Search

An improved pattern informatics (PI) method, inspired by the soup-of-groups model, is developed in this study. This improved method reveals its potential in reducing the noise that, when the classical PI is applied, can yield misleading conclusions about the existence of "hotspots" in the vicinity of the epicenter of a strong earthquake. The application of this new method to Italian seismicity from 1985 to 2018 properly reveals "hotspots" around the two strongest earthquakes that occurred in 2009 (L'Aquila earthquake) and 2016 (Norcia earthquake), suggesting its utility in studies devoted to earthquake prediction. [ABSTRACT FROM AUTHOR]

During the last millennia, all forests of the Italian Alps have been heavily affected by human land-use. Consequently, forest structures have been modified, and there are no old growth remains. In the last decades, however, many forests have been withdrawn from regular management, because wood production was unprofitable, and left to develop naturally. At the same time, in currently managed forests, silvicultural systems able to develop or maintain old-growth characteristics are being required. The aim of this paper was to assess the status and developmental dynamics of old-growth characteristics in mixed beech, silver fir, and Norway spruce montane forests of the eastern Italian Alps. We selected along a naturalness gradient (a) three old-growth forests in Bosnia and Montenegro (due to the lack of old-growth forests in the Italian Alps), (b) two forests withdrawn from regular management for at least 50 years, and (c) three currently managed forests. In each forest, we analysed 17 structural attributes, in order to assess their value as indicators of old-growth condition. Old-growth forests were characterized by significantly higher amounts of live and dead biomass, share of beech in the dominant and regeneration layers, and number of large trees. The diameter distribution was best described as a rotated sigmoid, differently from currently and formerly managed forest. We discuss the differences in old-growth characteristics across the management gradient and use our results to evaluate the effectiveness of retention prescriptions currently applied in the studied regions in maintaining or promoting old-growth structural attributes in managed forests. [ABSTRACT FROM AUTHOR]

Pattern informatics (PI) algorithm, which was introduced at the beginning of past decade, uses instrumental earthquake catalogs to investigate the time-dependent rate of seismicity in the study area and, based on the information from past events, calculates the probabilities for the occurrence of future large earthquakes. The main measure in this method is the number of events above a specified magnitude threshold M that is counted over a gridded area. PI has been applied in several regions of the world and different variants of the method have been developed over the past decade. Hence, the problem of formally evaluating and comparing the performances of the different PI variants needs to be addressed from an operational perspective, in order to identify the preferred application scheme and as well as to improve the performances of the method. In this study, PI is applied for the first time to the retrospective analysis of the earthquake catalogs of Iran and Italy, so as to check whether this method could forecast the past large events in these two regions with different level of data completeness and complex seismotectonic setting. The original PI algorithm and one of its modified variants, as well as the relative intensity (RI) model, are used to check the stability and statistical significance of the obtained results. In order to assess and compare the obtained results, the performances of the different PI variants are analyzed considering different evaluation strategies, which turn out to provide significantly different scores even for the same algorithm variant. We show that a critical point in the assessment of the obtained results is related with the definition and quantification of the space uncertainty of the issued forecasts, that is, with the extent of the territory where large earthquakes are to be expected. Accordingly, we emphasize the need for an appropriate definition of the evaluation strategies, clearly and unambiguously indicating the area where a large earthquake has to be expected. The study shows that, with respect to application in Iran and Italy, the performances of PI algorithm (both original and modified variants) are highly dependent on the selected evaluation strategy and do not provide better information than the simple RI model, which does not account for temporal properties of seismicity evolution. The overall performances can be improved by introducing specific thresholds that discard the less active cells; however, being based on some posterior optimization, a rigorous prospective testing is required to assess the forecasting capability of the method. In this paper, we aim to set up the rules for such testing, including advance definition of the evaluation strategy. [ABSTRACT FROM AUTHOR]