60 research outputs found

    Effect of Comorbidity on Prostate Cancer-Specific Mortality: A Prospective Observational Study.

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    Purpose To determine the effect of comorbidity on prostate cancer (PCa)-specific mortality across treatment types. Patients and Methods These are the results of a population-based observational study in Sweden from 1998 to 2012 of 118,543 men who were diagnosed with PCa with a median follow-up of 8.3 years (interquartile range, 5.2 to 11.5 years) until death from PCa or other causes. Patients were categorized by patient characteristics (marital status, educational level) and tumor characteristics (serum prostate-specific antigen, tumor grade and clinical stage) and by treatment type (radical prostatectomy, radical radiotherapy, androgen deprivation therapy, and watchful waiting). Data were stratified by Charlson comorbidity index (0, 1, 2, or ≄ 3). Mortality from PCa and other causes and after stabilized inverse probability weighting adjustments for clinical patient and tumor characteristics and treatment type was determined. Kaplan-Meier estimates and Cox proportional hazards regression models were used to calculate hazard ratios. Results In the complete unadjusted data set, we observed an effect of increased comorbidity on PCa-specific and other-cause mortality. After adjustments for patient and tumor characteristics, the effect of comorbidity on PCa-specific mortality was lost but maintained for other-cause mortality. After additional adjustment for treatment type, we again failed to observe an effect for comorbidity on PCa-specific mortality, although it was maintained for other-cause mortality. Conclusion This large observational study suggests that comorbidity affects other cause-mortality but not PCa-specific- mortality after accounting for patient and tumor characteristics and treatment type. Regardless of radical treatment type (radical prostatectomy or radical radiotherapy), increasing comorbidity does not seem to significantly affect the risk of dying from PCa. Consequently, differences in oncologic outcomes that were observed in population-based comparative effectiveness studies of PCa treatments may not be a result of the varying distribution of comorbidity among treatment groups

    Achieving conservation through cattle ranching: The case of the Brazilian Pantanal

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    Cattle ranching in the ~140,000 km2 Brazilian Pantanal is considered one of the most important cases of sustainable use of natural resources in the global south. The region has had a successful history of balancing environmental protection with the production of >3.8 million cattle. However, global change, infrastructure projects, and deforestation, threaten the sustainable use of the Pantanal. Here, using Ostrom's design principles as a framework, we interviewed 49 local stakeholders and conducted a review of secondary information aiming to evaluate the sustainability of cattle ranching practices across the region and the threats to it. We show that well-defined property boundaries, congruence between appropriation and provision rules through low-intensity cattle ranching, and co-management of resources, are all key components for achieving sustainability in the Pantanal. However, we documented shortcomings in satisfying critical aspects of Orstrom's design principles. Specifically, we argue that the Pantanal needs better biodiversity and behavior monitoring, the creation of platforms or mechanisms to solve local conflicts around resource access and use, recognition by governments and international bodies of the local efforts to promote local sustainability, and the creation of networks effectively connecting existing sustainability initiatives

    Biochemical Recurrence and Risk of Mortality Following Radiotherapy or Radical Prostatectomy

