Suchergebnisse

ABSTRACT. Deep-sea sponge-dominated communities are complex habitats considered hotspots of biodiversity and ecosystem functioning. They are classified as Vulnerable Marine Ecosystem and are listed as threatened or declining as a result of anthropogenic activities. Yet, studies into the distribution, community structure and composition of these habitats are scarce, hampering the development of appropriate management measures to ensure their conservation. In this study we describe a diverse benthic community, dominated by a lithistid sponge, found in two geomorphological features of important conservation status —Le Danois Bank and El Corbiro Canyon— of the Cantabrian Sea. Based on the analyses of visual transects using a photogrammetric towed vehicle and samples collected by rock dredge, we characterize the habitat and the associated community in detail. This deep-sea sponge aggregation was found on bedrock. It is dominated by one lithistid sponge, Neoschrammeniella aff. bowerbankii (0.2 ind./m2) and further composed of various sponge species as well as of other benthic invertebrates such as cnidarians, bryozoans and crustaceans. Using a non-invasive methodology (SfM – Structure from Motion) and empirical relationships of individuals size and biomass/volume obtained in laboratory for N. aff. bowerbankii, we were able to estimate a total biomass of 41 kg and volume of 39 l of this species in the surveyed area. This approach allows a fine tune methodology for estimating biomass and volume by image-based-observed area avoiding destructive techniques for this species. ; FUNDING. This research has been performed in the scope of the SponGES project, which received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no. 679849. This study was partially funded by the European Commission LIFE + "Nature and Biodiversity" call, and included in the INDEMARES (07/NAT/E/000732) and INTEMARES (LIFE15 IPE ES 012) projects. The Biodiversity Foundation, of the Ministry of ...

Se ha desarrollado un modelo matemático que permita analizar el comportamiento de la mortalidad en la República Popular de China ocasionado por COVID-2019. Se aplicó el modelo logístico para los datos reportados entre 11 de enero y el 12 de abril del 2020. El modelo formulado fue linealizado y planteado en dos formas. La primera, evaluando el factor de corrección B, que hace las veces de cantidad máxima de fallecidos. Se determinaron los parámetros A, k y r, obteniendo el modelo (Ecuación 7), con un coeficiente de correlación r=-0,9660 y el coeficiente de determinación r^2×100=93,31 %. La segunda forma, con el mismo valor de B, introduciendo un factor de corrección para la variable independiente, t, que hace las veces de "periodo". Se determinaron los parámetros A, k y r, obteniendo el modelo (Ecuación 10), con un coeficiente de correlación r=-0,9668 y el coeficiente de determinación r^2×100=93,48 %; lo que demuestra buena estimación del modelo (Ecuación 7 y Ecuación 10). Asimismo, se evaluó la velocidad de mortalidad, derivando, ordinariamente los modelos (Ecuación 7 y Ecuación 10), obteniendo los modelos de velocidad (Ecuación 8 y Ecuación 11); concluyendo que la máxima velocidad de mortalidad fue de 118 personas por día el día 24 de febrero de 2020.