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Since the early 2000s, digital soil maps have been successfully used for various applications, including precision agriculture, environmental assessments and land use management. Globally, however, there are large disparities in the availability of soil data on which digital soil mapping (DSM) models can be fitted. Several studies attempted to transfer a DSM model fitted from an area with a well-developed soil database to map the soil in areas with low sampling density. This usually is a challenging task because two areas have hardly ever the same soil-forming factors in two different regions of the world. In this study, we aim to determine whether finding homosoils (i.e., locations sharing similar soil-forming factors) can help transferring soil information by means of a DSM model extrapolation. We hypothesize that within areas in the world considered as homosoils, one can leverage on areas with high sampling density and fit a DSM model, which can then be extrapolated geographically to an area with little or no data. We collected publicly available soil data for clay, silt, sand, organic carbon (OC), pH and total nitrogen (N) within our study area in Mali, West Africa and its homosoils. We fitted a regression tree model between the soil properties and environmental covariates of the homosoils, and applied this model to our study area in Mali. Several calibration and validation strategies were explored. We also compared our approach with existing maps made at a global and a continental scale. We concluded that geographic model extrapolation within homosoils was possible, but that model accuracy dramatically improved when local data were included in the calibration dataset. The maps produced from models fitted with data from homosoils were more accurate than existing products for this study area, for three (silt, sand, pH) out of six soil properties. This study would be relevant to areas with very little or no soil data to carry critical soils and environmental risk assessments at a regional level.

Le ruissellement est un phénomène épisodique et localisé, donc difficile à mesurer. Il résulte de l'interaction de nombreux facteurs, dont les caractéristiques intrinsèques et de surface du sol, la morphologie du bassin versant, mais également les caractéristiques pluviométriques. Afin d'améliorer la compréhension de la genèse et de la propagation du ruissellement au sein de bassins versants de tête, cinq observatoires du ruissellement sont présentés, incluant 11 bassins versants. Pour chacun d'entre eux, la pluie et le ruissellement sont mesurés sur le terrain à haute fréquence (≤ 15 min) pendant des durées longues (1,5 à 11 ans). 1640 évènements pluvio-ruisselants sont extraits de ces chroniques en continu et statistiquement analysés, afin de cerner les facteurs influant significativement le ruissellement. La réponse ruisselante de chaque bassin versant est extrêmement complexe mais permet d'identifier des comportements communs. L'importance des caractéristiques des sols est montrée, ainsi que celle de leur occupation, de leurs états de surface et état hydrique. La dispersion de la relation pluie-débit observée au sein de chacun des observatoires permet par ailleurs de montrer et de quantifier l'impact des caractéristiques pluviométriques sur la lame d'eau ruisselée. Les leçons tirées de chacun des observatoires et leurs conséquences sur la compréhension et la modélisation du ruissellement dans différents contextes sont discutées.

In the tropics, the reduction in fallow periods in shifting rice cultivation and deforestation have led to soil degradation. How crop diversity is managed by farmers to adapt to this change remains poorly studied. Our study in Madagascar focuses on the management of 38 species in agroforestry, a practice that was gradually adopted by Betsimisaraka farmers to replace shifting rice cultivation. We describe how farmers perceived changes in the soil and how they adapted their farming practices to these changes, and analyze their knowledge of the interactions between the different plant species and the soil (soil-agrobiodiversity interactions) that underlie these adaptations. The farmers' perceptions of changes in the soil, their causes and consequences, were recorded in 19 individual interviews and three focus groups. Farmers' knowledge of soil-agrobiodiversity interactions was recorded in 84 individual surveys and one focus group. Farmers grouped soils in two main classes according to the topography and used four criteria to characterize them. The main change in the soil they observed was the decline in soil fertility due to deforestation. In response to these changes, farmers changed their crop species and management practices (e.g., spatial organization of crops, fertilization, species associations). These adaptations are based on shared knowledge of the soil requirements of crop species and their effect on fertility, despite the recent adoption of agroforestry. Our study highlights the dynamic and holistic dimension of farmers' knowledge of the soil and its interactions with different plant species.

So far, root reinforcement on soil has been primarily evaluated through direct shear and roots pull-out tests, while the effect of other stress paths and the behaviour at the soil–root¿ interface are still poorly investigated. In this regard, an apparatus with the facility to test soil and roots jointly under uniaxial extension is presented in the paper, together with its first results. Vegetated samples with Cynodon dactilon were tested after one and three months of growth. Soil exhibited a ductile response when close to saturation and a brittle one at drier states within the field capacity domain. The presence of roots increased the material’s tensile strength and enhanced its post-peak ductility. Measurements of matric suction and degree of saturation allowed interpreting the results in terms of constitutive stresses within a shear strength failure criterion for partially saturated soils. Even if plant roots critically impacted soil hydraulics, a positive strengthening effect was noticed on its mechanical behaviour. Roots mechanical and morphological features were characterised after tests. Two well-established root reinforcement models in the literature were used to interpret the results at the phenomenological scale while considering the hydro-mechanical behaviour at the soil–root interface, different root’s reinforcement mechanisms and the effect of soil’s hydro-mechanical states. The authors wish to acknowledge the support of the European Commission via the Marie Skłodowska-Curie Innovative Training Networks (ITN-ETN) project TERRE ‘Training Engineers and Researchers to Rethink geotechnical Engineering for a low carbon future’ (H2020-MSCA-ITN-2015- 675762). Furthermore, Alessandro Fraccica wishes to thank Mercedes Sondon (Universitat Politècnica de Catalunya, UPC), Luis Gandarillas, Ylenia Bianchi, Ferran Parera (support with PIV software) and Stefano Collico (support with statistical analysis). The H2020-ITN project TERRE ‘Training Engineers and Researchers to Rethink geotechnical Engineering for a low carbon future’ (H2020-MSCA-ITN-2015-675762) provided funding.