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    Importance: Stratifying patients with biochemical recurrence (BCR) after primary treatment for prostate cancer based on the risk of prostate cancer-specific mortality (PCSM) is essential for determining the need for further testing and treatments. Objective: To evaluate the association of BCR after radical prostatectomy or radiotherapy and its current risk stratification with PCSM. Design, Setting, and Participants: This population-based cohort study included a total of 16 311 male patients with 10 364 (64%) undergoing radical prostatectomy and 5947 (36%) undergoing radiotherapy with curative intent (cT1-3, cM0) and PSA follow-up in Stockholm, Sweden, between 2003 and 2019. Follow-up for all patients was until death, emigration, or end of the study (ie, December 31, 2018). Data were analyzed between September 2022 and March 2023. Main Outcomes and Measures: Primary outcomes of the study were the cumulative incidence of BCR and PCSM. Patients with BCR were stratified in low- and high-risk according to European Association of Urology (EAU) criteria. Exposures: Radical prostatectomy or radiotherapy. Results: A total of 16 311 patients were included. Median (IQR) age was 64 (59-68) years in the radical prostatectomy cohort (10 364 patients) and 69 (64-73) years in the radiotherapy cohort (5947 patients). Median (IQR) follow-up for survivors was 88 (55-138) months and 89 (53-134) months, respectively. Following radical prostatectomy, the 15-year cumulative incidences of BCR were 16% (95% CI, 15%-18%) for the 4024 patients in the low D'Amico risk group, 30% (95% CI, 27%-32%) for the 5239 patients in the intermediate D'Amico risk group, and 46% (95% CI, 42%-51%) for 1101 patients in the high D'Amico risk group. Following radiotherapy, the 15-year cumulative incidences of BCR were 18% (95% CI, 15%-21%) for the 1230 patients in the low-risk group, 24% (95% CI, 21%-26%) for the 2355 patients in the intermediate-risk group, and 36% (95% CI, 33%-39%) for the 2362 patients in the high-risk group. The 10-year cumulative incidences of PCSM after radical prostatectomy were 4% (95% CI, 2%-6%) for the 1101 patients who developed low-risk EAU-BCR and 9% (95% CI, 5%-13%) for 649 patients who developed high-risk EAU-BCR. After radiotherapy, the 10-year PCSM cumulative incidences were 24% (95% CI, 19%-29%) for the 591 patients in the low-risk EAU-BCR category and 46% (95% CI, 40%-51%) for the 600 patients in the high-risk EAU-BCR category. Conclusions and Relevance: These findings suggest the validity of EAU-BCR stratification system. However, while the risk of dying from prostate cancer in low-risk EAU-BCR after radical prostatectomy was very low, patients who developed low-risk EAU-BCR after radiotherapy had a nonnegligible risk of prostate cancer mortality. Improving risk stratification of patients with BCR is pivotal to guide salvage treatment decisions, reduce overtreatment, and limit the number of staging tests in the event of PSA elevations after primary treatment.</p

    Novel associations in disorders of sex development: findings from the I-DSD registry

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    Context: The focus of care in disorders of sex development (DSD) is often directed to issues related to sex and gender development. In addition, the molecular etiology remains unclear in the majority of cases.&lt;p&gt;&lt;/p&gt; Objective: To report the range of associated conditions identified in the international DSD (I-DSD) Registry.&lt;p&gt;&lt;/p&gt; Design, Setting, and Patients: Anonymized data were extracted from the I-DSD Registry for diagnosis, karyotype, sex of rearing, genetic investigations, and associated anomalies. If necessary, clarification was sought from the reporting clinician.&lt;p&gt;&lt;/p&gt; Results: Of 649 accessible cases, associated conditions occurred in 168 (26%); 103 (61%) cases had one condition, 31 (18%) had two conditions, 20 (12%) had three conditions, and 14 (8%) had four or more conditions. Karyotypes with most frequently reported associations included 45,X with 6 of 8 affected cases (75%), 45,X/46,XY with 19 of 42 cases (45%), 46,XY with 112 of 460 cases (24%), and 46,XX with 27 of 121 cases (22%). In the 112 cases of 46,XY DSD, the commonest conditions included small for gestational age in 26 (23%), cardiac anomalies in 22 (20%), and central nervous system disorders in 22 (20%), whereas in the 27 cases of 46,XX DSD, skeletal and renal anomalies were commonest at 12 (44%) and 8 (30%), respectively. Of 170 cases of suspected androgen insensitivity syndrome, 19 (11%) had reported anomalies and 9 of these had confirmed androgen receptor mutations.&lt;p&gt;&lt;/p&gt; Conclusions: Over a quarter of the cases in the I-DSD Registry have an additional condition. These associations can direct investigators toward novel genetic etiology and also highlight the need for more holistic care of the affected person.&lt;p&gt;&lt;/p&gt

