122 research outputs found

    Improved Fine-Scale Tropical Forest Cover Mapping for Southeast Asia Using Planet-NICFI and Sentinel-1 Imagery

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    The accuracy of existing forest cover products typically suffers from “rounding” errors arising from classifications that estimate the fractional cover of forest in each pixel, which often exclude the presence of large, isolated trees and small or narrow forest clearings, and is primarily attributable to the moderate resolution of the imagery used to make maps. However, the degree to which such high-resolution imagery can mitigate this problem, and thereby improve large-area forest cover maps, is largely unexplored. Here, we developed an approach to map tropical forest cover at a fine scale using Planet and Sentinel-1 synthetic aperture radar (SAR) imagery in the Google Earth Engine platform and used it to map all of Southeastern Asia’s forest cover. The machine learning approach, based on the Random Forests models and trained and validated using a total of 37,345 labels collected from Planet imagery across the entire region, had an accuracy of 0.937 and an F1 score of 0.942, while a version based only on Planet imagery had an accuracy of 0.908 and F1 of 0.923. We compared the accuracy of our resulting maps with 5 existing forest cover products derived from medium-resolution optical-only or combined optical-SAR approaches at 3,000 randomly selected locations. We found that our approach overall achieved higher accuracy and helped minimize the rounding errors commonly found along small or narrow forest clearings and deforestation frontiers where isolated trees are common. However, the forest area estimates varied depending on topographic location and showed smaller differences in highlands (areas \u3e300 m above sea level) but obvious differences in complex lowland landscapes. Overall, the proposed method shows promise for monitoring forest changes, particularly those caused by deforestation frontiers. Our study also represents one of the most extensive applications of Planet imagery to date, resulting in an open, high-resolution map of forest cover for the entire Southeastern Asia region. © 2023 Feng Yang et al

    Perioperative immunotherapy for stage II-III non-small cell lung cancer: a meta-analysis base on randomized controlled trials

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    BackgroundIn recent years, we have observed the pivotal role of immunotherapy in improving survival for patients with non-small cell lung cancer (NSCLC). However, the effectiveness of immunotherapy in the perioperative (neoadjuvant + adjuvant) treatment of resectable NSCLC remains uncertain. We conducted a comprehensive analysis of its antitumor efficacy and adverse effects (AEs) by pooling data from the KEYNOTE-671, NADIM II, and AEGEAN clinical trials.MethodsFor eligible studies, we searched seven databases. The randomized controlled trials (RCTs) pertaining to the comparative analysis of combination neoadjuvant platinum-based chemotherapy plus perioperative immunotherapy (PIO) versus perioperative placebo (PP) were included. Primary endpoints were overall survival (OS) and event-free survival (EFS). Secondary endpoints encompassed drug responses, AEs, and surgical outcomes.ResultsThree RCTs (KEYNOTE-671, NADIM II, and AEGEAN) were included in the final analysis. PIO group (neoadjuvant platinum-based chemotherapy plus perioperative immunotherapy) exhibited superior efficacy in OS (hazard ratio [HR]: 0.63 [0.49-0.81]), EFS (HR: 0.61 [0.52, 0.72]), objective response rate (risk ratio [RR]: 2.21 [1.91, 2.54]), pathological complete response (RR: 4.36 [3.04, 6.25]), major pathological response (RR: 2.79 [2.25, 3.46]), R0 resection rate (RR: 1.13 [1.00, 1.26]) and rate of adjuvant treatment (RR: 1.08 [1.01, 1.15]) compared with PP group (neoadjuvant platinum-based chemotherapy plus perioperative placebo). In the subgroup analysis, EFS tended to favor the PIO group in almost all subgroups. BMI (>25), T stage (IV), N stage (N1-N2) and pathological response (with pathological complete response) were favorable factors in the PIO group. In the safety assessment, the PIO group exhibited higher rates of serious AEs (28.96% vs. 23.51%) and AEs leading to treatment discontinuation (12.84% vs. 5.81%). Meanwhile, although total adverse events, grade 3-5 adverse events, and fatal adverse events tended to favor the PP group, the differences were not statistically significant.ConclusionPIO appears to be superior to PP for resectable stage II-III NSCLC, demonstrating enhanced survival and pathological responses. However, its elevated adverse event (AE) rate warrants careful consideration.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/#recordDetails, identifier CRD42023487475

