# BioTIME: A database of biodiversity time series for the Anthropocene

Maria Dornelas, Andrew Antão, Andrew Moyes, John Bates, Anne Magurran, Dušan Adam, Asem Akhmetzhanova, Ward Appeltans, José Arcos, Andrew Hale, et al.

► To cite this version:

Maria Dornelas, Andrew Antão, Andrew Moyes, John Bates, Anne Magurran, et al. BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography, 2018, 27 (7), pp.760 - 786. 10.1111/geb.12729. hal-01883395

HAL Id: hal-01883395

https://hal.umontpellier.fr/hal-01883395

Submitted on 25 Nov 2019

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<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# BioTIME: A database of biodiversity time series for the Anthropocene

Maria Dornelas¹ ID | Laura H. Antão¹,² ID | Faye Moyes¹ ID | Amanda E. Bates³,⁴ |

Anne E. Magurran¹ ID | Dušan Adam⁵ | Asem A. Akhmetzhanova⁶ |

Ward Appeltans⁷ | José Manuel Arcos⁸ | Haley Arnold¹ | Narayanan Ayyappan⁹ |

Gal Badihi¹ | Andrew H. Baird¹⁰ | Miguel Barbosa¹,² | Tiago Egydio Barreto¹¹ |

Claus Bässler¹² | Alecia Bellgrove¹³ | Jonathan Belmaker¹⁴ |

Lisandro Benedetti-Cecchi¹⁵ | Brian J. Bett³ | Anne D. Bjorkman¹⁶ |

Magdalena Błażewicz¹⁷ | Shane A. Blowes¹⁴,¹⁸ | Christopher P. Bloch¹⁹ |

Timothy C. Bonebrake²⁰ | Susan Boyd¹ | Matt Bradford²¹ | Andrew J. Brooks²² |

James H. Brown²³ | Helge Bruelheide¹⁸,²⁴ | Phaedra Budy²⁵ |

Fernando Carvalho²⁶ | Edward Castañeda-Moya²⁷ | Chaolun Allen Chen²⁸ |

John F. Chamblee²⁹ | Tory J. Chase¹⁰,³⁰ | Laura Siegwart Collier³¹ |

Sharon K. Collinge³² | Richard Condit³³ | Elisabeth J. Cooper³⁴ |

J. Hans C. Cornelissen³⁵ | Unai Cotano³⁶ | Shannan Kyle Crow³⁷ |

Gabriella Damasceno³⁸ | Claire H. Davies³⁹ | Robert A. Davis⁴⁰ | Frank P. Day⁴¹ |

Steven Degraer⁴²,⁴³ | Tim S. Doherty⁴⁰,⁴⁴ | Timothy E. Dunn⁴⁵ |

Giselda Durigan⁴⁶ | J. Emmett Duffy⁴⁷ | Dor Edelist⁴⁸ | Graham J. Edgar⁴⁹ |

Robin Elahi⁵⁰ | Sarah C. Elmendorf³² | Anders Enemar⁵¹ | S. K. Morgan Ernest⁵² |

Rubén Escribano⁵³ | Marc Estiarte⁵⁴,⁵⁵ | Brian S. Evans⁵⁶ | Tung-Yung Fan⁵⁷ |

Fabiano Turini Farah⁵⁸ | Luiz Loureiro Fernandes⁵⁹ | Fábio Z. Farneda⁶⁰,⁶¹,⁶² |

Alessandra Fidelis³⁸ | Robert Fitt⁶³ | Anna Maria Fosaa⁶⁴ |

Geraldo Antonio Daher Correa Franco⁶⁵ | Grace E. Frank³⁰ | William R. Fraser⁶⁶ |

Hernando García⁶⁷ | Roberto Cazzolla Gatti⁶⁸ | Or Givan¹⁴ |

Elizabeth Gorgone-Barbosa³⁸ | William A. Gould⁶⁹ | Corinna Gries⁷⁰ |

Gary D. Grossman⁷¹ | Julio R. Gutierrez⁷²,⁷³,⁷⁴ | Stephen Hale⁷⁵ |

Mark E. Harmon⁷⁶ | John Harte⁷⁷ | Gary Haskins⁷⁸ | Donald L. Henshaw⁷⁹ |

Luise Hermanutz³¹ | Pamela Hidalgo⁵³ | Pedro Higuchi⁸⁰ | Andrew Hoey¹⁰ |

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2018 The Authors. *Global Ecology and Biogeography* Published by John Wiley & Sons Ltd
Gert Van Hoey⁸¹

