Modelling bryophyte distribution based on ecological information for extent of occurrence assessment

By C. Sérgio, R. Figueira, D. Draper, Rui Menezes, A. Sousa. 2007

121 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Insect Science

View Paper: https://www.semanticscholar.org/paper/fd362bc65b23f77d033aff0de26e839746a86734

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In Ecological Modeling

In Ecology, Evolution, Behavior and Systematics

In Insect Science

Citations in the corpus

Habitat suitability modelling to correlate gene flow with landscape connectivity (2008, methodology): “Understanding the importance of each environmental variable is necessary for habitat management, but such quantification is not available from other models using presence-only data (Sérgio et al. 2007).”
Ocean‐scale prediction of whale shark distribution (2012, background): “…their application in non-terrestrial systems is rare with only a few marine examples such as seagrass beds (Kelly et al., 2001), bryophytes (Sérgio et al., 2007), coral communities (Garza-Pérez et al., 2004; Beger & Possingham, 2008; Tittensor et al., 2009; Mellin et al., 2010),…”
Habitat suitability for marine fishes using presence-only modelling and multibeam sonar (2010, methodology): “…predictor variables, the influence of response variables (i.e. the ecological characteristics of the species occurrence data) has been more widely investigated (e.g. Araújo & Williams 2000, Pearce & Ferrier 2000, Manel et al. 2001, Pearce et al. 2001, Segurado & Araújo 2004, Sérgio et al. 2007).”
Species Distribution Modeling in the Tropics: Problems, Potentialities, and the Role of Biological Data for Effective Species Conservation (2009, methodology): “…(2006) Iberian Peninsula Methodological Same data Reptiles P-A Seoane et al. (2005) Spain Methodological Same data + Prospective sampling Birds P-A Sérgio et al. (2007) Portugal Species conservation Informal validation Bryophytes P Silva et al. (2002) Portugal Methodological Partitioning Birds…”
Using species distribution models to inform IUCN Red List assessments (2014, methodology): “Recent studies have used SDMs to estimate species ranges and occupied areas for the purposes of informing IUCN Red List assessments (e.g. Cardoso et al. 2011; Jiménez-Alfaro et al. 2012; Papes and Gaubert 2007; Pena et al. 2014; Sergio et al. 2007).”
The sizes of species’ geographic ranges (2009, methodology): “However, more formal methods have also been applied, including calculation of the area that lies within (i) a minimum convex polygon or convex hull embracing the occurrences of a species (Shaw, Musina & Gichuki 2003; Standards and Petitions Working Group 2006; Miller, Enright & Lamont 2007; Sergio ”
A strict maximum likelihood explanation of MaxEnt, and some implications for distribution modelling (2013, methodology): “…have confirmed the results of Elith et al. (2006), ranking MaxEnt as the best method or among the best (Hernandez et al. 2006, Guisan et al. 2007, Sérgio et al. 2007, Wang et al. 2007, Wisz et al. 2008, Roura-Pascual et al. 2009, Tognelli et al. 2009, Václávik & Meentemeyer 2009, Veloz 2009,…”
Ecological niche modelling as a technique for assessing threats and setting conservation priorities for Asian slow lorises (Primates: Nycticebus) (2009, result): “As with other studies of this kind (e.g. Raxworthy et al., 2003; Papes & Gaubert, 2007; Pearson et al., 2007; Sergio et al., 2007; Ward, 2007), the resulting MaxEnt predictions demonstrate how ENM uses environmental variables to generate outputs not possible purely from observed localities.”