Author

Mathias I. Disney

City University of New YorkORCID 0000-0002-2407-4026Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:imaging· 3 Research Focus:ecology & biodiversity· 2 Approach:experimental assay· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Approach:statistical model· 1

Frequent Co-Authors

Alexander Frederick ShenkiniD· 1 shared Alvaro SarmientoiD· 1 shared Andrew BurtiD· 1 shared Brian Joseph EnquistiD· 1 shared Cansu Oktem· 1 shared Fernando González‐GarcíaiD· 1 shared Gustavo López Bautista· 1 shared Ivette PerfectoiD· 1 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 13 mutual co-author links

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1 shared paperEcology

Alexander Frederick ShenkinORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

Consistent and scalable monitoring of birds and habitats along a coffee production intensity gradient

Marius Somveille, Joe Grainger‐Hull, Nicole Ferguson, Sarab S. Sethi, Fernando González‐García, Valentine Chassagnon, Cansu Oktem, Mathias I. Disney, Gustavo López Bautista, John H. Vandermeer, Ivette Perfecto

This study shows that combining LiDAR and automated bioacoustic analysis can effectively monitor avian biodiversity along a coffee production intensity gradient.

Remote Sensing in Ecology and Conservation · Jun 21, 2025Peer-reviewedEcology

Tree Surface Area Allometry

Alexander Frederick Shenkin, Phil Wilkes, Brian Joseph Enquist, Alvaro Sarmiento, Andrew Burt, Kim Calders, Pasi Raumonen, Lisa Patrick Bentley, Mathias I. Disney, Yadvinder Singh Malhi

This study uses terrestrial laser scanning to measure tree surface areas, finding discrepancies between direct measurements and theoretical predictions, suggesting the need to revise allometric models.

bioRxiv · Apr 23, 2024 · PreprintEcology

Gaining insight into the allometric scaling of trees by utilizing 3d reconstructed tree models - a SimpleForest study

Jan Hackenberg, Mathias I. Disney, Jean‐Daniel Bontemps

The paper develops a method to estimate tree volume using 3D reconstructed models and compares it to harvested data, showing significant improvement in accuracy.

bioRxiv · May 5, 2022 · PreprintBioinformatics