A comparison of network and clustering methods to detect biogeographical regions

By Nathaniel J. Bloomfield, Nunzio Knerr, Francisco Encinas-Viso. 2018

175 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/0f2933f64ca037d62eb3eeb055ba3161ec6252a7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

1. Fabien Leprieur
2. T. Oberdorff
3. Boris Leroy
4. B. Hugueny
5. P. Tedesco

In Ecology, Evolution, Behavior and Systematics

1. Fabien Leprieur
2. T. Oberdorff
3. B. Hugueny
4. P. Tedesco

In Nature and Landscape Conservation

1. Fabien Leprieur
2. T. Oberdorff
3. Boris Leroy
4. B. Hugueny
5. P. Tedesco
6. G. Grenouillet
7. S. Brosse
8. Julian D. Olden

Citations in the corpus

• Global biogeographical regions of freshwater fish species (2019, methodology): “However, at subregional and finer scales, tran‐ sitions are likely to stand out as separate zones (Bloomfield et al., 2017), which may not necessarily be an appealing property since the participation coefficient is informative enough to describe transition zones.”
• Beyond trees: Biogeographical regionalization of tropical Africa (2018, unknown): “All clusters identified by the network-based approach should not necessarily be interpreted as distinct bioregions, since this method also allows to identify “transition zones” between bioregions (Bloomfield et al., 2017; Vilhena & Antonelli, 2015).”