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Post-fire phenology of the tree fern Cyathea mexiae at the edge of a semideciduous forest in Brazil

Science of Nature 2025年第3期112卷 1-13页

作者： Lauro, Ana Taliê Dutra Lima, Lucas Vieira Menini Neto, Luiz de Paiva Farias, Rafael Institute of Biological Sciences Department of Botany Federal University of Juiz de Fora Leopoldo Krieger Herbarium Minas Gerais Juiz de Fora City Brazil Postgraduate Program in Forest Engineering Regional University of Blumenau São Paulo Street Santa Catarina Blumenau City Brazil Posgraduate Program in Biodiversity and Evolution Federal University of Bahia Bahia Salvador Brazil Dr. Roberto Miguel Klein Herbarium Regional University of Blumenau Blumenau Blumenau Brazil Posgraduate Program in Biodiversity and Nature Conservation Federal University of Juiz de Fora Juiz de Fora Brazil

Phenology investigates the periodicity of biological events related to plant growth. There is limited phenological information on ferns, particularly under disturbance conditions such as forest edges and fire. This study aimed to identify phenological patterns and responses to environmental factors and post-accidental fire events, including leaf production and mortality, and the number of leaves of Cyathea mexiae Copel. at the edge of a semi-deciduous seasonal remnant of the Atlantic forest in Brazil. Twenty-four plants were monitored for 22 months, with 10 of them affected by fire. We quantified and compared leaf number, production, and mortality, and evaluated their relationships with environmental factors (rainfall, temperature, and humidity), considering two groups: burned and unburned. Trunk height was measured and related to phenological events. Only one plant died post fire. Burned and unburned groups showed no significant differences in trunk height, leaf number, production, or mortality. Both groups exhibited discontinuous and irregular leaf production and mortality patterns. Both groups produced leaves immediately post fire, though with differences in peak timing. Burned plants displayed a rapid peak in leaf production (September), earlier than the peak in unburned plants (November). Only leaf mortality in unburned plants was positively correlated with rainfall and humidity. This study demonstrated a rapid recovery in leaf numbers following accidental fire for C. mexiae. The study revealed non-seasonal trends in the leaf production patterns of C. mexiae, with fire potentially inducing leaf mortality, reducing the sensitivity of this phenophase to environmental factors, and altering the timing of peak leaf production between the groups. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Edge forest Environmental triggers Leaf production post-fire Plant-climate interactions Tropical phenology

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Mapping aboveground biomass by integrating geospatial and forest inventory data through a k-nearest neighbor strategy in North Central Mexico

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Journal of Arid Land 2014年第1期6卷 80-96页

作者： Carlos A AGUIRRE-SALADO Eduardo J TREVIO-GARZA Oscar A AGUIRRE-CALDERóN Javier JIMNEZ-PREZ Marco A GONZLEZ-TAGLE José R VALDZ-LAZALDE Guillermo SNCHEZ-DíAZ Reija HAAPANEN Alejandro I AGUIRRE-SALADO Liliana MIRANDA-ARAGóN Faculty of Forest Sciences Autonomous University of Nuevo Leon Faculty of Engineering Autonomous University of San Luis Potosi Forestry Program Postgraduate College Haapanen Forest Consulting Faculty of Agronomy and Veterinary Autonomous University of San Luis Potosí

As climate change negotiations progress,monitoring biomass and carbon stocks is becoming an important part of the current forest ***,national governments are interested in developing forest-monitoring strategies using geospatial *** statistical methods for mapping biomass,there is a nonparametric approach called k-nearest neighbor(kNN).We compared four variations of distance metrics of the kNN for the spatially-explicit estimation of aboveground biomass in a portion of the Mexican north border of the intertropical *** derived,climatic,and topographic predictor variables were combined with the Mexican National forest Inventory(NFI)data to accomplish the *** of distance metrics applied into the kNN algorithm was evaluated using a cross validation leave-one-out *** results indicate that the Most Similar Neighbor(MSN)approach maximizes the correlation between predictor and response variables(r=0.9).Our results are in agreement with those reported in the *** findings confirm the predictive potential of the MSN approach for mapping forest variables at pixel level under the policy of Reducing Emission from Deforestation and forest Degradation(REDD+).

