New approaches to modelling fish―habitat relationships
By Anders Knudby, Alexander Brenning, E. LeDrew. 2010
161 citations recorded by the source corpus.
Subfields: Ecology, Global and Planetary Change, Nature and Landscape Conservation
View Paper: https://www.semanticscholar.org/paper/eb879b2b20b74d95e45d86ea870ce5e5ef1eb950
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Ecology
- Stefan Gößling-Reisemann
- Hilmar Hinz
- P. Maxwell
- Andrew F. Johnson
- K. Pitt
- S. Jenkins
- Rod M. Connolly
- F. Mark
In Global and Planetary Change
- Stefan Gößling-Reisemann
- Hilmar Hinz
- P. Maxwell
- Andrew F. Johnson
- K. Pitt
- S. Jenkins
- Rod M. Connolly
- F. Mark
In Nature and Landscape Conservation
- Stefan Gößling-Reisemann
- Andrew F. Johnson
- S. Jenkins
- Rod M. Connolly
- F. Mark
- H. Poertner
- Hauke Reuter
- J. Hiddink
Citations in the corpus
- Primacy of seascape connectivity effects in structuring coral reef fish assemblages (2012, methodology): “BRTs provide superior predictive performance over conventional modelling techniques, such as generalised additive models and linear regression (Knudby et al. 2010).”
- Modelling climate change impacts on marine fish populations: process-based integration of ocean warming, acidification and other environmental drivers (2016, background): “Underlying assumptions of steady-state 843 relations in SDMs should always be critically examined (e.g. Guisan and Thuiller, 2005, 844 Knudby et al., 2010).”
- Linking temperate demersal fish species to habitat: scales, patterns and future directions (2013, methodology): “They are, however, not good predictors of habitat suitability for new or unsampled sites (Maravelias et al. 2003; Pittman et al. 2009; Knudby et al. 2010).”