8 research outputs found

    Detection pipeline for search-phase bat echolocation calls.

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    <p>(a) Raw audio files are converted into a spectrogram using a Fast Fourier Transform (b). Files are de-noised (c), and a sliding window Convolutional Neural Network (CNN) classifier (d, yellow box) produces a probability for each time step. Individual call detection probabilities using non-maximum suppression are produced (e, green boxes), and the time in file of each prediction along with the classifier probability are exported as text files.</p

    Comparison of the predicted bat detections (calls and passes) for two different acoustic systems using monitoring data collected from Jersey, UK.

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    <p>Acoustic systems used were SonoBat (version 3.1.7p) [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005995#pcbi.1005995.ref043" target="_blank">43</a>] using analysis in [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005995#pcbi.1005995.ref049" target="_blank">49</a>], and BatDetect CNN<sub>FAST</sub> using a probability threshold of 0.90. Detections are shown within each box plot, where the black line represents the mean across all transect sampling events from 2011–2015, boxes represent the middle 50% of the data, whiskers represent variability outside the upper and lower quartiles, with outliers plotted as individual points. See text for definition of a bat pass.</p

    Spatial distribution of the BatDetect CNNs training and testing datasets.

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    <p>(a) Location of training data for all experiments and one test dataset in Romania and Bulgaria (2006–2011) from time-expanded (TE) data recorded along road transects by the Indicator Bats Programme (iBats) [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005995#pcbi.1005995.ref007" target="_blank">7</a>], where red and black points represent training and test data, respectively. (b) Locations of additional test datasets from TE data recorded as part of iBats car transects in the UK (2005–2011), and from real-time recordings from static recorders from the Norfolk Bat Survey from 2015 (inset). Points represent the start location of each snapshot recording for each iBats transect or locations of static detectors for the Norfolk Bat Survey.</p

    The most important broad drivers of species’ population changes, 1970–2012.

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    <p>Positive (green) and negative (blue) impact for each broad driver of change accounting for two percent or more of the total in absolute terms, ordered by absolute impact. Results are presented using all strengths of evidence available and weighting species in the three major taxonomic groups equally (insects, plants and vertebrates).</p

    The most important broad drivers of species’ population changes, 1970–2012, showing constituent specific drivers.

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    <p>Positive (green) and negative (blue) impact for each broad driver of change accounting for three percent or more of the total in absolute terms, ordered by absolute impact. Specific drivers (narrow bars) are listed under their associated broad driver (broad bars, italicised text); the impact of specific drivers sum to the total for the broad driver in each case. Results are presented using all strengths of evidence available and weighting species in the three major taxonomic groups equally (insects, plants and vertebrates).</p

    The most important broad drivers of species’ population changes, 1970–2012, by higher taxonomic group.

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    <p>Positive (light green) and negative (dark blue) impact for each broad driver of change accounting for two percent or more of the total in absolute terms, ordered by absolute impact; by higher taxonomic group. Impact is shown as a percentage of the impact on that group, i.e. absolute impact sums to 100 for each of the three groups. Results are presented using all strength of evidence available.</p
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