Fire affects microhabitat selection, movement patterns, and body condition of an Australian rodent (Rattus fuscipes)

Resource selection by animals influences individual fitness, the abundance of local populations, and the distribution of species. Further, the degree to which individuals select particular resources can be altered by numerous factors including competition, predation, and both natural- and human-induced environmental change. Understanding the influence of such factors on the way animals use resources can guide species conservation and management in changing environments. In this study, we investigated the effects of a prescribed fire on small-scale (microhabitat) resource selection, abundance, body condition, and movement pathways of a native Australian rodent, the bush rat (Rattus fuscipes). Using a before-after, control-impact design, we gathered data from 60 individuals fitted with spool and line tracking devices. In unburnt forest, selection of resources by bush rats was positively related to rushes, logs and complex habitat, and negatively related to ferns and litter. Fire caused selection for spreading grass, rushes, and complex habitat to increase relative to an unburnt control location. At the burnt location after the fire, rats selected patches of unburnt vegetation, and no rats were caught at a trapping site where most of the understory had been burnt. The fire also reduced bush rat abundance and body condition and caused movement pathways to become more convoluted. After the fire, some individuals moved through burnt areas but the majority of movements occurred within unburnt patches. The effects of fire on bush rat resource selection, movement, body condition, and abundance were likely driven by several linked factors including limited access to shelter and food due to the loss of understory vegetation and heightened levels of perceived predation risk. Our findings suggest the influence of prescribed fire on small mammals will depend on the resulting mosaic of burnt and unburnt patches and how well this corresponds to the resource requirements of particular species.

Accelerometer validity to measure and classify movement in team sports

 In team sports accelerometers are used to monitor the physical demands of athletic performance. Daniel's research showed that accelerometer accuracy can be improved through filtering. He also showed that the accelerometer can be used to automatically classify the type of movement performed. Further improving the understanding of team sports.

Nonparametric discovery of movement patterns from accelerometer signals

Monitoring daily physical activity plays an important role in disease prevention and intervention. This paper proposes an approach to monitor the body movement intensity levels from accelerometer data. We collect the data using the accelerometer in a realistic setting without any supervision. The ground-truth of activities is provided by the participants themselves using an experience sampling application running on their mobile phones. We compute a novel feature that has a strong correlation with the movement intensity. We use the hierarchical Dirichlet process (HDP) model to detect the activity levels from this feature. Consisting of Bayesian nonparametric priors over the parameters the model can infer the number of levels automatically. By demonstrating the approach on the publicly available USC-HAD dataset that includes ground-truth activity labels, we show a strong correlation between the discovered activity levels and the movement intensity of the activities. This correlation is further confirmed using our newly collected dataset. We further use the extracted patterns as features for clustering and classifying the activity sequences to improve performance.

Modulation of corticomotor excitability after maximal or sustainable-rate repetitive finger movement is impaired in Parkinson’s disease and is reversed by levodopa

Objectives: In healthy subjects, fatiguing exercises induce a period of post-exercise corticomotor depression (PECD) that is absent in Parkinson’s disease (PD). Our objective is to determine the time-course of corticomotor excitability changes following a 10-s repetitive index finger flexion–extension task performed at maximal voluntary rate (MVR) and a slower sustainable rate (MSR) in PD patients OFF and ON levodopa.
Methods: In 11 PD patients and 10 healthy age-matched controls, motor evoked potentials (MEPs) were recorded from the extensor indicis proprius (EIP) and first dorsal interosseous (FDI) muscles of the dominant arm immediately after the two tasks and at 2-min intervals for 10 min.
Results: In the OFF condition the PECD was absent in the two test muscles after both the MVR and MSR tasks. In the ON condition finger movement kinematics improved and a period of PECD comparable to that in controls was present after both tasks.
Conclusion: The absence of PECD in PD subjects off medication indicates a persisting increase in corticomotor excitability after non-fatiguing repetitive finger movement that is reversed by levodopa.