Author

J. P. Ometto

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Ecology· 3

Signature Assays, Organisms & Methods

Click to filter · or open tag

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

Frequent Co-Authors

C. R. Reis· 3 shared D. Coomes· 3 shared E. B. Gorgens· 3 shared D. R. A. Almeida· 2 shared M. H. Nunes· 2 shared M. Keller· 2 shared A. Z. Motta· 1 shared B. Gimenez· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersEcology

C. R. Reis

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Tracking canopy gap dynamics across four sites in the Brazilian Amazon

E. B. Gorgens, M. Keller, T. D. Jackwon, D. M. Marra, C. R. Reis, D. R. A. Almeida, D. Coomes, J. P. Ometto

The paper uses remote sensing to analyze canopy gap dynamics across four Amazon regions, finding that gap recovery rates vary with environmental factors.

bioRxiv · Sep 3, 2022Ecology

Forest structure and degradation drive canopy gap sizes across the Brazilian Amazon

C. R. Reis, T. D. Jackson, E. B. Gorgens, R. Dalagnol, T. Jucker, M. H. Nunes, J. P. Ometto, L. Aragao, L. C. Rodriguez, D. Coomes

The paper investigates how forest structure and degradation influence canopy gap sizes across the Brazilian Amazon using LiDAR data.

bioRxiv · May 3, 2021Ecology

Resource availability and disturbance shape maximum tree height across the Amazon

E. B. Gorgens, M. H. Nunes, T. Jackson, D. Coomes, M. Keller, C. R. Reis, R. Valbuena, J. Rosette, D. R. A. Almeida, B. Gimenez, R. Z. Cantinho, A. Z. Motta, M. Assis, F. R. d. S. Pereira, G. Spanner, , J. P. Ometto

This study identifies environmental factors influencing the distribution of extremely tall trees in the Amazon using LiDAR data, finding wind speed as the strongest predictor.

bioRxiv · May 15, 2020Ecology