Annika Hofgaard⁸²

Kristen Holeck⁸³

Robert D. Hollister⁸⁴

Richard Holmes⁸⁵

Mia Hoogenboom¹⁰,³⁰

Chih-hao Hsieh⁸⁶

Stephen P. Hubbell⁸⁷

Falk Huettmann⁸⁸

Christine L. Huffard⁸⁹

Allen H. Hurlbert⁹⁰

Natália Macedo Ivanauskas⁶⁵

David Janík⁵

Ute Jandt¹⁸,²⁴

Anna Jażdżewska¹⁷

Tore Johannessen⁹¹

Jill Johnstone⁹²

Julia Jones⁹³

Faith A. M. Jones¹

Jungwon Kang¹

Tasrif Kartawijaya⁹⁴

Erin C. Keeley

Douglas A. Kelt⁹⁵

Rebecca Kinnear¹,⁹⁶

Kari Klanderud⁹⁷

Halvor Knutsen⁹¹,⁹⁸

Christopher C. Koenig⁹⁹

Alessandra R. Kortz¹

Kamil Král⁵

Linda A. Kuhnz⁸⁹

Chao-Yang Kuo¹⁰

David J. Kushner¹⁰⁰

Claire Laguionie-Marchais¹⁰¹

Lesley T. Lancaster⁶³

Cheol Min Lee¹⁰²

Jonathan S. Lefcheck¹⁰³

Esther Lévesque¹⁰⁴

David Lightfoot¹⁰⁵

Francisco Lloret⁵⁵

John D. Lloyd¹⁰⁶

Adrià López-Baucells⁶⁰,⁶¹,¹⁰⁷

Maite Louzao³⁶

Joshua S. Madin¹⁰⁸,¹⁰⁹

Borgþór Magnússon¹¹⁰

Shahar Malamud¹⁴

Iain Matthews¹

Kent P. McFarland¹⁰⁶

Brian McGill¹¹¹

Diane McKnight¹¹²

William O. McLarney¹¹³

Jason Meador¹¹³

Peter L. Meserve¹¹⁴

Daniel J. Metcalfe²¹

Christoph F. J. Meyer⁶⁰,⁶¹,¹¹⁵

Anders Michelsen¹¹⁶

Nataliya Milchakova¹¹⁷

Tom Moens⁴³

Even Moland⁹¹,⁹⁸

Jon Moore⁹⁶,¹¹⁸

Carolina Mathias Moreira¹¹⁹

Jörg Müller¹²,¹²⁰

Grace Murphy¹²¹

Isla H. Myers-Smith¹²²

Randall W. Myster¹²³

Andrew Naumov¹²⁴

Francis Neat¹²⁵

James A. Nelson¹²⁶

Michael Paul Nelson⁷⁶

Stephen F. Newton¹²⁷

Natalia Norden⁶⁷

Jeffrey C. Oliver¹²⁸

Esben M. Olsen⁹¹,⁹⁸

Vladimir G. Onipchenko⁶

Krzysztof Pabis¹⁷

Robert J. Pabst⁷⁶

Alain Paquette¹²⁹

Sinta Pardede⁹⁴

David M. Paterson¹,⁹⁶

Raphaël Pélissier¹³⁰

Josep Peñuelas⁵⁴,⁵⁵

Alejandro Pérez-Matus¹³¹

Oscar Pizarro¹³²

Francesco Pomati¹³³

Eric Post⁹⁵

Herbert H. T. Prins¹³⁴

John C. Priscu¹³⁵

Pieter Provoost⁷

Kathleen L. Prudic¹³⁶

Erkki Pulliainen

B. R. Ramesh⁹

Olivia Mendivil Ramos¹³⁷

Andrew Rassweiler¹⁰⁰

Jose Eduardo Rebelo¹³⁸

Daniel C. Reed²²

Peter B. Reich¹³⁹,¹⁴⁰

Suzanne M. Remillard⁷⁶

Anthony J. Richardson¹⁴¹,¹⁴²

J. Paul Richardson¹⁴³

Itai van Rijn¹⁴

Ricardo Rocha⁶⁰,⁶¹,¹⁴⁴

Victor H. Rivera-Monroy¹⁴⁵

Christian Rixen¹⁴⁶

Kevin P. Robinson⁷⁸

Ricardo Ribeiro Rodrigues⁵⁸

Denise de Cerqueira Rossa-Feres¹⁴⁷

Lars Rudstam⁸³

Henry Ruhl³

Catalina S. Ruz¹³¹

Erica M. Sampaio⁶¹,¹⁴⁸

Nancy Rybicki¹⁴⁹

Andrew Rypel¹⁵⁰

Sofia Sal¹⁵¹

Beatriz Salgado⁶⁷

Flavio A. M. Santos¹⁵²
Ana Paula Savassi-Coutinho¹⁵³

Sara Scanga¹⁵⁴

Jochen Schmidt³⁷

Robert Schooley¹⁵⁵

Fakhrizal Setiawan⁹⁴

Kwang-Tsao Shao¹⁵⁶

Gaius R. Shaver¹⁵⁷

Sally Sherman¹⁵⁸

Thomas W. Sherry¹⁵⁹

Jacek Siciński<fnref n="17" />

Caya Sievers<fnref n="1" />

Ana Carolina da Silva⁸⁰

Fernando Rodrigues da Silva¹⁶⁰

Fabio L. Silveira¹⁶¹

Jasper Slingsby¹⁶²,¹⁶³

Tracey Smart¹⁶⁴

Sara J. Snell⁹⁰

Nadejda A. Soudzilovskaia¹⁶⁵

Gabriel B. G. Souza¹⁶⁶

Flaviana Maluf Souza¹⁶⁷

Vinícius Castro Souza⁵⁸

Christopher D. Stallings¹⁶⁸

Rowan Stanforth<fnref n="1" />

Emily H. Stanley⁷⁰

José Mauro Sterza¹⁶⁹

Maarten Stevens¹⁷⁰

Rick Stuart-Smith⁴⁹

Yzel Rondon Suarez¹⁷¹

Sarah Supp¹⁷²

Jorge Yoshio Tamashiro¹⁵²

Sukmaraharja Tarigan⁹⁴

Gary P. Thiede²⁵

Simon Thorn¹²⁰

Anne Tolvanen¹⁷³

Maria Teresa Zugliani Toniato¹⁷⁴

Ørjan Totland¹⁷⁵

Robert R. Twilley¹⁴⁵

Gediminas Vaitkus¹⁷⁶

Nelson Valdivia¹⁷⁷

Martha Isabel Vallejo⁶⁷

Thomas J. Valone¹⁷⁸

Carl Van Colen⁴³

Jan Vanaverbeke⁴²

Fabio Venturoli¹⁷⁹

Hans M. Verheye¹⁸⁰,¹⁸¹

Marcelo Vianna¹⁶⁶

Rui P. Vieira<fnref n="3" />

Tomáš Vrška<fnref n="5" />

Con Quang Vu¹⁸²

Lien Van Vu¹⁸³,¹⁸⁴

Robert B. Waide²³

Conor Waldock<fnref n="3" />

Dave Watts³⁹

Sara Webb¹⁸⁵,¹⁸⁶

Tomasz Wesołowski¹⁸⁷

Ethan P. White¹⁸⁸,¹⁸⁹

Claire E. Widdicombe¹⁹⁰

Dustin Wilgers¹⁹¹

Richard Williams¹⁹²

Stefan B. Williams¹³²

Mark Williamson¹⁹³

Michael R. Willig¹⁹⁴

Trevor J. Willis¹⁹⁵

Sonja Wipf¹⁹⁶

Kerry D. Woods¹⁹⁷

Eric J. Woehler⁴⁹

<figure><img src="image_2.png" /></figure>

Kyle Zawada<fnref n="1" />,¹⁰⁹

Michael L. Zettler¹⁹⁸

<figure><img src="image_3.png" /></figure>

<footnote n="1">¹Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. Andrews, St Andrews, United Kingdom</footnote>

<footnote n="2">²Department of Biology and CESAM, Universidade de Aveiro, Campus Universitário de Santiago, Aveiro, Portugal</footnote>

<footnote n="3">³National Oceanography Centre, University of Southampton Waterfront Campus, Southampton, United Kingdom</footnote>

<footnote n="4">⁴Department of Ocean Sciences, Memorial University of Newfoundland, St John's, Newfoundland and Labrador, Canada</footnote>

<footnote n="5">⁵Department of Forest Ecology, Silva Tarouca Research Institute, Brno, Czech Republic</footnote>

<footnote n="6">⁶Department of Geobotany, Faculty of Biology, Moscow State University, Moscow, Russia</footnote>

<footnote n="7">⁷UNESCO, Intergovernmental Oceanographic Commission, IOC Project Office for IODE, Oostende, Belgium</footnote>

<footnote n="8">⁸SEO/BirdLife, Marine Programme, Barcelona, Spain</footnote>

<footnote n="9">⁹Department of Ecology, French Institute of Pondicherry, Puducherry, India</footnote>

<footnote n="10">¹⁰ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland, Australia</footnote>

<footnote n="11">¹¹Laboratório de Ecologia e Restauração Florestal, Fundação Espaço Eco, Piracicaba, São Paulo, Brazil</footnote>

<footnote n="12">¹²Bavarian Forest National Park, Grafenau, Germany</footnote>

<footnote n="13">¹³School of Life and Environmental Sciences, Centre for Integrative Ecology, Deakin University, Warrnambool, Victoria, Australia</footnote>

<footnote n="14">¹⁴School of Zoology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel</footnote>

<footnote n="15">¹⁵Department of Biology, University of Pisa, Pisa, CoNISMa, Italy</footnote>

<footnote n="16">¹⁶Section for Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University, Aarhus, Denmark</footnote>

<footnote n="17">¹⁷Laboratory of Polar Biology and Oceanobiology, Faculty of Biology and Environmental Protection, University of Łódź, Łódź, Poland</footnote>

<footnote n="18">¹⁸German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany</footnote>

<footnote n="19">¹⁹Department of Biological Sciences, Bridgewater State University, Bridgewater, Massachusetts</footnote>
<sup>20</sup>School of Biological Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong

<sup>21</sup>CSIRO Land & Water, Ecosciences Precinct, Dutton Park, Queensland, Australia

<sup>22</sup>Marine Science Institute, University of California, Santa Barbara, California

<sup>23</sup>Department of Biology, University of New Mexico, Albuquerque, New Mexico

<sup>24</sup>Institute of Biology/Geobotany and Botanical Garden, Martin-Luther-University Halle-Wittenberg, Halle, Germany

<sup>25</sup>Department of Watershed Sciences and the Ecology Center, US Geological Survey, UCFWRU and Utah State University, Logan, Utah

<sup>26</sup>Universidade do Extremo Sul Catarinense (PPG-CA), Criciúma, Santa Catarina, Brazil

<sup>27</sup>Southeast Environmental Research Center (OE 148), Florida International University, Miami, Florida

<sup>28</sup>Coral Reef Ecology and Evolution Lab, Biodiversity Research Centre, Academia Sinica, Taipei, Taiwan

<sup>29</sup>Anthropology, University of Georgia, Athens, Georgia

<sup>30</sup>Marine Biology and Aquaculture, College of Science and Engineering, James Cook University, Douglas, Queensland, Australia

<sup>31</sup>Memorial University, St John's, Newfoundland and Labrador, Canada

<sup>32</sup>Environmental Studies Program, University of Colorado-Boulder

<sup>33</sup>Center for Tropical Forest Science, Washington, District of Columbia

<sup>34</sup>Biosciences Fisheries and Economics, UiT- The Arctic University of Norway, Tromsø, Norway

<sup>35</sup>Systems Ecology, Department of Ecological Science, Vrije Universiteit, Amsterdam, The Netherlands

<sup>36</sup>AZTI Fundazioa, Herrera Kaia, Pasaia, Spain

<sup>37</sup>The National Institute of Water and Atmospheric Research, Auckland, New Zealand

<sup>38</sup>Lab of Vegetation Ecology, Instituto de Biociências, Universidade Estadual Paulista (UNESP), Rio Claro, Brazil

<sup>39</sup>CSIRO Oceans and Atmosphere Flagship, Hobart, Tasmania, Australia

<sup>40</sup>School of Science, Edith Cowan University, Joondalup, Western Australia, Australia

<sup>41</sup>Department of Biological Sciences, Old Dominion University, Norfolk, Virginia

<sup>42</sup>Royal Belgian Institute of Natural Sciences, Operational Directorate Natural Environment, Marine Ecology and Management, Brussels, Belgium

<sup>43</sup>Marine Biology Research Group, Ghent University, Gent, Belgium

<sup>44</sup>School of Life and Environmental Sciences, Centre for Integrative Ecology (Burwood Campus), Deakin University, Geelong, Victoria, Australia

<sup>45</sup>Joint Nature Conservation Committee, Aberdeen, United Kingdom

<sup>46</sup>Divisão de Florestas e Estações Experimentais, Floresta Estadual de Assis, Laboratório de Ecologia e Hidrologia Florestal, Instituto Florestal, São Paulo, Brazil

<sup>47</sup>Tennenbaum Marine Observatories Network, Smithsonian Institution, Washington, District of Columbia

<sup>48</sup>National Institute of Oceanography, Tel-Shikmona, Haifa, Israel

<sup>49</sup>Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia

<sup>50</sup>Hopkins Marine Station, Stanford University, Stanford, California

<sup>51</sup>Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden

<sup>52</sup>Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL

<sup>53</sup>Instituto Milenio de Oceanografía, Universidad de Concepción, Concepción, Chile

<sup>54</sup>CSIC, Global Ecology Unit CREAF-CSIC-UAB, Bellaterra, Catalonia, Spain

<sup>55</sup>CREAF, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Catalonia, Spain

<sup>56</sup>Migratory Bird Center, Smithsonian Conservation Biology Institute, National Zoological Park, Washington, District of Columbia

<sup>57</sup>National Museum of Marine Biology and Aquarium, Pingtung County, Taiwan

<sup>58</sup>Laboratório de Ecologia e Restauração Florestal, Escola Superior de Agricultura "Luiz de Queiroz", Universidade de São Paulo, São Paulo, Brazil

<sup>59</sup>Departamento de Oceanografia e Ecologia, Universidade Federal do Espírito Santo, Vitória, Espírito Santo, Brazil

<sup>60</sup>Centre for Ecology, Evolution and Environmental Changes – cE3c, Faculty of Sciences, University of Lisbon, Lisbon, Portugal

<sup>61</sup>Biological Dynamics of Forest Fragments Project, National Institute for Amazonian Research and Smithsonian Tropical Research Institute, Manaus, Brazil

<sup>62</sup>Department of Ecology/PPGE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

<sup>63</sup>School of Biological Sciences, University of Aberdeen, Aberdeen, United Kingdom

<sup>64</sup>Botanical Department, Faroese Museum of Natural History, Torshavn, Faroe Islands

<sup>65</sup>Instituto Florestal, Seção de Ecologia Florestal, São Paulo, Brazil

<sup>66</sup>Polar Oceans Research Group, Sheridan, Montana

<sup>67</sup>Alexander von Humboldt Biological Resources Research Institute, Bogotá DC, Colombia

<sup>68</sup>Department of Biology, Tomsk State University, Tomsk, Russia
⁶⁹USDA Forest Service, 65 USDA Forest Service, International Institute of Tropical Forestry, San Juan, Puerto Rico

⁷⁰Center for Limnology, University of Wisconsin, Madison, Wisconsin

⁷¹The Warnell School of Forestry and Natural Resources, University of Georgia, Athens, Georgia

⁷²Departamento de Biología, Facultad de Ciencias, Universidad de La Serena, La Serena, Chile

⁷³Centro de Estudios Avanzados en Zonas Aridas (CEAZA), La Serena, Chile

⁷⁴Institute of Ecology and Biodiversity (IEB), Santiago, Chile

⁷⁵U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Atlantic Ecology Division, Narragansett, Rhode Island

⁷⁶Department of Forest Ecosystems and Society, Oregon State University, Corvallis, Oregon

⁷⁷The Energy and Resources Group and The Department of Environmental Science, Policy and Management, University of California, Berkeley, California

⁷⁸Cetacean Research & Rescue Unit, Banff, United Kingdom

⁷⁹U.S. Forest Service Pacific Northwest Research Laboratory, Corvallis, Oregon

⁸⁰Laboratório de Dendrologia e Fitossociologia, Universidade do Estado de Santa Catarina, Florianópolis, Santa Catarina, Brazil

⁸¹Department of Aquatic Environment and Quality, Flanders Research Institute for Agriculture, Fisheries and Food, Oostende, Belgium

⁸²Norwegian Institute for Nature Research, Trondheim, Norway

⁸³Department of Natural Resources and Cornell Biological Field Station, Cornell University, Ithaca, New York

⁸⁴Biology Department, Grand Valley State University, Allendale, Michigan

⁸⁵Dartmouth College, Hanover, New Hampshire

⁸⁶Institute of Oceanography, National Taiwan University, Taipei, Taiwan

⁸⁷University of California, Los Angeles, Los Angeles, California

⁸⁸EWHALE lab- Biology and Wildlife Department, Institute of Arctic Biology, University of Alaska, Fairbanks, Alaska

⁸⁹Monterey Bay Aquarium Research Institute, Moss Landing, California

⁹⁰Department of Biology, University of North Carolina, Chapel Hill, North Carolina

⁹¹Institute of Marine Research, His, Norway

⁹²Department of Biology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada

⁹³College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, Oregon

⁹⁴Wildlife Conservation Society Indonesia Program, Bogor, Indonesia

⁹⁵Department of Wildlife, Fish, and Conservation Biology, University of California, Davis, California

⁹⁶Shetland Oil Terminal Environmental Advisory Group (SOTEAG), St Andrews, United Kingdom

⁹⁷Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway

⁹⁸Department of Natural Sciences, Faculty of Engineering and Science, Centre for Coastal Research, University of Agder, Kristiansand, Norway

⁹⁹Florida State University Coastal and Marine Laboratory, St Teresa, Florida

¹⁰⁰Channel Islands National Park, U. S. National Park Service, California, Ventura, California

¹⁰¹Zoology, Ryan Institute, School of Natural Sciences, NUI Galway, Galway, Ireland

¹⁰²Forest and Climate Change Adaptation Laboratory, Center for Forest and Climate Change, National Institute of Forest Science, Seoul, Republic of Korea

¹⁰³Department of Biological Sciences, Virginia Institute of Marine Science, The College of William & Mary, Gloucester Point, Virginia

¹⁰⁴Département des sciences de l'environnement, Université du Québec à Trois-Rivières and Centre d'études nordiques, Québec, Canada

¹⁰⁵Department of Biology, Museum of Southwestern Biology, University of New Mexico, Albuquerque, New Mexico

¹⁰⁶Vermont Center for Ecostudies, Hartford, Vermont, USA

¹⁰⁷Museu de Ciències Naturals de Granollers, Catalunya, Spain

¹⁰⁸Hawai'i Institute of Marine Biology, University of Hawai'i at Mānoa, Kaneohe, Hawai'i, USA

¹⁰⁹Department of Biological Sciences, Macquarie University, Sydney, New South Wales, Australia

¹¹⁰Icelandic Institute of Natural History, Garðabær, Iceland

¹¹¹School of Biology and Ecology, Sustainability Solutions Initiative, University of Maine, Orono, Maine

¹¹²INSTAAR, University of Colorado, Boulder, Colorado

¹¹³Stream Biomonitoring Program, Mainspring Conservation Trust, Franklin, North Carolina

¹¹⁴Department of Biological Sciences, University of Idaho, Moscow, Idaho

¹¹⁵Ecosystems and Environment Research Centre (EERC), School of Environment and Life Sciences, University of Salford, Salford, United Kingdom

¹¹⁶Terrestrial Ecology Section, Department of Biology, University of Copenhagen, Copenhagen, Denmark
¹¹⁷Laboratory of Phytoresources, Kovalevsky Institute of Marine Biological Research of RAS (IMBR), Sevastopol, Russia

¹¹⁸Aquatic Survey & Monitoring Ltd. ASML, Durham, United Kingdom

¹¹⁹Ceiba Consultoria Ambiental, Bragança Paulista, Brazil

¹²⁰Field Station Fabrikschleichach, University of Würzburg, Rauhenebrach, Germany

¹²¹Department of Biology, Dalhousie University, Halifax, Nova Scotia, Canada

¹²²School of Geosciences, University of Edinburgh, Edinburgh, United Kingdom

¹²³Biology Department, Oklahoma State University, Oklahoma City, Oklahoma

¹²⁴Zoological Institute, Russian Academy Sciences, St Petersburg, Russia

¹²⁵Marine Scotland, Marine Laboratory, Scottish Government, Edinburgh, United Kingdom

¹²⁶Department of Biology, University of Louisiana at Lafayette, Lafayette, Louisiana

¹²⁷BirdWatch Ireland, Kilcoole, Wicklow, Ireland

¹²⁸University of Arizona Health Sciences Library, University of Arizona, Tucson, Arizona

¹²⁹Center for Forest Research, Université du Québec à Montréal (UQAM), Montreal, Quebec, Canada

¹³⁰UMR AMAP, IRD, CIRAD, CNRS, INRA, Montpellier University, Montpellier, France

¹³¹Subtidal Ecology Laboratory & Center for Marine Conservation, Estación Costera de Investigaciones Marinas, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago, Casilla, Chile

¹³²Australian Centre of Field Robotics, University of Sydney, Sydney, New South Wales, Australia

¹³³Department of Aquatic Ecology, Eawag: Swiss Federal Institute of Aquatic Science and Technology, Switzerland

¹³⁴Resource Ecology Group, Wageningen University, Wageningen, The Netherlands

¹³⁵Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, Montana

¹³⁶Entomology, University of Arizona, Tucson, Arizona

¹³⁷Cold Spring Harbor Laboratory, Cold Spring Harbor, New York

¹³⁸Ichthyology Laboratory, Fisheries and Aquaculture, University of Aveiro, Aveiro, Portugal

¹³⁹Department of Forest Resources, University of Minnesota, St Paul, Minnesota

¹⁴⁰Hawkesbury Institute for the Environment, Western Sydney University, Penrith, New South Wales, Australia

¹⁴¹CSIRO Oceans and Atmosphere, Queensland, BioSciences Precinct (QBP), St Lucia, Brisbane, Qld, Australia

¹⁴²Centre for Applications in Natural Resource Mathematics, The University of Queensland, St Lucia, Queensland, Australia

¹⁴³Virginia Institute of Marine Science, Gloucester Point, Virginia

¹⁴⁴Metapopulation Research Centre, Faculty of Biosciences, University of Helsinki, Helsinki, Finland

¹⁴⁵Department of Oceanography and Coastal Sciences, College of the Coast and Environment, Louisiana State University, Baton Rouge, Louisiana

¹⁴⁶Swiss Federal Institute for Forest, Snow and Landscape Research, Davos Dorf, Switzerland

¹⁴⁷Departamento de Zoologia e Botânica, Universidade Estadual Paulista - UNESP, Campus São José do Rio Preto, São José do Rio Preto, Brazil

¹⁴⁸Department of Animal Physiology, Eberhard Karls University Tübingen, Tübingen, Germany

¹⁴⁹National Research Program, U.S. Geological Survey, Reston, Virginia

¹⁵⁰Wisconsin Department of Natural Resources and Center for Limnology, University of Wisconsin-Madison, Madison, Wisconsin

¹⁵¹Department of Life Sciences, Imperial College London, Ascot, Berkshire, United Kingdom

¹⁵²Departamento de Biologia Vegetal, UNICAMP, Campinas, Brazil

¹⁵³Departamento de Ciências Biológicas, Escola Superior de Agricultura 'Luiz de Queiroz', Universidade de São Paulo, São Paulo, Brazil

¹⁵⁴Department of Biology, Utica College, Utica, New York

¹⁵⁵Wildlife Ecology and Conservation, Department of Natural Resources and Environmental Sciences, University of Illinois, Champaign, Illinois

¹⁵⁶Biodiversity Research Center, Academia Sinica, Nankang, Taipei, Taiwan

¹⁵⁷Marine Biological Laboratory, Woods Hole, Massachusetts, USA

¹⁵⁸Maine Department of Marine Resources, Bangor, Maine

¹⁵⁹Tulane University, New Orleans, Louisiana

¹⁶⁰Environmental Sciences Department, Federal University of São Carlos, Sorocaba, Brazil

¹⁶¹USP/WSAOBIS, São Paulo, Brazil

¹⁶²Department of Biological Sciences, Centre for Statistics in Ecology, Environment and Conservation, University of Cape Town, Rondebosch, South Africa

¹⁶³Fynbos Node, South African Environmental Observation Network, Claremont, South Africa

¹⁶⁴Coastal Finfish Section, South Carolina Department of Natural Resources, Marine Resources Research Institute, Charleston, South Carolina
¹⁶⁵Conservation Biology Department, Institute of Environmental Studies, CML, Leiden University, Leiden, The Netherlands

¹⁶⁶Laboratório de Biologia e Tecnologia Pesqueira, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil

¹⁶⁷Instituto Florestal, Seção de Ecologia Florestal, São Paulo, Brazil

¹⁶⁸College of Marine Science, University of South Florida, St. Petersburg, Florida

¹⁶⁹Ethica Ambiental, Vila Velha, Brazil

¹⁷⁰INBO, Research Institute for Nature and Forest, Brussels, Belgium

¹⁷¹Centro de Estudos em Recursos Naturais, Universidade Estadual de Mato Grosso do Sul, Dourados, Mato Grosso do Sul, Brazil

¹⁷²School of Biology and Ecology, University of Maine, Orono, Maine

¹⁷³Natural Resources Institute Finland, University of Oulu, Oulu, Finland

¹⁷⁴Instituto Florestal, Divisão de Florestas e Estações Experimentais, Estação Experimental de Bauru, Bauru, Brazil

¹⁷⁵Department of Biology, University of Bergen, Bergen, Norway

¹⁷⁶GEOMATRIX UAB, Kaunas, Lithuania

¹⁷⁷Universidad Austral de Chile and Centro FONDAP en Dinámica de Ecosistemas Marinos de Altas Latitudes (IDEAL), Valdivia, Chile

¹⁷⁸Department of Biology, Saint Louis University, Saint Louis, Missouri

¹⁷⁹Escola de Agronomia, Universidade Federal de Goiás, Goiânia, Brazil

¹⁸⁰Department of Environmental Affairs, Oceans and Coastal Research, Cape Town, South Africa

¹⁸¹Department of Biological Sciences, Marine Research Institute, University of Cape Town, Cape Town, South Africa

¹⁸²Institute of Ecology and Biological Resources, VAST, Hanoi, Vietnam

¹⁸³Vietnam National Museum of Nature, Hanoi, Vietnam

¹⁸⁴Graduate University of Science and Technology, VAST, Hanoi, Vietnam

¹⁸⁵Biology Department, Drew University, Madison, New Jersey

¹⁸⁶Environmental Studies Department, Drew University, Madison, New Jersey

¹⁸⁷Laboratory of Forest Biology, Wrocław University, Wrocław, Poland

¹⁸⁸Department of Wildlife Ecology & Conservation, University of Florida, Gainesville, Florida

¹⁸⁹Informatics Institute, University of Florida, Gainesville, Florida

¹⁹⁰Plymouth Marine Laboratory, Plymouth, United Kingdom

¹⁹¹Department of Natural Sciences, McPherson College, McPherson, Kansas

¹⁹²Australian Antarctic Division, Channel Highway, Kingston, Tasmania, Australia

¹⁹³Department of Biology, University of York, York, United Kingdom

¹⁹⁴Department of Ecology & Evolutionary Biology, Center for Environmental Sciences & Engineering, University of Connecticut, Mansfield, Connecticut

¹⁹⁵Institute of Marine Sciences, School of Biological Sciences, University of Portsmouth, Portsmouth, United Kingdom

¹⁹⁶Research Team Mountain Ecosystems, WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland

¹⁹⁷Natural Sciences, Bennington College, Bennington, Vermont

¹⁹⁸Leibniz Institute for Baltic Sea Research Warnemünde, Seestr. 15, D-18119 Rostock, Germany

### Correspondence

Maria Dornelas, Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St Andrews, St Andrews, United Kingdom.
Email: biotimeproj@st-andrews.ac.uk

### Funding information

European Research Council and EU, Grant/ Award Number: AdG-250189, PoC-727440 and ERC-SyG-2013-610028; Natural Envi- ronmental Research Council, Grant/Award Number: NE/L002531/1; National Science Foundation, Grant/Award Number: DEB- 1237733, DEB-1456729, 9714103, 0632263, 0856516, 1432277, DEB- 9705814, BSR-8811902, DEB 9411973, DEB 0080538, DEB 0218039, DEB 0620910, DEB 0963447, DEB-1546686, DEB-129764, OCE 95-21184, OCE-

### Abstract

**Motivation:** The BioTIME database contains raw data on species identities and abundances in eco- logical assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.

**Main types of variables included:** The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.
0099226, OCE 03-52343, OCE-0623874, OCE-1031061, OCE-1336206 and DEB-1354563; National Science Foundation (LTER), Grant/Award Number: DEB-1235828, DEB-1440297, DBI-0620409, DEB-9910514, DEB-1237517, OCE-0417412, OCE-1026851, OCE-1236905, OCE-1637396, DEB 1440409, DEB-0832652, DEB-0936498, DEB-0620652, DEB-1234162 and DEB-0823293; Fundação para a Ciência e Tecnologia, Grant/Award Number: POPH/FSE SFRH/BD/90469/2012, SFRH/BD/84030/2012, PTDC/BIA-BIC/111184/2009; SFRH/BD/80488/2011 and PD/BD/52597/2014; Ciência sem Fronteiras/CAPES, Grant/Award Number: 1091/13-1; Instituto Milenio de Oceanografia, Grant/Award Number: IC120019; ARC Centre of Excellence, Grant/Award Number: CE0561432; NSERC Canada; CONICYT/FONDECYT, Grant/Award Number: 1160026, ICM PO5-002, CONICYT/FONDECYT, 11110351, 1151094, 1070808 and 1130511; RSF, Grant/Award Number: 14-50-00029; Gordon and Betty Moore Foundation, Grant/Award Number: GBMF4563; Catalan Government; Marie Curie Individual Fellowship, Grant/Award Number: QLK5-CT2002-51518 and MERG-CT-2004-022065; CNPq, Grant/Award Number: 306170/2015-9, 475434/2010-2, 403809/2012-6 and 561897/2010; FAPESP (São Paulo Research Foundation), Grant/Award Number: 2015/10714-6, 2015/06743-0, 2008/10049-9, 2013/50714-0 and 1999/09635-0 e 2013/50718-5; EU CLIMOOR, Grant/Award Number: ENV4-CT97-0694; VULCAN, Grant/Award Number: EVK2-CT-2000-00094; Spanish, Grant/Award Number: REN2000-0278/CCI, REN2001-003/GLO and CGL2016-79835-P; Catalan, Grant/Award Number: AGAUR SGR-2014-453 and SGR-2017-1005; DFG, Grant/Award Number: 120/10-2; Polar Continental Shelf Program; CENPES - PETROBRAS; FAPERJ, Grant/Award Number: E-26/110.114/2013; German Academic Exchange Service; sDiv; iDiv; New Zealand Department of Conservation; Wellcome Trust, Grant/Award Number: 105621/Z/14/Z; Smithsonian Atherton Seidell Fund; Botanic Gardens and Parks Authority; Research Council of Norway; Conselleria de Innovació, Hisenda i Economia; Yukon Government Herschel Island-Qikiqtaruk Territorial Park; UK Natural Environment Research Council ShrubTundra Grant, Grant/Award Number: NE/M016323/1; IPY; Memorial University; ArcticNet. DOI: 10.13039/50110000027. Netherlands Organization for Scientific Research in the Tropics NWO, grant W84-194. Ciências sem Fronteiras and Coordenação de Pessoal de Nível Superior (CAPES, Brazil), Grant/Award Number: 1091/13-1. National Science foundation (LTER), Award Number: OCE-9982105, OCE-0620276, OCE-1232779.

**Spatial location and grain:** BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km² (158 cm²) to 100 km² (1,000,000,000,000 cm²).

**Time period and grain:** BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.

**Major taxa and level of measurement:** BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.

**Software format:** .csv and .SQL.

### KEYWORDS

biodiversity, global, spatial, species richness, temporal, turnover
FCT - SFRH / BPD / 82259 / 2011. U.S.
Fish and Wildlife Service/State Wildlife
federal grant number T-15. Australian
Research Council Centre of Excellence for
Coral Reef Studies (CE140100020). Austra-
lian Research Council Future Fellowship
FT110100609. M.B., A.J., K.P., J.S. received
financial support from internal funds of
University of Lódź. NSF DEB 1353139.
Catalan Government fellowships (DURSI):
1998FI-00596, 2001BEAI200208, MECD
Post-doctoral fellowship EX2002-0022.
National Science Foundation Award OPP-
1440435. FONDECYT 1141037 and FON-
DAP 15150003 (IDEAL). CNPq Grant
306595-2014-1

Editor: Thomas Hickler

1 | BACKGROUND

Quantifying changes in biodiversity in the Anthropocene is a key chal-
lenge of our time given the paucity of temporal and spatial data for most
taxa on Earth. The nature and extent of the reorganization of natural
assemblages are currently controversial because conflicting estimates of
biodiversity change have been obtained using different methodological
approaches and for different regions, time periods and taxa. Some reports
suggest alarming and systematic biodiversity loss. For example, estimates
of global extinction rates place global losses orders of magnitude above
background rates (Pereira, Navarro, & Martins, 2012). In addition, esti-
mates of population trends for vertebrates suggest average declines of
the order of 60% in the past 30 years (Collen et al., 2009). Nonetheless,
analyses based on spatial variation yield more modest declines in the
range of 8% (Newbold et al., 2015). In contrast, some analyses of assem-
blage time series consistently detect no systematic trend in temporal
α-diversity (such as species richness), on average, across local commun-
ities (Brown, Ernest, Parody, & Haskell, 2001; Dornelas et al., 2014; Vel-
lend et al., 2013, 2016), but instead uncover substantial variation in
composition (temporal β-diversity; i.e., temporal turnover), including both
losses and gains of species (Dornelas et al., 2014; Magurran, Dornelas,
Moyes, Gotelli, & McGill, 2015). Spatially structured gains and losses are
also predicted from climate change projections (García Molinos et al.,
2016). Some of these discrepancies are a result of differences in the tem-
poral and spatial scales at which analyses were performed (McGill, Dorne-
las, Gotelli, & Magurran, 2014), whereas other differences may be
attributable to the organizational level on which an analysis is focused
(e.g., population vs. community). Clearly, more research is needed into
how populations, communities and ecosystems are changing in the face
of widespread human influence on the planet (Waters et al., 2016). Here,
we introduce BioTIME, a curated database of biodiversity time series,
with the goal of facilitating and promoting research in this area.