    Characteristics of Patients in SPCG-15-A Randomized Trial Comparing Radical Prostatectomy with Primary Radiotherapy plus Androgen Deprivation Therapy in Men with Locally Advanced Prostate Cancer

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    Background: There is no high-grade evidence for surgery as primary treatment for locally advanced prostate cancer. The SPCG-15 study is the first randomized trial comparing surgical treatment with radiotherapy. Objective: To describe the baseline characteristics of the first 600 randomized men in the SPCG-15 study. The study will compare mortality and functional outcomes. Design, setting, and participants: This study is a Scandinavian prospective, open, multicenter phase III randomized clinical trial aiming to randomize 1200 men. Intervention: Radical prostatectomy with or without consecutive radiotherapy (experimental) and radiotherapy with neoadjuvant androgen deprivation therapy (standard of care). Outcome measurements and statistical analysis: Cause-specific survival, metastasis-free survival, overall survival, and patient-reported bowel function, sexual health, and lower urinary tract symptoms were measured. Results and limitations: The distribution of characteristics was similar in the two study arms. The median age was 67 yr (range 45-75 yr). Among the operated men, 36% had pT3a stage of disease and 39% had pT3b stage. International Society of Urological Pathology grades 2, 3, 4, and 5 were prevalent in 21%, 35%, 7%, and 27%, respectively. Half of the men (51%) in the surgery arm had no positive lymph nodes. The main limitation is the pragmatic design comparing the best available practice at each study site leading to heterogeneity of treatment regimens within the study arms. Conclusions: We have proved that randomization between surgery and radiotherapy for locally advanced prostate cancer is feasible. The characteristics of the study population demonstrate a high prevalence of advanced disease, well-balanced comparison groups, and a demography mirroring the Scandinavian population of men with prostate cancer at large. Patient summary: This study, which has recruited >600 men, compares radiotherapy with surgery for prostate cancer, and an analysis at the time of randomization indicates that the study will be informative and generalizable to most men with locally advanced but not metastasized prostate cancer. (C) 2022 The Author(s). Published by Elsevier B.V. on behalf of European Association of Urology.Peer reviewe

    An image dataset of cleared, x-rayed, and fossil leaves vetted to plant family for human and machine learning

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    Leaves are the most abundant and visible plant organ, both in the modern world and the fossil record. Identifying foliage to the correct plant family based on leaf architecture is a fundamental botanical skill that is also critical for isolated fossil leaves, which often, especially in the Cenozoic, represent extinct genera and species from extant families. Resources focused on leaf identification are remarkably scarce; however, the situation has improved due to the recent proliferation of digitized herbarium material, live-plant identification applications, and online collections of cleared and fossil leaf images. Nevertheless, the need remains for a specialized image dataset for comparative leaf architecture. We address this gap by assembling an open-access database of 30,252 images of vouchered leaf specimens vetted to family level, primarily of angiosperms, including 26,176 images of cleared and x-rayed leaves representing 354 families and 4,076 of fossil leaves from 48 families. The images maintain original resolution, have user-friendly filenames, and are vetted using APG and modern paleobotanical standards. The cleared and x-rayed leaves include the Jack A. Wolfe and Leo J. Hickey contributions to the National Cleared Leaf Collection and a collection of high-resolution scanned x-ray negatives, housed in the Division of Paleobotany, Department of Paleobiology, Smithsonian National Museum of Natural History, Washington D.C.; and the Daniel I. Axelrod Cleared Leaf Collection, housed at the University of California Museum of Paleontology, Berkeley. The fossil images include a sampling of Late Cretaceous to Eocene paleobotanical sites from the Western Hemisphere held at numerous institutions, especially from Florissant Fossil Beds National Monument (late Eocene, Colorado), as well as several other localities from the Late Cretaceous to Eocene of the Western USA and the early Paleogene of Colombia and southern Argentina. The dataset facilitates new research and education opportunities in paleobotany, comparative leaf architecture, systematics, and machine learning.Fil: Wilf, Peter. State University of Pennsylvania; Estados UnidosFil: Wing, Scott L.. National Museum of Natural History; Estados UnidosFil: Meyer, Herbert W.. State University of Pennsylvania; Estados UnidosFil: Rose, Jacob A.. State University of Pennsylvania; Estados UnidosFil: Saha, Rohit. State University of Pennsylvania; Estados UnidosFil: Serre, Thomas. State University of Pennsylvania; Estados UnidosFil: CĂșneo, NĂ©stor RubĂ©n. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; Argentina. Museo PaleontolĂłgico Egidio Feruglio; ArgentinaFil: Donovan, Michael P.. State University of Pennsylvania; Estados UnidosFil: Erwin, Diane M.. State University of Pennsylvania; Estados UnidosFil: Gandolfo, MarĂ­a A.. Cornell University; Estados UnidosFil: GonzĂĄlez Akre, Erika. State University of Pennsylvania; Estados UnidosFil: Herrera, Fabiany. National Museum of Natural History; Estados UnidosFil: Hu, Shusheng. State University of Pennsylvania; Estados UnidosFil: Iglesias, Ari. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Johnson, Kirk R.. Smithsonian Tropical Research Institute; PanamĂĄFil: Karim, Talia S.. University of Colorado; Estados UnidosFil: Zou, Xiaoyu. State University of Pennsylvania; Estados Unido