JJL received funding from the Research Foundation Flanders (grant nr. 12P1819N). The project received funding from the Research Foundation Flanders (grants nrs, G018919N, W001919N). JVDH and TWC received funding from DOB Ecology. JA received funding from the University of Helsinki, Faculty of Science (MICROCLIM, grant nr. 7510145) and Academy of Finland Flagship (grant no. 337552). PDF, CM and PV received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (ERC Starting Grant FORMICA 757833). JK received funding from the Arctic Interactions at the University of Oulu and Academy of Finland (318930, Profi 4), Maaja vesitekniikan tuki ry., Tiina and Antti Herlin Foundation, Nordenskiold Samfundet and Societas pro Fauna et Flora Fennica. MK received funding from the Czech Science Foundation (grant nr. 20-28119S) and the Czech Academy of Sciences (grant nr. RVO 67985939). TWC received funding from National Geographic Society grant no. 9480-14 and WW-240R-17. MA received funding from CISSC (program ICRP (grant nr:2397) and INSF (grant nr: 96005914). The Royal Botanic Garden Edinburgh is supported by the Scottish Government's Rural and Environment Science and Analytical Services Division. JMA received funding from the Funding Org. Qatar Petroleum (grant nr. QUEX-CAS-QP-RD-18/19). JMA received funding from the European Union's Horizon 2020 research and innovation program (grant no. 678841) and from the Swiss National Science Foundation (grant no. 31003A_176044). JA was supported by research grants LTAUSA19137 (program INTER-EXCELLENCE, subprogram INTER-ACTION) provided by Czech Ministry of Education, Youth and Sports and 20-05840Y of the Czech Science Foundation. AA was supported by the Ministry of Science and Higher Education of the Russian Federation (grant FSRZ-2020-0014). SN, UAT, JJA, and JvO received funding from the Independent Research Fund Denmark (7027-00133B). LvdB, KT, MYB and RC acknowledge funding from the German Research Foundation within the Priority Program SPP-1803 'EarthShape: Earth Surface Shaping by Biota' (grant TI 338/14-1&2 and BA 3843/6-1). PB was supported by grant project VEGA of the Ministry of Education of the Slovak Republic and the Slovak Academy of Sciences No. 2/0132/18. Forest Research received funding from the Forestry Commission (climate change research programme). JCB acknowledges the support of Universidad Javeriana. JLBA received funding from the Direccion General de Cambio Climatico del Gobierno de Aragon; JLBA acknowledges fieldwork assistance by Ana Acin, the Ordesa y Monte Perdido National Park, and the Servicio de Medio Ambiente de Soria de la Junta de Castilla y Leon. RGB and MPB received funding from BECC - Biodiversity and Ecosystem services in a Changing Climate. MPB received funding from The European Union's Horizon 2020 research and innovation program under the Marie Skodowska-Curie Grant Agreement No. 657627 and The Swedish Research Council FORMAS - future research leaders No. 2016-01187. JB received funding from the Czech Academy of Sciences (grant nr. RVO 67985939). NB received funding from the SNF (grant numbers 40FA40_154245, 20FI21_148992, 20FI20_173691, 407340_172433) and from the EU (contract no. 774124). ICOS EU research infrastructure. EU FP7 NitroEurope. EU FP7 ECLAIRE. The authors from Biological Dynamics of Forest Fragments Project, PDBFF, Instituto Nacional de Pesquisas da Amazonia, Brazil were supported by the MCTI/CNPq/FNDCT - AcAo Transversal no68/2013 - Programa de Grande Escala da Biosfera-Atmosfera na Amazonia - LBA; Project 'Como as florestas da Amazonia Central respondem as variacoes climaticas? Efeitos sobre dinamica florestal e sinergia com a fragmentacAo florestal'. This is the study 829 of the BDFFP Technical Series. to The EUCFLUX Cooperative Research Program and Forest Science and Research Institute-IPEF. NC acknowledges funding by Stelvio National Park. JC was funded by the Spanish government grant CGL2016-78093-R. ANID-FONDECYT 1181745 AND INSTITUTO ANTARTICO CHILENO (INACH FR-0418). SC received funding from the German Research Foundation (grant no. DFG- FZT 118, 202548816). The National Science Foundation, Poland (grant no. UMO-2017/27/B/ST10/02228), within the framework of the 'Carbon dioxide uptake potential of sphagnum peatlands in the context of atmospheric optical parameters and climate changes' (KUSCO2) project. SLC received funding from the South African National Research Foundation and the Australian Research Council. FM, M, KU and MU received funding from Slovak Research and Development Agency (no. APVV-19-0319). Instituto Antartico Chileno (INACH_RT-48_16), Iniciativa Cientifica Milenio Nucleo Milenio de Salmonidos Invasores INVASAL, Institute of Ecology and Biodiversity (IEB), CONICYT PIA APOYO CCTE AFB170008. PC is supported by NERC core funding to the BAS 'Biodiversity, Evolution and Adaptation Team. EJC received funding from the Norwegian Research Council (grant number 230970). GND was supported by NERC E3 doctoral training partnership grant (NE/L002558/1) at the University of Edinburgh and the Carnegie Trust for the Universities of Scotland. Monitoring stations on Livingston Island, Antarctica, were funded by different research projects of the Gobern of Spain (PERMAPLANET CTM2009-10165-E; ANTARPERMA CTM2011-15565-E; PERMASNOW CTM2014-52021-R), and the PERMATHERMAL arrangement between the University of Alcala and the Spanish Polar Committee. GN received funding from the Autonomous Province of Bolzano (ITA). The infrastructure, part of the UK Environmental Change Network, was funded historically in part by ScotNature and NERC National Capability LTS-S: UK-SCAPE; NE/R016429/1). JD was supported by the Czech Science Foundation (GA17-19376S) and MSMT (LTAUSA18007). ED received funding from the Kempe Foundation (JCK-1112 and JCK-1822). The infrastructure was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme I (NPU I), grant number LO1415 and by the project for national infrastructure support CzeCOS/ICOS Reg. No. LM2015061. NE received funding from the German Research Foundation (DFG- FZT 118, 202548816). BE received funding from the GLORIA-EU project no EVK2-CT2000-00056, the Autonomous Province of Bolzano (ITA), from the Tiroler Wissenschaftsfonds and from the University of Innsbruck. RME was supported by funding to the SAFE Project from the Sime Darby Foundation. OF received funding from the German Research Foundation (DFG- FZT 118, 202548816). EFP was supported by the Jardin Botanico Atlantico (SV-20-GIJON-JBA). MF was funded by the German Federal Ministry of Education and Research (BMBF) in the context of The Future Okavango (Grant No. 01LL0912) and SASSCAL (01LG1201M; 01LG1201N) projects. EFL received funding from ANID PIA / BASAL FB210006. RAG received funding from Fondecyt 11170516, CONICYT PIA AFB170008 and ANID PIA / BASAL FB210006. MBG received funding from National Parks (DYNBIO, #1656/2015) and The Spanish Research Agency (VULBIMON, #CGL2017-90040-R). MG received funding from the Swiss National Science Foundation (ICOS-CH Phase 2 20FI20_173691). FG received funding from the German Research Foundation (DFG- FZT 118, 202548816). KG and TS received funding from the UK Biotechnology and Biological Research Council (grant = 206/D16053). SG was supported by the Research Foundation Flanders (FWO) (project G0H1517N). KJ and PH received funding from the EU Horizon2020 INFRAIA project eLTER-PLUS (871128), the project LTER-CWN (FFG, F&E Infrastrukturforderung, project number 858024) and the Austrian Climate Research Program (ACRP7 - CentForCSink - KR14AC7K11960). SH and ARB received funding through iDiv funded by the German Research Foundation (DFG- FZT 118, 202548816). LH received funding from the Czech Science Foundation (grant nr. 20-28119S) and the Czech Academy of Sciences (grant nr. RVO 67985939). MH received funding from the Baden-Wurttemberg Ministry of Science, Research and Arts via the project DRIeR (Drought impacts, processes and resilience: making the in-visible visible). LH received funding from International Polar Year, Weston Foundation, and ArcticNet. DH received funding from Natural Sciences and Engineering Council (Canada) (RGPIN-06691). TTH received funding from Independent Research Fund Denmark (grant no. 8021-00423B) and Villum Foundation (grant no. 17523). Ministry of Education, Youth and Sports of the Czech Republic (projects LM2015078, VAN2020/01 and CZ.02.1.01/0.0/0.0/16_013/0001708). KH, CG and CJD received funding from Bolin Centre for Climate Research, Stockholm University and from the Swedish research council Formas [grant n:o 2014-00530 to KH]. JJ received funding from the Funding Org. Swedish Forest Society Foundation (grant nr. 2018-485-Steg 2 2017) and Swedish Research Council FORMAS (grant nr. 2018-00792). AJ received funding from the German Federal Ministry of Education and Research BMBF (Grant Nr. FKZ 031B0516C SUSALPS) and the Oberfrankenstiftung (Grant Nr. OFS FP00237). ISJ received funding from the Energy Research Fund (NYR-11 - 2019, NYR-18 - 2020). TJ was supported by a UK NERC Independent Research Fellowship (grant number: NE/S01537X/1). RJ received funding from National Science Centre of Poland (grant number: 2016/21/B/ST10/02271) and Polish National Centre for Research and Development (grant number: Pol-Nor/203258/31/2013). VK received funding from the Czech Academy of Sciences (grant nr. RVO 67985939). AAK received funding from MoEFCC, Govt of India (AICOPTAX project F. No. 22018/12/2015/RE/Tax). NK received funding from FORMAS (grants nr. 2018-01781, 2018-02700, 2019-00836), VR, support from the research infrastructure ICOS-SE. BK received funding from the National Research, Development and Innovation Fund of Hungary (grant nr. K128441). Ministry of Education, Youth and Sports of the Czech Republic (projects LM2015078 and CZ.02.1.01/0.0/0.0/16_013/0001708). Project B1-RNM-163-UGR-18-Programa Operativo FEDER 2018, partially funded data collection. Norwegian Research Council (NORKLIMA grants #184912 and #244525) awarded to Vigdis Vandvik. MM received funding from the Czech Science Foundation (grant nr. 20-28119S) and the Czech Academy of Sciences (grant nr. RVO 67985939). Project CONICYT-PAI 79170119 and ANID-MPG 190029 awarded to Roy Mackenzie. This work was partly funded by project MIUR PON Cluster OT4CLIMA. RM received funding from the SNF project number 407340_172433. FM received funding from the Stelvio National Park. PM received funding from AIAS-COFUND fellowship programme supported by the Marie Skodowska- Curie actions under the European Union's Seventh Framework Pro-gramme for Research, Technological development and Demonstration (grant agreement no 609033) and the Aarhus University Research Foundation, Denmark. RM received funding from the Ministry of Education, Youth and Sports of the Czech Republic (project LTT17033). SM and VM received funding from EU FP6 NitroEurope (grant nr. 17841), EU FP7 ECLAIRE (grant nr. 282910), the Ministry of Education and Science of Ukraine (projects nr. 505, 550, 574, 602), GEF-UNEP funded "Toward INMS" project (grant nr. NEC05348) and ENI CBC BSB PONTOS (grant nr. BSB 889). The authors from Biological Dynamics of Forest Fragments Project, PDBFF, Instituto Nacional de Pesquisas da Amazonia, Brazil were supported by the MCTI/CNPq/FNDCT - AcAo Transversal no68/2013 - Programa de Grande Escala da Biosfera-Atmosfera na Amazonia - LBA; Project 'Como as florestas da Amazonia Central respondem as variacoes climaticas? Efeitos sobre dinamica florestal e sinergia com a fragmentacAo florestal'. FJRM was financially supported by the Netherlands Organization for Scientific Research (VICI grant 016.VICI.170.072) and Research Foundation Flanders (FWO-SBO grant S000619N). STM received funding from New Frontiers in Research Fund-Exploration (grant nr. NFRF-2018-02043) and NSERC Discovery. MMR received funding from the Australian Research Council Discovery Early Career Research Award (grant nr. DE180100570). JAM received funding from the National Science Foundation (DEB 1557094), International Center for Advanced Renewable Energy and Sustainability (I-CARES) at Washington University in St. Louis, ForestGEO, and Tyson Research Center. IM-S was funded by the UK Natural Environment Research Council through the ShrubTundra Project (NE/M016323/1). MBN received funding from FORMAS, VR, Kempe Foundations support from the research infrastructures ICOS and SITES. MDN received funding from CONICET (grant nr. PIP 112-201501-00609). Spanish Ministry of Science grant PID2019-110521GB-I00 and Catalan government grant 2017-1005. French National Research Agency (ANR) in the frame of the Cluster of Excellence COTE (project HydroBeech, ANR-10-LABX-45). VLIR-OUS, under the Institutional University Coorperation programme (IUC) with Mountains of the Moon University. Project LAS III 77/2017/B entitled: \"Estimation of net carbon dioxide fluxes exchanged between the forest ecosystem on post-agricultural land and between the tornado-damaged forest area and the atmosphere using spectroscopic and numerical methods\", source of funding: General Directorate of State Forests, Warsaw, Poland. Max Planck Society (Germany), RFBR, Krasnoyarsk Territory and Krasnoyarsk Regional Fund of Science, project number 20-45-242908. Estonian Research Council (PRG609), and the European Regional Development Fund (Centre of Excellence EcolChange). Canada-Denmark Arctic Research Station Early Career Scientist Exchange Program, from Polar knowledge Canada (POLAR) and the Danish Agency for Science and Higher Education. AP received funding from Fondecyt 1180205, CONICYT PIA AFB170008 and ANID PIA / BASAL FB210006. MP received funding from the Funding Org. Knut and Alice Wallenberg Foundation (grant nr. 2015.0047), and acknowledges funding from the Swedish Research Council (VR) with contributing research institutes to both the SITES and ICOS Sweden infrastructures. JP and RO were funded by the Spanish Ministry of Science grant PID2019-110521GB-I00, the fundacion Ramon Areces grant ELEMENTAL-CLIMATE, and the Catalan government grant 2017-1005. MPB received funding from the Svalbard Environmental Protection Fund (grant project number 15/128) and the Research Council of Norway (Arctic Field Grant, project number 269957). RP received funding from the Ministry of Education, Youth and Sports of the Czech Republic (grant INTER-TRANSFER nr. LTT20017). LTSER Zone Atelier Alpes; Federation FREE-Alpes. RP received funding from a Humboldt Fellowship for Experienced Researchers. Prokushkin AS and Zyryanov VI contribution has been supported by the RFBR grant #18-05-60203-Arktika. RPu received founding from the Polish National Science Centre (grant project number 2017/27/B/NZ8/00316). ODYSSEE project (ANR-13-ISV7-0004, PN-II-ID-JRP-RO-FR-2012). KR was supported through an Australian Government Research Training Program Scholarship. Fieldwork was supported by the Global Challenges program at the University of Wollongong, the ARC the Australian Antarctic Division and INACH. DR was funded by the project SUBANTECO IPEV 136 (French Polar Institute Paul-Emile Victor), Zone Atelier CNRS Antarctique et Terres Australes, SAD Region Bretagne (Project INFLICT), BiodivERsa 2019-2020 BioDivClim call 'ASICS' (ANR-20-EBI5-0004). SAR received funding from the Australian Research Council. NSF grant #1556772 to the University of Notre Dame. Pavia University (Italy). OR received funding from EU-LEAP-Agri (RAMSES II), EU-DESIRA (CASSECS), EU-H2020 (SustainSahel), AGROPOLIS and TOTAL Foundations (DSCATT), CGIAR (GLDC). AR was supported by the Russian Science Foundation (Grant 18-74-10048). Parc national des Ecrins. JS received funding from Vetenskapsradet grant nr (No: 2014-04270), ALTER-net multi-site grant, River LIFE project (LIFE08 NAT/S/000266), Flexpeil. Helmholtz Association long-term research program TERENO (Terrestrial Environmental Observatories). PS received funding from the Polish Ministry of Science and Higher Education (grant nr. N N305 304840). AS acknowledges funding by ETH Zurich project FEVER ETH-27 19-1. LSC received funding from NSERC Canada Graduate Scholarship (Doctoral) Program; LSC was also supported by ArcticNet-NCE (insert grant #). Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (141513/2017-9); FundacAo Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro (E26/200.84/2019). ZS received funding from the SRDA (grants nos. APVV-16-0325 and APVV-20-0365) and from the ERDF (grant no. ITMS 313011S735, CE LignoSilva). JS, MB and CA received funding from core budget of ETH Zurich. State excellence Program M-V \"WETSCAPES\". AfricanBioServices project funded by the EU Horizon 2020 grant number 641918. The authors from KIT/IMK-IFU acknowledge the funding received within the German Terrestrial Environmental Observatories (TERENO) research program of the Helmholtz Association and from the Bavarian Ministry of the Environment and Public Health (UGV06080204000). Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project number 192626868, in the framework of the collaborative German-Indonesian research project CRC 990 (SFB): 'EFForTS, Ecological and Socioeconomic Functions of Tropical Lowland Rainforest Transformation Systems (Sumatra, Indonesia)'. MS received funding from the Ministry of Education, Youth and Sports of the Czech Republic (grant nr. INTER-TRANSFER LTT19018). TT received funding from the Swedish National Space Board (SNSB Dnr 95/16) and the CASSECS project supported by the European Union. HJDT received funding from the UK Natural Environment Research Council (NERC doctoral training partnership grant NE/L002558/1). German Science Foundation (DFG) GraKo 2010 \"Response\". PDT received funding from the MEMOIRE project (PN-III-P1-1.1-PD2016-0925). Arctic Challenge for Sustainability II (ArCS II; JPMXD1420318865). JU received funding from Czech Science Foundation (grant nr. 21-11487S). TU received funding from the Romanian Ministry of Education and Research (CCCDI - UEFISCDI -project PN-III-P2-2.1-PED-2019-4924 and PN2019-2022/19270201-Ctr. 25N BIODIVERS 3-BIOSERV). AV acknowledge funding from RSF, project 21-14-00209. GFV received funding from the Dutch Research Council NWO (Veni grant, no. 863.14.013). Australian Research Council Discovery Early Career Research Award DE140101611. FGAV received funding from the Portuguese Science Foundation (FCT) under CEECIND/02509/2018, CESAM (UIDP/50017/2020+UIDB/50017/2020), FCT/MCTES through national funds, and the co-funding by the FEDER, within the PT2020 Partnership Agreement and Compete 2020. Ordesa y Monte Perdido National Park. MVI received funding from the Spanish Ministry of Science and Innovation through a doctoral grant (FPU17/05869). JW received funding from the Czech Science Foundation (grant nr. 20-28119S) and the Czech Academy of Sciences (grant nr. RVO 67985939). CR and SW received funding from the Swiss Federal Office for the Environment (FOEN) and the de Giacomi foundation. YY received funding from the National Natural Science Foundation of China (Grant no. 41861134039 and 41941015). ZY received funding from the National Natural Science Foundation of China (grant nr. 41877458). FZ received funding from the Swiss National Science Foundation (grant nr. 172198 and 193645). PZ received funding from the Funding Org. Knut and Alice Wallenberg Foundation (grant no. 2015.0047). JL received funding from (i) the Agence Nationale de la Recherche (ANR), under the framework of the young investigators (JCJC) funding instrument (ANR JCJC Grant project NoANR-19-CE32-0005-01: IMPRINT) (ii) the Centre National de la Recherche Scientifique (CNRS) (Defi INFINITI 2018: MORFO); and the Structure Federative de Recherche (SFR) Condorcet (FR CNRS 3417: CREUSE). Fieldwork in the Arctic got facilitated by funding from the EU INTERACT program. SN, UAT, JJA and JvO would like to thank the field team of the Vegetation Dynamics group for their efforts and hard work. We acknowledge Dominique Tristan for letting access to the field. For the logistic support the crew of INACH and Gabriel de Castilla Station team on Deception Island. We thank the Inuvialuit and Kluane First Nations for the opportunity to work on their land. MAdP acknowledges fieldwork assistance and logistics support to Unidad de Tecnologia Marina CSIC, and the crew of Juan Carlos I and Gabriel de Castilla Spanish Antarctic Stations, as well as to the different colleagues from UAH that helped on the instrument maintenance. ERF acknowledges fieldwork assistance by Martin Heggli. MBG acknowledges fieldwork and technical assistance by P Abadia, C Benede, P Bravo, J Gomez, M Grasa, R Jimenez, H Miranda, B Ponz, J Revilla and P Tejero and the Ordesa and Monte Perdido National Park staff. LH acknowledges field assistance by John Jacobs, Andrew Trant, Robert Way, Darroch Whitaker; we acknowledge the Inuit of Nunatsiavut, and the Co-management Board of Torngat Mountains National Park for their support of this project and acknowledge that the field research was conducted on their traditional lands. We thank our many bear guides, especially Boonie, Eli, Herman, John and Maria Merkuratsuk. AAK acknowledges field support of Akhtar Malik, Rameez Ahmad. Part of microclimatic records from Saxony was funded by the Saxon Switzerland National Park Administration. Tyson Research Center. JP acknowledges field support of Emmanuel Malet (Edytem) and Rangers of Reserves Naturelles de Haute-Savoie (ASTERS). Practical help: Roel H. Janssen, N. Huig, E. Bakker, Schools in the tepaseforsoket, Forskar fredag, Erik Herberg. The support by the Bavarian Forest National Park administration is highly appreciated. LvdB acknowledges CONAF and onsite support from the park rangers from PN Pan de Azucar, PN La Campana, PN Nahuelbuta and from communidad agricola Quebrada de Talca. JL and FS acknowledge Manuel Nicolas and all forest officers from the Office National des Forets (ONF) who are in charge of the RENECOFOR network and who provided help and local support for the installation and maintenance of temperature loggers in the field., Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 p ixels ( summarized f rom 8 519 u nique t emperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications., FWO G018919N W001919N 12P1819N, DOB Ecology, University of Helsinki, Faculty of Science (MICROCLIM) 7510145, European Research Council (ERC) FORMICA 757833, Arctic Interactions at the University of Oulu, Academy of Finland 318930 337552, Maaja vesitekniikan tuki ry., Tiina and Antti Herlin Foundation, Nordenskiold Samfundet, Societas pro Fauna et Flora Fennica, Grant Agency of the Czech Republic 20-28119S 20-05840Y GA17-19376S 21-11487S, Czech Academy of Sciences RVO 67985939, National Geographic Society 9480-14 WW-240R-17, CISSC (program ICRP) 2397, Iran National Science Foundation (INSF) 96005914, Scottish Government's Rural and Environment Science and Analytical Services Division, Qatar Petroleum QUEX-CAS-QP-RD-18/19, European Union's Horizon 2020 research and innovation program 678841, Swiss National Science Foundation (SNSF), European Commission 172198 193645 31003A_176044, Ministry of Education, Youth & Sports - Czech Republic LTAUSA19137, Ministry of Science and Higher Education of the Russian Federation FSRZ-2020-0014, Independent Research Fund Denmark 8021-00423B 7027-00133B, German Research Foundation (DFG) DFG- FZT 118 202548816 TI 338/14-1 TI 338/14-2 BA 3843/6-1, grant project VEGA of the Ministry of Education of the Slovak Republic Slovak Academy of Sciences 2/0132/18, Forestry Commission, Universidad Javeriana, Direccion General de Cambio Climatico del Gobierno de Aragon, European Union's Horizon 2020 research and innovation program under the Marie Skodowska-Curie Grant 657627 SNF 407340_172433 40FA40_154245 20FI21_148992 20FI20_173691, European Commission 17841 774124, MCTI/CNPq/FNDCT 68/2013, Project 'Como as florestas da Amazonia Central respondem as variacoes climaticas? Efeitos sobre dinamica florestal e sinergia com a fragmentacAo florestal', Spanish Government, European Commission CGL2016-78093-R, ANID-FONDECYT 1181745, National Science Foundation, Poland UMO-2017/27/B/ST10/02228, National Research Foundation - South Africa, Australian Research Council, Slovak Research and Development Agency APVV-19-0319, Instituto Antartico Chileno INACH_RT-48_16 INACH FR-0418, Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) PIA APOYO CCTE AFB170008 PIA AFB170008, UK Research & Innovation (UKRI), Natural Environment Research Council (NERC), Research Council of Norway, European Commission 230970, NERC E3 doctoral training partnership grant at the University of Edinburgh NE/L002558/1, Carnegie Trust for the Universities of Scotland, Gobern of Spain PERMAPLANET CTM2009-10165-E ANTARPERMA CTM2011-15565-E PERMASNOW CTM2014-52021-R, University of Alcala, Spanish Polar Committee, Autonomous Province of Bolzano (ITA), ScotNature, NERC National Capability LTS-S: UK-SCAPE NE/R016429/1, Ministry of Education, Youth & Sports - Czech Republic LTAUSA18007, Kempe Foundation JCK-1112 JCK-1822, Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme I (NPU I) LO1415, project for national infrastructure support CzeCOS/ICOS LM2015061 GLORIA-EU EVK2-CT2000-00056, Tiroler Wissenschaftsfonds, University of Innsbruck, Sime Darby Foundation, Jardin Botanico Atlantico SV-20-GIJON-JBA, Federal Ministry of Education & Research (BMBF) 01LL0912 01LG1201M 01LG1201N, Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) CONICYT FONDECYT 11170516 1180205, ANID PIA / BASAL FB210006, National Parks (DYNBIO) 1656/2015, Spanish Research Agency (VULBIMON) CGL2017-90040-R, Swiss National Science Foundation (SNSF) 20FI20_173691, Biotechnology and Biological Sciences Research Council (BBSRC) 206/D16053 FWO G0H1517N, EU Horizon2020 INFRAIA project eLTER-PLUS 871128, project LTER-CWN (FFG, F&E Infrastrukturforderung) 858024, Austrian Climate Research Program ACRP7 - CentForCSink - KR14AC7K11960, iDiv by the German Research Foundation DFG- FZT 118 202548816, Baden-Wurttemberg Ministry of Science, Research and Arts, Weston Foundation, ArcticNet, Natural Sciences and Engineering Research Council of Canada (NSERC) RGPIN-06691, Villum Foundation 17523, Ministry of Education, Youth & Sports - Czech Republic LM2015078 VAN2020/01 CZ.02.1.01/0.0/0.0/16_013/0001708 LTT17033 LTT20017 INTER-TRANSFER LTT19018, Bolin Centre for Climate Research, Stockholm University, Swedish Research Council Swedish Research Council Formas 2014-00530 2018-00792 2016-01187, Swedish Forest Society Foundation 2018-485-Steg 2 2017, Federal Ministry of Education & Research (BMBF) FKZ 031B0516C SUSALPS, Oberfrankenstiftung OFS FP00237, Energy Research Fund NYR-11 - 2019 NYR-18 - 2020, UK NERC Independent Research Fellowship NE/S01537X/1, National Science Centre, Poland 2016/21/B/ST10/02271, Polish National Centre for Research and Development Pol-Nor/203258/31/2013, MoEFCC, Govt of India (AICOPTAX project) 22018/12/2015/RE/Tax, Swedish Research Council Formas 2018-01781 2018-02700 2019-00836, research infrastructure ICOS-SE, National Research, Development and Innovation Fund of Hungary K128441, Programa Operativo FEDER 2018 B1-RNM-163-UGR-18, Norwegian Research Council (NORKLIMA grants) 184912 244525, CONICYT-PAI 79170119, ANID-MPG 190029, project MIUR PON Cluster OT4CLIMA, Stelvio National Park, AIAS-COFUND fellowship programme - Marie Skodowska- Curie actions under the European Union's Seventh Framework Pro-gramme for Research, Technological development and Demonstration 609033, Aarhus University Research Foundation, Denmark, EU FP6 NitroEurope 17841, EU FP7 ECLAIRE 282910, Ministry of Education and Science of Ukraine 505 550 574 602, GEF-UNEP NEC05348, ENI CBC BSB PONTOS BSB 889, Netherlands Organization for Scientific Research (NWO) 016.VICI.170.072, New Frontiers in Research Fund-Exploration NFRF-2018-02043, Natural Sciences and Engineering Research Council of Canada (NSERC), Australian Research Council DE180100570, National Science Foundation (NSF) DEB 1557094, International Center for Advanced Renewable Energy and Sustainability (I-CARES) at Washington University in St. Louis, Smithsonian Institution Smithsonian Tropical Research Institute, Tyson Research Center, UK Natural Environment Research Council through the ShrubTundra Project NE/M016323/1, Swedish Research Council Formas Swedish Research Council, Kempe Foundations - research infrastructure ICOS Kempe Foundations - research infrastructure SITES, Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET) PIP 112-201501-00609, Spanish Government PID2019-110521GB-I00, Catalan government 2017-1005, French National Research Agency (ANR) ANR-10-LABX-45, General Directorate of State Forests, Warsaw, Poland, Max Planck Society, Russian Foundation for Basic Research (RFBR), Krasnoyarsk Territory Krasnoyarsk Regional Fund of Science 20-45-242908, Estonian Research Council PRG609, Knut & Alice Wallenberg Foundation 2015.0047, Swedish Research Council, fundacion Ramon Areces grant ELEMENTAL-CLIMATE, Svalbard Environmental Protection Fund 15/128, Research Council of Norway 269957, Humboldt Fellowship for Experienced Researchers, Russian Foundation for Basic Research (RFBR) 18-05-60203-Arktika, Polish National Science Centre 2017/27/B/NZ8/00316, ODYSSEE project (PN-II-ID-JRP-RO-FR-2012) ANR-13-ISV7-0004, Australian Government, Department of Industry, Innovation and Science, Global Challenges program at the University of Wollongong, ARC the Australian Antarctic Division, INACH, project SUBANTECO IPEV 136 (French Polar Institute Paul-Emile Victor), Zone Atelier CNRS Antarctique et Terres Australes, SAD Region Bretagne (Project INFLICT), BiodivERsa 2019-2020 BioDivClim call 'ASICS' ANR-20-EBI5-0004, National Science Foundation (NSF) 1556772, EU-LEAP-Agri (RAMSES II) EU-DESIRA (CASSECS) EU-H2020 (SustainSahel), AGROPOLIS, Total SA, CGIAR, Russian Science Foundation (RSF) 18-74-10048, Swedish Research Council 2014-04270, ALTER-net multi-site grant, River LIFE project LIFE08 NAT/S/000266, Flexpeil, Ministry of Science and Higher Education, Poland N N305 304840, ETH Zurich FEVER ETH-27 19-1, NSERC Canada Graduate Scholarship (Doctoral) Program, ArcticNet-NCE, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ) 141513/2017-9, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio De Janeiro (FAPERJ) E26/200.84/2019, SRDA APVV-16-0325 APVV-20-0365, ERDF (CE LignoSilva) ITMS 313011S735, ETH Zurich, EU Horizon 2020 641918, German Terrestrial Environmental Observatories (TERENO) research program of the Helmholtz Association, Bavarian Ministry of the Environment and Public Health UGV06080204000 German Research Foundation (DFG) 192626868, Swedish National Space Board (SNSB) 95/16, CASSECS project by the European Union, Natural Environment Research Council (NERC) NE/L002558/1, MEMOIRE project PN-III-P1-1.1-PD2016-0925, Arctic Challenge for Sustainability II (ArCS II) JPMXD1420318865, Consiliul National al Cercetarii Stiintifice (CNCS), Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii (UEFISCDI) PN-III-P2-2.1-PED-2019-4924 PN2019-2022/19270201, 25N BIODIVERS 3-BIOSERV, Russian Science Foundation (RSF) 21-14-00209., Netherlands Organization for Scientific Research (NWO) 863.14.013, Australian Research Council DE140101611, Portuguese Foundation for Science and Technology CEECIND/02509/2018 CESAM UIDP/50017/2020+UIDB/50017/2020, Portuguese Foundation for Science and Technology European Commission, FEDER, within the PT2020 Partnership Agreement, Compete 2020, Spanish Government FPU17/05869, Swiss Federal Office for the Environment (FOEN), Giacomi foundation, National Natural Science Foundation of China (NSFC) 41861134039 41941015 41877458, French National Research Agency (ANR) ANR-19-CE32-0005-01 Centre National de la Recherche Scientifique (CNRS), Structure Federative de Recherche (SFR) Condorcet (FR CNRS 3417: CREUSE), EU INTERACT program, Inuit of Nunatsiavut, Co-management Board of Torngat Mountains National Park, Saxon Switzerland National Park Administration, Bavarian Forest National Park administration, BECC - Biodiversity and Ecosystem services in a Changing Climate, Research Foundation Flanders (FWO-SBO) S000619N

