Thermal models, lithosphere thickness and heat flow in South Portugal. Some comments about the subject

Reinterpretation of old heat flow data or use of new data and new techniques of detection of the temperature under the surface have conducted to new heat flow density values in some regions of the globe. The problem of ice melting in Greenland and Antarctica caught the public's attention to the importance of knowledge on heat flow values and thermal structure of the globe. In the last years, several models were presented trying to obtain lithosphere and Moho thickness of the Iberia Peninsula. The work we intend to present is related with the SW part of the Iberia Peninsula ( south of the Ossa Morena zone, South Portuguese Zone and Algarve). The results obtained show a decrease in the thickness of the crust and the lithosphere in this region. Density anomalies in the crust are also referred. I intend to make the connection between the results of these models and the heat flow thermal conductivity, heat production and geological data available for the region, trying to explain the results of heat flow density data obtained.

Occurrence and abundance models of threatened plant species: Applications to mitigate the impact of hydroelectric power dams

Species occurrence and abundance models are important tools that can be used in biodiversity conservation, and can be applied to predict or plan actions needed to mitigate the environmental impacts of hydropower dams. In this study our objectives were: (i) to model the occurrence and abundance of threatened plant species, (ii) to verify the relationship between predicted occurrence and true abundance, and (iii) to assess whether models based on abundance are more effective in predicting species occurrence than those based on presence–absence data. Individual representatives of nine species were counted within 388 randomly georeferenced plots (10 m × 50 m) around the Barra Grande hydropower dam reservoir in southern Brazil. We modelled their relationship with 15 environmental variables using both occurrence (Generalised Linear Models) and abundance data (Hurdle and Zero-Inflated models). Overall, occurrence models were more accurate than abundance models. For all species, observed abundance was significantly, although not strongly, correlated with the probability of occurrence. This correlation lost significance when zero-abundance (absence) sites were excluded from analysis, but only when this entailed a substantial drop in sample size. The same occurred when analysing relationships between abundance and probability of occurrence from previously published studies on a range of different species, suggesting that future studies could potentially use probability of occurrence as an approximate indicator of abundance when the latter is not possible to obtain. This possibility might, however, depend on life history traits of the species in question, with some traits favouring a relationship between occurrence and abundance. Reconstructing species abundance patterns from occurrence could be an important tool for conservation planning and the management of threatened species, allowing scientists to indicate the best areas for collection and reintroduction of plant germplasm or choose conservation areas most likely to maintain viable populations.