    Impacts of Vegetation Change on the Regional Surface Climate: A Scenario-Based Analysis of Afforestation in Jiangxi Province, China

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    The afforestation is one of the most noticeable human activities that affect the climate through influencing not only the carbon sink but also the thermal properties of the land surface. This research accessed the potential effects of artificial vegetation change on the regional climate in Jiangxi Province, China. Based on simulation with the Weather Research and Forecasting (WRF) model, a comparative analysis was carried out on the future temperature and precipitation under four hypothetical vegetation cover scenarios. The simulation results indicated that the vegetation change would have significant effects on the regional climate. The simulated effects of annual average temperature showed a decreasing order: evergreen broadleaf > evergreen needleleaf > deciduous needleleaf > deciduous broadleaf, and the effects of annual average precipitation of the evergreen forests would be bigger than those of the deciduous forests. The deciduous forests play a positive role in decreasing the annual average temperature, while the evergreen forests promote the annual average temperature rise. Besides, the expansion of deciduous forests may result in severe drought in the summer in Jiangxi Province. These conclusions are of important policy implication to the future afforestation in Jiangxi Province, China, and other regions of the world

    Pretracheal Lymph Node Subdivision in Predicting Contralateral Central Lymph Node Metastasis for Unilateral Papillary Thyroid Carcinoma: Preliminary Results

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    BackgroundThe aims of this study were to assess the clinical value of pretracheal lymph node subdivision in identifying patients with contralateral central lymph node metastasis (CLNM) and risk factors for occult contralateral CLNM in unilateral PTC.MethodsA total of 139 unilateral PTC patients with a clinically node-negative neck (cN0) who underwent bilateral central neck dissection (CND) were prospectively enrolled. Intraoperatively, the pretracheal region was further divided into ipsilateral and contralateral subregions. Ipsilateral and contralateral pretracheal lymph nodes (LNs) as well as other CLNs (prelaryngeal, ipsilateral paratracheal and contralateral paratracheal) were labeled separately and sent for pathological examination. Demographic and clinicopathologic variables were analyzed to identify factors predictive of contralateral CLNM.ResultsOf 139 patients, bilateral CLNM was present in 37 (26.6%) patients. Contralateral pretracheal LNM was significantly associated with contralateral CLNM. In multivariate analysis, prelaryngeal LNM (P = 0.004, odds ratio = 3.457) and contralateral pretracheal LNM (P = 0.006, odds ratio = 3.362) were identified as risk factors for contralateral CLNM. Neither neck recurrence nor distant metastasis was observed within the mean follow-up duration of 9.1 ± 1.8 months.ConclusionsIn most unilateral cN0 PTCs, performing ipsilateral CND is appropriate, while patients presenting with evident nodal disease intraoperatively or preoperatively in the contralateral central neck should undergo bilateral CND. Intraoperative re-evaluation of prelaryngeal and contralateral pretracheal LNs may be helpful in determining the extent of CND

    Stakeholder efforts to mitigate antiretroviral therapy interruption among people living with HIV during the COVID-19 pandemic in China: a qualitative study.