International audience; Le changement d’usage des terres et l’impact de l’anthropisation sur les milieux forestiers tropicaux sont en progression constante sous les tropiques et en Guyane française. Ces changements sont souvent accompagnés de défriches mécanisées qui favorisent la compaction du sol. Notre objectif était de suivre l’évolution de la compaction du sol d’une parcelle de forêt naturelle exploitée (7 ha) soumise à une défriche mécanisée alternative (itinéraire « chop and mulch », couvert herbacé de Stylosanthes guianensis), puis replantée de quatre espèces forestières commerciales. Sur cet espace présentant finalement diverses couvertures de sol (sol nu, mulch, couvert herbacé), nous avons mesuré la densité apparente jusqu’à 30 cm de profondeur et effectué le test d’infiltration simplifié de Beerkan lors de trois campagnes : avant, juste après et neuf mois après la défriche. Avant la défriche, les sols avaient une très bonne capacité d’infiltration (111 cm/h), étaient peu denses à 0-5 cm de profondeur (0,88) et denses à 5-30 cm (1,19 à 1,40). Juste après la défriche, les sols avaient une capacité d’infiltration très réduite (2 cm/h) et leur couche de surface avait été fortement compactée (1,28) contrairement aux couches plus profondes (1,41 à 1,49). Neuf mois après la défriche, les sols avaient retrouvé une très bonne capacité d’infiltration (149 cm/h), particulièrement sous le couvert herbacé de S. guianensis, et leur couche de surface avait retrouvé une densité proche de l’état initial (1,01), contrairement aux couches plus profondes (1,46 à 1,58). De futures recherches sont nécessaires pour expliquer le retour rapide à l’état initial de la couche de surface et estimer la contribution relative de la macrofaune du sol, des racines et de la fissuration.

