguaramos, Ciudad Universitaria, Caracas, VenezuelaDanilo López-HernándezDepartment of Natural Resource Ecology and Management, Oklahoma State University, 008C, Ag Hall, Stillwater, USAScott R. Loss & Shishir PaudelUPR Systèmes de Pérennes, CIRAD, Univ Montpellier, TA B-34/02 Avenue Agropolis, Montpellier, FranceRaphael MarichalDepartment of Forest Ecology, Faculty of Forestry and Wood Technology, Czech University of Life Sciences Prague, Kamýcká 129, Prague, Czech RepublicRadim MatulaTochigi Prefectural Museum, 2-2 Mutsumi-cho, Utsunomiya, JapanYukio MinamiyaThuenen-Institute of Biodiversity, Bundesallee 65, Braunschweig, GermanyJan Hendrik MoosThuenen-Institute of Organic Farming, Trenthorst 32, Westerau, GermanyJan Hendrik MoosPlant Biology, Ecology and Earth Science, INDEHESA, University of Extremadura, Plasencia, SpainGerardo MorenoConservación de la Biodiversidad, El Colegio de la Frontera Sur, Av. Rancho, poligono 2 A, Cd. Industrial de Lerma, Campeche, MexicoAlejandro Morón-RíosDepartment of Environmental Systems Science, Faculty of Science and Engineering, Doshisha University, Kyoto, 602-8580, JapanHasegawa MotohiroDepartment of Earth & Environmental Sciences, Division of Forest, Nature and Landscape, KU Leuven, Celestijnenlaan 200E Box, 2411, Leuven, BelgiumBart MuysResearch Institute for Nature and Forest, Gaverstraat 35, 9500, Geraardsbergen, BelgiumJohan NeirynckSchool of Agricultural, Forest and Food Sciences, Bern University of Applied Sciences, Länggasse 85, Zollikofen, SwitzerlandLindsey NorgroveSoil Ecosystems, Natural Resources Institute Finland (Luke), Tietotie 4, Jokioinen, FinlandVisa NuutinenNatural Area Consultants, 1 West Hill School Road, Richford, NY, USAVictoria NuzzoDepartment of Zoology, PSMO College, Tirurangadi, Malappuram, Kerala, India, Malappuram, IndiaP. Mujeeb RahmanCSIRO Ocean and Atmosphere, CSIRO, New Illawarra Road, Lucas Heights, NSW, AustraliaJohan PansuUMR7144 Adaptation et Diversité en Milieu Marin, Station Biologique de Roscoff, CNRS/Sorbonne Université, Place Georges Teissier, Roscoff, FranceJohan PansuPhipps Conservatory and Botanical Gardens, Pittsburgh, PA, 15213, USAShishir PaudelUMR SAS, INRAE, Institut Agro Agrocampus Ouest, 35000, Rennes, FranceGuénola PérèsForest Ecology and Restoration Group, Department of Life Sciences, University of Alcalá, 28805, Alcalá De Henares, SpainLorenzo Pérez-Camacho & Salvador RebolloAdaptations du Vivant, CNRS UMR 7179, Muséum National d’Histoire Naturelle, 4 Avenue du Petit Château, Brunoy, FranceJean-François PongeDepartment of Ecology and Ecosystem Management, Technical University of Munich, Emil-Ramann-Str. 2, 85354, Freising, GermanyJörg PrietzelTembotov Institute of Ecology of Mountain Territories, Russian Academy of Sciences, I. Armand, 37a, Nalchik, RussiaIrina B. RapoportCenter of Excellence in Environmental Studies, King Abdulaziz University, P.O Box 80216, Jeddah, 21589, Saudi ArabiaMuhammad Imtiaz RashidGlobal Change Ecology and Evolution Research Group (GloCEE), Department of Life Sciences, University of Alcalá, 28805, Alcalá De Henares, SpainMiguel Á. RodríguezDepartment of Forest Resources, University of Minnesota, 1530, Cleveland Ave. N, St. Paul, USAAlexander M. RothFriends of the Mississippi River, 101 E 5th St. Suite 2000, St Paul, USAAlexander M. RothBiology, Biodiversity and Conservation Postgraduate Program, Federal University of Maranhão, Avenida dos Portugueses 1966, São Luis, BrazilGuillaume X. RousseauInstitute of Environmental Sciences, Jagiellonian University, Gronostajowa 7, Kraków, PolandAnna RozenCollege of Natural Resources, University of Wisconsin, Stevens Point, WI, 54481, USABryant ScharenbrochThe Morton Arboretum, 4100 Illinois Route 53, Lisle, IL, 60532, USABryant ScharenbrochDepartment Engineering for Crop Production, Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Max-Eyth-Allee 100, Potsdam, GermanyMichael SchirrmannSchool of Agriculture and Food Science, University College Dublin, Agriculture and Food Science Centre, Dublin, IrelandOlaf SchmidtUCD Earth Institute, University College Dublin, Dublin, IrelandOlaf SchmidtLandscape Ecology and Environmental Systems Analysis, Institute of Geoecology, Technische Universität Braunschweig, Langer Kamp 19c, Braunschweig, GermanyBoris SchröderDepartment of Ecology, University of Innsbruck, Technikerstrasse 25, Innsbruck, AustriaJulia SeeberInstitute for Alpine Environment, Eurac Research, Viale Druso 1, Bozen/Bolzano, ItalyJulia Seeber & Michael SteinwandterLaboratory of Ecosystem