Robert Muscarella
Nature and Landscape Conservation · 2014–2021
A researcher in the Science corpus: 5 papers; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Nature and Landscape Conservation — 76 citations into it
- Ecological Modeling — 74 citations into it
- Ecology — 55 citations into it
- Genetics — 9 citations into it
- Statistics and Probability — 8 citations into it
- Artificial Intelligence — 5 citations into it
Whom Robert Muscarella trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- R. P. Anderson
- Dan L. Warren
- S. Veloz
- Steven J. Phillips
- Mariya Shcheglovitova
- Robert J. Hijmans
- Miguel B. Araújo
- K. Burnham
- Stephanie N. Seifert
- Jane Elith
Who trusts Robert Muscarella overall
- B. Low
- Yoan Fourcade
- Dan L. Warren
- F. Breiner
- A. Castellanos
- Roozbeh Valavi
- J. Kass
- Yiwen Zeng
- Jane Elith
- Damaris Zurell
Papers from Robert Muscarella's perspective
Ordered by how strongly the researchers Robert Muscarella trusts endorse each paper. Same corpus, a different order for every researcher.
- Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation
- Real vs. artefactual absences in species distributions: tests for Oryzomys albigularis (Rodentia: Muridae) in Venezuela
- Predicting species distribution: offering more than simple habitat models. (Ecology Letters)
- Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. (Ecological Applications)
- Predicting species distributions from small numbers of occurrence records: A test case using cryptic geckos in Madagascar
- Spatially autocorrelated sampling falsely inflates measures of accuracy for presence‐only niche models
- Maximum entropy modeling of species geographic distributions
- Mapping Species Distributions: Spatial Inference and Prediction
- AUC: a misleading measure of the performance of predictive distribution models
- Do they? How do they? WHY do they differ? On finding reasons for differing performances of species distribution models
Their papers
- ENMeval 2.0: Redesigned for customizable and reproducible modeling of species’ niches and distributions (2021) — 599 citations
- The challenge of modeling niches and distributions for data‐poor species: a comprehensive approach to model complexity (2018) — 149 citations
- Carbon sequestration potential of second-growth forest regeneration in the Latin American tropics (2016) — 625 citations
- Biomass resilience of Neotropical secondary forests (2016) — 1,039 citations
- ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models (2014) — 1,878 citations