Multivariate geostatistical methods for analysis of relationships between ecological indicators and environmental factors at multiple spatial scales - Ribeiro, Manuel Castro; Pinho, Pedro; Llop, Esteve; Branquinho, Cristina; Sousa, António Jorge; Pereira, Maria João; Castro, Manuel; Jorge, António; João, Maria (Ecological Indicators, 2013)
As all biodiversity-related variables, ecological indicators are influenced by environmental factors working at different spatial scales. However, assessing the relationship between environmental factors and ecological indicators is limited to a set of spatial scales determined a priori. This a priori assumption can hide important relationships, especially for ecological indicators with a complex spatial structure that can be driven, for example, by the influence of multiple pollutants with different dispersion ranges or by the influence of local and regional factors such as land-cover and climate. To relate ecological indicators and environmental factors without assuming a priori spatial scales of analysis, we used a Linear Model of Coregionalization. This method has been used in literature to analyze the joint distribution of biodiversity variables. Here we show that it can be used to gain insight into spatial patterns of relationships between ecological indicators and underlying environmental factors. We applied this method to a region of south-west Europe, relating data from land-cover, altitude and climate with an ecological indicator, the abundance of fruticose lichen species, known to be very sensitive to multiple environmental factors. Based on variogram analysis we identified distinct spatial scales of relationships between the ecological indicator and environmental factors. For each spatial scale we described relationships using Principal Component Analysis applied to the coregionalization matrices. This way we could assess how strong the relationship between each environmental factor and ecological indicator at each spatial scale was: at medium scales (c. 15 km) open spaces areas (a proxy for particle emissions) were more important; at larger scales (c. 45 km) open spaces, artificial areas (a proxy for gaseous pollutants) and also climate were preponderant. Thus, multivariate geostatistics provided a tool to improve knowledge on relationships between ecological indicators and environmental factors at multiple spatial scales without setting a priori spatial scales of analysis.
Keywords: biomonitoring; linear model of coregionalization; Multivariate geostatistics; spatial analysis

A step towards the use of biomonitors as estimators of atmospheric PAHs for regulatory purposes. - Augusto, Sofia; Pereira, Maria J.; Máguas, Cristina; Branquinho, Cristina (Chemosphere, 2013)
One of the main drawbacks of using lichens to monitor atmospheric PAHs has been reported as the inexistence of studies aiming to translate PAH values in lichens into the atmospheric equivalents ones, in order to use this information for regulatory purposes. In this work, PAH concentrations in lichens were compared with PAH concentrations measured in a conventional active sampler in an outdoor environment for a 9-month span. Significant positive correlations between HMW-PAHs, Σ16 EPA-PAHs, and BaP equivalent concentrations in lichens and those in air (TSP) were found. Concentrations of Σ16 EPA-PAHs in lichens and air showed a seasonal variation, with highest values during winter and lowest values during summer. Meteorological variables - temperature, atmospheric pressure, relative humidity, and wind speed - showed to significantly influence PAH concentrations in both lichens and air. Based on the significant linear correlations, equations for translating PAH concentrations measured in lichens into equivalent ones for air were proposed for the first time, allowing a broader use of lichens' information regarding PAHs in monitoring schemes and decision-making.
The following values have no corresponding Zotero field: publisher: Elsevier Ltd accession-num: 23668962
Keywords: Air; BaP; Biomonitors; Environment; Human health; PAHs

Using lichen functional diversity to assess the effects of atmospheric ammonia in Mediterranean woodlands - Pinho, Pedro; Dias, Teresa; Cruz, Cristina; Sim Tang, Y; Sutton, Mark A; Martins-Loução, Maria-Amélia; Máguas, Cristina; Branquinho, Cristina (Journal of Applied Ecology, 2011)
1. Atmospheric ammonia (NH3) is one of the main drivers for ecosystem changes world-wide, including biodiversity loss. Modelling its deposition to evaluate its impact on ecosystems has been the focus of many studies. For that, universal indicators are needed to determine and compare the early effects of NH3 across ecosystems. 2. We evaluate the effects of atmospheric NH3 in ecosystems using lichens, which are one of the most sensitive communities at the ecosystem level. Rather than measuring total diversity, we use a functional diversity approach because this is potentially a more universal tool. 3. We evaluated the spatial and temporal patterns of atmospheric NH3 concentrations ([NH3]atm) emitted from a point-source over a 1-year period in a cork oak Mediterranean woodland. We observed a temporal pattern of [NH3]atm, with maximum concentrations during autumn. 4. The distribution of lichen species was c. 90% explained by [NH3]atm. The tolerance of lichen species to atmospheric NH3, based on expert knowledge from literature, was tested for the first time against direct measurements of atmospheric NH3. Most species were well classified, with the exception of Lecanora albella and Chrysothrix candelaris, which were more tolerant than expected. Our updated lichen classification can be used to establish lichen functional groups that respond to atmospheric NH3, and these can be used in other Mediterranean countries. 5. Increasing [NH3]atm led to a complete replacement of oligotrophic by nitrophytic species within 65 m of the NH3 source. The geostatistical analysis of functional diversity variables yielded a spatial model with low non-spatial variance, indicating that these variables can cope robustly with high spatial variation in NH3. 6. Synthesis and applications. Our results support the use of functional diversity variables, such as a lichen diversity value, as accurate and robust indicators of the effects of atmospheric NH3 on ecosystems. The spatial modelling of these indicators can provide information with high spatial resolution about the effects of atmospheric NH3 around point- and diffuse sources. As this methodology is based on functional groups, it can be applied to monitor both the impact of atmospheric NH3 and the success of mitigation strategies.
Keywords: Agriculture; atmospheric NH3; biodiversity loss; Cattle; Ecological indicators; Global change; spatial analysis