1 resultado para DeepLearning NeuralNetwork StackedDenoisingAuto-encoder ArtificialIntelligence IntelligenzaArtificiale RetiNeurali TimeSeries SerieStoriche SerieTemporali Forecasting Previsione Auto-encoder
em National Center for Biotechnology Information - NCBI
Resumo:
Although most ecologists agree that both top-down and bottom-up forces (predation and resource limitation, respectively) act in concert to influence populations of herbivores, it has proven difficult to estimate the relative contributions of such forces in terrestrial systems. Using a combination of time–series analysis of population counts recorded over 16 years and experimental data, we present the first estimates of the relative roles of top-down and bottom-up forces on the population dynamics of two terrestrial insect herbivores on the English oak (Quercus robur). Data suggest that temporal variation in winter moth, Operophtera brumata, density is dominated by time-lagged effects of pupal predators. By comparison, spatial variation in O. brumata density is dominated by host–plant quality. Overall, top-down forces explain 34.2% of population variance, bottom-up forces explain 17.2% of population variance, and 48.6% remains unexplained. In contrast, populations of the green oak tortrix, Tortrix viridana, appear dominated by bottom-up forces. Resource limitation, expressed as intraspecific competition among larvae for oak leaves, explains 29.4% of population variance. Host quality effects explain an additional 5.7% of population variance. We detected no major top-down effects on T. viridana populations. An unknown factor causing a linear decline in T. viridana populations over the 16-year study period accounts for most of the remaining unexplained variance. We discuss the observed differences between the insect species and the utility of time–series analysis as a tool in assessing the relative importance of top-down and bottom-up forces on herbivore populations.