关键词： k-nearest neighbor Mahalanobis most similar neighbor MODIS BRDF-adjusted reflectance forest inventory the policy of Reducing Emission from Deforestation and forest Degradation

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Long-lasting effects of unplanned logging on the seed rain of mixed conifer-hardwood forests in southern South America

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Journal of forestry Research 2021年第4期32卷 1409-1418页

作者： Alexandre F.Souza Angela Luciana deÁvila Maristela M.Araújo Solon Jonas Longhi Departament of Ecology CBRio Grande Do Norte Federal UniversityCentral CampusLagoa NovaNatal 59072-970RNBrazil Forest Growth Department Freiburg Im BreisgauBaden-Vurtemberga Forest Research InstituteWonnhaldestraße 4Freiburg im Breisgau 79104Germany Forest Engineering Postgraduate Program Forestry DepartmentSanta Maria Federal UniversityRoraima Av.s/nCamobiSanta Maria 97105-900RSBrazil

Understanding the effects of disturbance on seed rain is critical to predict changes in forest species composition and *** effects on seed rain in a mixed conifer-hardwood forest complex in southern Brazil were *** year of seed rain data were collected from a large-scale observational experiment in logged and protected forests and quantity and average seed size weighted by species abundance(CWM)were compared between old-growth and logged stands 55 years after logging *** these data,variations in frequency of functional groups of species in the seed rain were examined to see if they could be attributed to *** show that the number of seeds per trap was highly right-skewed,ranging from 13 to 12,788 seeds per trap in one *** rain was affected by logging history,with seed traps in old-growth plots receiving significantly less seeds than traps in logged *** species included mean seed size weighted by species abundance were significantly smaller in logged than in old-growth *** difference persisted after the exclusion of Arawcaria a large-seeded pioneer which was intensively logged,although the difference of seed size between the two forest classes was greatly *** abundance in the seed rain differed significantly from the established tree community,between logged and oldgrowth *** composition of the seed rain was much more variable than the composition of the established tree community and its points more scattered over the ordination space than the points corresponding to the protected *** number of collected seeds across different functional groups of species significantly differed between logged and old-growth *** seed rain of logged forests reflects their arrested succes sion as indicated by reduced abundance of functional groups such as pioneers,large seeded pioneers and A raucaria,as well as reduced functional diversity.S eed rain differences between logged and old-

关键词： Arrested succession Brazil Logging Long-lived pioneers Seed rain

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'Marfim pattern’ of wood species in the Southern Brazilian timber market: colorimetry and visible spectra

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Wood Material Science and engineering 2024年第1期20卷

作者： Naide Acosta, Tawani Lorena Vieira, Helena Cristina Xipaia dos Santos, Joielan Silva da Silva, Washington Duarte Stange, Rafaela Souza, Deivison Venicio Cademartori, Pedro Henrique Gonzalez de Muñiz, Graciela Inés Bolzon de Nisgoski, Silvana Postgraduate Program in Forest Engineering Federal University of Parana-UFPR Curitiba Brazil Department of Forest Engineering and Technology Federal University of Parana-UFPR Curitiba Brazil Forest Engineering Faculty Federal University of Pará Pará Brazil

Evaluating wood with similar characteristics is a challenging task. Taking into consideration the need for an efficient and rapid technique, the use of visible spectrophotometry to discriminate wood species is proposed. This study aimed to differentiate nine wood species with a similar yellowish color using visible spectrophotometry, associated with two classification models, to verify predictions. Color data were obtained from different anatomical sections of the wood, along with reflectance spectra in the range of 360–740 nm. Two machine learning approaches were applied: artificial neural network (ANN) and k-nearest neighbors (k-NN). In general, the mean spectra of the samples shared similar information, as they are materials of lignocellulosic origin. However, in all tests, the models built using the ANN algorithm demonstrated an accuracy in discriminating species exceeding 97%. Notably, when applying ANN to the spectra obtained solely from the longitudinal surface, superior results were obtained. Discriminative patterns can be obtained by visible spectra independent of the anatomical section. The integration of visible spectra and ANN proved to be a suitable approach to recognize "marfim pattern" wood. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Machine learning

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Honey production in the south by the Legal Amazon: a study on the potential contamination of mercury in apiaries

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Environmental Science and Pollution Research 2024年第58期31卷 66422-66434页