    The risk of cryptorchidism among sons of women working in horticulture in Denmark: a cohort study

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    <p>Abstract</p> <p>Background</p> <p>Androgens are crucial for normal testicular descent. Studies show that some pesticides have estrogenic or antiandrogenic effects, and that female workers exposed to pesticides have increased risk of having a boy with cryptorchidism. The main objective of the present study was to investigate whether pregnant women exposed to pesticides due to their work in horticulture experience excess risk of having sons with cryptorchidism.</p> <p>Methods</p> <p>We conducted a cohort study of pregnant women working in horticulture using four cohorts including one cohort established with data from the departments of occupational medicine in Jutland and Funen and three existing mother-child cohorts (n = 1,468). A reference group was established from the entire Danish population of boys born in the period of 1986-2007 (n = 783,817). Nationwide Danish health registers provided information on birth outcome, cryptorchidism diagnosis and orchiopexy. The level of occupational exposure to pesticides was assessed by expert judgment blinded towards outcome status. Risk of cryptorchidism among exposed horticulture workers compared to the background population and to unexposed horticulture workers was assessed by Cox regression models.</p> <p>Results</p> <p>Pesticide exposed women employed in horticulture had a hazard ratio (HR) of having cryptorchid sons of 1.39 (95% CI 0.84; 2.31) and a HR of orchiopexy of 1.34 (0.72; 2.49) compared to the background population. Analysis divided into separate cohorts revealed a significantly increased risk of cryptorchidism in cohort 2: HR 2.58 (1.07;6.20) and increased risk of orchiopexy in cohort 4: HR 2.76 (1.03;7.35), but no significant associations in the other cohorts. Compared to unexposed women working in horticulture, pesticide exposed women had a risk of having sons with cryptorchidism of 1.34 (0.30; 5.96) and of orchiopexy of 1.93 (0.24;15.4).</p> <p>Conclusions</p> <p>The data are compatible with a slightly increased risk of cryptorchidism in sons of women exposed to pesticides by working in horticulture.</p