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    INTRODUCTION: The COVID-19 pandemic has affected antiretroviral therapy (ART) continuity among people living with HIV (PLHIV) worldwide. We conducted a qualitative study to explore barriers to ART maintenance and solutions to ART interruption when stringent COVID-19 control measures were implemented in China, from the perspective of PLHIV and relevant key stakeholders. METHODS: Between 11 February and 15 February 2020, we interviewed PLHIV, community-based organization (CBO) workers, staff from centres for disease control and prevention (CDC) at various levels whose work is relevant to HIV care (CDC staff), HIV doctors and nurses and drug vendors from various regions in China. Semi-structured interviews were conducted using a messaging and social media app. Challenges and responses relevant to ART continuity during the COVID-19 pandemic were discussed. Themes were identified by transcript coding and mindmaps. RESULTS: Sixty-four stakeholders were recruited, including 16 PLHIV, 17 CBO workers, 15 CDC staff, 14 HIV doctors and nurses and two drug vendors. Many CDC staff, HIV doctors and nurses responsible for ART delivery and HIV care were shifted to COVID-19 response efforts. Barriers to ART maintenance were (a) travel restrictions, (b) inadequate communication and bureaucratic obstacles, (c) shortage in personnel, (d) privacy concerns, and (e) insufficient ART reserve. CBO helped PLHIV maintain access to ART through five solutions identified from thematic analysis: (a) coordination to refill ART from local CDC clinics or hospitals, (b) delivery of ART by mail, (c) privacy protection measures, (d) mental health counselling, and (e) providing connections to alternative sources of ART. Drug vendors contributed to ART maintenance by selling out-of-pocket ART. CONCLUSIONS: Social and institutional disruption from COVID-19 contributed to increased risk of ART interruption among PLHIV in China. Collaboration among key stakeholders was needed to maintain access to ART, with CBO playing an important role. Other countries facing ART interruption during current or future public health emergencies may learn from the solutions employed in China

    Robotic versus laparoscopic right hemicolectomy with complete mesocolic excision: a retrospective multicenter study with propensity score matching

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    ObjectiveDuring the past decade, the concept of complete mesocolic excision (CME) has been developed in an attempt to minimize recurrence for right-sided colon cancer. This study aims to compare outcomes of robotic versus laparoscopic right hemicolectomy with CME for right-sided colon cancer.MethodsWe performed a retrospective multicenter propensity score matching study. From July 2016 to July 2021, 382 consecutive patients from different Chinese surgical departments were available for inclusion out of an initial cohort of 412, who underwent robotic or laparoscopic right hemicolectomy with CME. Data of all patients were retrospectively collected and reviewed. Of these, 149 cases were performed by a robotic approach, while the other 233 cases were done by laparoscopy. Propensity score matching was applied at a ratio of 1:1 to compare perioperative, pathologic, and oncologic outcomes between the robotic and the laparoscopic groups (n = 142).ResultsBefore propensity score matching, there were no statistical differences regarding the sex, history of abdominal surgery, body mass index (BMI), American Joint Committee on Cancer (AJCC) staging system, tumor location, and center between groups (p > 0.05), while a significant difference was observed regarding age (p = 0.029). After matching, two comparable groups of 142 cases were obtained with equivalent patient characteristics (p > 0.05). Blood loss, time to oral intake, return of bowel function, length of stay, and complications were not different between groups (p > 0.05). The robotic group showed a significantly lower conversion rate (0% vs. 4.2%, p = 0.03), but a longer operative time (200.9 min vs. 182.3 min, p < 0.001) and a higher total hospital cost (85,016 RMB vs. 58,266 RMB, p < 0.001) compared with the laparoscopic group. The number of harvested lymph nodes was comparable (20.4 vs. 20.5, p = 0.861). Incidence of complications, mortality, and pathologic outcomes were similar between groups (p > 0.05). The 2-year disease-free survival rates were 84.9% and 87.1% (p = 0.679), and the overall survival rates between groups were 83.8% and 80.7% (p = 0.943).ConclusionDespite the limitations of a retrospective analysis, the outcomes of robotic right hemicolectomy with CME were comparable to the laparoscopic procedures with fewer conversions to open surgery. More clinical advantages of the robotic surgery system need to be further confirmed by well-conducted randomized clinical trials with large cohorts of patients

    Cassava genome from a wild ancestor to cultivated varieties

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    Cassava is a major tropical food crop in the Euphorbiaceae family that has high carbohydrate production potential and adaptability to diverse environments. Here we present the draft genome sequences of a wild ancestor and a domesticated variety of cassava and comparative analyses with a partial inbred line. We identify 1,584 and 1,678 gene models specific to the wild and domesticated varieties, respectively, and discover high heterozygosity and millions of single-nucleotide variations. Our analyses reveal that genes involved in photosynthesis, starch accumulation and abiotic stresses have been positively selected, whereas those involved in cell wall biosynthesis and secondary metabolism, including cyanogenic glucoside formation, have been negatively selected in the cultivated varieties, reflecting the result of natural selection and domestication. Differences in microRNA genes and retrotransposon regulation could partly explain an increased carbon flux towards starch accumulation and reduced cyanogenic glucoside accumulation in domesticated cassava. These results may contribute to genetic improvement of cassava through better understanding of its biology

