Foraging ecology of chick rearing seabirds is affected mainly by the food availability on feeding grounds, but it can be also modulated by environmental conditions during the foraging trip, in that wind force. Considering predicted strengthening of surface winds over the Arctic Ocean, this factor may have a growing impact on the foraging performance of Arctic seabirds. Here, we studied how wind speed could affect prey accessibility for the High Arctic zooplanktivorous seabird, the little auk Alle alle breeding in Svalbard in 2015-2019. First, we estimated availability of its preferred prey, a cold water copepod Calanus glacialis, based on wider-scale mesozooplankton biomass model and environmental conditions. Then we estimated prey accessibility by including wind speed, the factor affecting the flapping flight performance of little auks commuting from/to the colony. Finally, we compared reproductive performance of the little auks (chick diet, growth rate and survival and duration of foraging flights of adults) between the studied years differing in wind and food availability conditions. We found that wind speed could affect significantly food accessibility for a zooplanktivorous seabird. Despite high spatial and temporal variability in prey availability and accessibility in shelf waters of SW Spitsbergen, interannual differences in duration of foraging flights and chick growth rate, little auks were able to sustain high breeding success confirming their capacity to buffer suboptimal foraging conditions. Our multidisciplinary work, combining multi-year remote sensing of oceanographic conditions, zooplankton availability and accessibility modelling, little auks diet composition and chick growth and survival emphasizes the importance of including wind conditions in the studies of foraging ecology of seabirds.
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http://dx.doi.org/10.1016/j.scitotenv.2022.158533 | DOI Listing |
Biosensors (Basel)
December 2024
Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576, Singapore.
To face the increasing requirement for grains as the global population continues to grow, improving both crop yield and quality has become essential. Plant health directly impacts crop quality and yield, making the development of plant health-monitoring technologies essential. Variable sensing technologies for outdoor/indoor farming based on different working principles have emerged as important tools for monitoring plants and their microclimates.
View Article and Find Full Text PDFZhongguo Dang Dai Er Ke Za Zhi
December 2024
Department of Respiratory Medicine, Jiangxi Children's Hospital, Nanchang 330003, China.
Objectives: To explore the epidemiological characteristics of respiratory syncytial virus (RSV) infection in children in Nanchang and its correlation with climate environmental factors.
Methods: The clinical data were collected from children with acute respiratory infection in Nanchang who were tested for RSV at Jiangxi Provincial Children's Hospital from January 2019 to December 2023, along with climate environmental data for the same period. The epidemiological characteristics of RSV and their correlation with climate environmental factors were investigated.
Acta Trop
December 2024
Department of Geography and Planning, University of Saskatchewan, 117 Science Place, Saskatoon, Saskatchewan, S7N 5C8, Canada; Global Institute for Water Security, University of Saskatchewan, Saskatoon, Canada. Electronic address:
Environ Geochem Health
December 2024
Department of Environmental Health Engineering, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran.
The study delved into an extensive assessment of outdoor air pollutant levels, focusing specifically on PM, SO, NO, and CO, across the Mashhad metropolis from 2017 to 2021. In tandem, it explored their intricate correlations with meteorological conditions and the consequent health risks posed. Employing EPA health risk assessment methods, the research delved into the implications of pollutant exposure on human health.
View Article and Find Full Text PDFEnviron Monit Assess
December 2024
Department of VLSI Microelectronics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, 602105, Tamil Nadu, India.
Knowledge of soil temperature (ST) is important for analysing environmental conditions and climate change. Moreover, ST is a vital element of soil that impacts crop growth as well as the germination of the seeds. In this study, four machine-learning (ML) paradigms including random forest (RF), radial basis neural network (RBNN), multi-layer perceptron neural network (MLPNN), and co-active neuro-fuzzy inference system (CANFIS) were used for estimation of daily ST at different soil depths (i.
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