Species Distribution Models at Regional Scale: Cymodocea nodosa Seagrasses

Despite their ecological and socio-economic importance, seagrasses are often overlooked in comparison with terrestrial ecosystems. In the Canarian archipelago (Spain), Cymodocea nodosa is the best-established species, sustaining the most important marine ecosystem and providing ecosystem services (ES) of great relevance. Nevertheless, we lack accurate and standardized information regarding the distribution of this species and its ES supply. As a first step, the use of species distribution models is proposed. Various machine learning algorithms and ensemble model techniques were considered along with freely available remote sensing data to assess Cymodocea nodosa’s potential distribution. In a second step, we used InVEST software to estimate the ES provision by this phanerogam on a regional scale, providing spatially explicit monetary assessments and a habitat degradation characterization due to human impacts. The distribution models presented great predictive capabilities and statistical significance, while the ES estimations were in concordance with previous studies. The proposed methodology is presented as a useful tool for environmental management of important communities sensitive to human activities, such as C. nodosa meadows.En prensa0,64

Spanish expert consensus on the use of safinamide in Parkinson's disease

La safinamida es un nuevo fármaco para el tratamiento de pacientes con enfermedad de Parkinson (EP) con fluctuaciones como tratamiento complementario a levodopa. Dado que por el momento aún no existen estudios de fase IV postautorización debido a la reciente incorporación de la safinamida a la práctica clínica habitual, el interés de este proyecto radica en el desarrollo de una guía de manejo clínico de la safinamida basada en las opiniones de expertos de trastornos del movimiento. Este proyecto se desarrolló en 2 fases: una primera fase que constó de 16 reuniones locales y una segunda fase que consistió en una reunión nacional. Dichas reuniones siguieron un guion de trabajo preestablecido. Tras la reunión nacional se recopilaron las principales conclusiones de los expertos, que han supuesto la base para redactar la presente guía clínica. Se concluyó que la safinamida es eficaz en la reducción de las fluctuaciones motoras y no motoras. Los pacientes con EP con fluctuaciones leves-moderadas son los que más se benefician del tratamiento, si bien el fármaco puede contribuir a mejorar diversos problemas clínicos en pacientes con EP avanzada. Se ha destacado la posibilidad de reducir la dosis de otros fármacos dopaminérgicos tras la introducción de la safinamida, lo cual contribuiría a reducir efectos adversos como el trastorno de control de impulsos. Se hipotetizó sobre el posible efecto de la safinamida sobre la mejoría de las discinesias a dosis más altas de las habitualmente utilizadas. Se ha consensuado que la safinamida es bien tolerada y presenta un perfil de efectos adversos favorable frente a placebo.Safinamide is a new add-on drug to levodopa for the treatment of Parkinson's disease (PD) with motor fluctuations. Due to the recent incorporation of safinamide into routine clinical practice, no post-authorisation phase IV studies on the safety of safinamide have been conducted to date. This study provides clinical management guidelines for safinamide based on the opinion of a group of experts in movement disorders. This project was developed in 2 phases: 16 local meetings in phase 1 and a national meeting in phase 2. The meetings followed a pre-established agenda. The present clinical practice guidelines are based on the main conclusions reached during the national meeting. The group concluded that safinamide is effective in reducing motor and non-motor fluctuations. PD patients with mild-to-moderate fluctuations benefit most from treatment, although the drug may also improve the clinical status of patients with advanced PD. The dose of other dopaminergic drugs may be reduced after introducing safinamide, which would contribute to reducing such adverse reactions as impulse control disorder. At doses higher than those usually prescribed, safinamide may also improve dyskinesia. The experts agreed that safinamide is well tolerated and causes few adverse reactions when compared with placebo

A Three-Dimensional Ply Failure Model for Composite Structures

A fully 3D failure model to predict damage in composite structures subjected to multiaxial loading is presented in this paper. The formulation incorporates shear nonlinearities effects, irreversible strains, damage and strain rate effects by using a viscoplastic damageable constitutive law. The proposed formulation enables the prediction of failure initiation and failure propagation by combining stress-based, damage mechanics and fracture mechanics approaches within an unified energy based context. An objectivity algorithm has been embedded into the formulation to avoid problems associated with strain localization and mesh dependence. The proposed model has been implemented into ABAQUS/Explicit FE code within brick elements as a userdefined material model. Numerical predictions for standard uniaxial tests at element and coupon levels are presented and discussed