International audience; We, the co‐authors of this letter, are an international group of soil scientists at early career stages, from PhD students to postdoctoral researchers, lecturers, and research fellows with permanent positions. Here, we present our collective musings on soil research challenges and opportunities and, in particular, the points raised by Philippe Baveye (Baveye, 2020a, 2020b) and Johan Bouma (Bouma, 2020) on bypass and hyperbole in soil science. Raising awareness about these issues is a first and necessary step. To this end, we would like to thank Philippe Baveye and Johan Bouma for initiating this debate........

Peatlands play an important role as carbon pools, storing a third of the world's soil carbon. However, peatlands in Southeast Asia have suffered from depletion due to economic pressure and the demand for natural resources, often caused by land use changes and fires. Usually, land preparation requires drainage and fires, resulting in major greenhouse gas (GHG) emissions into the atmosphere. In this work, we propose a general equation to estimate GHG emissions from fires on peatlands. The contribution of each parameter to the variance of the estimated GHG emissions was also evaluated. We used Monte Carlo simulation, meta‐analyses, and an analytical expression of variance. GHG emissions of a single fire episode were estimated at 842 Mg ha−1 CO2 eq. with a standard deviation of 466 Mg ha−1 CO2 eq. The parameter contributing most to variance was the depth of burn, at 94.2%, followed by bulk density, at 5.5%, and emission factors, at 0.3%. Our estimated GHG emissions were close to the amount estimated from the default values provided by the IPCC, strengthening confidence in the IPCC methodology. When the depth of burn was assessed by remote sensing, the parameter that most contributed to variance became the fire‐damaged area, followed by the depth of burn. The contribution of each parameter to variance, as estimated in this study, made it possible to prioritize the effort in uncertainty reduction. Combining Monte Carlo simulation and an analytical expression of variance could be a promising way of obtaining more reliable confidence intervals.

International audience; The sensitivity of C and N mineralization in soil to water potential is mostly described in simulation models as a linear function independent of the pedoclimatic conditions. We hypothesized that water sensitivity could be sitespecific and dependent of climate or soil properties. In this study, we characterized the responses of C and N mineralization to water stress in ten soils representing a range of French arable cropping systems and evaluated whether the responses differ between soils and pedoclimatic contexts. C and N mineralization kinetics were quantified in laboratory incubations at four soil water potentials (pF) ranging from pF = 2.0 (~field capacity) to 4.2 (~permanent wilting point). The C and N mineralization rates, calculated by curve fitting, were linearly correlated with pF or relative water content (RWC). The slope of the linear regression, representing the sensitivity to water potential, differed significantly between sites, ranging from 0.12 to 0.35 pF-1 for C mineralization and 0.20 to 0.44 pF-1 for N mineralization. The sensitivity of C or N mineralization rate to pF or RWC could be well predicted by a couple of two soil properties: either microbial quotient (ratio of microbial biomass-C to total organic C) and soil pH or soil organic C:N ratio and soil pH. The sensitivity of soil to water stress was more accurately predicted by these site-specific variables than a model common to all pedoclimatic conditions. These results open the possibility of improving soil and soil-crop models for a more accurate prediction of water stress on C and N mineralization particularly in the context of climate change.

