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Tsunamis and storms cause considerable coastal flooding, numerous fatalities, destruction of structures, and erosion. The characterization of energy and frequency associated with each wave contribute to the risk assessment in coastal regions. Coastal boulder deposits represent a physical proof of extreme inundation and allow us to study the effects of marine floods further back in time than instrumental and historical records. Age estimation of these deposits is challenging due to lack of materials (such as sand, shells, corals, or organic matter) that retain information about the passage of time. Lichenometry, a simple age estimation method, which is cost-effective, quick to apply, and non-destructive, is here proposed as a solution. A lichen growth model for a calcium-tolerant lichen species was developed and used to estimate the age of a boulder deposit related to extreme marine inundation(s) in Portugal. Estimated ages indicate several very recent events (<700 years) for most of the boulders' stabilization and agree with results obtained with optically stimulated luminescence of marine sands found beneath boulders. Frequent and recent boulder transport implies a storm-origin for this deposit. These conclusions contrast with other works describing identical deposits that are attributed to paleotsunamis. This study presents a methodology using lichenometry as a successful alternative for age estimation in rocky coastal settings. These results offer an alternative explanation for coastal boulder deposits found on the west coast of Portugal. [ABSTRACT FROM AUTHOR]

During a pre-congress excursion (23 July 2019) to the Sintra mountain range, led by the organizers of the XXII Symposium of Cryptogamic Botany, we found foliicolous (epiphyllous) lichens growing abundantly in the "enchanted forest" of Peninha (38°46'9.06"N, 9°27'32.27"W), I c i . 40 km north-west of Lisbon. However, while diverse indigenous tree species comprise laurisilva, the "enchanted forest" of Peninha is principally just I Pittosporum undulatum i Vent., an Australian tree introduced to the area in the 19th century. Elsewhere in the Iberian Peninsula, where foliicolous lichens occur on native vegetation, the main substratum is usually boxwood leaves ( I Buxus sempervirens i L.), but that shrub/tree was not seen at the Peninha site. A number of authors have considered the role of non-native tree plantations in potentially reducing epiphytic lichen diversity (Quine & Humphrey [14]; Nascimbene I et al i . [Extracted from the article]

Abstract: Functional groups of epiphytic lichens are proposed as indicators of air quality in a Mediterranean urban area in the south of Portugal. Local land use: traffic (for areas near roads), green (for park areas) and house (residential areas); and bark pH are applied as proxies of air quality. Epiphytic lichen diversity was evaluated using lichen diversity values (LDV) methodology. Global LDV value decreases on traffic areas, as well as absolute values of LDV for the examined functional groups, which are lower in traffic areas than green and house areas. However, the composition of lichen communities shows a different pattern, based on the relative values of functional groups. Some functional groups, such as oligotrophic, hygrophytic and acidophilous lichens, are sensitive to pollution caused by traffic, and their richness declines markedly close to roads. These groups are well represented in areas without traffic, especially in park and residential areas. Otherwise, eutrophic, xerophytic and basophilous lichens are more represented in traffic areas. Sensitive functional groups seemed to be more reliable than total diversity for evaluating the impact of atmospheric pollution on small urban areas. [Copyright &y& Elsevier]

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In most studies correlating health outcomes with air pollution, personal exposure assignments are based on measurements collected at air-quality monitoring stations not coinciding with health data locations. In such cases, interpolators are needed to predict air quality in unsampled locations and to assign personal exposures. Moreover, a measure of the spatial uncertainty of exposures should be incorporated, especially in urban areas where concentrations vary at short distances due to changes in land use and pollution intensity. These studies are limited by the lack of literature comparing exposure uncertainty derived from distinct spatial interpolators. Here, we addressed these issues with two interpolation methods: regression Kriging (RK) and ordinary Kriging (OK). These methods were used to generate air-quality simulations with a geostatistical algorithm. For each method, the geostatistical uncertainty was drawn from generalized linear model (GLM) analysis. We analyzed the association between air quality and birth weight. Personal health data ( n = 227) and exposure data were collected in Sines (Portugal) during 2007–2010. Because air-quality monitoring stations in the city do not offer high-spatial-resolution measurements ( n = 1), we used lichen data as an ecological indicator of air quality ( n = 83). We found no significant difference in the fit of GLMs with any of the geostatistical methods. With RK, however, the models tended to fit better more often and worse less often. Moreover, the geostatistical uncertainty results showed a marginally higher mean and precision with RK. Combined with lichen data and land-use data of high spatial resolution, RK is a more effective geostatistical method for relating health outcomes with air quality in urban areas. This is particularly important in small cities, which generally do not have expensive air-quality monitoring stations with high spatial resolution. Further, alternative ways of linking human activities with their environment are needed to improve human well-being. [ABSTRACT FROM AUTHOR]