Biologging has proven to be a powerful approach to investigate diverse questions related to movement ecology across a range of spatiotemporal scales and increasingly relies on multidisciplinary expertise. However, the variety of animal-borne equipment, coupled with little consensus regarding analytical approaches to interpret large, complex data sets presents challenges and makes comparison between studies and study species difficult. Here, we present a combined hardware and analytical approach for standardizing the collection, analysis, and interpretation of multisensor biologging data. Here, we present (i) a custom-designed integrated multisensor collar (IMSC), which was field tested on 71 free-ranging wild boar (Sus scrofa) over 2 years; (ii) a machine learning behavioral classifier capable of identifying six behaviors in free-roaming boar, validated across individuals equipped with differing collar designs; and (iii) laboratory and field-based calibration and accuracy assessments of animal magnetic heading measurements derived from raw magnetometer data. The IMSC capacity and durability exceeded expectations, with a 94% collar recovery rate and a 75% cumulative data recording success rate, with a maximum logging duration of 421 days. The behavioral classifier had an overall accuracy of 85% in identifying the six behavioral classes when tested on multiple collar designs and improved to 90% when tested on data exclusively from the IMSC. Both laboratory and field tests of magnetic compass headings were in precise agreement with expectations, with overall median magnetic headings deviating from ground truth observations by 1.7° and 0°, respectively. Although multisensor equipment and sophisticated analyses are now commonplace in biologging studies, the IMSC hardware and analytical framework presented here provide a valuable tool for biologging researchers and will facilitate standardization of biologging data across studies. In addition, we highlight the potential of additional analyses available using this framework that can be adapted for use in future studies on terrestrial mammals.
- Klíčová slova
- GPS, accelerometer, behavioral classification, biologging, dead‐reckoning, machine learning, magnetic compass heading, magnetometer,
- Publikační typ
- časopisecké články MeSH
BACKGROUND: The COVID-19 pandemic had a major impact on the mental health and well-being of children with neurodevelopmental conditions (NDCs) and of their families worldwide. However, there is insufficient evidence to understand how different factors (e.g., individual, family, country, children) have impacted on anxiety levels of families and their children with NDCs developed over time. METHODS: We used data from a global survey assessing the experience of 8043 families and their children with NDCs (mean of age (m) = 13.18 years, 37% female) and their typically developing siblings (m = 12.9 years, 45% female) in combination with data from the European Centre for Disease Prevention and Control, the University of Oxford, and the Central Intelligence Agency (CIA) World Factbook, to create a multilevel data set. Using stepwise multilevel modelling, we generated child-, family- and country-related factors that may have contributed to the anxiety levels of children with NDCs, their siblings if they had any, and their parents. All data were reported by parents. RESULTS: Our results suggest that parental anxiety was best explained by family-related factors such as concerns about COVID-19 and illness. Children's anxiety was best explained by child-related factors such as children's concerns about loss of routine, family conflict, and safety in general, as well as concerns about COVID-19. In addition, anxiety levels were linked to the presence of pre-existing anxiety conditions for both children with NDCs and their parents. CONCLUSIONS: The present study shows that across the globe there was a raise in anxiety levels for both parents and their children with NDCs because of COVID-19 and that country-level factors had little or no impact on explaining differences in this increase, once family and child factors were considered. Our findings also highlight that certain groups of children with NDCs were at higher risk for anxiety than others and had specific concerns. Together, these results show that anxiety of families and their children with NDCs during the COVID-19 pandemic were predicted by very specific concerns and worries which inform the development of future toolkits and policy. Future studies should investigate how country factors can play a protective role during future crises.
- MeSH
- COVID-19 * MeSH
- lidé MeSH
- mladiství MeSH
- pandemie * MeSH
- rodiče psychologie MeSH
- rodina psychologie MeSH
- úzkost epidemiologie MeSH
- Check Tag
- lidé MeSH
- mladiství MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