    TRY plant trait database – enhanced coverage and open access

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

    TRY plant trait database – enhanced coverage and open access

    Get PDF
    Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Rest of authors: Decky Junaedi, Robert R. Junker, Eric Justes, Richard Kabzems, Jeffrey Kane, Zdenek Kaplan, Teja Kattenborn, Lyudmila Kavelenova, Elizabeth Kearsley, Anne Kempel, Tanaka Kenzo, Andrew Kerkhoff, Mohammed I. Khalil, Nicole L. Kinlock, Wilm Daniel Kissling, Kaoru Kitajima, Thomas Kitzberger, Rasmus KjĂžller, Tamir Klein, Michael Kleyer, Jitka KlimeĆĄovĂĄ, Joice Klipel, Brian Kloeppel, Stefan Klotz, Johannes M. H. Knops, Takashi Kohyama, Fumito Koike, Johannes Kollmann, Benjamin Komac, Kimberly Komatsu, Christian König, Nathan J. B. Kraft, Koen Kramer, Holger Kreft, Ingolf KĂŒhn, Dushan Kumarathunge, Jonas Kuppler, Hiroko Kurokawa, Yoko Kurosawa, Shem Kuyah, Jean-Paul Laclau, Benoit Lafleur, Erik Lallai, Eric Lamb, Andrea Lamprecht, Daniel J. Larkin, Daniel Laughlin, Yoann Le Bagousse-Pinguet, Guerric le Maire, Peter C. le Roux, Elizabeth le Roux, Tali Lee, Frederic Lens, Simon L. Lewis, Barbara Lhotsky, Yuanzhi Li, Xine Li, Jeremy W. Lichstein, Mario Liebergesell, Jun Ying Lim, Yan-Shih Lin, Juan Carlos Linares, Chunjiang Liu, Daijun Liu, Udayangani Liu, Stuart Livingstone, Joan LlusiĂ , Madelon Lohbeck, Álvaro LĂłpez-GarcĂ­a, Gabriela Lopez-Gonzalez, Zdeƈka LososovĂĄ, FrĂ©dĂ©rique Louault, BalĂĄzs A. LukĂĄcs, Petr LukeĆĄ, Yunjian Luo, Michele Lussu, Siyan Ma, Camilla Maciel Rabelo Pereira, Michelle Mack, Vincent Maire, Annikki MĂ€kelĂ€, Harri MĂ€kinen, Ana Claudia Mendes Malhado, Azim Mallik, Peter Manning, Stefano Manzoni, Zuleica Marchetti, Luca Marchino, Vinicius Marcilio-Silva, Eric Marcon, Michela Marignani, Lars Markesteijn, Adam Martin, Cristina MartĂ­nez-Garza, Jordi MartĂ­nez-Vilalta, Tereza MaĆĄkovĂĄ, Kelly Mason, Norman Mason, Tara Joy Massad, Jacynthe Masse, Itay Mayrose, James McCarthy, M. Luke McCormack, Katherine McCulloh, Ian R. McFadden, Brian J. McGill, Mara Y. McPartland, Juliana S. Medeiros, Belinda Medlyn, Pierre Meerts, Zia Mehrabi, Patrick Meir, Felipe P. L. Melo, Maurizio Mencuccini, CĂ©line Meredieu, Julie Messier, Ilona MĂ©szĂĄros, Juha Metsaranta, Sean T. Michaletz, Chrysanthi Michelaki, Svetlana Migalina, Ruben Milla, Jesse E. D. Miller, Vanessa Minden, Ray Ming, Karel Mokany, Angela T. Moles, Attila MolnĂĄr V, Jane Molofsky, Martin Molz, Rebecca A. Montgomery, Arnaud Monty, Lenka MoravcovĂĄ, Alvaro Moreno-MartĂ­nez, Marco Moretti, Akira S. Mori, Shigeta Mori, Dave Morris, Jane Morrison, Ladislav Mucina, Sandra Mueller, Christopher D. Muir, Sandra