Component processes of detection probability in camera-trap studies: understanding the occurrence of false-negatives

Camera-trap studies in the wild record true-positive data, but data loss from false-negatives (i.e. an animal is present but not recorded) is likely to vary and widely impact data quality. Detection probability is defined as the probability of recording an animal if present in the study area. We propose a framework of sequential processes within detection-a pass, trigger, image registration, and images being of sufficient quality. Using Closed Circuit TV (CCTV) combined with camera-trap arrays we quantified variation in, and drivers of, these processes for three medium sized mammal species. We also compared trigger success of wet and dry otter Lutra lutra, as an example of a semi-aquatic species. Data loss from failed trigger, failed registration and poor capture quality varied between species, camera-trap model and settings, and were affected by different environmental and animal variables. Distance had a negative effect on trigger probability and a positive effect on registration probability. Faster animals had both reduced trigger and registration probabilities. Close passes (1m) frequently did not generate triggers, resulting in over 20% data loss for all species. Our results, linked to the framework describing processes, can inform study design to minimise, or account for data loss during analysis and interpretation

Optimising camera trap data quality at mammal resting places.

A thorough understanding of how camera traps function is essential for ensuring correct set-up and quality of data. We illustrate the challenges through a case study of camera trapping an otter Lutra lutra resting and breeding place. Appropriate survey design, such as using multiple cameras, decreasing the distance between cameraand otter holt entrance, and camera trapping for sufficient duration, is likely to reduce the propensity for false negatives and increase our ability to correctly identify and protect mammal resting places

Assessment of the accuracy of counting large ungulate species (red deer Cervus elaphus) with UAV‐mounted thermal infrared cameras during night flights

Unmanned aerial vehicles (UAVs) are increasingly used in wildlife surveying, including estimation of population densities. It is essential that we evaluate and test new survey methods to guide optimal sampling strategies. This study aimed to assess the accuracy of using a UAV-mounted thermal infrared (TIR) camera to count red deer Cervus elaphus populations, and how this was influenced by flight season, height and velocity, in order to help guide future census design. We flew 57 flights across a captive population of red deer in a 13 ha deer park enclosure of semi-natural habitat, representative of the species' range in northern Germany. Flights and image assessments were performed with no prior knowledge of actual population size. Accuracy was quantified by comparing real population size (known only to deer park staff) and independently estimated population sizes from UAV TIR images. Accuracy was significantly influenced by ecological season (early and late winter, spring and early summer) and height. Across all seasons, lower flights (100 m) performed better than higher ones (120 m), with lower flights in early winter and early summer being on average accurate to within 1% of actual population counts. For the season where we had the largest range of temperatures between flights (late winter) we found that accuracy was highest when temperatures were lowest. Flights were also able to identify all five stags (defined as a male deer ≥ 2 years old) present in early summer, but not in spring. Deer appeared to avoid the landing/take-off area, but there were no noted behavioural responses to drones flying over animals when at constant height and velocity during surveys. Our results indicate that UAV-mounted TIR camera have the potential to accurately count populations of large ungulate species, but that flight season, height and potentially temperature need to be taken into account to maximise accuracy. This approach has the potential to be scaled up to more accurately estimate densities of wild populations compared to existing approaches

Optimising camera trap data quality at mammal resting places.

A thorough understanding of how camera traps function is essential for ensuring correct set-up and quality of data. We illustrate the challenges through a case study of camera trapping an otter Lutra lutra resting and breeding place. Appropriate survey design, such as using multiple cameras, decreasing the distance between cameraand otter holt entrance, and camera trapping for sufficient duration, is likely to reduce the propensity for false negatives and increase our ability to correctly identify and protect mammal resting places

An evidence-based approach to identifying resting sites of Eurasian otter (Lutra lutra) from camera-trap and field-sign data

Mammals' resting sites (dens) are important features of their ecology. Eurasian otter Lutra lutra resting sites are strictly protected by UK and European legislation and are ostensibly identified from associated field-signs. This legislation is difficult to apply given the poor understanding of resting sites coupled with the lack of evidence supporting a field-sign signature. We aimed to use camera-trap data to identify resting sites, investigate whether field-signs differed between resting and non-resting sites and describe behaviours recorded on camera-traps that are associated with resting. An evidence-based approach to identifying resting sites of Eurasian otter Lutra lutra from camera-trap and field-sign data camera-trap data showed that otters frequently visited potential resting sites, characterised by a very short time within the structure (often < 4 min). Resting sites were characterised by longer durations (often hours) during the daytime and night-time. Based on these data, six of our 26 sites were identified as resting sites. Modelling suggested that no single field-sign had a clear association with resting sites. However, we found a hitherto unrecognised distinction between otter latrines (defecation sites) and spraint (scent-marking) sites, and that camera-trap observations of latrine behaviour and bedding collection were exclusive to resting sites. As bedding and latrines are not always visible, presence of either indicates a resting site but no interpretation can be drawn from their absence, so camera-trapping would be recommended to identify resting site status. Data simulations found that camera-trapping for 38 d in winter, followed by 38 d in spring, was the optimal approach for a 95% chance of detecting a rest across all resting sites. Ours is the first study to identify standards and expectations for surveys using camera-trap and field-signs at Eurasian otter resting sites. Our novel account of their resting activity facilitates better interpretation of legislation

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy