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  • Article
    BioTIME : a database of biodiversity time series for the Anthropocene
    (John Wiley & Sons, 2018-07-24) Dornelas, Maria ; Antao, Laura H. ; Moyes, Faye ; Bates, Amanda E. ; Magurran, Anne E. ; Adam, Dusan ; Akhmetzhanova, Asem A. ; Appeltans, Ward ; Arcos, Jose Manuel ; Arnold, Haley ; Ayyappan, Narayanan ; Badihi, Gal ; Baird, Andrew H. ; Barbosa, Miguel ; Barreto, Tiago Egydio ; Bässler, Claus ; Bellgrove, Alecia ; Belmaker, Jonathan ; Benedetti-Cecchi, Lisandro ; Bett, Brian J. ; Bjorkman, Anne D. ; Błazewicz, Magdalena ; Blowes, Shane A. ; Bloch, Christopher P. ; Bonebrake, Timothy C. ; Boyd, Susan ; Bradford, Matt ; Brooks, Andrew J. ; Brown, James H. ; Bruelheide, Helge ; Budy, Phaedra ; Carvalho, Fernando ; Castaneda-Moya, Edward ; Chen, Chaolun Allen ; Chamblee, John F. ; Chase, Tory J. ; Collier, Laura Siegwart ; Collinge, Sharon K. ; Condit, Richard ; Cooper, Elisabeth J. ; Cornelissen, Johannes H. C. ; Cotano, Unai ; Crow, Shannan Kyle ; Damasceno, Gabriella ; Davies, Claire H. ; Davis, Robert A. ; Day, Frank P. ; Degraer, Steven ; Doherty, Tim S. ; Dunn, Timothy E. ; Durigan, Giselda ; Duffy, J. Emmett ; Edelist, Dor ; Edgar, Graham J. ; Elahi, Robin ; Elmendorf, Sarah C. ; Enemar, Anders ; Ernest, S. K. Morgan ; Escribano, Ruben ; Estiarte, Marc ; Evans, Brian S. ; Fan, Tung-Yung ; Farah, Fabiano Turini ; Fernandes, Luiz Loureiro ; Farneda, Fabio Z. ; Fidelis, Alessandra ; Fitt, Robert ; Fosaa, Anna Maria ; Franco, Geraldo Antonio Daher Correa ; Frank, Grace E. ; Fraser, William R. ; García, Hernando ; Gatti, Roberto Cazzolla ; Givan, Or ; Gorgone-Barbosa, Elizabeth ; Gould, William A. ; Gries, Corinna ; Grossman, Gary D. ; Gutierrez, Julio R. ; Hale, Stephen ; Harmon, Mark E. ; Harte, John ; Haskins, Gary ; Henshaw, Donald L. ; Hermanutz, Luise ; Hidalgo, Pamela ; Higuchi, Pedro ; Hoey, Andrew S. ; Hoey, Gert Van ; Hofgaard, Annika ; Holeck, Kristen ; Hollister, Robert D. ; Holmes, Richard ; Hoogenboom, Mia ; Hsieh, Chih-hao ; Hubbell, Stephen P. ; Huettmann, Falk ; Huffard, Christine L. ; Hurlbert, Allen H. ; Ivanauskas, Natalia Macedo ; Janík, David ; Jandt, Ute ; Jazdzewska, Anna ; Johannessen, Tore ; Johnstone, Jill F. ; Jones, Julia ; Jones, Faith A. M. ; Kang, Jungwon ; Kartawijaya, Tasrif ; Keeley, Erin C. ; Kelt, Douglas A. ; Kinnear, Rebecca ; Klanderud, Kari ; Knutsen, Halvor ; Koenig, Christopher C. ; Kortz, Alessandra R. ; Kral, Kamil ; Kuhnz, Linda A. ; Kuo, Chao-Yang ; Kushner, David J. ; Laguionie-Marchais, Claire ; Lancaster, Lesley T. ; Lee, Cheol Min ; Lefcheck, Jonathan S. ; Levesque, Esther ; Lightfoot, David ; Lloret, Francisco ; Lloyd, John D. ; Lopez-Baucells, Adria ; Louzao, Maite ; Madin, Joshua S. ; Magnusson, Borgbor ; Malamud, Shahar ; Matthews, Iain ; McFarland, Kent P. ; McGill, Brian ; McKnight, Diane ; McLarney, William O. ; Meador, Jason ; Meserve, Peter L. ; Metcalfe, Daniel J. ; Meyer, Christoph F. J. ; Michelsen, Anders ; Milchakova, Nataliya ; Moens, Tom ; Moland, Even ; Moore, Jon ; Moreira, Carolina Mathias ; Muller, Jorg ; Murphy, Grace ; Myers-Smith, Isla H. ; Myster, Randall W. ; Naumov, Andrew ; Neat, Francis ; Nelson, James A. ; Nelson, Michael Paul ; Newton, Stephen F. ; Norden, Natalia ; Oliver, Jeffrey C. ; Olsen, Esben M. ; Onipchenko, Vladimir G. ; Pabis, Krzysztof ; Pabst, Robert J. ; Paquette, Alain ; Pardede, Sinta ; Paterson, David M. ; Pelissier, Raphael ; Penuelas, Josep ; Perez-Matus, Alejandro ; Pizarro, Oscar ; Pomati, Francesco ; Post, Eric ; Prins, Herbert H. T. ; Priscu, John C. ; Provoost, Pieter ; Prudic, Kathleen L. ; Pulliainen, Erkki ; Ramesh, B. B. ; Ramos, Olivia Mendivil ; Rassweiler, Andrew ; Rebelo, Jose Eduardo ; Reed, Daniel C. ; Reich, Peter B. ; Remillard, Suzanne M. ; Richardson, Anthony J. ; Richardson, J. Paul ; Rijn, Itai van ; Rocha, Ricardo ; Rivera-Monroy, Victor H. ; Rixen, Christian ; Robinson, Kevin P. ; Rodrigues, Ricardo Ribeiro ; Rossa-Feres, Denise de Cerqueira ; Rudstam, Lars ; Ruhl, Henry A. ; Ruz, Catalina S. ; Sampaio, Erica M. ; Rybicki, Nancy ; Rypel, Andrew ; Sal, Sofia ; Salgado, Beatriz ; Santos, Flavio A. M. ; Savassi-Coutinho, Ana Paula ; Scanga, Sara ; Schmidt, Jochen ; Schooley, Robert ; Setiawan, Fakhrizal ; Shao, Kwang-Tsao ; Shaver, Gaius R. ; Sherman, Sally ; Sherry, Thomas W. ; Sicinski, Jacek ; Sievers, Caya ; da Silva, Ana Carolina ; da Silva, Fernando Rodrigues ; Silveira, Fabio L. ; Slingsby, Jasper ; Smart, Tracey ; Snell, Sara J. ; Soudzilovskaia, Nadejda A. ; Souza, Gabriel B. G. ; Souza, Flaviana Maluf ; Souza, Vinícius Castro ; Stallings, Christopher D. ; Stanforth, Rowan ; Stanley, Emily H. ; Sterza, Jose Mauro ; Stevens, Maarten ; Stuart-Smith, Rick ; Suarez, Yzel Rondon ; Supp, Sarah ; Tamashiro, Jorge Yoshio ; Tarigan, Sukmaraharja ; Thiede, Gary P. ; Thorn, Simon ; Tolvanen, Anne ; Toniato, Maria Teresa Zugliani ; Totland, Orjan ; Twilley, Robert R. ; Vaitkus, Gediminas ; Valdivia, Nelson ; Vallejo, Martha Isabel ; Valone, Thomas J. ; Van Colen, Carl ; Vanaverbeke, Jan ; Venturoli, Fabio ; Verheye, Hans M. ; Vianna, Marcelo ; Vieira, Rui P. ; Vrska, Tomas ; Vu, Con Quang ; Vu, Lien Van ; Waide, Robert B. ; Waldock, Conor ; Watts, David ; Webb, Sara ; Wesołowski, Tomasz ; White, Ethan P. ; Widdicombe, Claire E. ; Wilgers, Wilgers ; Williams, Richard ; Williams, Stefan B. ; Williamson, Mark ; Willig, Michael R. ; Willis, Trevor J. ; Wipf, Sonja ; Woods, Kerry D. ; Woehler, Eric ; Zawada, Kyle ; Zettler, Michael L.
    The BioTIME database contains raw data on species identities and abundances in ecological 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. 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. 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). BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. 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.
  • Article
    Steering operational synergies in terrestrial observation networks : opportunity for advancing Earth system dynamics modelling
    (Copernicus Publications on behalf of the European Geosciences Union, 2018-05-23) Baatz, Roland ; Sullivan, Pamela L. ; Li, Li ; Weintraub, Samantha R. ; Loescher, Henry W. ; Mirtl, Michael ; Groffman, Peter M. ; Wall, Diana H. ; Young, Michael ; White, Tim ; Wen, Hang ; Zacharias, Steffen ; Kühn, Ingolf ; Tang, Jianwu ; Gaillardet, Jerome ; Braud, Isabelle ; Flores, Alejandro N. ; Kumar, Praveen ; Lin, Henry ; Ghezzehei, Teamrat ; Jones, Julia ; Gholz, Henry L. ; Vereecken, Harry ; Van Looy, Kris
    Advancing our understanding of Earth system dynamics (ESD) depends on the development of models and other analytical tools that apply physical, biological, and chemical data. This ambition to increase understanding and develop models of ESD based on site observations was the stimulus for creating the networks of Long-Term Ecological Research (LTER), Critical Zone Observatories (CZOs), and others. We organized a survey, the results of which identified pressing gaps in data availability from these networks, in particular for the future development and evaluation of models that represent ESD processes, and provide insights for improvement in both data collection and model integration. From this survey overview of data applications in the context of LTER and CZO research, we identified three challenges: (1) widen application of terrestrial observation network data in Earth system modelling, (2) develop integrated Earth system models that incorporate process representation and data of multiple disciplines, and (3) identify complementarity in measured variables and spatial extent, and promoting synergies in the existing observational networks. These challenges lead to perspectives and recommendations for an improved dialogue between the observation networks and the ESD modelling community, including co-location of sites in the existing networks and further formalizing these recommendations among these communities. Developing these synergies will enable cross-site and cross-network comparison and synthesis studies, which will help produce insights around organizing principles, classifications, and general rules of coupling processes with environmental conditions.