Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Análisis de Preferencia de Microhábitat× | Modelado de Nicho× | |
|---|---|---|
| Campo≠ | Ciencias veterinarias | Ecología |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1970s–1980s (formalized) | 1999 |
| Autor original≠ | Multiple contributors (Morris, Manly, Johnson, and others) | Steven Phillips and David Stockwell |
| Tipo≠ | Quantitative observational method | species distribution prediction |
| Fuente seminal≠ | Morris, D. W. (1987). Ecological scale and habitat use. Ecology, 68(2), 362–369. DOI ↗ | Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3-4), 231-259. DOI ↗ |
| Alias≠ | habitat selection analysis, microhabitat use analysis, fine-scale habitat preference study, microhabitat utilization assessment | species distribution modeling, habitat suitability modeling, ecological niche model, MaxEnt |
| Relacionados≠ | 1 | 4 |
| Resumen≠ | Microhabitat Preference Analysis is a quantitative ecological method used to determine which fine-scale environmental features — such as vegetation structure, substrate type, temperature, or cover — animals actively select beyond what is randomly available to them. Widely applied in veterinary science, wildlife biology, and ethology, it compares the characteristics of locations an animal uses against those of randomly sampled available locations to infer habitat preference, avoidance, or random use. | Niche modeling, also called species distribution modeling (SDM), predicts the geographic range and habitat suitability of species using presence-only or presence-background occurrence data and environmental variables. MaxEnt (Maximum Entropy, Phillips et al. 2006) and GARP (Genetic Algorithm for Rule-set Prediction, Stockwell & Peters 1999) are two prominent algorithms. These methods identify the environmental conditions under which species are likely to occur, enabling prediction of distribution beyond sampled areas and assessment of habitat suitability across landscapes. |
| ScholarGateConjunto de datos ↗ |
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