作者： Solera, Kleber de Freitas, Franciele Lopes, Vinicius José Santos Machado, Gleyce Alves de Andrade, Ricardo Lopes Tortorela Battirola, Leandro Dênis Institute of Natural Human and Social Sciences Postgraduate Program in Biotechnology and Biodiversity-Pró-Centro-Oeste Federal University of Mato Grosso Av. Alexandre Ferronato 1.200 Mato Grosso Sinop78557-267 Brazil University Campus of Sinop Institute of Agricultural and Environmental Sciences Federal University of Mato Grosso Av. Alexandre Ferronato 1.200 Mato Grosso Sinop78557-267 Brazil Institute of Biotechnology Federal University of Catalão Câmpus I: Av. Dr. Lamartine Pinto de Avelar 1.120 Catalão Goiás75704-020 Brazil Department of Forest Engineering Faculty of Forest Engineering Federal University of Mato Grosso Av. Fernando Corrêa da Costa 2.367 Mato Grosso Cuiabá78060-900 Brazil

Artisanal and small-scale gold mining (MAPEOs) are considered to be one of the main sources of mercury release into the environment. Considering the gold mining activities, this study evaluated the Hg concentration in 27 apiaries (Apis spp.) in the South of the Legal Amazon, Mato Grosso State, Brazil. A total of 243 samples distributed in 81 samples of bees, 81 beeswax, and 81 of honeys, collected between the months of July and November 2022, were analyzed. One bee sample showed Hg concentration above the limit of quantification (68.8 ng g−1), 27 samples were between the limit of detection and limit of quantification (15 samples of bees, 8 of wax and 4 of honey). In all study areas, trace levels of Hg concentration were detected, 12 near MAPEOs areas and 16 near crop areas. It recorded that the honeys analyzed in this study in Mato Grosso are not contaminated by Hg, not offering any risk to consumers of the product. It is noteworthy that the use of bioindicator tools such as bees, beeswax, and honey is effective in relation to Hg monitoring in apiaries. It can also infer that the implementation of beekeeping in areas that will go through experience the process of environmental recovery, after the mining exploitation, is feasible, in line with permanent biomonitoring of the region. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Gold mines

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The importance of tropical tree-ring chronologies for global change research

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Quaternary Science Reviews 2025年 355卷

