Mechanical traits as drivers of trophic interaction between macrodetritivores and leaf litter.

In ecosystems, the rates of resource consumption by animals drive the flows of matter and energy. Consumption rates are known to vary according to consumer energy requirements, resource nutrient content and mechanical properties. The aim of our study is to determine how mechanical constraints, compared to energetic and nutritional constraints, explain the variation in leaf litter consumption rates by macrodetritivores. In particular, we focus on the impact of litter toughness. To this end, we propose a non-linear model describing leaf litter consumption rates of detritivore as a function of litter toughness. We also investigate a possible match between bite force and litter toughness, since consumer-resource co-occurrence is thought to be driven by the match between invertebrate mandibular traits and resource toughness. Our study was designed as follows: leaf litter from oak and hornbeam was exposed to field physical and microbial decomposition in aquatic and terrestrial ecosystems for selected time periods before it was offered to eight macrodetritivore taxa (three forest stream taxa and five forest soil taxa) in no-choice laboratory feeding experiments. Our findings show that, compared to energetic and nutritional constraints, mechanical traits have a greater impact on litter consumption rate by detritivores. After subtracting the contribution of the detritivore body mass, we report that litter consumption rates depend primarily on litter toughness. A sigmoid function is best suited to characterize the relationship between mass-independent consumption rate and litter toughness. We note that the parameters of our sigmoid model are taxon-specific, suggesting biomechanical thresholds and biological differences among taxa. Interestingly, we found no correlation with detritivore bite force, suggesting that food processing by detritivores does not only depend on mandibles strength.

The EPIDIA4Kids protocol for a digital epidemiology study on brain functioning in children, based on a multimodality biometry tool running on an unmodified tablet.

Introduction: Neurodevelopment and related mental disorders (NDDs) are one of the most frequent disabilities among young people. They have complex clinical phenotypes often associated with transnosographic dimensions, such as emotion dysregulation and executive dysfunction, that lead to adverse impacts in personal, social, academic, and occupational functioning. Strong overlap exists then across NDDs phenotypes that are challenging for diagnosis and therapeutic intervention. Recently, digital epidemiology uses the rapidly growing data streams from various devices to advance our understanding of health's and disorders' dynamics, both in individuals and the general population, once coupled with computational science. An alternative transdiagnostic approach using digital epidemiology may thus better help understanding brain functioning and hereby NDDs in the general population. Objective: The EPIDIA4Kids study aims to propose and evaluate in children, a new transdiagnostic approach for brain functioning examination, combining AI-based multimodality biometry and clinical e-assessments on an unmodified tablet. We will examine this digital epidemiology approach in an ecological context through data-driven methods to characterize cognition, emotion, and behavior, and ultimately the potential of transdiagnostic models of NDDs for children in real-life practice. Methods and analysis: The EPIDIA4Kids is an uncontrolled open-label study. 786 participants will be recruited and enrolled if eligible: they are (1) aged 7 to 12 years and (2) are French speaker/reader; (3) have no severe intellectual deficiencies. Legal representative and children will complete online demographic, psychosocial and health assessments. During the same visit, children will perform additionally a paper/pencil neuro-assessments followed by a 30-min gamified assessment on a touch-screen tablet. Multi-stream data including questionnaires, video, audio, digit-tracking, will be collected, and the resulting multimodality biometrics will be generated using machine- and deep-learning algorithms. The trial will start in March 2023 and is expected to end by December 2024. Discussion: We hypothesize that the biometrics and digital biomarkers will be capable of detecting early onset symptoms of neurodevelopment compared to paper-based screening while as or more accessible in real-life practice.

Fine scale behaviour and time-budget in the cryptic ectotherm European pond turtle Emys orbicularis.

For ectotherms, behaviour and associated energetic costs are directly related to thermal conditions. In the present context of global change, estimating time-budget for these species is relevant to assess and predict their capacity to adapt to near future. We tested the hypothesis that in ectotherms where reproduction is highly energy consuming, energy expenditure should vary throughout the breeding season with a maximum around nesting events. To test this hypothesis, we assessed the fine-scale behaviour, time-budget and estimated energetic costs in eight adult female European pond turtles Emys orbicularis equipped with data-loggers recording ambient temperature, pressure, light and the animals' 3-axis acceleration. Deployments occurred over four months throughout the nesting season 2017 in semi-natural captive conditions in Alsace, France. All study turtles showed a clear daily pattern over the 24h cycle, with four distinct phases (referred to as Night, Morning, Midday and Evening), associated with different behaviours and activity levels. Before oviposition, turtles were mostly active during Morning, and activity was positively driven by ambient temperature. Activity levels doubled during the nesting period, mostly due to the increased activity in the Evening, when nesting events occurred. Throughout the active season, basking occurrence at Midday was related to air temperature but cloud coverage was an even more important factor. Our results are a first step in predicting the seasonal time and energy budgets of the European pond turtle, and demonstrate the usefulness of animal-borne accelerometers to study free living freshwater turtles over extended periods of time.