Economic mapping and assessment of Cymodocea nodosa meadows as nursery grounds for commercially important fish species. A case study in the Canary Islands

Cymodocea nodosa seagrass meadows provide several socio-economically ecosystem services, including nurseries for numerous species of commercial interest. These seagrasses are experiencing a worldwide decline, with global loss rates approaching 5% per year, mainly related to coastal human activities. Cymodocea nodosa, the predominant seagrass in the Canary Archipelago (Spain), is also exposed to these threats, which could lead to habitat loss or even local disappearance. In this case study, we estimated the potential economic value of Cymodocea nodosa seagrass meadows for local fisheries at an archipelago scale. Habitat suitability maps were constructed using MAXENT 3.4.1, a software for modelling species distributions by applying a maximum entropy machine-learning method, from a set of environmental variables and presence and background records extracted from historical cartographies. This model allows characterising and assessing the C. nodosa habitat suitability, overcoming the implicit complexity derived from seasonal changes in this species highly dynamic meadows and using it as a first step for the mapping and assessment of ecosystem services. In a second step, value transfer methodologies were used, along with published economic valuations of commercially-interesting fish species related to C. nodosa meadows. We estimate that the potential monetary value of these species can add up to more than 3 million euros per year for the entire Archipelago. The simplicity of the proposed methodology facilitates its repeatability in other similar regions, using freely available data and hence, being suitable for data-scarce scenarios.En prens

Methodology and Neuromarkers for Cetaceans’ Brains

Cetacean brain sampling may be an arduous task due to the difficulty of collecting and histologically preparing such rare and large specimens. Thus, one of the main challenges of working with cetaceans’ brains is to establish a valid methodology for an optimal manipulation and fixation of the brain tissue, which allows the samples to be viable for neuroanatomical and neuropathological studies. With this in view, we validated a methodology in order to preserve the quality of such large brains (neuroanatomy/neuropathology) and at the same time to obtain fresh brain samples for toxicological, virological, and microbiological analysis (neuropathology). A fixation protocol adapted to brains, of equal or even three times the size of human brains, was studied and tested. Finally, we investigated the usefulness of a panel of 20 antibodies (neuromarkers) associated with the normal structure and function of the brain, pathogens, age-related, and/or functional variations. The sampling protocol and some of the 20 neuromarkers have been thought to explore neurodegenerative diseases in these long-lived animals. To conclude, many of the typical measures used to evaluate neuropathological changes do not tell us if meaningful cellular changes have occurred. Having a wide panel of antibodies and histochemical techniques available allows for delving into the specific behavior of the neuronal population of the brain nuclei and to get a “fingerprint” of their real status

Brillouin light scattering study of Co2_{2}Cr0.6_{0.6}Fe0.4_{0.4}Al and Co2_{2}FeAl Heusler compounds

The thermal magnonic spectra of Co$_{2}$Cr$_{0.6}$Fe$_{0.4}$Al (CCFA) and Co$_2$FeAl were investigated using Brillouin light scattering spectroscopy (BLS). For CCFA, the exchange constant A (exchange stiffness D) is found to be 0.48 $\mu$erg/cm (203 meV A$^2$), while for Co$_2$FeAl the corresponding values of 1.55 $\mu$erg/cm (370 meV A$^2$) were found. The observed asymmetry in the BLS spectra between the Stokes and anti-Stokes frequencies was assigned to an interplay between the asymmetrical profiles of hybridized Damon-Esbach and perpendicular standing spin-wave modes, combined with the optical sensitivity of the BLS signal to the upper side of the CCFA or Co$_2$FeAl film

Fire mediated geochemical alterations in Andosol’s SOM under Canarian Pine (Pinus canariensis) forest

4 páginas, 1 figura, 2 tablas, 26 referencias.-- FUEGORED 2010.-- Jornadas Internacionales celebradas del 6-10 de octubre 2010, en Santiago de Compostela, España.Peer reviewe

Methodology for the detection of land cover changes in time series of daily satellite images. Application to burned area detection

