Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Дистанционно изследване× | Population Viability Analysis× | |
|---|---|---|
| Област | Екология | Екология |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1993 | 1981 |
| Създател≠ | Stephen Buckland | Mark Shaffer |
| Тип≠ | population abundance estimation | extinction risk assessment |
| Основополагащ източник≠ | Buckland, S. T., Anderson, D. R., Burnham, K. P., Laake, J. L., Borchers, D. L., & Thomas, L. (1993). Distance Sampling: Estimating Abundance of Biological Populations. Chapman and Hall, London. link ↗ | Shaffer, M. L. (1981). Minimum population sizes for species conservation. BioScience, 31(2), 131-134. DOI ↗ |
| Други названия | line transect, point transect, distance estimation, detection probability | PVA, extinction risk, minimum viable population, MVP |
| Свързани | 4 | 4 |
| Резюме≠ | Distance sampling is a statistical method for estimating population abundance from data on distances between observers and detected individuals. Developed by Buckland and colleagues (1993) and formalized in the software Distance, this approach accounts for imperfect detection: animals far from an observer are less likely to be detected. By modeling the detection function (probability of detecting an animal at various distances), distance sampling produces unbiased estimates of abundance and density even when detection is incomplete. | 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. |
| ScholarGateНабор от данни ↗ |
|
|