ClassifyMe: A Field-Scouting Software for the Identification of Wildlife in Camera Trap Images.

We present ClassifyMe a software tool for the automated identification of animal species from camera trap images. ClassifyMe is intended to be used by ecologists both in the field and in the office. Users can download a pre-trained model specific to their location of interest and then upload the images from a camera trap to a laptop or workstation. ClassifyMe will identify animals and other objects (e.g., vehicles) in images, provide a report file with the most likely species detections, and automatically sort the images into sub-folders corresponding to these species categories. False Triggers (no visible object present) will also be filtered and sorted. Importantly, the ClassifyMe software operates on the user's local machine (own laptop or workstation)-not via internet connection. This allows users access to state-of-the-art camera trap computer vision software in situ, rather than only in the office. The software also incurs minimal cost on the end-user as there is no need for expensive data uploads to cloud services. Furthermore, processing the images locally on the users' end-device allows them data control and resolves privacy issues surrounding transfer and third-party access to users' datasets.

Camera traps can be heard and seen by animals.

Camera traps are electrical instruments that emit sounds and light. In recent decades they have become a tool of choice in wildlife research and monitoring. The variability between camera trap models and the methods used are considerable, and little is known about how animals respond to camera trap emissions. It has been reported that some animals show a response to camera traps, and in research this is often undesirable so it is important to understand why the animals are disturbed. We conducted laboratory based investigations to test the audio and infrared optical outputs of 12 camera trap models. Camera traps were measured for audio outputs in an anechoic chamber; we also measured ultrasonic (n = 5) and infrared illumination outputs (n = 7) of a subset of the camera trap models. We then compared the perceptive hearing range (n = 21) and assessed the vision ranges (n = 3) of mammals species (where data existed) to determine if animals can see and hear camera traps. We report that camera traps produce sounds that are well within the perceptive range of most mammals' hearing and produce illumination that can be seen by many species.

Taxonomic uncertainty and the loss of biodiversity on Christmas Island, Indian Ocean.

The taxonomic uniqueness of island populations is often uncertain which hinders effective prioritization for conservation. The Christmas Island shrew (Crocidura attenuata trichura) is the only member of the highly speciose eutherian family Soricidae recorded from Australia. It is currently classified as a subspecies of the Asian gray or long-tailed shrew (C. attenuata), although it was originally described as a subspecies of the southeast Asian white-toothed shrew (C. fuliginosa). The Christmas Island shrew is currently listed as endangered and has not been recorded in the wild since 1984-1985, when 2 specimens were collected after an 80-year absence. We aimed to obtain DNA sequence data for cytochrome b (cytb) from Christmas Island shrew museum specimens to determine their taxonomic affinities and to confirm the identity of the 1980s specimens. The Cytb sequences from 5, 1898 specimens and a 1985 specimen were identical. In addition, the Christmas Island shrew cytb sequence was divergent at the species level from all available Crocidura cytb sequences. Rather than a population of a widespread species, current evidence suggests the Christmas Island shrew is a critically endangered endemic species, C. trichura, and a high priority for conservation. As the decisions typically required to save declining species can be delayed or deferred if the taxonomic status of the population in question is uncertain, it is hoped that the history of the Christmas Island shrew will encourage the clarification of taxonomy to be seen as an important first step in initiating informed and effective conservation action.