Revista oficial de la Asociación Española de Teledetección[EN] We have developed a methodology for detection of observable phenomena at pixel level over time series of daily satellite images, based on using a Bayesian classifier. This methodology has been applied successfully to detect burned areas in the North American boreal forests using the LTDR dataset. The LTDR dataset represents the longest time series of global daily satellite images with 0.05° (~5 km) of spatial resolution. The proposed methodology has several stages: 1) pre-processing daily images to obtain composite images of n days; 2) building of space of statistical variables or attributes to consider; 3) designing an algorithm, by selecting and filtering the training cases; 4) obtaining probability maps related to the considered thematic classes; 5) post-processing to improve the results obtained by applying multiple techniques (filters, ranges, spatial coherence, etc.). The generated results are analyzed using accuracy metrics derived from the error matrix (commission and omission errors, percentage of estimation) and using scattering plots against reference data (correlation coefficient and slope of the regression line). The quality of the results obtained improves, in terms of spatial and timing accuracy, to other burned area products that use images of higher spatial resolution (500 m and 1 km), but they are only available after year 2000 as MCD45A1 and BA GEOLAND-2: the total burned area estimation for the study region for the years 2001-2011 was 28.56 millions of ha according to reference data and 12.41, 138.43 and 19.41 millions of ha for the MCD45A1, BA GEOLAND-2 and BA-LTDR burned area products, respectively.[ES] Se ha desarrollado una metodología para la detección de cambios de la cubierta vegetal, a nivel de píxel, en se-ries temporales de imágenes de satélites diarias mediante la utilización de un clasificador bayesiano. Dicha metodología ha sido aplicada satisfactoriamente a la detección de áreas quemadas en los bosques boreales de Norte América en el período 1981 a 2011, utilizando el conjunto de datos Long Term Data Record (LTDR) que constituye la serie temporal más larga de imágenes diarias de satélite a escala global, con una resolución espacial de 0,05° (~5 km). La metodología pro-puesta consta de varias etapas: 1) pre-procesamiento de las imágenes diarias y obtención de imágenes compuestas de ndías; 2) construcción del espacio de las variables o atributos a considerar; 3) diseño del algoritmo, mediante la selección y refinamiento de los casos de entrenamiento; 4) obtención de los mapas de probabilidad relacionados con las clases temáticas a considerar; 5) post-procesamiento para mejorar los resultados obtenidos mediante la aplicación de múltiples técnicas (filtros, rangos, coherencia espacial, etc.). Los resultados finales obtenidos son comparados con los datos de referencia mediante métricas de exactitud derivadas de la matriz de error (errores de comisión y omisión, porcentaje de estimación) y de gráficos de dispersión (coeficiente de correlación y pendientes de la recta de regresión, etc.). La calidad de los resultados obtenidos al aplicar esta metodología a las imágenes LTDR para la detección de área quemada en la región boreal de Norte América mejora en términos de exactitud espacio-temporal a la de los otros dos productos de área quemada globales comparados (MCD45A1, BA GEOLAND-2) a pesar de que utilizan imágenes de mayor resolución espa-cial (y sólo disponibles a partir del año 2000): la estimación de área quemada total sobre la región de estudio en el periodo 2001-2011 fue de 28,56 millones de hectáreas según los datos de referencia y de 12,41, 138,43 y de 19,41 millones de hectáreas para los productos MCD45A1, BA GEOLAND-2 y BA-LTDR, respectivamente.Este trabajo está financiado por el Ministerio de Economía y Competitividad de España a través del proyecto CGL2013-48202-C2-2-R. Un especial agradecimiento a las Agencias y Servicios de procesamiento de datos de satélite de NASA y NOAA, las cuales nos han suministrado la mayor parte de las imágenes empleadas en este trabajo (LANDSAT, MODIS, LAC and LTDR). Finalmente agradecer a los revisores anónimos por sus comentarios constructivos, los cuales fueron especialmente tenidos en consideración.Moreno-Ruiz, J.; Arbelo, M.; García-Lázaro, J.; Riaño-Arribas, D. (2014). Desarrollo de una metodología para la detección de cambios de la cubierta vegetal en series temporales de imágenes de satélite diarias. Aplicación a la detección de áreas quemadas. Revista de Teledetección. (42):11-28. https://doi.org/10.4995/raet.2014.2280SWORD11284