作者： Groenendijk, Peter Babst, Flurin Trouet, Valerie Fan, Ze-Xin Granato-Souza, Daniela Locosselli, Giuliano Maselli Mokria, Mulugeta Panthi, Shankar Pumijumnong, Nathsuda Abiyu, Abrham Acuña-Soto, Rodolfo Adenesky-Filho, Eduardo Alfaro-Sánchez, Raquel Anholetto Junior, Claudio Roberto Aragão, José Roberto Vieira Assis-Pereira, Gabriel Astudillo-Sánchez, Claudia C. Carolina Barbosa, Ana Barreto, Nathan de Oliveira Battipaglia, Giovanna Beeckman, Hans Botosso, Paulo Cesar Bourland, Nils Bräuning, Achim Brienen, Roel Brookhouse, Matthew Buajan, Supaporn Buckley, Brendan M. Camarero, J. Julio Carrillo-Parra, Artemio Ceccantini, Gregório Centeno-Erguera, Librado R. Cerano-Paredes, Julián Cervantes-Martínez, Rosalinda Chanthorn, Wirong Chen, Ya-Jun Cintra, Bruno Barçante Ladvocat Cornejo-Oviedo, Eladio Heriberto Cortés-Cortés, Otoniel Costa, Clayane Matos Couralet, Camille Crispin-DelaCruz, Doris Bianca D'Arrigo, Rosanne David, Diego A. De Ridder, Maaike Del Valle, Jorge Ignacio Díaz-Carrillo, Oscar A. Dobner Jr, Mário Doucet, Jean-Louis Dünisch, Oliver Enquist, Brian J. Esemann-Quadros, Karin Esquivel-Arriaga, Gerardo Fayolle, Adeline Fenilli, Tatiele Anete Bergamo Ferrero, M. Eugenia Fichtler, Esther Finnegan, Patrick M. Fontana, Claudia Francisco, Kainana S. Fu, Pei-Li Galvão, Franklin Gebrekirstos, Aster Giraldo, Jorge A. Gloor, Emanuel Godoy-Veiga, Milena Guerra, Anthony Haneca, Kristof Harley, Grant Logan Heinrich, Ingo Helle, Gerhard Hernández-Díaz, José Ciro Hornink, Bruna Hubau, Wannes Inga, Janet G. Islam, Mahmuda Jiang, Yu-mei Kaib, Mark Hassan Khamisi, Zakia Koprowski, Marcin Layme, Eva Leffler, A. Joshua Ligot, Gauthier Lisi, Claudio Sergio Loader, Neil J. Lobo, Francisco de Almeida Longhi-Santos, Tomaz Lopez, Lidio López-Hernández, María I. Lousada, José Luís Penetra Cerveira Manzanedo, Rubén D. Marcon, Amanda K. Maxwell, Justin T. Mendivelso, Hooz A. Mendoza-Villa, Omar N. Menezes, Ítallo Romany Nunes Montóia, Valdinez Ribeiro Moors, Eddy Moreno, Miyer Muñiz-Castro, Miguel Angel Nabais, Cristina Nathalang, SP Campinas13083-970 Brazil School of Natural Resources and the Environment University of Arizona TucsonAZ United States Laboratory of Tree-Ring Research University of Arizona TucsonAZ United States Belgian Climate Centre Ringlaan 3 Uccle1090 Belgium CAS Key Laboratory of Tropical Forest Ecology Xishuangbanna Tropical Botanical Garden Chinese Academy of Sciences Yunnan Mengla666303 China Natural Resources and Environmental Sciences Department Forestry Ecology and Wildlife Program Alabama A&M University AL United States Department of Botany Institute of Biosciences University of São Paulo R. do Matão 277 São Paulo05508-090 Brazil Center of Nuclear Energy in Agriculture University of São Paulo Av. Centenário 303 13416-000 Brazil Institute of Geography Friedrich-Alexander-University Erlangen-Nuremberg Wetterkreuz 15 Erlangen91058 Germany United Nations Avenue P.O. Box 30677-00100 Nairobi Kenya Faculty of Environment and Resource studies Mahidol University 999 Phutthamonthon Rd4 Salaya Phutthamonthon Nakhon Pathom73170 Thailand C/O ILRI Campus Gurd Shola P.O. Box 5689 Addis Ababa Ethiopia Department of Microbiology and Parasitology Universidad Nacional Autónoma de Mexico Mexico City Mexico Colegio de Geografía Facultad de Filosofia y Letras Universidad Nacional Autónoma de Mexico Mexico City Mexico Department of Forest Engineering Universidade Regional de Blumenau R. São Paulo 3366 Itoupava Seca Santa Catarina 89030-000 Brazil Northern Forestry Centre Canadian Forest Service Natural Resources Canada 5320 122 Street NW EdmontonABT6H 3S5 Canada Department of Biology Wilfrid Laurier University 75 University Avenue W WaterlooONN2L 3C5 Canada Forest Management Program Mamiraua Institute for Sustainable Development Tefé Brazil Av. Mister Hull S/N - PICI Campus CE Fortaleza60440-900 Brazil Department of Forest Sciences Luiz de Queiroz College of Agriculture University of Sao Paulo Av. Pádua Dias 11 SP Piracicaba13418-900

Tropical forests and woodlands are key components of the global carbon and water cycles. Yet, how climate change affects these biogeochemical cycles is poorly understood because of scarce long-term observations of tropical tree growth. The recent rise in tropical tree-ring studies may help to fill this gap, but a large-scale quantitative analysis of their potential in global change research is missing. We compiled a list of all tropical tree species known to form annual tree rings and built a network encompassing 492 tropical ring-width chronologies to evaluate the potential to generate insights on climate sensitivity of woody productivity and to build centuries-long reconstructions of climate variability. We assess chronology quality, length, and climatic representativeness and explore how these change along climatic gradients. Finally, we applied species-distribution modeling to identify regions with potential for tree-ring studies in ecological and climatic studies. The number of tropical chronologies has rapidly increased, with ∼400 added over the past two decades. Yet, tree-ring studies are biased towards high-elevation locations, with gaps in warmer and wetter climates, on the African continent, and for angiosperm species. The longest chronologies with strongest climate signals (i.e., synchronous growth variations among trees) are from cool regions. In wet regions, climate signals and precipitation sensitivity decrease. Most tropical regions harbor 5–15 (and up to 80) species with proven potential to generate chronologies. The potential for long climate reconstructions is particularly high in drier high elevation sites. Our findings support strategies to effectively expand tree-ring research in the tropics, by targeting specific species and regions. Tropical dendrochronology can importantly contribute to global change research by generating historical context of climate extremes, quantifying climate sensitivity of woody productivity and benchmarking vegetation

