Search

Abstract Deoxygenation is a major threat to the coastal ocean health as it impacts marine life and key biogeochemical cycles. Understanding its drivers is crucial in the thriving and highly exploited Peru upwelling system, where naturally low-oxygenated subsurface waters form the so-called oxygen minimum zone (OMZ), and a slight vertical shift in its upper limit may have a huge impact. Here we investigate the long-term deoxygenation trends in the upper part of the nearshore OMZ off Peru over the period 1970–2008. We use a unique set of dissolved oxygen in situ observations and several high-resolution regional dynamical-biogeochemical coupled model simulations. Both observation and model present a nearshore deoxygenation above 150 m depth, with a maximum trend of – 10 µmol kg−1 decade1, and a shoaling of the oxycline depth (− 6.4 m decade−1). Model sensitivity analysis shows that the modeled oxycline depth presents a non-significant (+ 0.9 m decade−1) trend when remote forcing is suppressed, while a significant oxycline shoaling (− 3 m decade−1) is obtained when the wind variability is suppressed. This indicates that the nearshore deoxygenation can be attributed to the slowdown of the near-equatorial eastward currents, which transport oxygen-rich waters towards the Peruvian shores. The large uncertainties in the estimation of this ventilation flux and the consequences for more recent and future deoxygenation trends are discussed.

Abstract Background For prospective meta-analyses (PMAs), eligible studies are identified, and the PMA hypotheses, selection criteria, and analysis methods are pre-specified before the results of any of the studies are known. This reduces publication bias and selective outcome reporting and provides a unique opportunity for outcome standardisation/harmonisation. We conducted a world-first PMA of four trials investigating interventions to prevent early childhood obesity. The aims of this study were to quantitatively analyse the effects of prospective planning on variations across trials, outcome harmonisation, and the power to detect intervention effects, and to derive recommendations for future PMA. Methods We examined intervention design, participant characteristics, and outcomes collected across the four trials included in the EPOCH PMA using their registration records, protocol publications, and variable lists. The outcomes that trials planned to collect prior to inclusion in the PMA were compared to the outcomes that trials collected after PMA inclusion. We analysed the proportion of matching outcome definitions across trials, the number of outcomes per trial, and how collaboration increased the statistical power to detect intervention effects. Results The included trials varied in intervention design and participants, this improved external validity and the ability to perform subgroup analyses for the meta-analysis. While individual trials had limited power to detect the main intervention effect (BMI z-score), synthesising data substantially increased statistical power. Prospective planning led to an increase in the number of collected outcome categories (e.g. weight, child’s diet, sleep), and greater outcome harmonisation. Prior to PMA inclusion, only 18% of outcome categories were included in all trials. After PMA inclusion, this increased to 91% of outcome categories. However, while trials mostly collected the same outcome categories after PMA inclusion, some inconsistencies in how the outcomes were measured remained (such as measuring physical activity by hours of outside play versus using an activity monitor). Conclusion Prospective planning led to greater outcome harmonisation and greater power to detect intervention effects, while maintaining acceptable variation in trial designs and populations, which improved external validity. Recommendations for future PMA include more detailed harmonisation of outcome measures and careful pre-specification of analyses to avoid research waste by unnecessary over-collection of data.

The northern Humboldt Current system (NHCS or Peru upwelling system) sustains the world's largest small pelagic fishery. While a nearshore surface cooling has been observed off southern Peru in recent decades, there is still considerable debate on the impact of climate change on the regional ecosystem. This calls for more accurate regional climate projections of the 21st century, using adapted tools such as regional eddy-resolving coupled biophysical models. In this study three coarse-grid Earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are selected based on their biogeochemical biases upstream of the NHCS, and simulations for the RCP8.5 climate scenario are dynamically downscaled at ∼12 km resolution in the NHCS. The impact of regional climate change on temperature, coastal upwelling, nutrient content, deoxygenation, and the planktonic ecosystem is documented. We find that the downscaling approach allows us to correct major physical and biogeochemical biases of the ESMs. All regional simulations display a surface warming regardless of the coastal upwelling trends. Contrasted evolutions of the NHCS oxygen minimum zone and enhanced stratification of phytoplankton are found in the coastal region. Whereas trends of downscaled physical parameters are consistent with ESM trends, downscaled biogeochemical trends differ markedly. These results suggest that more realism of the ESM circulation, nutrient, and dissolved oxygen fields is needed in the eastern equatorial Pacific to gain robustness in the projection of regional trends in the NHCS.