Recycling of organic waste (OW) as fertilizer on farmland is a widespread practice that fosters sustainable development via resource reuse. However, the advantages of OW fertilization should be weighed against the potentially negative environmental impacts due to the presence of contaminants such as zinc (Zn). Current knowledge on the parameters controlling the environmental fate of Zn following OW application on cultivated soils is scant. We addressed this shortcoming by combining soil column experiments and Zn speciation characterization in OWs and amended soils. Soil column experiments were first carried out using two contrasted soils (sandy soil and sandy clay loam) that were amended with sewage sludge or poultry manure and cropped with lettuce. The soil columns were irrigated with identical amounts of water twice a week, and the leachates collected at the column outlet were monitored and analyzed. This scheme (OW application and lettuce crop cycle) was repeated for each treatment. Lettuce yields and Zn uptake were assessed at the end of each cycle. The soil columns were dismantled and seven soil layers were sampled and analyzed at the end of the second cycle (total experiment time: 12 weeks). X-ray absorption spectroscopy analyses were then conducted to assess Zn speciation in OW and OW-amended soils. The results of this study highlighted that (i) the fate of Zn in water–soil–plant compartments was similar, regardless of the type of soil and OW, (ii) >97.6% of the Zn input from OW accumulated in the soil surface layer, (iii) Zn uptake by lettuce increased with repeated OW applications, and (iv) no radical change in Zn speciation was observed at the end of the 12-week experiment, and phosphate was found to drive Zn speciation in both OW and amended soils (i.e., amorphous Zn-phosphate and Zn sorbed on hydoxylapatite). These results suggest that Zn speciation in OW is a key determinant controlling the environmental fate of this element in OW-amended soils.

International audience; We here present a reference database and three land use maps produced in 2017 over the Reunion island using a machine learning based methodology. These maps are the result of a satellite image analysis performed using the Moringa land cover processing chain developed in our laboratory. The input dataset for map production consists of a single very high spatial resolution Pleiades images, a time series of Sentinel-2 and Landsat-8 images, a Digital Terrain Model (DTM) and the aforementioned reference database. The Moringa chain adopts an object based approach: the Pleiades image provides spatial accuracy with the delineation of land samples via a segmentation process, the time series provides information on landscape and vegetation dynamics, the DTM provides information on topography and the reference database provides annotated samples (6256 polygons) for the supervised classification process and the validation of the results. The three land use maps follow a hierarchical nomenclature ranging from 4 classes for the least detailed level to 34 classes for the most detailed one. The validation of these maps shows a good quality of the results with overall accuracy rates ranging from 86% to 97%. The maps are freely accessible and used by researchers, land managers (State services and local authorities) and also private companies.

Made available in DSpace on 2020-12-12T02:29:22Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-01-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Colorado State University North Carolina State University Universidade Federal de Lavras Universidade Federal do Rio Grande do Norte Università degli Studi di Sassari U.S. Forest Service Universidade de São Paulo ArcelorMittal International Paper Brazilian roundwood industry is one of the most important and productive in the world, with Eucalyptus plantations alone representing 73% of the total planted forests. Deep rooting in these plantations represents a more common phenomena than generally expected. However, there is still a lack of information on environmental factors that drive root growth in deep soil layers, with particular emphasis on edaphoclimatic conditions, and related consequence in terms of soil water behavior. As a part of a larger project, this research aimed to investigate soil water and fine root system distribution in deep tropical soils under a commercial Eucalyptus plantation chronosequence. Along a 2800-km gradient (from south- to north-east Brazil), 14 experimental areas were planted with a “plastic” clone (E. urophylla) and investigated in terms of climatic conditions, soil and water features, and plant/stand development for an entire 6-years rotation period. Fine roots distribution were investigated in one site (in Brazil) till to 20 m deep at 3, 9, 24, 48, and 65 months after planting. Results showed a fast displacement of the root front down to 75, 325, 825, 1250, and 1575 cm at month 3, 9, 24, 48, and 65 after planting, respectively. Fine root densities (g cm−3) and proportional water capture exponentially decreased with soil depth. Deep fine roots showed a relativelly higher efficiency in acquiring water than the shallower, denser roots. The relationship between stand height vs root front depth followed an exponential trend, suggesting that these stands developed relatively faster in height rather than in depth during the first 48 months, with the opposite characterizing plantation afterwards. Regardless of stand age, E. urophylla trees rapidly explored a considerable volume of soil at a relatively limited carbon cost. Multivariate statistics showed that edaphoclimatic conditions play a major role in Eucalyptus plant/stand development. This study outlined the major role played by soil development. From poorly developed sandy Entisols, to medium developed Inceptisols, and to most developed fine textured Oxisols, both plant growth and stand productivity greatly improved accordingly. This study suggests that soil type, together with other environmental factors, are likely to influence both the development and behavior of Eucalyptus plantations for an extent greater than commonly anticipated. Vimef-Soluções Florestais Ltda, Rua Juca Prates, 1014 UNESP São Paulo State University School of Agricultural Sciences Department of Plant Protection Rural Engineering and Soils School of Engineering São Paulo State University Universidade de São Paulo Center of Nuclear Energy in Agriculture, Av. Centenário, 303 Institute of Food and Agricultural Sciences Indian River Research and Education Center University of Florida Eco&Sols Univ Montpellier CIRAD INRA IRD Montpellier SupAgro CIRAD UMR Eco&Sols Dipartimento di Scienze e Tecnologie Ambientali Biologiche e Farmaceutiche Università della Campania “Luigi Vanvitelli”, Via Vivaldi n◦ 43 Dipartimento di Architettura Design e Urbanistica Università degli Studi di Sassari Polo Bionaturalistico, Via Piandanna n° 4 School of Agricultural Forest and Food Sciences Bern University of Applied Science, Laenggasse 85 Desertification Research Centre Università degli Studi di Sassari, Viale Italia n◦ 39 UNESP São Paulo State University School of Agricultural Sciences Department of Plant Protection Rural Engineering and Soils School of Engineering São Paulo State University

Assessing the effect of land management on soil quality is nowadays a key environmental concern, as the soil system is linked to major ecosystem services. There is a strong methodological shortage to integrate the impact of anthropogenic pressure on the soil system within large scale environmental frameworks, such as the Life Cycle Assessment. The LANCA® method was proposed to meet this need, integrating five impact categories of soil functions and directly applicable within the Life Cycle Assessment framework. Although the most recent 2016-LANCA® version shows readiness to be integrated in this large scale environmental framework to meet the demand, it has not yet been applied and validated on case studies. This study proposes a first application of the LANCA® model on two contrasted agricultural-based case studies to share experience in implementing the model through both background and foreground approaches, to analyze the first model outputs and to provide tracks for further model improvements. The results proved that both LANCA® approaches were poorly sensitive to the agricultural land managements tested. The foreground approach was difficult to implement due to the lack of transparency of the targeted characterization factors calculation procedure. Further global sensitivity and redundancy analysis should also be proposed in order to validate the consistency of the global model.

Increasing soil organic matter (SOM) is of primary importance for maintaining soil fertility and mitigating climate change. Leaving crop residues on top of soil is not always an efficient means of increasing SOM because (i) of the high mineralization of the crop residues, (ii) crop residues may increase the mineralization of existing SOM (priming effect) and (iii) wetting-drying cycles may increase mineralization of SOM and crop residues. Little research has been carried out into these mechanisms under Sudano-Sahelian conditions where the rainfall is mostly irregular with wetting-drying cycles during the transition between the wet and the dry season. To evaluate the effect of wetting-drying cycles on the mineralization of SOM and crop residues and the priming effect, an agricultural soil from the North Region of Cameroon with or without (controls) 13 C-labeled rice straw amendment as crop residues was either subjected to five wetting-drying cycles or maintained at constant water potential after a single rewetting event. Soil samples were incubated for 70 days at 28 °C and the CO 2 and 13 CO 2 emissions and mineral N were monitored. Adding straw (+ 833 μg C g − 1 soil) increased the cumulative CO 2 emissions from the soil (+ 921 μg C-CO 2 g − 1 soil). A positive priming effect was observed (+ 92 μg C-CO 2 g − 1 soil). Only the first wetting cycle created a mineralization flush of the SOM and the straw. This flush did not recur probably because of a lack of labile SOM. However an extra addition of straw after 28 days increased CO 2 emissions but did not result in further mineralization flushes after re-wetting while SOM mineralization was not limited by N availability. We conclude that SOM depletion under Sudano-Sahelian conditions was not explained by SOM mineralization enhancement due to multiple rewetting events or to priming effect following crop residues addition. Indeed, SOM depletion could rather be explained by a high level of mineralization of both, SOM and crop residues, when the soil reached its water retention capacity.

