The thermal journey of macroalgae: Four decades of temperature-induced changes in the southeastern Bay of Biscay.

Global warming is triggering significant shifts in temperate macroalgal communities worldwide, favoring small, warm-affinity species over large canopy-forming, cold-affinity species. The Cantabrian Sea, a region acutely impacted by climate change, is also witnessing this shift. This study delved into the impacts of increasing sea surface temperature on the subtidal macroalgal communities in the southeastern Bay of Biscay over the last four decades, by using data from the years 1982, 2007, 2014, and 2020. We found that temperature has shaped the community structure, with warm-affinity species steadily displacing their cold-affinity counterparts. Notably, new communities exhibited a profusion of smaller algal species, explaining the observed increased biodiversity within the area. In the last period investigated (2014-2020), we observed a partial recovery of the communities, coinciding with cooler sea surface temperatures. Shallow algal communities were more reactive to temperature variations than deeper communities, possibly associated with higher exposure to increased temperatures. Our study offered insights into the intricate relationship between the changes in ocean temperature and algal species in the southeastern Bay of Biscay, shedding light on the ongoing ecological shifts in this region.

Short-term response of macroalgal communities to ocean warming in the Southern Bay of Biscay.

Climate change is causing significant shifts in biological communities worldwide, including the degradation of marine communities. Previous research has predicted that southern Bay of Biscay canopy-forming subtidal macroalgal communities will shift into turf-forming Mediterranean-like communities by the end of the century. These predictions were based on a community-environment relationship model that used macroalgal abundance data and IPCC environmental projections. We have tested the short-term accuracy of that model by resampling the same communities and locations four years later and found the short-term predictions to be consistent with the observed communities. Changes in sea surface temperature were positively correlated with changes in the Community Temperature Index, suggesting that macroalgal communities had responded quickly to global warming. The changes over four years were significant, but canopy-forming macroalgae were more resilient in local sites with favourable temperature conditions. Our study demonstrated that updating predictive models with new data has the potential to yield reliable predictions and inform effective conservation strategies.

A spatially-modelled snapshot of future marine macroalgal assemblages in southern Europe: Towards a broader Mediterranean region?

The effect of climate change on species distribution has been the focus of much recent research, but the community-level approach remains poorly studied. Our investigation applies a present assemblage-environment relationship model for the first time to the predict changes in subtidal macroalgal assemblages in the northern Iberian Peninsula under the RCP 4.5 and RCP 8.5 climate scenarios by 2100. Water temperature is the most relevant factor in shaping assemblage distribution, whilst nutrient availability plays a secondary role. The results partially support our hypothesis that there may well be a potential meridionalisation of northern Iberian assemblages in the future. Under the most pessimistic scenario, the model projects that the north-western assemblages will remain distinct from the rest, whereas the central and eastern assemblages of the north coast of the Iberian Peninsula will come to resemble those of the Mediterranean region more closely than those of the northwest coast. This research may help predict how the biodiversity of the coastal ecosystem will respond to new environmental conditions. This is essential information for developing proper management and conservation policies.

GMM y LDA aplicado a la detección de enfermedades pulmonares / GMM and LDA Applied to Lung Diseases Detection

El propósito de este artículo es presentar metodologías que pueden ser usadas para la valoración cuantitativa de los sonidos del pulmón, así como los indicadores de desórdenes respiratorios. En este contexto, se realizaron experimentos utilizando señales normales y anormales de la respiración (LS), las cuales fueron modeladas y evaluadas utilizando principalmente la base de datos RALE y señales de sujetos saludables y no saludables, logrando hasta un 98% de eficiencia. En la práctica médica la evaluación de enfermedades respiratorias involucra a la auscultación, pero la aplicación de métodos de análisis cuantitativos de señales podría mejorar estas valoraciones. En particular, se sugiere una metodología de evaluación acústica basada en representaciones de vectores acústicos MFCC (Coeficientes Cepstrales en Frecuencia Mel), GMM (Modelos Mezclados Gaussianos) y LDA (Análisis Discriminante Lineal). Estas técnicas podrían asistir en un análisis más amplio, identificación y diagnóstico de desórdenes pulmonares manifestados por sonidos respiratorios peculiares tales como sibilancias, crepitancias y asma, y distinguiéndolos de los sonidos respiratorios normales.

This study presents experimentally tested methods, which can be used for a quantitative assessment of respiratory sounds as the indicators of pulmonary disorders. In particular, conducted experiments considered both normal and abnormal lung sounds (LS). As a part of the RALE Database, signals were recorded from healthy subjects and those with respiratory disorders. Current medical practices including evaluation of respiratory diseases often involve qualitative and frequently subjective auscultation. However, the application of quantitative signal analysis methods could improve the assessments of these diseases. In particular, we utilized acoustic evaluation methodologies based on the MFCC (Mel frequency Cepstral Coefficients) acoustic vectors representation, GMM (Gaussian Mixed Models), and LDA (Linear Discriminant Analysis). To assure the validity of determined class models representing diagnostic classification, the LS signals were cross validated within sequential sets of respiratory cycles for a given subject as well as cross correlated within the specific groups of subjects representing particular conditions of normal or given class of abnormal pulmonary functions. Higher order MFCC vectors, including 9, 10 and 11 Gaussian mixtures, resulted in improved classification of the LS attributes, reached up to 98% of efficiency recognition. This documented automated classification of LS makes it suitable for a more efficient mass screening of respiratory disorders. In particular, the presence of peculiar sounds such as crackles and wheezes lead to more robust models thus reflecting the useful applicability of the presented diagnostic tool. These techniques can assist in broader analysis, identification, and diagnosis of pulmonary disorders manifested by peculiar auscultatory findings.

Study of the regional air quality south of Mexico City (Morelos state).

Results from the first study of the regional air quality in Morelos state (located south of Mexico City) are presented. Criteria pollutants concentrations were measured at several sites within Morelos in February and March of 2007 and 2009; meteorological data was also collected along the state for the same time periods; additionally, a coupled meteorology-chemistry model (Mesoscale Climate Chemistry Model, MCCM) was used to gain understanding on the atmospheric processes occurring in the region. In general, concentrations of almost all the monitored pollutants (O(3), NO(x), CO, SO(2), PM) remained below the Mexican air quality standards during the campaign; however, relatively high concentrations of ozone (8-hour average concentrations above the 60 ppb level several times during the campaigns, i.e. exceeding the World Health Organization and the European Union maximum levels) were observed even at sites with very low reported local emissions. In fact, there is evidence that a large percentage of Morelos vegetation was probably exposed to unhealthy ozone levels (estimated AOT40 levels above the 3 ppm h critical limit). The MCCM qualitatively reproduced ozone daily variations in the sites with an urban component; though it consistently overestimated the ozone concentration in all the sites in Morelos. This is probably because the lack of an updated and detailed emission inventory for the state. The main wind patterns in the region corresponded to the mountain-valley system (downslope flows at night and during the first hours of the day, and upslope flows in the afternoon). At times, Morelos was affected by emissions from surrounding states (Distrito Federal or Puebla). The results are indicative of an efficient transport of ozone and its precursors at a regional level. They also suggest that the state is divided in two atmospheric basins by the Sierras de Tepoztlán, Texcal and Monte Negro.