Biodiversity is a multifaceted concept, which can be measured in many
different ways. Similar to the approach of essential biodiversity variables
(Pereira et al., 2013), we focus on assembling data that maximize the num-
ber of metrics that can be calculated. Specifically, BioTIME is composed of
species abundance records for assemblages that have been sampled
through time with a consistent methodology. The focus on assemblages

differentiates BioTIME from population databases, such as the Global Pop-
ulation Dynamics Database (https://www.imperial.ac.uk/cpb/gpdd2/
secure/login.aspx) and the Living Planet Index database (http://www.living-
planetindex.org/home/index), and enables users to quantify patterns at dif-
ferent organizational levels, including both the assemblage and the
population level. BioTIME complements the PREDICTS database (http://
www Predicts.org.uk/) in providing time series rather than space for time
comparisons. Moreover, most previous databases have been either terres-
trial (e.g., vertebrates, GPDD; vegetation, sPlot; multiple taxa, PREDICTS)
or marine (e.g., OBIS), whereas BioTIME includes marine, freshwater and
terrestrial realms; hence, it facilitates comparisons across realms. Finally,
previous databases are not specifically focused on temporal assemblage
data, which means that BioTIME fills an important gap in allowing spatial
and temporal comparisons. In addition, coupling BioTIME with additional
information will allow analyses of temporal change in phylogenetic diversity
and trait diversity alongside taxonomic diversity.

The goals of the BioTIME database are as follows: (a) to assemble and format raw species abundance data for assemblages consistently sampled through time; (b) to encourage re-use of these data through open-source access of standardized and curated versions of the data; and (c) to promote appropriate crediting of data sources. These goals are in line with best practice in promoting maximal use of ecological data (Costello et al., 2014; White et al., 2013) and highlight data gaps to funding agencies. In addition, we hope that BioTIME will engage ecologists in the collection, standardization, sharing and quality control of assemblage-level species abundance data, particularly in poorly sampled parts of the world, and highlight the value of such data to funding agencies.

2 | METHODS

The BioTIME database is composed of 11 tables: a main table contain-
ing the core observations (records), and 10 tables that provide contex-
tual information as described below and in Supporting Information
Figure S1. There are five main levels of organization: record, sample,
plot, site and study. A record is our fundamental unit of observation of
the abundance of a species in a sample. A sample includes all the
records that belong to the same sampling event; for example, a quadrat
on the seashore, a single plankton tow or a bird transect. A sample is
defined by a single location and a single date. If the exact location has
been repeatedly sampled through time, then all the samples that corre-
spond to that location belong to the same plot. Multiple samples and
plots can be located in the same area, which we term a site. Finally, the
highest observational unit is a study, which is defined by having a regu-
lar and consistent sampling methodology. Sources of data in which the
sampling methodology changed during the course of the study were
classified as separate studies. Every organizational level has contextual
variables that are kept either in dedicated tables or are part of the main
table (see Supporting Information Figure S1 for a complete list of the
fields in each table). In addition, the database also includes tables with
information relating to the sampling methodology, and treatments
associated with some samples when applicable, citation information,
contacts and licenses for each study, and the curation steps performed
on each study before it was entered in the database.

## 2.1 | Data acquisition

Searches began in 2010, and data were acquired from a variety of sources: literature searches, large databases [specifically, OBIS (www.iobis.org/), GBIF (www.gbif.org/) and Ecological Data Wiki (https://ecological-data.org/)], through personal networking and through broadcasted data requests at conferences and on social media. We have used four main criteria for data inclusion on BioTIME: (a) abundance observations come from samples of assemblages where all individuals within the sample were counted and identified (i.e., assemblage rather than population data); (b) most of the individuals were identified to species; (c) sampling methods were constant through time; and (d) the time series spans a minimum of 2 years. The last condition was changed relative to the initial criteria because it became apparent that it would allow better spatial representation given the many locations that have been surveyed historically and then resurveyed. Each study is kept separate within the database and has a specific license from the CC spectrum, whose terms must be observed (https://creativecommons.org/). A static version of the database is released with this publication (http://biotime.st-andrews.ac.uk and https://zenodo.org/record/1095627). However, data entry and curation is ongoing (http://biotime.st-andrews.ac.uk/contribute.php), and we expect the database to keep growing in the foreseeable future. We plan to release static updates of the database periodically.

## 2.2 | Data curation and quality control

Before inclusion in the database, data were subjected to standardiza-
tion in a curation process described specifically for each study in the
curation table of the database. Specifically, these were checked for
the presence of the following: duplicates within each study and against
the entire database; species with zero abundance; and non-organismal
records, all of which were removed. Abundances of zero for a particular
population can be inferred from their absence from samples in the
study. Additionally, species names were checked for typographic errors
and misspellings, and a standardized notation was used for records of
morphospecies and species complexes. Most records were included as
provided and may not always conform to the latest nomenclature. Fur-
thermore, latitudes and longitudes were checked for their location

relative to other descriptors (e.g., country or marine vs. terrestrial).
Finally, the grain and extent of each study were calculated from infor-
mation in the methods where available, or by applying a convex hull
algorithm to locations of the samples.

# 3 | DESCRIPTION OF DATA

In total, the version of BioTIME released with this paper includes 8,777,413 records, across 547,161 unique locations, gathered from 361 studies (Figure 1; see Appendix for a full list of citations). These observations span the Poles to the Equator, from depths of c. 5,000 m to elevations of c. 4,000 m above sea level, and include the terrestrial, freshwater and marine realms. The database includes records spanning 21 out of 26 ecoregions [WWF; (http://www.worldwildlife.org/biomes)]. Nonetheless, there are spatial biases in the distribution of sampling locations, with most studies occurring in Europe, North America and Australia. This geographical bias has persisted despite the growth of the database. For example, a comparison between Supporting Information Figure S2 and the data included in the study by Dornelas et al. (2014) displays only small differences, despite the database having more than tripled its size in the interim. It is our hope that this geographical bias will decrease over time via targeted searches and data recruitment.

There are 44,440 taxa in BioTIME. The majority of these (88.8%) are species, but some organisms are identified only to coarser taxonomic levels, such as genus. BioTIME includes assemblages across the animal and plant kingdoms, ranging from mammals to microscopic plankton. As with the spatial distribution, there are also taxonomic biases in the data in BioTIME (Figure 2). Almost 70% of records fall into one of four categories: terrestrial plants, birds, fish and marine invertebrates, with fish accounting for 28% of the total database.

BioTIME records span 118 years (from 1874 to 2016), with the longest time series having 97 years and an average duration of 13 years. In more detail, 56.5% of studies contain up to 10 years of data, 42% between 10 and 50 years and 1.4% > 50 years.

# 4 | USAGE NOTES

Version 1.0 of the BioTIME database can be downloaded from https://zenodo.org/record/1095627 or from http://biotime.st-andrews.ac.uk/. The use of data contained in BioTIME should cite original data citations in addition to the present paper. There is considerable variation in the spatial and temporal grain and extent among studies, which must be considered in any analysis of BioTIME data. Moreover, the number of samples was often not constant through time within studies; consequently, we recommend the use of sample-based rarefaction and provide R code to query the database, implement sample-based rarefaction and calculate a suite of biodiversity metrics. Specifically, we provide a tutorial guiding users to interact with both formats of the database (.csv and .sql; Allaire et al., 2015; Becker, Wilks, & Brownrigg, 2014; Oksanen et al., 2013; Ooms, James, DebRoy, Wickham, & Horner, 2015; R Development Core Team, 2013; Wickham, 2009; Wickham & Francois, 2015). Please note that for interacting with the .sql version of the database, users will have to set up a connection with
<figure><img src="image_4.png" /><figcaption>**FIGURE 1** Top: Geographical locations of all the records included in BioTIME in dark grey, with central points per study shown as circles of different colour and size, according to taxa and number of species. Bottom: Map overlaid with ~4° grid cells coloured by the length of the full or partial time series contained within each cell</figcaption></figure>

the server where they have installed the SQL database. For interacting with the .csv version, users have to download both the data and the metadata csv files, making sure that all the paths to these files are modified accordingly.

