G. Newell
Ecological Modeling · 2006–2019
A researcher in the Science corpus: 9 papers; trusts 79 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Ecological Modeling — 212 citations into it; #562 of 2,530 by trust here, #644 by citations
- Nature and Landscape Conservation — 195 citations into it; #1,503 of 6,941 by trust here, #1,600 by citations
- Ecology — 149 citations into it; #1,998 of 10,717 by trust here, #2,597 by citations
- Ecology, Evolution, Behavior and Systematics — 51 citations into it
- Statistics and Probability — 25 citations into it
- Global and Planetary Change — 24 citations into it
- Artificial Intelligence — 20 citations into it
- Genetics — 18 citations into it
Whom G. Newell trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Canran Liu
- Antoine Guisan
- Richard G. Pearson
- Miguel B. Araújo
- Steven J. Phillips
- Wilfried Thuiller
- A. Townsend Peterson
- Jorge M. Lobo
- David R. B. Stockwell
- Catherine H. Graham
Who trusts G. Newell overall
Papers from G. Newell's perspective
Ordered by how strongly the researchers G. Newell trusts endorse each paper. Same corpus, a different order for every researcher.
- Predicting species distribution: offering more than simple habitat models. (Ecology Letters)
- Predictive habitat distribution models in ecology
- Extinction risk from climate change (Nature)
- The meaning and use of the area under a receiver operating characteristic (ROC) curve.
- Maximum entropy modeling of species geographic distributions
- Spatial prediction of species distribution: an interface between ecological theory and statistical modelling
- Generalized linear and generalized additive models in studies of species distributions: setting the scene
- Modelling species distributions in Britain: a hierarchical integration of climate and land-cover data
- Patterns and uncertainties of species' range shifts under climate change
- Evaluating the predictive performance of habitat models developed using logistic regression
Their papers
- The effect of sample size on the accuracy of species distribution models: considering both presences and pseudo‐absences or background sites (2019) — 146 citations
- A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels (2019) — 493 citations
- On the selection of thresholds for predicting species occurrence with presence‐only data (2015) — 661 citations
- Selecting thresholds for the prediction of species occurrence with presence‐only data (2013) — 1,471 citations
- Measuring and comparing the accuracy of species distribution models with presence–absence data (2011) — 440 citations
- How Useful Are Species Distribution Models for Managing Biodiversity under Future Climates (2010) — 372 citations
- Measuring the accuracy of species distribution models: a review (2009) — 119 citations
- International articles : the growth of REIT markets in Asia (2006) — 113 citations
- Factors Influencing Hotel Investment Decision-Making (2006) — 131 citations