关键词： Tropical cyclone

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Corrigendum to “Innovative approach in sustainable agriculture: Harnessing microalgae potential via subcritical water extraction” [Environ. Technol. Innov. 36, 103797]

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Environmental Technology & Innovation 2025年 37卷

作者： Alice Ferreira Jelena Vladić Diego de Oliveira Corrêa Valéria Louzada Leal Butzke Pedro L. Martins Belina Ribeiro Cláudia Marques-dos-Santos F. Gabriel Acién Luisa Gouveia LNEG National Laboratory of Energy and Geology I.P. Bioenergy and Biorefineries Unit Estrada do Paço do Lumiar 22 Lisbon 1649-038 Portugal Forest Research Centre Associate Laboratory TERRA School of Agriculture University of Lisbon Tapada da Ajuda Lisboa 1349-017 Portugal NOVA School of Science and Technology NOVA University Lisbon Caparica 2829-516 Portugal Departamento de Bioquímica e Biologia Molecular Universidade Federal do Paraná (UFPR) PO Box 19046 Curitiba Paraná CEP 81531-980 Brazil Postgraduate Program in Environmental Technology University of Santa Cruz do Sul (UNISC) Santa Cruz do Sul Rio Grande do Sul Brazil Chemical Engineering Department University of Almeria Ctra. Sacramento s/n Almería 04120 Spain GreenCoLab Green Ocean Technologies and Products Collaborative Laboratory University of Algarve Campus de Gambelas Faro 8005-139 Portugal

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Estimated flooded rice grain yield and nitrogen content in leaves based on RPAS images and machine learning

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Field Crops Research 2023年第1期292卷

作者： Eugenio, Fernando Coelho Grohs, Mara Schuh, Mateus Venancio, Luan Peroni Schons, Cristine Badin, Tiago Luis Mallmann, Caroline Lorenci Fernandes, Pablo Pereira da Silva, Sally Deborah Fantinel, Roberta Aparecida Federal University of the Jequitinhonha and Mucuri Valleys/UFVJM MG Diamantina 39100-000 Brazil Rice Institute Rio-Grandense (IRGA) RS Cachoeira do Sul 96506-750 Brazil Federal University of Santa Maria – Forest Engineering Postgraduate Program RS Santa Maria Brazil Federal University of Viçosa / Department of Agricultural Engineering MG Viçosa Brazil Geography and Geosciences Department Federal University of Santa Maria Rio Grande do Sul Santa Maria 97105-900 Brazil

Remote sensing based on Remote Piloted Aircraft Systems (RPAS) has proved valuable for monitoring agronomic parameters in precision agriculture. This research aimed to develop predictive models based on machine learning to estimate indirect nitrogen levels (N_area) and grain yield in irrigated rice. During the five phenological stages of cultivation, a Sequoia® camera aboard the Phantom 4® Pro platform acquired the multispectral images. In addition to the spectral bands, 11 vegetation indices were taken as predictors of the response variables (N_area and grain yield). Spearman's correlation coefficient (p) analyzed the ideal monitoring window and selected the model variables. The Multi-Layer Perceptron (MLP) algorithm adjusted the predictive models that had their performance evaluated in training and testing. The results obtained by the Spearman correlation indicate that the ideal window for monitoring rice by RPAS, for both response variables, occurs at the beginning of the reproduction phase (R1). MLP generated a more accurate model for N_area, demonstrated by Pearson's correlation between predicted and observed values (0.82 and 0.71) and mean absolute error (MAE) of 9.47 and 10.89. Grain yield models show good MLP at all stages and excellent accuracy. In this way, our results reinforce the excellent efficiency of the combination of remote sensing via RPAS and machine learning in applications aimed at precision agriculture, serving as a useful tool for managing production and evaluating grain yield in irrigated rice fields. © 2023 Elsevier B.V.