The data included in the present paper represent the subset of data within the BioTIME database for which we were able to secure licences to republish. The additional studies held in the full database have been obtained from publicly available data and are listed in

Supporting Information Table S1. In total, BioTIME currently holds 387 studies, containing 12,623,386 records from a total of 652,675 distinct geographical locations, and 45,093 species. These records span a total of 124 years from 1858 to 2016 inclusive. We will continue to interact with data providers in order to increase data availability and to recruit additional data. Instructions on how to contribute to future releases can be found here (http://biotime.st-andrews.ac.uk/contribute.php).
<figure><img src="image_5.png" /><figcaption>FIGURE 2 Proportion of studies that fall into the different classifications of: Climate, number of years sampled, realm, taxa and biome</figcaption></figure>

ACKNOWLEDGMENTS

European Research Council and EU: A.E.M., M.D. and F.M. are
grateful for the support of the ERC grants BioTIME [AdG-250189]
and BioCHANGE [PoC-727440]. J.P. and M.E. acknowledge the
financial support from the ERC Synergy grant ERC-SyG-2013-306
610028 IMBALANCE-P, Spanish CGL2016-79835-P and Catalan
SGR-2017-1005. Long-term sampling of Calafuria rocky shores (L.B.-
C.) has been supported by various E.U. projects, in addition to the
University of Pisa and the Census of Marine Life. Natural Environ-
mental Research Council: C.W. is grateful for the support of the
Natural Environmental Research Council [grant number NE/
L002531/1]. The Porcupine Abyssal Plain Sustained Observatory is
funded by the U.K. Natural Environment Research Council. We
thank the Atlantic Meridional Program (supported by the U.K.Natu-
ral Environment Research Council through the Atlantic Meridional
Transect consortium) and the L4 programme (funded under the U.K.

NERC Oceans 2025 programme as part of Theme 10, Sustained
Observations). C.E.W. thanks the U.K.'s Natural Environment
Research Council for funding the Western Channel Observatory's
plankton time-series through the National Capability programme.
National Science Foundation (NSF): S.K.M.E. acknowledges the U.S.
National Science Foundation for funding data collection. S.R.S. was
supported by NSF grant 1400911. The research of F.P.D. was
funded by NSF grant DEB-1237733. D.A.K. thanks the National Sci-
ence Foundation (most recently DEB-1456729) for their support.
This material (R.D.H.) is based upon work supported by the National
Science Foundation under Grant No. 9714103, 0632263, 0856516,
and 1432277. K.D.W. thanks the U.S. Forest Service, National Sci-
ence Foundation and Andrew W. Mellon Foundation. Research (M.
W., R.B.W. and C.B.) was supported by grants DEB-9705814, BSR-
8811902, DEB 9411973, DEB 0080538, DEB 0218039, DEB
0620910, DEB 0963447, DEB-1546686 and DEB-129764 from the
National Science Foundation to the Department of Environmental
Science, University of Puerto Rico, and to the International Institute
of Tropical Forestry USDA Forest Service, as part of the Luquillo
Long-Term Ecological Research Program. The U.S. Forest Service
(Department of Agriculture) and the University of Puerto Rico gave
additional support. J.E.D. thanks the U.S. National Science Founda-
tion for support with grants OCE 95-21184, OCE-0099226, OCE
03-52343, OCE-0623874, OCE-1031061 and OCE-1336206. Data
compilation and cleaning by A.H.H., B.S.E. and S.J.S. was funded by
NSF grant DEB-1354563 to A.H.H. W.A.G. thanks the AON ITEX
program (awards 1432982, 0856710 and 1504381). All research at
the U.S. Forest Service International Institute of Tropical Forestry is
done in collaboration with the University of Puerto Rico. National
Science Foundation (LTER): Jornada LTER, Research Site Manager –
New Mexico State University. Datasets were provided by the
Jornada Basin Long-Term Ecological Research (LTER) project. Fund-
ing for these data was provided by the U.S. National Science
Foundation (Grant DEB-1235828). C.G. was supported under
Cooperative Agreement #DEB-1440297, NTL LTER. Support for A.L.
R. was provided under Cooperative Agreement #DEB-1440297,
NTL-LTER. Data collection (E.H.S.) was supported by the National
Science Foundation #DEB-1440297, NTL LTER. J.J. is grateful for
funding to the H. J. Andrews Long-Term Ecological Research pro-
gram from the U.S. National Science Foundation; U.S. Forest Service
support of the H. J. Andrews Experimental Forest. V.H.R.-M. and R.
R.T. thank NSF-Florida Coastal Everglades Long-Term Ecological
Research (FCE-LTER) program (grant nos DBI-0620409, DEB-
9910514 and DEB-1237517). D.C.R. is grateful for support from the
NSF's LTER Program. D.C.R. thanks the U.S. National Science Foun-
dation for supporting the Santa Barbara Coastal Long-Term Ecologi-
cal Research (SBC-LTER) program. Data (A.J.B. and R.C.) were
provided by the Moorea Coral Reef Long-Term Ecological Research
Program (OCE-0417412, OCE-1026851, OCE-1236905 and OCE-
1637396). D.L. thanks the Jornada Basin LTER Program and the Sev-
illeta LTER Program. Data (J.J., M.N. and S.M.R.) were provided by
the H. J. Andrews Experimental Forest research program, funded by
the NSF's LTER Program (DEB-1440409), U.S. Forest Service Pacific
Northwest Research Station and Oregon State University. The
authors are grateful to the LTER program for the data they provide.
This includes material based upon work supported under Coopera-
tive Agreements DEB-0832652 and DEB-0936498, and by grants
from the LTER including DEB-0620652 and DEB-1234162; further
support was provided by the Cedar Creek Ecosystem Science
Reserve and the University of Minnesota. J.F.C. acknowledges fund-
ing from NSF (DEB-0823293) from the LTER to the Coweeta LTER
Program at the University of Georgia. Other funding: L.H.A. was
supported by Fundação para a Ciência e Tecnologia, Portugal
(POPH/FSE SFRH/BD/90469/2012). A.R.K. is funded by Ciências
sem Fronteiras and Coordenação de Pessoal de Nível Superior
(CAPES, Brazil), Grant/Award Number: 1091/13-1. R.E. is grateful
for support by Instituto Milenio de Oceanografia IC120019. A.H.B.
is grateful for ARC Centre of Excellence (Grant CE0561432). R.P.V.
is currently supported by a doctoral grant from Fundação para a

