Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Le cadre DPSIR× | Modèles de distribution d'espèces (MaxEnt)× | |
|---|---|---|
| Domaine | Durabilité | Durabilité |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1993 | 2004 |
| Auteur d'origine≠ | OECD, refined by European Environment Agency | Steven Phillips, Robert Anderson, Robert Schapire |
| Type≠ | Diagnostic framework | Statistical learning algorithm |
| Source fondatrice≠ | European Environment Agency (1999). Environmental Indicators: Typology and Overview. EEA Technical Report No. 25. Copenhagen: EEA. link ↗ | Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modelling of species geographic distributions. Ecological Modelling, 190(3-4), 231-259. DOI ↗ |
| Alias | DPSIR, PSR, Pressure-State-Response | MaxEnt, SDM, Maximum Entropy Model |
| Apparentées | 3 | 3 |
| Résumé≠ | The DPSIR Framework (Driving force, Pressure, State, Impact, Response) is a diagnostic and policy tool developed by the OECD (1993) and refined by the European Environment Agency (1999) to structure environmental and sustainability problems. It organizes causal relationships from economic activity through to policy interventions, enabling governments and organizations to identify where to intervene for environmental improvement. | Species Distribution Models (SDMs) using Maximum Entropy (MaxEnt) are statistical methods developed by Phillips, Anderson, and Schapire (2004) to predict where species are likely to occur based on known occurrence points and environmental variables. MaxEnt has become one of the most widely used algorithms in conservation biology and biogeography for mapping suitable habitat and assessing climate change impacts. |
| ScholarGateJeu de données ↗ |
|
|