Y1.86Eu0.14WO6 phosphors were prepared using a solid-state reaction method. Their optical properties were analysed, and they was mixed with TiO2, sintered, and used as a photoelectrode (PE) in dye-sensitized solar cells (DSSCs). The as-prepared photoelectrode was characterized by photoluminescence spectroscopy, diffuse reflectance, electrochemical impedance spectroscopy (EIS) and X-ray diffraction. The photoelectric conversion efficiency of the DSSC with TiO2:Y1.86Eu0.14WO6 (100:2.5) was 25.8% higher than that of a DSCC using pure TiO2 as PE. This high efficiency is due to the ability of the luminescent material to convert ultraviolet radiation from the sun to visible radiation, thus improving the solar light harvesting of the DSSC.

This paper presents the semantic indexing of TerraSAR-X images and in situ data. Image processing together with machine learning methods, relevance feedback techniques, and human expertise are used to annotate the image content into a land use land cover catalogue. All the generated information is stored into a geo-database supporting the link between different types of information and the computation of queries and analytics. We used 11 TerraSAR-X scenes over Germany and LUCAS as in situ data. The semantic index is composed of about 73 land use land cover categories found in TerraSAR-X test dataset and 84 categories found in LUCAS dataset.

The continuous increase in the size of the archives and in the variety and complexity of Earth-Observation (EO) sensors require new methodologies and tools that allow the end-user to access a large image repository, to extract and to infer knowledge about the patterns hidden in the images, to retrieve dynamically a collection of relevant images, and to support the creation of emerging applications (e.g.: change detection, global monitoring, disaster and risk management, image time series, etc.). In this context, we are concerned with providing a platform for data mining and knowledge discovery content from EO archives. The platform’s goal is to implement a communication channel between Payload Ground Segments and the end-user who receives the content of the data coded in an understandable format associated with semantics that is ready for immediate exploitation. It will provide the user with automated tools to explore and understand the content of highly complex images archives. The challenge lies in the extraction of meaningful information and understanding observations of large extended areas, over long periods of time, with a broad variety of EO imaging sensors in synergy with other related measurements and data. The platform is composed of several components such as 1.) ingestion of EO images and related data providing basic features for image analysis, 2.) query engine based on metadata, semantics and image content, 3.) data mining and knowledge discovery tools for supporting the interpretation and understanding of image content, 4.) semantic definition of the image content via machine learning methods. All these components are integrated and supported by a relational database management system, ensuring the integrity and consistency of Terabytes of Earth Observation data.

Las prácticas de restauración ecológica realizadas después de los incendios forestales en los bosques mixtos de pino encino del Parque Ecológico Chipinque (PECh), México, han sido escasamente monitoreadas, y se desconoce su efectividad. Para ello, se evaluó en el 2007 el estrato arbóreo de áreas restauradas y no restauradas del incendio suscitado en 1998 y se compararon con un ecosistema maduro de referencia. Los resultados mostraron diferencias significativas en términos de diversidad-abundancia con base en el método de t de Hutcheson (P

Strengthening young people's scientific literacy and civic engagement are important educational goals for Cooperative Extension. We implemented youth participatory action research (YPAR) projects over three years at five schools. The YPAR approach integrates science learning and civic engagement by empowering youth, with the help of adult facilitators, to decide upon a community issue to research, design and implement their research, and then plan a service project based on research findings to address the issue. We explored young people's and educators' perspectives on which project elements influenced youth participation, examined opportunities for youth science and civic-related learning, and asked educators to reflect on their own learning and development. Using data generated from youth focus groups and educator interviews, we found that YPAR grounds science learning in young people's lived experience. It also provides a meaningful approach to science learning through raising young people's critical consciousness of community issues. YPAR may be used in other extension programs to increase motivation for deeper and sustained participation in learning experiences.

Objective: To quantify the performance of food products in a sustainable diet based on the balance of their contribution to nutrient intake and environmental impact, within the context of the Dutch diet.Design: While fixing the quantity of a specific food group at different levels, optimized diets that met nutrient requirements and stayed as close as possible to the current Dutch diet were calculated, in order to understand its potential environmental impact and its nutritional quality. Bread & breakfast cereals, dairy, and meat were compared between 0 and 250% of current intake. Their performance is expressed in the relationship between the quantity of these food products and (1) the environmental impact of diets and (2) the nutrient balance of the diets.Setting: The Netherlands.Subjects: Women aged 31–50.Results: The amount of bread & breakfast cereals in the optimized diets were inversely correlated with their environmental impact. The nutrient balance of the optimized diets was maintained despite varying cereal content, with the expected improvement over the current diet. Increasing amounts of dairy in the optimized diet were associated with an increase in environmental impact and meat with a steep increase. The nutrient balance of optimized diets with varying dairy and meat contents was also maintained at high levels, even at 0% content.Conclusions: Bread and breakfast cereals are sources of nutrients with a better environmental performance compared to dairy or meat within the context of the Dutch diet. It is possible to optimize diets for environmental impact whilst maintaining a high nutrient balance.