Zobrazeno 1 - 10
of 94
pro vyhledávání: '"Carl Boettiger"'
Autor:
Elizabeth H. Wenk, Hervé Sauquet, Rachael V. Gallagher, Rowan Brownlee, Carl Boettiger, David Coleman, Sophie Yang, Tony Auld, Russell Barrett, Timothy Brodribb, Brendan Choat, Lily Dun, David Ellsworth, Carl Gosper, Lydia Guja, Gregory J. Jordan, Tom Le Breton, Andrea Leigh, Patricia Lu-Irving, Belinda Medlyn, Rachael Nolan, Mark Ooi, Karen D. Sommerville, Peter Vesk, Matthew White, Ian J. Wright, Daniel S. Falster
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-15 (2024)
Abstract Traits with intuitive names, a clear scope and explicit description are essential for all trait databases. The lack of unified, comprehensive, and machine-readable plant trait definitions limits the utility of trait databases, including rean
Externí odkaz:
https://doaj.org/article/2dc55a442d5c433e97d6408aee524963
Autor:
Michael C. Dietze, R. Quinn Thomas, Jody Peters, Carl Boettiger, Gerbrand Koren, Alexey N. Shiklomanov, Jaime Ashander
Publikováno v:
Ecosphere, Vol 14, Iss 11, Pp n/a-n/a (2023)
Abstract This paper summarizes the open community conventions developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata associated with these forecasts. Such open standar
Externí odkaz:
https://doaj.org/article/73136c4054164feab162425efdd0de25
Publikováno v:
Methods in Ecology and Evolution, Vol 14, Iss 3, Pp 728-731 (2023)
Externí odkaz:
https://doaj.org/article/300df8e10a3346d6b7ccbd5fb11decd3
Limits to ecological forecasting: Estimating uncertainty for critical transitions with deep learning
Autor:
Marcus Lapeyrolerie, Carl Boettiger
Publikováno v:
Methods in Ecology and Evolution, Vol 14, Iss 3, Pp 785-798 (2023)
Abstract In the current age of a rapidly changing environment, it is becoming increasingly important to study critical transitions and how to best anticipate them. Critical transitions pose extremely challenging forecasting problems, which necessitat
Externí odkaz:
https://doaj.org/article/91cdb626bef84ee5ac9febba47a8e125
Publikováno v:
Conservation Science and Practice, Vol 5, Iss 4, Pp n/a-n/a (2023)
Abstract Coincident with international movements to protect 30% of land and sea over the next decade (“30×30”), the United States has committed to more than doubling its current protected land area by 2030. While publicly owned and managed prote
Externí odkaz:
https://doaj.org/article/e48f16dcccf74b8db3b4b1042dfdf75e
Autor:
Marcus A.M. de Aguiar, Erica A. Newman, Mathias M. Pires, Justin D. Yeakel, Carl Boettiger, Laura A. Burkle, Dominique Gravel, Paulo R. Guimarães Jr, James L. O’Donnell, Timothée Poisot, Marie-Josée Fortin, David H. Hembry
Publikováno v:
PeerJ, Vol 7, p e7566 (2019)
The structure of ecological interactions is commonly understood through analyses of interaction networks. However, these analyses may be sensitive to sampling biases with respect to both the interactors (the nodes of the network) and interactions (th
Externí odkaz:
https://doaj.org/article/9e7a5fdfbc0a42f6a2396a31732b5c28
Publikováno v:
Big Data & Society, Vol 6 (2019)
To improve the quality and efficiency of research, groups within the scientific community seek to exploit the value of data sharing. Funders, institutions, and specialist organizations are developing and implementing strategies to encourage or mandat
Externí odkaz:
https://doaj.org/article/20b868a89ae24ef7acc0c5dc941ce260
Autor:
Daniel S. Katz, Gabrielle Allen, Lorena A. Barba, Devin R. Berg, Holly Bik, Carl Boettiger, Christine L. Borgman, C. Titus Brown, Stuart Buck, Randy Burd, Anita de Waard, Martin Paul Eve, Brian E. Granger, Josh Greenberg, Adina Howe, Bill Howe, May Khanna, Timothy L. Killeen, Matthew Mayernik, Erin McKiernan, Chris Mentzel, Nirav Merchant, Kyle E. Niemeyer, Laura Noren, Sarah M. Nusser, Daniel A. Reed, Edward Seidel, MacKenzie Smith, Jeffrey R. Spies, Matt Turk, John D. Van Horn, Jay Walsh
Publikováno v:
F1000Research, Vol 7 (2018)
In the 21st Century, research is increasingly data- and computation-driven. Researchers, funders, and the larger community today emphasize the traits of openness and reproducibility. In March 2017, 13 mostly early-career research leaders who are buil
Externí odkaz:
https://doaj.org/article/eec975fce52d412387bf3133ef457f04
Publikováno v:
Journal of Open Research Software, Vol 3, Iss 1, Pp e8-e8 (2015)
rOpenSci is a developer collective originally formed in 2011 by graduate students and post-docs from ecology and evolutionary biology to collaborate on building software tools to facilitate a more open and synthetic approach in the face of transforma
Externí odkaz:
https://doaj.org/article/fd122277474042eeaaade0f21b8f7420
Limits to ecological forecasting: Estimating uncertainty for critical transitions with deep learning
Autor:
Marcus Lapeyrolerie, Carl Boettiger
Publikováno v:
Methods in Ecology and Evolution. 14:785-798