PCI Ecology

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Title *

Data-based, synthesis-driven: setting the agenda for computational ecologyuse asterix (*) to get italics

Authors *

Timothée Poisot, Richard Labrie, Erin Larson, Anastasia RahlinPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

Year *

2018

Picture *

Abstract *

<p>Computational ecology, defined as the application of computational thinking to ecological problems, has the potential to transform the way ecologists think about the integration of data and models. As the practice is gaining prominence as a way to conduct ecological research, it is important to reflect on what its agenda could be, and how it fits within the broader landscape. In this contribution, we suggest areas in which empirical ecologists, modelers, and the emerging community of computational ecologists could engage in a constructive dialogue to build on one another expertise. We discuss how training can be amended to improve the computational literacy of ecologists.</p>

Indicate the full web address (DOI or URL) giving public access to these data (if you have any problems with the deposit of your data, please contact contact@ecology.peercommunityin.org). In case all raw data are included in the preprint, indicate the DOI or URL of the preprint. *

You should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https://

Indicate the full web address (DOI or URL) giving public access to these scripts (if you have any problems with the deposit of your scripts, please contact contact@ecology.peercommunityin.org). In case all raw scripts are included in the preprint, indicate the DOI or URL of the preprint. *

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Indicate the full web address (DOI, SWHID or URL) giving public access to these codes (if you have any problems with the deposit of your codes, please contact contact@ecology.peercommunityin.org). In case all raw codes are included in the preprint, indicate the DOI or URL of the preprint. *

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Keywords (optional)

None

Methods that require specific expertise (optional)

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Thematic fields *

Meta-analyses, Statistical ecology, Theoretical ecology

Suggested reviewers - Suggest up to 10 reviewers (provide names and Email addresses). (Optional)

e.g. John Doe john@doe.com

No need for them to be recommenders of PCIEcology. Please do not suggest reviewers for whom there might be a conflict of interest. Reviewers are not allowed to review preprints written by close colleagues (with whom they have published in the last four years, with whom they have received joint funding in the last four years, or with whom they are currently writing a manuscript, or submitting a grant proposal), or by family members, friends, or anyone for whom bias might affect the nature of the review - see the code of conduct

Opposed reviewers - Suggest up to 5 people not to invite as reviewers. (Optional)

e.g. John Doe john@doe.com

Submission date

2018-02-05 20:51:41

Recommender

Phillip P.A. Staniczenko

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Direct submissions to PCI Ecology from bioRxiv.org are possible using the B2J service

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