Reed Daniel C.

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Reed
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Daniel C.
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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
    A review of the opportunities and challenges for using remote sensing for management of surface-canopy forming kelps
    (Frontiers Media, 2021-10-20) Cavanaugh, Kyle C. ; Bell, Tom W. ; Costa, Maycira ; Eddy, Norah E. ; Gendall, Lianna ; Gleason, Mary G. ; Hessing-Lewis, Margot ; Martone, Rebecca ; McPherson, Meredith L. ; Pontier, Ondine ; Reshitnyk, Luba ; Beas-Luna, Rodrigo ; Carr, Mark H. ; Caselle, Jennifer E. ; Cavanaugh, Katherine C. ; Flores Miller, Rebecca ; Hamilton, Sara L. ; Heady, Walter N. ; Hirsh, Heidi K. ; Hohman, Rietta ; Lee, Lynn Chi ; Lorda, Julio ; Ray, James ; Reed, Daniel C. ; Saccomanno, Vienna R. ; Schroeder, Sarah B.
    Surface-canopy forming kelps provide the foundation for ecosystems that are ecologically, culturally, and economically important. However, these kelp forests are naturally dynamic systems that are also threatened by a range of global and local pressures. As a result, there is a need for tools that enable managers to reliably track changes in their distribution, abundance, and health in a timely manner. Remote sensing data availability has increased dramatically in recent years and this data represents a valuable tool for monitoring surface-canopy forming kelps. However, the choice of remote sensing data and analytic approach must be properly matched to management objectives and tailored to the physical and biological characteristics of the region of interest. This review identifies remote sensing datasets and analyses best suited to address different management needs and environmental settings using case studies from the west coast of North America. We highlight the importance of integrating different datasets and approaches to facilitate comparisons across regions and promote coordination of management strategies.