Author

Dan Pagendam

Commonwealth Scientific and Industrial Research OrganisationORCID 0000-0002-8347-4767Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Ecology· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:ecology & biodiversity· 1 Approach:statistical model· 1

Frequent Co-Authors

Andrew J. HoskinsiD· 2 shared Christopher DrovandiiD· 2 shared Jonathan R. PottsiD· 2 shared Michael BodeiD· 2 shared Scott W. ForrestiD· 2 shared Conor HassaniD· 1 shared Eric Peter VanderduysiD· 1 shared Justin PerryiD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 26 mutual co-author links

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2 shared papersEcology

Andrew J. HoskinsORCID

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2 papers

Recent·Most cited

Predicting animal movement with deepSSF: a deep learning step selection framework

Scott W. Forrest, Dan Pagendam, Conor Hassan, Christopher Drovandi, Jonathan R. Potts, Michael Bode, Andrew J. Hoskins

This paper introduces deepSSF, a deep learning framework for predicting animal movement by learning from environmental and temporal data, showing it can capture complex habitat interactions and temporal dynamics.

Methods in Ecology and Evolution · Aug 13, 2025Peer-reviewedEcology

Predicting fine-scale distributions and emergent spatiotemporal patterns from temporally dynamic step selection simulations

Scott W. Forrest, Dan Pagendam, Michael Bode, Christopher Drovandi, Jonathan R. Potts, Justin Perry, Eric Peter Vanderduys, Andrew J. Hoskins

This study shows that incorporating fine-scale temporal dynamics improves both hourly and seasonal spatial predictions of water buffalo movement and habitat use.

Ecography · Dec 12, 2024Peer-reviewedEcology