Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Análise de Preferência de Micro-habitat× | Modelagem de Nicho× | |
|---|---|---|
| Área≠ | Ciências veterinárias | Ecologia |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 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 |
| Fonte 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 ↗ |
| Outros nomes≠ | 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 |
| Resumo≠ | 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. |
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