Nos complace anunciar que el Departamento ha lanzado su nueva página web, diseñada para ofrecer una experiencia más intuitiva, moderna y accesible para toda la comunidad universitaria y el público en...
Destacados
Actualidad
Últimas publicaciones
Pardos, M., Calama, R., Alejano, R., Madrigal, G., Calzado, A., Hevia, A., Tíscar, P.A., Vázquez-Piqué, J. 2025. Carbon storage potentiality in successional and secondary old growth forests. European Journal of Forest Research, 144(1): 193-211
As the capacity of old-growth forests to store carbon until very old ages has been proved, their conservation has become a mitigation strategy to reduce net CO2 emissions and moderate climate warming. We investigated the effect of tree age, competition and climate on aboveground standing biomass and C stocks over a 50-years period in two Spanish forest stands (successional Pinus pinea forests with old-growth attributes, OGFA and secondary Pinus nigra old-growth Forest, SOGF), combining dendroecological methods with forest inventory data, using semiparametric modeling.
Castro-Gutiérrez, J., Gutiérrez-Estrada, J.C., Bellido, J.J., Báez, J.C. 2025. Distribution modelling of jellyfish in Spanish coastal areas: An approach based on the maximum entropy principle. Ocean and Coastal Management 266, 107694.
Jellyfish blooms are natural events with significant ecological and socio-economic impacts, particularly in regions like the Andalusian Mediterranean coast, where tourism is an important industry. This study employs Maximum Entropy (MaxEnt) species distribution model to predict jellyfish presence using citizen science data from the Infomedusa app and environmental variables derived from the Copernicus platform. In particular, while users reports do not enforce species-level identification, Pelagia noctiluca likely dominated the sightings in our study region.
Pulido-Calvo, I., Gutiérrez-Estrada, J.C., Sanz-Fernández, V. 2024. Persistent neural calibration for discharges modelling in drought-stressed catchments. Expert Systems with Applications 249(c), 123785
Cross-sector coordination between all water uses and the environmental flows is an essential target for achieving sustainable management in any hydrographic region. In this framework, a novel neural approach was developed and implemented, by the software ANNPI 1.0, to characterise and infer of the discharges regime in a specific basin using only a few attributes as independent variables. The calibration procedure is controlled by the Persistence Index (PI), which is function of a determined estimation lead-time, to facilitate the dynamic character of these simulations.