TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Los modelos de niveles múltiples: una estrategia analítica para el estudio de los problemas de salud de la población Multilevel models: an analysis strategy for the study of health problems in society

Se presenta una discusión teórico metodológica sobre la aplicabilidad de modelos de niveles múltiples para el estudio de los procesos de salud/enfermedad, sus determinantes y condicionantes, en función de la estratificación de la sociedad y de las condiciones de vida de sus habitantes. Se recupera una noción de población según la perspectiva de la teoría de los sistemas complejos jerárquicos que busca no reducir la realidad, sino una construcción del problema procurando identificar distintos niveles de abstracción para su abordaje. Estos modelos constituyen una opción que supera las experiencias previas, con la aplicación de técnicas estadísticas convencionales, dado que permiten analizar simultáneamente distintos niveles de agregación conservando su estructura jerárquica. Se consideran la influencia de las variables teniendo en cuenta su pertenencia a unidades mayores y la asociación potencialmente existente entre las unidades de un mismo nivel, es decir, la correlación intraclase entre variables relativas a individuos, familias, grupos, próximos entre sí, que comparten condiciones semejantes. Se evita de este modo sobredimensionar el efecto de las variables de macro nivel. Los modelos de niveles múltiples resultan particularmente adecuados para valorar desigualdades en el proceso salud/enfermedad/atención de los grupos poblacionales y analizar cómo los contextos sociales afectan los resultados y los riesgos de salud individuales. Se destaca la necesidad de desarrollar estrategias de producción de información y de análisis que posibiliten reconocer niveles de explicación y de intervención, para proveer insumos y desencadenar acciones adecuadas a las especificidades locales, a nivel de las micro-áreas, con miras a lograr una mayor equidad en salud.<br>This paper presents the theoretical-methodological discussion about the applicability of multiple level models in the study of the health/sickness process, its determinants and conditioning factors, as a function of the stratification of society and the living conditions of its inhabitants. It goes back to the concept of population according to the theory of hierarchical complex systems, which seeks not to reduce reality, but rather to build the problem trying to identify different levels of abstraction in its approach. These models are options to overcome prior experiences, with the application of conventional statistical techniques, given that they make it possible to simultaneously analyze different levels of aggregation, while keeping its hierarchical structure. They consider the influence of the variables taking into account their belonging to lager units and the potential association existing between the units of a same level, that is, the intraclass correlation among variables relative to individuals, families and groups, close amongst themselves, which share similar conditions. In this manner, it tries to avoid oversizing the effect of macro level variables. The multiple level models are particularly appropriate to evaluate inequalities in the health/sickness/care process of the population groups and to analyze how social contexts affect the results and health risks of people. It highlights the need to develop information production strategies and analyses that make it possible to recognize levels of explanation and intervention to provide inputs and trigger actions suited to local specificities, at the level of micro-areas, so as to have more equity in healthcare

Reduction of sodium additives in cooked sausages: effect on physicochemical, sensory and microbiological characteristics

Several efforts have been made to reduce sodium in meat products due to its demonstrated negative health effects. This study evaluated the effect on physicochemical, sensory and microbiological characteristics of cooked sausages after a simultaneous reduction of salt (2.2% and 1.8%), Na-lactate (2.8% and 1.5%) and sodium tripolyphosphate (STPP) (0.4% and 0.2%). Salt and STPP reduction affected cooking loss, while no significant differences (P > 0.05) were obtained in instrumental and sensory texture for all factors. Discrimination tests showed significant perceived differences between some pairs, however, d′ values were below 0.55 in all comparisons, meaning consumer awareness of the reduction might be irrelevant in a real-life scenario. A simultaneous reduction of Na-lactate and salt did not affect microbial stability (psychrotrophic and LAB counts) of the product. Reducing sodium-containing additives might be a low cost, promising strategy to reduce total sodium content in cooked sausages with no detrimental of their physicochemical, sensory and microbiological characteristics.Universidad de Costa Rica/[735-B6-118]/UCR/Costa RicaCITAUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Agroalimentarias::Centro Nacional de Ciencia y Tecnología de Alimentos (CITA)UCR::Vicerrectoría de Docencia::Ciencias Agroalimentarias::Facultad de Ciencias Agroalimentarias::Escuela de Tecnología de AlimentosUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Centro de Investigación en Enfermedades Tropicales (CIET