As a response to the worldwide challenge raised by soil degradation, Conservation Agriculture (CA) was proposed to help restoring the three main soil functions, i.e. carbon transformation, nutrient cycling and structure maintenance. However, there is still a lack of integrative studies that assess the overall impact of CA on soil health. To fill the gap, Biofunctooll (R), a set of in-field indicators, was developed to monitor changes in soil biological functioning. In this study, Biofunctool (R) was used to assess the impact of a conventional tillage (CT) and three CA annual-based cropping systems on soil health on a Cambodian Oxisol. Eight indicators related to the three soil functions were monitored and integrated into a Soil Quality index (SQI), i.e. the Biofunctool (R) Index. Overall, we found that soil health was twice higher under the CA treatments than under CT treatment. Although it was similar in the three CA treatments, the contribution of each soil function to the soil health diverged. An analysis of soil carbon dynamics also showed that CA support short-term soil organic carbon stabilization compared to CT. This study demonstrates that Biofunctool (R) is a robust, relevant, time-and cost-effective in-field assessment tool that can be used in multiple ways including cropping system management, capacity building of local stakeholders, and policy dialogue.

Made available in DSpace on 2019-10-04T12:35:11Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-19 Aiming to comprehend the relationship among restoration techniques and soil attributes, we compared the soil attributes of four forest stands: three regarding an experiment initiated eight years ago with distinct techniques: perch, abandonment and transposition, and one that was pristine forest used as a reference. In each local, five soil samples were taken at 0-20 cm, and another sample was taken in a profile (layers: 20-40, 40-60 and 60-80 cm) for analysis of the major physical, chemical and isotopic attributes. The soil density varied from 1.20 to 1.24 g.cm(-3). The different values of chemical attributes among the treatments and reference revealed that the yet the areas are no longer degraded, they cannot be considered restored (reasons explained in the text). Evaluating the characteristics of the soils and making specific silvicultural and soil-related practices before implementing the intervention, is a prerequisite that should be considered by managers in restoration projects. Univ Estadual Paulista, Dept Environm Engn, Sorocaba, SP, Brazil CIRAD, UMR Eco & Sols, Montpellier, France Univ Estadual Paulista, Dept Forest Sci, Campus Botucatu, Botucatu, SP, Brazil Eucatex Corp Fazenda Santa Terezinha, Bofete, SP, Brazil Univ Estadual Paulista, Dept Environm Engn, Sorocaba, SP, Brazil Univ Estadual Paulista, Dept Forest Sci, Campus Botucatu, Botucatu, SP, Brazil

With a view to introducing white lupin (Lupinus albus L.) for cultivation in Tunisian calcareous soils, compatible indigenous rhizobia for nitrogen-fixing symbiosis were investigated and characterized. Two L. albus varieties, Mekna and Lumen, were used to trap rhizobia in soil samples collected from 56 sites with high active lime contents (0–49%). Nodulation occurred in only 15 soils. The local variety, Mekna, developed significantly more root nodules and had a trapping capacity in more soils than the imported variety Lumen. A phylogenetic analysis based on the partial 16S-23S ribosomal RNA internal transcribed spacer region (ITS) and multi-locus sequence analysis (MLSA) of three chromosomal housekeeping genes, recA, atpD and dnaK, showed that strains were affiliated to Agrobacterium, Rhizobium, and Neorhizobium, with large internal diversity, including separate lineages. Infectivity tests highlighted some nodulation specificity at the plant variety level, since the strains originating from Mekna could only nodulate this variety, while strains trapped in Lumen could nodulate both varieties. When inoculated, almost all strains resulted in a significant increase in plant shoot dry weight on L. albus. Although Agrobacterium sp. strains isolated from L. albus could nodulate and had a plant growth promoting effect, no nodA and nodC genes could be amplified. This is discussed together with the absence of bradyrhizobia and the general infrequency of L. albus–nodulating rhizobia in Tunisian soils. The adapted and efficient rhizobial strains reported here were promising candidates for inoculant development and represent a contribution towards successful cultivation of L. albus in Tunisia, especially the most promising Mekna variety.

Soil redox potential is an important factor affecting soil functioning. Yet, very few agronomy studies included soil redox potential in relation to soil processes. The objective of this study was to evaluate the spatial and temporal variation in soil redox potential and to determine the soil parameters affecting its variation. Soil redox potential, soil moisture, soil temperature, pH and bulk electrical conductivity were measured in upland rice fields during two growing seasons at six positions along an upland&ndash, lowland continuum, including two positions at the upland, two at the fringe and two at the lowlands in central C&ocirc, te d&rsquo, Ivoire (West Africa). The measurements were made at the following soil depths: 3, 8, 20 and 35 cm. Soil redox potential varied between 500 and 700 mV at the upland positions, 400 and 700 mV at the fringe positions and 100 and 750 mV at the lowland positions, and increased with soil depth. Variations in soil redox potential were driven by soil moisture, bulk electrical conductivity and soil organic carbon. We concluded that for proper interpretation of soil redox potential, sampling protocols should systematically include soil pH, moisture and bulk electrical conductivity measurements.

International audience; Over the past decade, the exponential growth in the production of biomass for energy use has raised concerns as to the environmental impacts of this type of land use, as well as the potential land-use changes (LUC) associated with an extension of agricultural land areas. Determining the environmental impacts of an expanding bioenergy sector requires reconstructing the chains of cause and effect from the determinants of land-use change (both direct and indirect) and land-use practices through to the impacts of those practices. Conducting an exhaustive literature review from 1975 to 2014, we identified 241 articles relevant to this causal chain, thus enabling an analysis of the environmental impacts of LUC for bioenergy. This chapter presents the results of a detailed literature analysis and literature review of the 52 articles within this corpus specifically addressing impacts on soils. The variation in soil organic carbon (SOC) is the most commonly used impact indicator, followed by soil loss to erosion and, to a lesser extent, the potential for environmental acidification as determined by life-cycle assessments. Background and transitional SOC levels during LUC affect the predictive value of estimated final SOC variations but are not generally accounted for in default static stock-difference approaches. Perennial crops tend to be better at maintaining or even improving SOC levels, but results vary according to pedoclimatic and agronomic conditions. The mechanisms involved notably include protection of the soil surface with a dense perennial cover and the limitation of tillage operations, especially deep plowing; accumulation of organic matter and SOC linked to biomass production, especially belowground production of rhizomes and deep, dense root systems; associated reductions in nutrient loss via runoff and erosion. Nevertheless, additional research is needed to improve our understanding of and ability to model the full range of processes underlying soil quality and LUC impacts on soil quality.

Depuis les trente dernières années, de nombreuses études scientifiques s’intéressent aux dynamiques hydrologiques relevées dans le bassin versant du lac Tchad. En effet, ce bassin versant a été, et est encore, une zone emblématique des impacts du changement climatique sur la ressource en eau en région sub-saharienne. la gestion de cette ressource est d’autant plus complexe que ce bassin versant se partage entre le Tchad, le Niger, le Nigéria et le Cameroun. Ce dernier, bien que important pour le fonctionnement hydrique du lac Tchad, est encore trop peu étudié par la communauté scientifique. Nous nous proposons donc de travailler sur le bassin versant du Mayo-Tsanaga, situé au Nord Cameroun et connecté au fleuve Logone, affluent du fleuve Chari et principal contributeur au bilan hydrique du lac Tchad. Quelques chercheurs de l’ORSTOM (Office de la Recherche Scientifique et Technique Outre-Mer) ont déjà travaillé sur ce bassin versant dans les années 1970, mais très peu de travaux ont été mis en place ces vingt-cinq dernières années sur celui-ci. de ce fait, il est primordial aujourd’hui, afin de pouvoir relancer une étude du bassin versant du Mayo-Tsanaga par instrumentation, de remettre à jour nos connaissances géomorphologiques, hydrographiques et d’occupation du sol. Pour ce faire, nous avons recours à des données récentes et plus précises (MNT Aster, images satellites landsat TM et etM+) afin de suivre les dynamiques Hommes / milieux ayant cours depuis les 25 dernières années. Ce travail montre une mutation et une organisation complexe des pratiques, en relation notamment avec la géomorphologie et la pédologie du bassin versant du Mayo-Tsanaga

The purpose of history matching is to find one or several reservoir models which can reproduce as best as possible all the available data. The available data are traditionally some production data, but today seismic data are often integrated in the history matching process. The way of measuring the misfit between real data and simulated responses has a significant impact on the optimization process and hence on the final optimal model obtained. The classical formulation of the misfit is the least square one, which was used with success for production data. This formulation was naturally extended for seismic data. However, it yields an objective function term which is difficult to reduce. Indeed, seismic data are different from production data since they are defined by millions of points and are generally very noisy. When matching seismic data, the goal is then to capture the main features. As a result, computing a point to point error is not adapted and the resulting objective function is not representative of the quality expected for the match. We propose in this paper to define a more appropriate formulation. The idea is to use some image analysis tools to define a formulation focusing on the main features of seismic images. More precisely, it is based on image segmentation and on a modified Hausdorff metric. We illustrate the success of this formulation on a simple history matching case.

