| Popis: |
Easdale and Bruzzone (2015) recently indicated that to better capture temporal patterns of rangeland dynamics, there is a need to move forward from simple measures of variability such as mean, standard deviation, and coefficient of variation (CV). They note that this is especially true in cases where long time series are available (e.g., ten or more years at a monthly resolution), as with remotely sensed data. To support this viewpoint, Easdale and Bruzzone (2015) presented multiple simulated time series datasets that had same mean and standard deviation, but different seasonal patterns. These seasonal pattern differences were only captured using Fourier analysis (i.e., power spectrum analysis, Chatfield, 1996), highlighting the utility of the method. Here, however, we show the opposite phenomenon, where multiple datasets can show similar temporal patterns from Fourier analysis, but have different and meaningful means, standard deviations, and CVs. Fil: Irisarri, Jorge Gonzalo Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Texeira González, Marcos Alexis. Universidad de Buenos Aires. Facultad de Agronomia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Reeves, Justin. United States Department Of Agriculture. Agricultural Research Service; Estados Unidos |
