Uncertainty analysis of transient population dynamics Export

@article{citeulike:3906814, abstract = {Two types of demographic analyses, perturbation analysis and uncertainty analysis, can be conducted to gain insights about matrix population models and guide population management. Perturbation analysis studies how the perturbation of demographic parameters (survival, growth, and reproduction parameters) may affect the population projection, while uncertainty analysis evaluates how much uncertainty there is in population dynamic predictions and where the uncertainty comes from. Previously, both perturbation analysis and uncertainty analysis were conducted on the long-term population growth rate. However, the population may not reach its equilibrium state, especially when there is management by harvesting or hunting. Recently, there has been an increased interest in short-term transient dynamics, which can differ from asymptotic long-term dynamics. There are currently techniques to conduct perturbation analyses of short-term transient dynamics, but no techniques have been proposed for uncertainty analysis of such dynamics. In this study, we introduced an uncertainty analysis technique, the general Fourier Amplitude Sensitivity Test (FAST), to study uncertainties in transient population dynamics. The general FAST is able to identify the amount of uncertainty in transient dynamics and contributions by different demographic parameters. We applied the general FAST to a mountain goat ( Oreamnos americanus ) matrix population model to give a clear illustration of how uncertainty analysis can be conducted for transient dynamics arising from matrix population models.}, author = {Xu, C. and Gertner, G.}, citeulike-article-id = {3906814}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.ecolmodel.2008.10.005}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/S030438000800481X}, day = {10}, doi = {10.1016/j.ecolmodel.2008.10.005}, issn = {03043800}, journal = {Ecological Modelling}, keywords = {population\_modeling, uncertainty}, month = {February}, number = {3}, pages = {283--293}, posted-at = {2009-01-19 05:05:51}, priority = {2}, title = {Uncertainty analysis of transient population dynamics}, url = {http://dx.doi.org/10.1016/j.ecolmodel.2008.10.005}, volume = {220}, year = {2009} }

TY - JOUR ID - citeulike:3906814 L3 - citeulike-article-id:3906814 N2 - Two types of demographic analyses, perturbation analysis and uncertainty analysis, can be conducted to gain insights about matrix population models and guide population management. Perturbation analysis studies how the perturbation of demographic parameters (survival, growth, and reproduction parameters) may affect the population projection, while uncertainty analysis evaluates how much uncertainty there is in population dynamic predictions and where the uncertainty comes from. Previously, both perturbation analysis and uncertainty analysis were conducted on the long-term population growth rate. However, the population may not reach its equilibrium state, especially when there is management by harvesting or hunting. Recently, there has been an increased interest in short-term transient dynamics, which can differ from asymptotic long-term dynamics. There are currently techniques to conduct perturbation analyses of short-term transient dynamics, but no techniques have been proposed for uncertainty analysis of such dynamics. In this study, we introduced an uncertainty analysis technique, the general Fourier Amplitude Sensitivity Test (FAST), to study uncertainties in transient population dynamics. The general FAST is able to identify the amount of uncertainty in transient dynamics and contributions by different demographic parameters. We applied the general FAST to a mountain goat ( Oreamnos americanus ) matrix population model to give a clear illustration of how uncertainty analysis can be conducted for transient dynamics arising from matrix population models. IS - 3 JF - Ecological Modelling SN - 03043800 EP - 293 TI - Uncertainty analysis of transient population dynamics VL - 220 SP - 283 KW - population_modeling KW - uncertainty AU - Xu, C AU - Gertner, G PY - 2009/02/10/ UR - http://dx.doi.org/10.1016/j.ecolmodel.2008.10.005 ER -