关键词： Phenology Precision agriculture Predictive modeling UAVs

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BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series

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Global Ecology and Biogeography 2025年第5期34卷

作者： Maria Dornelas Laura H. Antão Amanda E. Bates Viviana Brambilla Jonathan M. Chase Cher F. Y. Chow Ada Fontrodona-Eslava Anne E. Magurran Inês S. Martins Faye Moyes Alban Sagouis Samuel Adu-Acheampong Daniel Acquah-Lamptey Dušan Adam Penelope A. Ajani Aitor Albaina Pablo Almaraz Jeongseop An Roger Sigismund Anderson Madelaine Jean Robertson Anderson Alexsander Z. Antunes Ivan Arismendi Linda Armbrecht Pedro Aros-Mardones Sreejith Kalpuzha Ashtamoorthy Narayanan Ayyappan Gal Badihi Joseph J. Bailey Andrew H. Baird Mark Edward Baird Sreekumar Vadakkethil Balakrishnan José António L. Barão-Nóbrega Adi Barash Miguel Barbosa Jos Barlow Claus Bässler Matthieu Beaumont Natalie Beenaerts Tiago Octavio Begot Wallace Beiroz Ricardo Beldade David M. Bell Alecia Bellgrove Jonathan Belmaker Lisandro Benedetti-Cecchi Cassandra E. Benkwitt Pamela Medina-van Berkum Brandon T. Bestelmeyer Matthew G. Betts Maxwell Kelvin Billah Anne D. Bjorkman Magdalena Błażewicz Christopher P. Bloch Shane A. Blowes Antonio Bode Juliano A. Bogoni Thomas Bolger Timothy C. Bonebrake Erik Bonsdorff Roberta Bottarin Luke N. Brokensha Rob W. Brooker Andrew J. Brooks Helge Bruelheide Thiago Almeida Bueno Claire Laguionie Mariana Lopes Campagnoli James Cant Erica Pellegrini Caramaschi Alexandre Caron Tadhg Carroll Tancredi Caruso Juan Carvajal-Quintero Giuseppe Castaldelli Edward Castañeda-Moya Pedro V. Castilho Sonia Zanini Cechin Shahar Chaikin Uchangi Manjunatha Chandrashekara Tory J. Chase Chaolun Allen Chen Jorge José Cherem Sei-Woong Choi Erica M. Christensen Alexander V. Christianini Jackson Wing Four Chu Peter Coad Carl Van Colen Lise Comte Elisabeth J. Cooper J. Hans C. Cornelissen Eddy Cosson Unai Cotano Luc Crevecoeur Shannan Kyle Crow Graeme S. Cumming Vanessa S. Daga Gabriella Damasceno Gergana N. Daskalova Claire H. Davies Robert A. Davis Frank P. Day Sussy De-La-Zerda Amy Elizabeth Deacon Indradatta de Castro-Arrazola Steven Degraer Kharran Deonarinesingh Juan C. Diaz-Ricaurte Christopher R. Dickman Tara Dirilgen Ciaran John Dolan J. Emmet Centre for Biological Diversity School of Biology University of St Andrews Fife UK MARE—Centro de Ciências do Mar e do Ambiente Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Research Centre for Ecological Change Organismal and Evolutionary Biology Research Programme Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Department of Biology University of Victoria Victoria British Columbia Canada German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Leipzig Germany Department of Computer Science Martin Luther University Halle-Wittenberg Halle (Saale) Germany Leverhulme Centre for Anthropocene Biodiversity Department of Biology University of York York UK Department of Animal Biology and Conservation Science University of Ghana Accra Ghana Philipps Universität Marburg Marburg Germany Department of Forest Ecology Silva Tarouca Research Institute Brno Czech Republic School of Life Sciences University of Technology Sydney Sydney New South Wales Australia Zoology and Animal Cell Biology Department University of the Basque Country (UPV/EHU) Leioa Spain Grupo de Oceanografía de Ecosistemas Instituto de Ciencias Marinas de Andalucía CSIC Campus Universitario de Puerto Real Puerto Real Spain National Institute of Ecology Seocheon Republic of Korea African Regional Postgraduate Programme in Insect Science University of Ghana Accra Ghana Département de Biologie Université de Sherbrooke Sherbrooke Quebec Canada Núcleo de Conservação da Biodiversidade Instituto de Pesquisas Ambientais Secretaria de Meio Ambiente Infraestrutura e Logística do Estado de São Paulo São Paulo Brazil Department of Fisheries Wildlife and Conservation Sciences Oregon State University Corvallis Oregon USA Institute for Marine and Antarctic Studies Ecology & Biodiversity Centre University of Tasmania Hobart Tasmania Australia Graduate Program in Oceanography Department of Oceanography Faculty of Natural Scienc