Cristina MĂŒller, François Munoz, Isla H. Myers-Smith, Randall W. Myster, Masahiro Nagano, Shawna Naidu, Ayyappan Narayanan, Balachandran Natesan, Luka Negoita, Andrew S. Nelson, Eike Lena Neuschulz, Jian Ni, Georg Niedrist, Jhon Nieto, Ülo Niinemets, Rachael Nolan, Henning Nottebrock, Yann Nouvellon, Alexander Novakovskiy, The Nutrient Network, Kristin Odden Nystuen, Anthony O'Grady, Kevin O'Hara, Andrew O'Reilly-Nugent, Simon Oakley, Walter Oberhuber, Toshiyuki Ohtsuka, Ricardo Oliveira, Kinga Öllerer, Mark E. Olson, Vladimir Onipchenko, Yusuke Onoda, Renske E. Onstein, Jenny C. Ordonez, Noriyuki Osada, Ivika Ostonen, Gianluigi Ottaviani, Sarah Otto, Gerhard E. Overbeck, Wim A. Ozinga, Anna T. Pahl, C. E. Timothy Paine, Robin J. Pakeman, Aristotelis C. Papageorgiou, Evgeniya Parfionova, Meelis PĂ€rtel, Marco Patacca, Susana Paula, Juraj Paule, Harald Pauli, Juli G. Pausas, Begoña Peco, Josep Penuelas, Antonio Perea, Pablo Luis Peri, Ana Carolina Petisco-Souza, Alessandro Petraglia, Any Mary Petritan, Oliver L. Phillips, Simon Pierce, ValĂ©rio D. Pillar, Jan Pisek, Alexandr Pomogaybin, Hendrik Poorter, Angelika Portsmuth, Peter Poschlod, Catherine Potvin, Devon Pounds, A. Shafer Powell, Sally A. Power, Andreas Prinzing, Giacomo Puglielli, Petr PyĆĄek, Valerie Raevel, Anja Rammig, Johannes Ransijn, Courtenay A. Ray, Peter B. Reich, Markus Reichstein, Douglas E. B. Reid, Maxime RĂ©jou-MĂ©chain, Victor Resco de Dios, Sabina Ribeiro, Sarah Richardson, Kersti Riibak, Matthias C. Rillig, Fiamma Riviera, Elisabeth M. R. Robert, Scott Roberts, Bjorn Robroek, Adam Roddy, Arthur Vinicius Rodrigues, Alistair Rogers, Emily Rollinson, Victor Rolo, Christine Römermann, Dina Ronzhina, Christiane Roscher, Julieta A. Rosell, Milena Fermina Rosenfield, Christian Rossi, David B. Roy, Samuel Royer-Tardif, Nadja RĂŒger, Ricardo Ruiz-Peinado, Sabine B. Rumpf, Graciela M. Rusch, Masahiro Ryo, Lawren Sack, Angela Saldaña, Beatriz Salgado-Negret, Roberto Salguero-Gomez, Ignacio Santa-Regina, Ana Carolina Santacruz-GarcĂ­a, Joaquim Santos, Jordi Sardans, Brandon Schamp, Michael Scherer-Lorenzen, Matthias Schleuning, Bernhard Schmid, Marco Schmidt, Sylvain Schmitt, Julio V. Schneider, Simon D. Schowanek, Julian Schrader, Franziska Schrodt, Bernhard Schuldt, Frank Schurr, Galia Selaya Garvizu, Marina Semchenko, Colleen Seymour, Julia C. Sfair, Joanne M. Sharpe, Christine S. Sheppard, Serge Sheremetiev, Satomi Shiodera, Bill Shipley, Tanvir Ahmed Shovon, Alrun SiebenkĂ€s, Carlos Sierra, Vasco Silva, Mateus Silva, Tommaso Sitzia, Henrik Sjöman, Martijn Slot, Nicholas G. Smith, Darwin Sodhi, Pamela Soltis, Douglas Soltis, Ben Somers, GrĂ©gory Sonnier, Mia