This study was performed on the experimental Crop-News site of Kamboinsé. This research was initiated by Agro-ecology Based Aggradation-Conservation agriculture (ABACO) and Woody Amendments for Sub-Sahelian Agriculture (WASSA) projects to carry out soil restoration to improve harvests. Knowing these two parameters is important for evaluating the available stock of water in the root zone of sorghum and Piliostigma reticulatum. Given the importance of these soils, an experimental site of 25 parcels was installed on the distinct agricultural practices (Zaï + Mulch, Zaï + Mulch + P. reticulatum, direct seedling + Mulch + P. reticulatum). Sampling was performed on soil at 10 centimeters from the surface to 60 cm which were tested in the laboratory for bulk density and total porosity. The results obtained showed that the soil at the experimental site is less dense at the surface in the first 20 cm and denser in the last 20 cm in depth.The effect of P. reticulatum was also remarkable in the parcels with shrubs where the smallest range of variation is observed in parcel 7 (with High Shrubs Density) which varies from 1.82 to 1.99 g /cm3 along the whole depth (up to 60 cm) for bulk density and from 24.95 to 31.19 % for total porosity.Parcels with Zaï but without shrubs (parcel 1, 9, 13 and 23) have lesser bulk density ranging from 1.73 to 1.86 g /cm3and lesser total porosity ranging from 34.81 % to 29.72 % at the surface.

Summary The Merguellil catchment (1183 km2), whose runoff is a major water resource for the Kairouan area in semi-arid Tunisia, was equipped with water and soil conservation works (WSCW) during the 1990s, mainly to reduce soil erosion and silting of the downstream El Haouareb dam. The spatial configuration of the hydro-meteorological station network makes it possible to characterize the catchment-scale hydrological impact of the WSCW. The catchment is subdivided into two parts, the upper subcatchment and the lower subarea. The latter covers 84% of the catchment surface area and gathers 97% of the surfaces controlled by WSCW. The space–time variability of the rainfall–runoff relationship is first analysed, comparing the runoff responses from the two nested catchments for different rain event depth ranges. A non-parametric test, based on a resampling approach, is applied to the lower subarea runoff simulated with the GR4J daily lumped rainfall–runoff model, which is calibrated for several subsets of data. Results indicate that from 1989 to 2005, the runoff produced by rainfall below 40 mm in the lower subarea was reduced by some 71–75%, a significant change at the 95% confidence level. This drop in runoff is estimated at 41–50% when considering all rain depths and at 28–32% when including the upper subcatchment in the analysis. No runoff change is found for above-40 mm rains in the lower subarea, nor for any rain depth range in the upper subcatchment. An analysis of various possible sources for the runoff reduction such as climate, land use/land cover, or water exchanges with the aquifer, led to the conclusion that WSCW, which were developed over 32% of the lower subarea since 1989, are the most likely cause for that reduction. Their sharp hydrological effects should be taken into account in order to manage the water resources at the river basin scale, especially in populated semi-arid areas where conflicts between water uses increase dramatically.

We compare the effects of minimum and conventional tillage on banana growth, under irrigated and rain-fed conditions. Measurements of leaf growth, root length density and soil water depletion were made. We used a crop simulation model to understand and explain the differential behavior of banana plants in the experiments. Our approach consisted of (i) an adaptation of the STICS model, initially developed for temperate crops, to the banana crop grown under tropical conditions and (ii) use of the integrative ability of the model to identify the respective roles of irrigation and tillage. The adaptation of the model concerned the phasic development, and leaf and root growth. Some specific characteristics of the tropical environment were also introduced. The model points out that under irrigated conditions crop water requirements were always satisfied whatever the tillage depth. In that case, the difference in terms of leaf growth and yield between shallow and deep tillage treatments can be explained by the nitrogen deficit due to a poor root system. Rain-fed crops suffered from water shortage, but the increase in soil exploration, allowed by conventional tillage, compensated for the absence of irrigation. This work improves knowledge of the agro-physiology of the banana crop. It demonstrates the fundamental part played by the root system, which appears as an important limiting factor for a correct water and nutrient supply. It provides an opportunity to elaborate a global model for the banana crop. (Resume d'auteur)

En Afrique, les efforts de diffusion d'innovations techniques potentiellement bénéfiques et répondant à la problématique de la gestion durable des sols se sont heurtés à des difficultés récurrentes. À partir du concept de capital sol, cet article propose d'aborder cette problématique en examinant les implications en termes d'innovations institutionnelles complémentaires. Ce nouveau cadre d'analyse aboutit à la définition d'une nouvelle typologie des innovations, en fonction de l'importance relative de la composante technique ou institutionnelle.

International audience; Habitat loss and soil organic carbon (SOC) stock variations linked to land-cover change were estimated over two decades in the most densely populated biodiversity hotspot in the world, in order to assess the possible influence of conservation practices on the protection of SOC. For a study area of 88 484 km2, 70% of which lie inside the Western Ghats Biodiversity Hotspot (WGBH), land-cover maps for two dates (1977, 1999) were built from various data sources including remote sensing images and ecological forest maps. SOC stocks were calculated from climatic parameters, altitude, physiography, rock type, soil type and land-cover, with a modelling approach used in predictive learning and based on Multiple Additive Regression Tree. The model was trained on 361 soil profiles data, and applied to estimate SOC stocks from predictor variables using a Geographical Information System (GIS). Comparison of 1977 and 1999 land-cover maps showed 628 km2 of dense forests habitat loss (6%), corresponding to an annual deforestation rate of 0.44%. This was found consistent with other studies carried out in other parts of the WGBH, but not with FAO figures showing an increase in forest area. This could be explained by the different forest definitions used, based on ecological classification in the former, and on percentage tree cover in the latter. Unexpectedly, our results showed that despite ongoing deforestation, overall SOC stock was maintained (similar to 0.43 Pg). But a closer examination of spatial differences showed that soil carbon losses in deforested areas were compensated by sequestration elsewhere, mainly in recent plantations and newly irrigated croplands. This suggests that more carbon sequestration in soils could be achieved in the future through appropriate wasteland management. It is also expected that increasing concerns about biodiversity loss will favour more conservation and reinforce the already prevailing protective measures, thus further maintaining C stocks.

Water contamination by pesticides from agricultural activities is a worldwide environmental problem. In volcanic tropical humid conditions, given the heavy rainfalls and soils with high infiltration capacities, the risk of contamination is high in case of cropping systems with intensive use of pesticides, like bananas. However, previous studies on a cultivated catchment (17.8 ha) in the French West Indies showed that pesticide transfer can be complex: catchment runoff results from the interaction of overland and groundwater flows (Charlier et al, 2008, Hydrological Processes, 22, 22, p.4355-4370). Its contamination by a nematicide applied in banana cropping (Charlier et al, 2009, Journal of Environmental Quality, 38, 3, p.1031-1041) showed two successive phases, which were interpreted as stemming from two distinct contamination mechanisms: an event-dominated contamination phase when transport was linked to overland flow during precipitation shortly after pesticide application, and a stabilized contamination phase when transport originated mainly from the drainage of the shallow aquifer. Comparing the losses of the two phases during two monitoring campaigns showed that shallow groundwater, which is promoted in such permeable soils under abundant tropical rainfalls, seems to be the main contributor to runoff water contamination. The aim of this work is to develop a modelling system of both overland and groundwater flows able to simulate the dynamic of water contamination by cadusafos observed in Charlier et al (2009, Journal of Environmental Quality, 38, 3, p.1031-1041) to confirm the contamination mechanisms that were hypothesized. The modelling system is based on linking two models. First, a distributed surface model, MHYDAS (Moussa et al, 2002, Hydrological Processes, 16, 2, p393-412), is used to compute infiltration and Hortonian runoff at the field scale and its routing from the fields to the catchment outlet. Then, a three-dimensional finite-difference groundwater flow model, MODFLOW (McDonald and Harbaugh, 1988, USGS Book) and a modular three-dimensional transport model, MT3D (Zheng, 1990, USEPA Report), simulates water flow and cadusafos transport in the groundwater zone and their interaction with the hydrographic network. Results from the modelling system are compared with the observed data from the two monitoring campaigns mentioned previously which consisted in spreading cadusafos on a portion of the catchment and monitoring the concentrations in the soil and in runoff and groundwaters. Preliminary results on parameter calibration and test of water flow hypothesis will be presented. (Texte intégral)