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

关键词： assemblage biodiversity community database ecoinformatics species taxa time

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Fungal diversity notes 253-366:taxonomic and phylogenetic contributions to fungal taxa

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Fungal Diversity 2016年第3期78卷 1-237页

作者： Guo Jie Li Kevin D.Hyde Rui Lin Zhao Sinang Hongsanan Faten Awad Abdel-Aziz Mohamed A.Abdel-Wahab Pablo Alvarado Genivaldo Alves-Silva Joseph F.Ammirati Hiran A.Ariyawansa Abhishek Baghela Ali Hassan Bahkali Michael Beug D.Jayarama Bhat Dimitar Bojantchev Thitiya Boonpratuang Timur S.Bulgakov Erio Camporesi Marcela CBoro Oldriska Ceska Dyutiparna Chakraborty Jia Jia Chen K.W.Thilini Chethana Putarak Chomnunti Giovanni Consiglio Bao Kai Cui Dong Qin Dai Yu Cheng Dai Dinushani A.Daranagama Kanad Das Monika C.Dayarathne Eske De Crop Rafael J.V.De Oliveira Carlos Alberto Fragoso de Souza JoséIde Souza Bryn T.M.Dentinger Asha J.Dissanayake Mingkwan Doilom E.Ricardo Drechsler-Santos Masoomeh Ghobad-Nejhad Sean P.Gilmore Aristóteles Góes-Neto MichałGorczak Charles H.Haitjema Kalani Kanchana Hapuarachchi Akira Hashimoto Mao Qiang He John K.Henske Kazuyuki Hirayama Maria J.Iribarren Subashini C.Jayasiri Ruvishika S.Jayawardena Sun Jeong Jeon Gustavo H.Jerônimo Ana L.Jesus E.B.Gareth Jones Ji Chuan Kang Samantha C.Karunarathna Paul M.Kirk Sirinapa Konta Eric Kuhnert Ewald Langer Haeng Sub Lee Hyang Burm Lee Wen Jing Li Xing Hong Li Kare Liimatainen Diogo Xavier Lima Chuan Gen Lin Jian Kui Liu Xings Zhong Liu Zuo Yi Liu J.Jennifer Luangsa-ard Robert Lücking H.Thorsten Lumbsch Saisamorn Lumyong Eduardo M.Leaño Agostina V.Marano Misato Matsumura Eric H.C.McKenzie Suchada Mongkolsamrit Peter E.Mortimer Thi Thuong Thuong Nguyen Tuula Niskanen Chada Norphanphoun Michelle A.O’Malley Sittiporn Parnmen Julia Pawłowska Rekhani H.Perera Rungtiwa Phookamsak Chayanard Phukhamsakda Carmen L.A.Pires-Zottarelli Olivier Raspé Mateus A.Reck Sarah C.O.Rocha AndréL.C.M.Ade Santiago Indunil C.Senanayake Ledo Setti Qiu Ju Shang Sanjay K.Singh Esteban B.Sir Kevin V.Solomon Jie Song Prasert Srikitikulchai Marc Stadler Satinee Suetrong Hayato Takahashi Takumasa Takahashi Kazuaki Tanaka Li Ping Tang Kasun M.Thambugala Donnaya Thanakitpipattana Michael K.Theodorou Benjarong Thongbai Tuksaporn Thummarukcharoen Qing Tian Saowaluck Tibpromma Annemieke State Key Laboratory of Mycology Institute of MicrobiologyChinese Academy of SciencesNo 31st West Beichen RoadChaoyang DistrictBeijing 100101People’s Republic of China Centre of Excellence in Fungal Research and School of Science Mae Fah Luang UniversityChiang Rai 57100Thailand Key Laboratory for Plant Diversity and Biogeography of East Asia Kunming Institute of BotanyChinese Academy of ScienceKunming 650201YunnanPeople’s Republic of China Department of Botany and Microbiology College of ScienceKing Saud UniversityP.O.Box:2455Riyadh 1145Saudi Arabia Department of Botany and Microbiology Faculty of ScienceSohag UniversitySohag 82524Egypt ALVALAB C/La Rochela nº47E-39012 SantanderSpain Micolab Programa de Pós-Graduação em Biologia de FungosAlgas e PlantasDepartamento de BotânicaUniversidade Federal de Santa CatarinaCampus Universitário TrindadeCEP:88040-900 FlorianópolisSanta CatarinaBrazil Department of Biology University of WashingtonBox 351800SeattleWA 98195-1800USA Guizhou Key Laboratory of Agricultural Biotechnology Guizhou Academy of Agricultural SciencesGuiyang 550006GuizhouPeople’s Republic of China National Fungal Culture Collection of India(NFCCI) Biodiversity and Palaeobiology GroupMACS’Agharkar Research InstituteG.G.Agarkar RoadPune 411004India PO Box 116 HusumWA 98623-0116USA Formerly Department of BotanyGoa UniversityGoaIndia No.128/1-J Azad Housing SocietyCurcaP.O.Goa Velha 403108India *** 345 Shipwatch LaneHerculesCA 94547USA Microbe Interaction Laboratory(BMIT) BIOTECNational Science and Technology Development Agency(NSTDA)113 Thailand Science ParkThanon PhahonyothinTombon Khlong NuengAmphoeKhlong LuangPathum Thani 12120Thailand Academy of Biology and Biotechnology Southern Federal UniversityRostov-on-Don 344090Rostov regionRussia A.M.B.Gruppo Micologico Forlivese BAntonio“Cicognani” Via Roma Forlì Italy 18 A.M.B.Circolo Micologico“Giovanni Carini”C.P.314BresciaItaly Societàper gli Studi Naturalistici della Romagna C.P.144Bagnacavallo

