Identification of reindeer fine-scale foraging behaviour using tri-axial accelerometer data

Animal behavioural responses to the environment ultimately affect their survival. Monitoring animal fine-scale behaviour may improve understanding of animal functional response to the environment and provide an important indicator of the welfare of both wild and domesticated species. In this study, we illustrate the application of collar-attached acceleration sensors for investigating reindeer fine-scale behaviour. Using data from 19 reindeer, we tested the supervised machine learning algorithms Random forests, Support vector machines, and hidden Markov models to classify reindeer behaviour into seven classes: grazing, browsing low from shrubs or browsing high from trees, inactivity, walking, trotting, and other behaviours. We implemented leave-one-subject-out cross-validation to assess generalizable results on new individuals. Our main results illustrated that hidden Markov models were able to classify collar-attached accelerometer data into all our pre-defined behaviours of reindeer with reasonable accuracy while Random forests and Support vector machines were biased towards dominant classes. Random forests using 5-s windows had the highest overall accuracy (85%), while hidden Markov models were able to best predict individual behaviours and handle rare behaviours such as trotting and browsing high. We conclude that hidden Markov models provide a useful tool to remotely monitor reindeer and potentially other large herbivore species behaviour. These methods will allow us to quantify fine-scale behavioural processes in relation to environmental events

Herbivore diversity effects on Arctic tundra ecosystems: a systematic review

Background: Northern ecosystems are strongly influenced by herbivores that differ in their impacts on the ecosystem. Yet the role of herbivore diversity in shaping the structure and functioning of tundra ecosystems has been overlooked. With climate and land-use changes causing rapid shifts in Arctic species assemblages, a better understanding of the consequences of herbivore diversity changes for tundra ecosystem functioning is urgently needed. This systematic review synthesizes available evidence on the effects of herbivore diversity on different processes, functions, and properties of tundra ecosystems. Methods: Following a published protocol, our systematic review combined primary field studies retrieved from bibliographic databases, search engines and specialist websites that compared tundra ecosystem responses to different levels of vertebrate and invertebrate herbivore diversity. We used the number of functional groups of herbivores (i.e., functional group richness) as a measure of the diversity of the herbivore assemblage. We screened titles, abstracts, and full texts of studies using pre-defined eligibility criteria. We critically appraised the validity of the studies, tested the influence of different moderators, and conducted sensitivity analyses. Quantitative synthesis (i.e., calculation of effect sizes) was performed for ecosystem responses reported by at least five articles and meta-regressions including the effects of potential modifiers for those reported by at least 10 articles. Review findings: The literature searches retrieved 5944 articles. After screening titles, abstracts, and full texts, 201 articles including 3713 studies (i.e., individual comparisons) were deemed relevant for the systematic review, with 2844 of these studies included in quantitative syntheses. The available evidence base on the effects of herbivore diversity on tundra ecosystems is concentrated around well-established research locations and focuses mainly on the impacts of vertebrate herbivores on vegetation. Overall, greater herbivore diversity led to increased abundance of feeding marks by herbivores and soil temperature, and to reduced total abundance of plants, graminoids, forbs, and litter, plant leaf size, plant height, and moss depth, but the effects of herbivore diversity were difficult to tease apart from those of excluding vertebrate herbivores. The effects of different functional groups of herbivores on graminoid and lichen abundance compensated each other, leading to no net effects when herbivore effects were combined. In turn, smaller herbivores and large-bodied herbivores only reduced plant height when occurring together but not when occurring separately. Greater herbivore diversity increased plant diversity in graminoid tundra but not in other habitat types. Conclusions: This systematic review underscores the importance of herbivore diversity in shaping the structure and function of Arctic ecosystems, with different functional groups of herbivores exerting additive or compensatory effects that can be modulated by environmental conditions. Still, many challenges remain to fully understand the complex impacts of herbivore diversity on tundra ecosystems. Future studies should explicitly address the role of herbivore diversity beyond presence-absence, targeting a broader range of ecosystem responses and explicitly including invertebrate herbivores. A better understanding of the role of herbivore diversity will enhance our ability to predict whether and where shifts in herbivore assemblages might mitigate or further amplify the impacts of environmental change on Arctic ecosystems

Burden of childhood-onset arthritis

Juvenile arthritis comprises a variety of chronic inflammatory diseases causing erosive arthritis in children, often progressing to disability. These children experience functional impairment due to joint and back pain, heel pain, swelling of joints and morning stiffness, contractures, pain, and anterior uveitis leading to blindness. As children who have juvenile arthritis reach adulthood, they face possible continuing disease activity, medication-associated morbidity, and life-long disability and risk for emotional and social dysfunction. In this article we will review the burden of juvenile arthritis for the patient and society and focus on the following areas: patient disability; visual outcome; other medical complications; physical activity; impact on HRQOL; emotional impact; pain and coping; ambulatory visits, hospitalizations and mortality; economic impact; burden on caregivers; transition issues; educational occupational outcomes, and sexuality

Animal Botulism Outcomes in the AniBioThreat Project

Botulism disease in both humans and animals is a worldwide concern. Botulinum neurotoxins produced by Clostridium botulinum and other Clostridium species are the most potent biological substances known and are responsible for flaccid paralysis leading to a high mortality rate. Clostridium botulinum and botulinum neurotoxins are considered potential weapons for bioterrorism and have been included in the Australia Group List of Biological Agents. In 2010 the European Commission (DG Justice, Freedom and Security) funded a 3-year project named AniBioThreat to improve the EU's capacity to counter animal bioterrorism threats. A detection portfolio with screening methods for botulism agents and incidents was needed to improve tracking and tracing of accidental and deliberate contamination of the feed and food chain with botulinum neurotoxins and other Clostridia. The complexity of this threat required acquiring new genetic information to better understand the diversity of these Clostridia and develop detection methods targeting both highly specific genetic markers of these Clostridia and the neurotoxins they are able to produce. Several European institutes participating in the AniBioThreat project collaborated on this program to achieve these objectives. Their scientific developments are discussed here

Identification of reindeer fine-scale foraging behaviour using tri-axial accelerometer data.

Animal behavioural responses to the environment ultimately affect their survival. Monitoring animal fine-scale behaviour may improve understanding of animal functional response to the environment and provide an important indicator of the welfare of both wild and domesticated species. In this study, we illustrate the application of collar-attached acceleration sensors for investigating reindeer fine-scale behaviour. Using data from 19 reindeer, we tested the supervised machine learning algorithms Random forests, Support vector machines, and hidden Markov models to classify reindeer behaviour into seven classes: grazing, browsing low from shrubs or browsing high from trees, inactivity, walking, trotting, and other behaviours. We implemented leave-one-subject-out cross-validation to assess generalizable results on new individuals. Our main results illustrated that hidden Markov models were able to classify collar-attached accelerometer data into all our pre-defined behaviours of reindeer with reasonable accuracy while Random forests and Support vector machines were biased towards dominant classes. Random forests using 5-s windows had the highest overall accuracy (85%), while hidden Markov models were able to best predict individual behaviours and handle rare behaviours such as trotting and browsing high. We conclude that hidden Markov models provide a useful tool to remotely monitor reindeer and potentially other large herbivore species behaviour. These methods will allow us to quantify fine-scale behavioural processes in relation to environmental events