Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uundaji wa Niche× | Uchanganuzi wa Uwezekano wa Kuishi kwa Idadi ya Watu× | |
|---|---|---|
| Nyanja | Ikolojia | Ikolojia |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1999 | 1981 |
| Mwanzilishi≠ | Steven Phillips and David Stockwell | Mark Shaffer |
| Aina≠ | species distribution prediction | extinction risk assessment |
| Chanzo asilia≠ | 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 ↗ | Shaffer, M. L. (1981). Minimum population sizes for species conservation. BioScience, 31(2), 131-134. DOI ↗ |
| Majina mbadala≠ | species distribution modeling, habitat suitability modeling, ecological niche model, MaxEnt | PVA, extinction risk, minimum viable population, MVP |
| Zinazohusiana | 4 | 4 |
| Muhtasari≠ | 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. | Population Viability Analysis (PVA), introduced by Shaffer (1981), estimates the probability that a population will persist over a given time period under specified conditions. PVA combines demographic models (Leslie matrices, IPMs) with stochastic simulation to project population trajectories, quantifying extinction risk. This allows conservation planners to assess whether a population will likely persist, evaluate management scenarios, and estimate the minimum viable population (MVP) size for long-term persistence. PVA is a decision-support tool, not a precise predictor. |
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