    A comprehensive analysis of autocorrelation and bias in home range estimation

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    Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated-Gaussian reference function [AKDE], SilvermanÂŽs rule of thumb, and least squares cross-validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half-sample cross-validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ((Formula presented.)) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID-based estimates by a mean factor of 2. The median number of cross-validated locations included in the hold-out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing (Formula presented.). To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animalÂŽs movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small (Formula presented.). While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an (Formula presented.) >1,000, where 30% had an (Formula presented.) <30. In this frequently encountered scenario of small (Formula presented.), AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.Fil: Noonan, Michael J.. National Zoological Park; Estados Unidos. University of Maryland; Estados UnidosFil: Tucker, Marlee A.. Senckenberg Gesellschaft FĂŒr Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Fleming, Christen H.. University of Maryland; Estados Unidos. National Zoological Park; Estados UnidosFil: Akre, Thomas S.. National Zoological Park; Estados UnidosFil: Alberts, Susan C.. University of Duke; Estados UnidosFil: Ali, Abdullahi H.. Hirola Conservation Programme. Garissa; KeniaFil: Altmann, Jeanne. University of Princeton; Estados UnidosFil: Antunes, Pamela Castro. Universidade Federal do Mato Grosso do Sul; BrasilFil: Belant, Jerrold L.. State University of New York; Estados UnidosFil: Beyer, Dean. Universitat Phillips; AlemaniaFil: Blaum, Niels. Universitat Potsdam; AlemaniaFil: Böhning Gaese, Katrin. Senckenberg Gesellschaft FĂŒr Naturforschung; Alemania. Goethe Universitat Frankfurt; AlemaniaFil: Cullen Jr., Laury. Instituto de Pesquisas EcolĂłgicas; BrasilFil: de Paula, Rogerio Cunha. National Research Center For Carnivores Conservation; BrasilFil: Dekker, Jasja. Jasja Dekker Dierecologie; PaĂ­ses BajosFil: Drescher Lehman, Jonathan. George Mason University; Estados Unidos. National Zoological Park; Estados UnidosFil: Farwig, Nina. Michigan State University; Estados UnidosFil: Fichtel, Claudia. German Primate Center; AlemaniaFil: Fischer, Christina. Universitat Technical Zu Munich; AlemaniaFil: Ford, Adam T.. University of British Columbia; CanadĂĄFil: Goheen, Jacob R.. University of Wyoming; Estados UnidosFil: Janssen, RenĂ©. Bionet Natuuronderzoek; PaĂ­ses BajosFil: Jeltsch, Florian. Universitat Potsdam; AlemaniaFil: Kauffman, Matthew. University Of Wyoming; Estados UnidosFil: Kappeler, Peter M.. German Primate Center; AlemaniaFil: Koch, FlĂĄvia. German Primate Center; AlemaniaFil: LaPoint, Scott. Max Planck Institute fĂŒr Ornithologie; Alemania. Columbia University; Estados UnidosFil: Markham, A. Catherine. Stony Brook University; Estados UnidosFil: Medici, Emilia Patricia. Instituto de Pesquisas EcolĂłgicas (IPE) ; BrasilFil: Morato, Ronaldo G.. Institute For Conservation of The Neotropical Carnivores; Brasil. National Research Center For Carnivores Conservation; BrasilFil: Nathan, Ran. The Hebrew University of Jerusalem; IsraelFil: Oliveira Santos, Luiz Gustavo R.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Olson, Kirk A.. Wildlife Conservation Society; Estados Unidos. National Zoological Park; Estados UnidosFil: Patterson, Bruce. Field Museum of National History; Estados UnidosFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș | Universidad Nacional de Misiones. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste; ArgentinaFil: Ramalho, Emiliano Esterci. Institute For Conservation of The Neotropical Carnivores; Brasil. Instituto de Desenvolvimento Sustentavel MamirauĂĄ; BrasilFil: Rösner, Sascha. Michigan State University; Estados UnidosFil: Schabo, Dana G.. Michigan State University; Estados UnidosFil: Selva, Nuria. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Sergiel, Agnieszka. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Xavier da Silva, Marina. Parque Nacional do Iguaçu; BrasilFil: Spiegel, Orr. Universitat Tel Aviv; IsraelFil: Thompson, Peter. University of Maryland; Estados UnidosFil: Ullmann, Wiebke. Universitat Potsdam; AlemaniaFil: Ziឝba, Filip. Tatra National Park; PoloniaFil: Zwijacz Kozica, Tomasz. Tatra National Park; PoloniaFil: Fagan, William F.. University of Maryland; Estados UnidosFil: Mueller, Thomas. Senckenberg Gesellschaft FĂŒr Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Calabrese, Justin M.. National Zoological Park; Estados Unidos. University of Maryland; Estados Unido

    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. 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