Vedel SĂžrensen, Enio Egon Sosinski Jr, Nadejda A. Soudzilovskaia, Alexandre F. Souza, Marko Spasojevic, Marta Gaia Sperandii, Amanda B. Stan, James Stegen, Klaus Steinbauer, Jörg G. Stephan, Frank Sterck, Dejan B. Stojanovic, Tanya Strydom, Maria Laura Suarez, Jens-Christian Svenning, Ivana SvitkovĂĄ, Marek Svitok, Miroslav Svoboda, Emily Swaine, Nathan Swenson, Marcelo Tabarelli, Kentaro Takagi, Ulrike Tappeiner, RubĂ©n Tarifa, Simon Tauugourdeau, Cagatay Tavsanoglu, Mariska te Beest, Leho Tedersoo, Nelson Thiffault, Dominik Thom, Evert Thomas, Ken Thompson, Peter E. Thornton, Wilfried Thuiller, LubomĂ­r TichĂœ, David Tissue, Mark G. Tjoelker, David Yue Phin Tng, Joseph Tobias, PĂ©ter Török, Tonantzin Tarin, JosĂ© M. Torres-Ruiz, BĂ©la TĂłthmĂ©rĂ©sz, Martina Treurnicht, Valeria Trivellone, Franck Trolliet, Volodymyr Trotsiuk, James L. Tsakalos, Ioannis Tsiripidis, Niklas Tysklind, Toru Umehara, Vladimir Usoltsev, Matthew Vadeboncoeur, Jamil Vaezi, Fernando Valladares, Jana Vamosi, Peter M. van Bodegom, Michiel van Breugel, Elisa Van Cleemput, Martine van de Weg, Stephni van der Merwe, Fons van der Plas, Masha T. van der Sande, Mark van Kleunen, Koenraad Van Meerbeek, Mark Vanderwel, Kim AndrĂ© Vanselow, Angelica VĂ„rhammar, Laura Varone, Maribel Yesenia Vasquez Valderrama, Kiril Vassilev, Mark Vellend, Erik J. Veneklaas, Hans Verbeeck, Kris Verheyen, Alexander Vibrans, Ima Vieira, Jaime VillacĂ­s, Cyrille Violle, Pandi Vivek, Katrin Wagner, Matthew Waldram, Anthony Waldron, Anthony P. Walker, Martyn Waller, Gabriel Walther, Han Wang, Feng Wang, Weiqi Wang, Harry Watkins, James Watkins, Ulrich Weber, James T. Weedon, Liping Wei, Patrick Weigelt, Evan Weiher, Aidan W. Wells, Camilla Wellstein, Elizabeth Wenk, Mark Westoby, Alana Westwood, Philip John White, Mark Whitten, Mathew Williams, Daniel E. Winkler, Klaus Winter, Chevonne Womack, Ian J. Wright, S. Joseph Wright, Justin Wright, Bruno X. Pinho, Fabiano Ximenes, Toshihiro Yamada, Keiko Yamaji, Ruth Yanai, Nikolay Yankov, Benjamin Yguel, KĂĄtia Janaina Zanini, Amy E. Zanne, David ZelenĂœ, Yun-Peng Zhao, Jingming Zheng, Ji Zheng, Kasia ZiemiƄska, Chad R. Zirbel, Georg Zizka, IriĂ© Casimir Zo-Bi, Gerhard Zotz, Christian Wirth.Max Planck Institute for Biogeochemistry; Max Planck Society; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; International Programme of Biodiversity Science (DIVERSITAS); International Geosphere-Biosphere Programme (IGBP); Future Earth; French Foundation for Biodiversity Research (FRB); GIS ‘Climat, Environnement et SociĂ©tĂ©'.http://wileyonlinelibrary.com/journal/gcbhj2021Plant Production and Soil Scienc
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