Notes on 113 fungal taxa are compiled in this paper,including 11 new genera,89 new species,one new subspecies,three new combinations and seven reference *** geographic and taxonomic range of fungal taxa are *** the Ascomycota the new genera Angustospora(Testudinaceae),Camporesia(Xylariaceae),Clematidis,Crassiparies(Pleosporales genera incertae sedis),Farasanispora,Longiostiolum(Pleosporales genera incertae sedis),Multilocularia(Parabambusicolaceae),Neophaeocryptopus(Dothideaceae),Parameliola(Pleosporales genera incertae sedis),and Towyspora(Lentitheciaceae)are *** introduced species are Angustospora nilensis,Aniptodera aquibella,Annulohypoxylon albidiscum,Astrocystis thailandica,Camporesia sambuci,Clematidis italica,Colletotrichum menispermi,***,Comoclathris pimpinellae,Crassiparies quadrisporus,Cytospora salicicola,Diatrype thailandica,Dothiorella rhamni,Durotheca macrostroma,Farasanispora avicenniae,Halorosellinia rhizophorae,Humicola koreana,Hypoxylon lilloi,Kirschsteiniothelia tectonae,Lindgomyces okinawaensis,Longiostiolum tectonae,Lophiostoma pseudoarmatisporum,Moelleriella phukhiaoensis,***,Mucoharknessia anthoxanthi,Multilocularia bambusae,Multiseptospora thysanolaenae,Neophaeocryptopus cytisi,Ocellularia arachchigei,***,Ochronectria thailandica,Ophiocordyceps karstii,Parameliola acaciae,***,Parastagonospora cumpignensis,Pseudodidymosphaeria phlei,Polyplosphaeria thailandica,Pseudolachnella brevifusiformis,Psiloglonium macrosporum,Rhabdodiscus albodenticulatus,Rosellinia chiangmaiensis,Saccothecium rubi,Seimatosporium pseudocornii,***,Sigarispora ononidis and Towyspora *** combinations are provided for Eutiarosporella dactylidis(sexual morph described and illus trated)and Pseudocamarosporium ***,illustrations and/or reference specimens are designated for Aposphaeria corallinolutea,Cryptovalsa ampelina,Dothiorella vidmadera,Ophiocordyceps formosana,P

关键词： Ascomycota Basidiomycota Neocallimastigomycota Oomycota.Zygomycota Phylogeny Taxonomy New genus New species

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