Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Анализ Circuitscape× | Нишевое моделирование× | |
|---|---|---|
| Область | Экология | Экология |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2008 | 1999 |
| Автор метода≠ | Brad McRae | Steven Phillips and David Stockwell |
| Тип≠ | movement and connectivity modeling | species distribution prediction |
| Основополагающий источник≠ | Bradford, D. F., McCreary, D. D., & Groves, C. R. (2014). Optimizing sampling for large-area habitat assessment. Ecological Monographs, 84(3), 351-375. link ↗ | 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 ↗ |
| Другие названия≠ | circuit theory, resistance distance, connectivity analysis, landscape conductance | species distribution modeling, habitat suitability modeling, ecological niche model, MaxEnt |
| Связанные | 4 | 4 |
| Сводка≠ | Circuitscape, developed by Brad McRae (2008), applies circuit theory from electrical engineering to predict organism movement and genetic connectivity across landscapes. The method treats landscapes as electrical networks where habitat quality is resistance and organism movement is electrical current. By analogy, organisms diffusing through a landscape follow paths determined by landscape resistance: corridors of low resistance (good habitat) are preferentially used. Circuitscape predicts movement probabilities, identifies critical corridors, and quantifies connectivity between habitat patches. | 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. |
| ScholarGateНабор данных ↗ |
|
|