Ciência e Tecnologia, Portugal (SFRH/BD/84030/2012). J.J. is grateful for funding for data collection from NSERC Canada. J.R.G. is grateful for the support from CONICYT/FONDECYT no. 1160026, ICM PO5-002, CONICYT/FPB-23. A.P.M. is grateful for the support of FONDECYT Grants 11110351 and 1151094. A.A. and V.O. thank RSF (14-50-00029). E.P.W. is supported by the Gordon and Betty Moore Foundation's Data-Driven Discovery Initiative Grant GBMF4563. J.M.A. was supported by FI/FIAP (1998FI-00596) and BE (2001BEAI200208) fellowships from the Catalan Government (DURSI) during the fieldwork and by a MECD-Post-doctoral fellowship (EX2002-0022), a Marie Curie Individual Fellowship (QLK5-CT2002-51518) and Marie Curie project MARIBA (MERG-CT-2004-022065) afterwards. A.F. receives a scholarship from CNPq (306170/2015-9); G.D. receives a scholarship from FAPESP (2015/10714-6); projects to collect data received financial support from FAPESP (São Paulo Research Foundation) (2015/06743-0, 2008/10049-9), CNPq (475434/2010-2) and DFG (German Research Foundation, Project PF 120/10-2). F.L. acknowledges support from EU CLIMOOR ENV4-CT97-0694, VULCAN EVK2-CT-2000-00094), Spanish REN2000-0278/CCI and REN2001-003/GLO, and Catalanian AGAUR 2014 SGR 453. Y.R.S. is grateful for funding from FUNDECT, CNPq. F.R.S. is grateful for the support of the São Paulo Research Foundation (FAPESP, Proc. 2013/50714-0). D.A.K. is grateful for the support of FONDECYT (most recently, no. 1070808). E.L. acknowledges funding from NSERC and logistical support from Polar Continental Shelf Program. P.H. is grateful for the support of FONDECYT no. 1130511. G.B.G.S. and M.V. thank the staff who assisted in the field and laboratory research from the Laboratory of Fishery Biology and Technology. This study was part of the programme 'Environmental Assessment of Guanabara Bay' coordinated and funded by CENPES - PETROBRAS, which has given permission for the publication of the results. This study was also supported by the Long Term Ecological Programme (PELD programme - CNPq 403809/2012-6) and by FAPERJ (Thematic Programme, process E-26/110.114/2013). G.B.G.S. was funded by CAPES/Brazil. C.M. is grateful for the support of the German Academic Exchange Service (DAAD) and the German Research Foundation (DFG). H.B. and U.J. acknowledge the support of sDiv, the Synthesis Centre of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. C.F.J.M., R.R. and A.L.-B. acknowledge funding from Fundação para a Ciência e Tecnologia, Portugal (PTDC/BIA-BIC/111184/2009, SFRH/BD/80488/2011 and PD/BD/52597/2014, respectively). F.Z.F. was funded by CAPES/Brazil. T.J.W. acknowledges support from the New Zealand Department of Conservation. General acknowledgments: Bioinformatics and Computational Biology analyses were supported by the University of St Andrews Bioinformatics Unit, which is funded by a Wellcome Trust ISSF award (grant 105621/Z/14/Z). We would like to acknowledge Richard Osman for his work in the Woods Hole study, and the Smithsonian Atherton Seidell Fund, which provides funds within the Smithsonian to make old studies and publications more available. Any use of trade, firm or product names is for descriptive purposes only and does not imply endorsement by the
U.S. Government. This study (P.B.) was performed under the auspices of Utah State University IACUC protocol number 1539. L.V.V. thanks Earthwatch Institute and their volunteers. R.A.D. and T.S.D. thank the Botanic Gardens and Parks Authority for the financial and logistical support, without which their reptile monitoring project would not be possible. R.S.S. and G.E. thank the Reef Life Survey volunteer divers. P.H. thanks Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). F.H. acknowledges the EWHALE laboratory, Biology and Wildlife Department, Institute of Arctic Biology. H.K. thanks the Ministry of Trade, Industry and Fisheries. A.H. is supported by the Research Council of Norway. J.S. thanks the many researchers and field assistants who over the years contributed to the collection and curation of data for the studies presented in this database. S.K.C. thanks the City of Boulder Department of Open Space and Mountain Parks. N.A. thanks Karnataka Forest Department and IFP staff Messrs. S. Aravajy, S. Ramalingam, N. Barathan, G. Orukaimani, G. Jayapalan, K. Anthapa Gowda, Obbaya Gowda and Manoj Gowda. M.L. and J.M.A. wish to thank all participants in the MEDITS series cruises on board R/V Cornide de Saavedra, both scientists and crew (Spanish Institute of Oceanography), for all their help and support, and especially Pere Abelló and Luis Gil de Sola. Thanks to Daniel Oro and the Population Ecology research team at the Institut Mediterrani d'Estudis Avançats (IME-DEA, CSIC-UIB). M.L. was supported by a fellowship of Conselleria de Innovació, Hisenda i Economia (Govern de les Illes Balears). R.K., D.P. and J.M. acknowledge SOTEAG (Shetland Oil Terminal Environmental Advisory Group) for providing access to the dataset. We thank SOTEAG (Shetland Oil Terminal Advisory group) for providing data from the long term rocky shore monitoring programme after dataset. We thank Jake Goheen and Rob Pringle for providing data from the UHURU herbivore-exclusion experiment in central Kenya. J.S.M. thanks the Australian Research Council. J.S.M. thanks the staff of Lizard Island Research Station. F.P. would like to thank the Waserversorgung Zurich for collecting and allowing access to the data. Data (C.H.D.) was sourced from the Integrated Marine Observing System (IMOS); IMOS is a national collaborative research infrastructure, supported by the Australian Government. J.M.A. would like to thank the Spanish Institute of Oceanography (IEO), Pere Abelló, Luis Gil de Sola and Daniel Oro. M.T.Z.T. thanks Dr Ary Teixeira de Oliveira-Filho. I.H.M.-S. thanks the Herschel Island-Qikiqtaruk Territorial Park management and, in particular, Cameron D. Eckert, Catherine Kennedy, Dorothy Cooley and Jill F. Johnstone for establishing the ITEX protocols for plant composition monitoring on Qikiqtaruk. We thank the Herschel Island-Qikiqtaruk Territorial Park rangers for data collection logistical support, including in particular Richard Gordon, Edward McLeod, Sam McLeod, Ricky Joe, Paden Lennie, Deon Arey and LeeJohn Meyook. We thank the researchers and field assistants who helped with data collection, including Haydn Thomas, Sandra Angers-Blondie, Jakob Assmann, Meagan Grabowski, Catherine Henry, Annika Trimble, Louise Beveridge, Clara Flintrop, Santeri Lehtonen, Joe Boyle, John Godlee and Eleanor Walker. Funding was provided by the Yukon Government Herschel Island-Qikiqtaruk Territorial Park and the U.K. Natural Environment Research Council

ShrubTundra Grant NE/M016323/1. We thank the Inuvialuit People for the opportunity to conduct research on their traditional lands. L. H. and L.S.C. are grateful for the support of IPY, Memorial University and ArcticNet for funding. T.J.C. thanks the LIRS Trimodal Mapping Study. M.H. thanks the staff of Lizard Island Research Station. R.R.S. would like to thank E. E. de Assis, Santa Genebra and E. E. Caetetus and acknowledges funding from FAPESP (projetos temáticos: 1999/09635-0 and 2013/50718-5) and CNPq (Processo: 561897/2010). F.C. thanks SIBELCO Ltda. of Brazil for the logistic support in the accomplishment of the field work. We acknowledge the thousands of U.S. and Canadian volunteers who annually perform the North American Breeding Bird survey, as well as those who manage the program at the U.S. Geological Survey (USGS). The term 'Anthropocene' is not formally recognized by the USGS as a description of geological time. We use it here informally. We hope that data providers will continue to share their data (and any new updates) with OBIS and GBIF and encourage them to correct any errors identified by BioTIME. D.A., D.J., K.K., T.V. acknowledges support from Czech Science Foundation, project No. 16-18022S and from Czech Ministry of Environment, project No. 170368. We thank Jan Wittoeck and other colleagues who assisted in the sampling and compilation of the macrobenthic data and the Belgian Federal Science Policy Office who funded MACROBEL through the programme 'Sustainable management of the North Sea' (SPSD I MN/02/96). M. B., A.J., K.P., J.S. received financial support from internal funds of University of Lódź. W.R.F. thanks the National Science Foundation for support through award OPP-1440435. N.V. thanks CONICYT grants FONDECYT 1141037 and FONDAP 15150003 (IDEAL).

## DATA ACCESSIBILITY

The BioTIME database is accessible through the BioTIME website (http://biotime.st-andrews.ac.uk) and through the Zenodo repository (https://zenodo.org/record/1095627).

## ORCID

Maria Dornelas http://orcid.org/0000-0003-2077-7055

Laura H. Antão http://orcid.org/0000-0001-6612-9366

Faye Moyes https://orcid.org/0000-0001-9687-0593

Anne E. Magurran https://orcid.org/0000-0002-0036-2795

Eric J. Woehler http://orcid.org/0000-0002-1125-0748

Michael L. Zettler http://orcid.org/0000-0002-5437-5495

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## BIOSKETCH

The BIOTIME CONSORTIUM emerged from the ERC project BioTIME in 2010. The consortium currently includes 271 authors distributed among 35 countries engaged in collecting biodiversity time series data

and committed to sharing it for wider use. We hope that the BioTIME database allows analysis of large-scale patterns of biodiversity change and contributes to giving credit to the data collectors, without whom synthesis would not be possible.

## SUPPORTING INFORMATION

Additional Supporting Information may be found online in the supporting information tab for this article.

**How to cite this article:** Dornelas M, Antão LH, Moyes F, et al. BioTIME: A database of biodiversity time series for the Anthropocene. *Global Ecol Biogeogr.* 2018;27:760–786. https://doi.org/10.1111/geb.12729

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