Modelling, Institute of Physicochemical and Biological Problems in Soil Science of the Russian Academy of Sciences, Institutskaya str., 2, Pushchino, RussiaMaxim P. ShashkovLaboratory of Computational Ecology, Institute of Mathematical Problems of Biology RAS – the Branch of Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences, Vitkevicha str., 1, Pushchino, RussiaMaxim P. ShashkovDepartment of Zoology, Khalsa College Amritsar, Amritsar, Punjab, IndiaJaswinder SinghDepartment of Earth and Planetary Sciences, Johns Hopkins University, 3400 N. Charles Street, Baltimore, USAKatalin SzlaveczDepartment of animal biology, edaphology and geology, Faculty of Sciences (Biology), University of La Laguna, La Laguna, Santa Cruz De Tenerife, SpainJosé Antonio TalaveraForest Science, Kochi University, Monobe Otsu 200, Nankoku, JapanJiro TsukamotoJuárez Autonomous University of Tabasco, Nanotechnology Engineering, Multidisciplinary Academic Division of Jalpa de Méndez, Carr. Estatal libre Villahermosa-Comalcalco, Km 27 S/N, C.P. 86205 Jalpa de Méndez, Tabasco, MexicoSheila Uribe-LópezUnit Food & Agriculture, WWF-Netherlands, Driebergseweg 10, Zeist, The NetherlandsAnne W. de ValençaDpto. Ciencias, IS-FOOD, Universidad Pública de Navarra, Edificio Olivos – Campus Arrosadia, Pamplona, SpainIñigo VirtoDepartment of Soil, Water and Climate, University of Minnesota, 1991 Upper Buford Circle, St Paul, USAAdrian A. WackettEarth Innovation Institute, 98 Battery Street Suite 250, San Francisco, USAMatthew W. WarrenUniversity of California Davis, 1 Shields Avenue, Davis, USAEmily R. WebsterNatural Resources & Environmental Management, University of Hawaii at Manoa, 1910 East West Rd, Honolulu, USANathaniel H. WehrNatural Resource Sciences, McGill University, 21111 Lakeshore Road, Ste-Anne-de-Bellevue, CanadaJoann K. WhalenThe Nature Conservancy, 4245 Fairfax Drive, Arlington, USAMichael B. WironenAnimal Ecology, Justus Liebig University, Heinrich-Buff-Ring 26, Giessen, GermanyVolkmar WoltersInstitute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, ChinaPengfei WuLaboratory of terrestrial ecosystems, Federal Research Centre “Kola Science Centre of the Russian Academy of Sciences”, Institute of North Industrial Ecology Problems (INEP KSC RAS), Akademgorodok, 14a, Apatity, Murmansk, Province, RussiaIrina V. ZenkovaKey Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, College of Environment and Planning, Henan University, Kaifeng, ChinaWeixin ZhangFaculty of Biological and Environmental Sciences, Post Office Box 65, FI 00014, University of Helsinki, Helsinki, FinlandErin K. CameronThe sWorm workshops were organised by N.E., E.K.C. and H.R.P.P., with funding acquired by N.E., E.K.C. and M.P.T. Data collation and formatting was led by H.R.P.P., with assistance from J.K., M.J.I.B., G.B., K.B.G. and B.S. Harmonisation of earthworm species names was completed by G.B., M.J.I.B., M.L.C.B. and P.L. Advice and feedback on data collation protocols was provided by E.M.B., M.J.I.B., G.B., O.F., C.A.G., B.K.R., A.O., D.R., and D.H.W. Writing of the manuscript was led by H.R.P.P. All authors provided input and comments on the manuscript. The majority of authors provided data to the database. More

RESEARCH SUMMARY

21 May 2021

Balancing carbon storage under elevated CO2

A global synthesis of experiments reveals that increases in plant biomass under conditions of elevated CO2 mean that plants need to mine the soil for nutrients, which decreases soil’s ability to store carbon. In forests, elevated CO2 generally seems to greatly increase plant biomass, but not soil carbon. In grasslands, by contrast, it causes small changes in biomass and large increases in soil carbon.

César Terrer

 ORCID: http://orcid.org/0000-0002-5479-3486

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César Terrer

Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, USA; and the Department of Earth System Science, Stanford University, Stanford, CA, USA.

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This is a summary of Terrer, C. et al. A trade-off between plant and soil carbon storage under elevated CO2. Nature https://doi.org/10.1038/s41586-021-03306-8 (2021).

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doi: https://doi.org/10.1038/d41586-021-01117-5

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Leipzig, Germany

JOB POST

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Subjects

Climate sciences

Climate change

Ecology

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