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Fig 1.

Two-step decision tree for classifying the main activities of freshwater turtles.

Acceleration data are first binned according to activity level (Step 1) based on visual observation and acceleration thresholds, and then further classified according to habitat type based on a water conductivity sensor deployed in tandem with the accelerometer (Step 2). The same process was used to classify activity in both turtle species, resulting in four categories.

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Fig 1 Expand

Fig 2.

Mean overall dynamic body acceleration (ODBA) as a function of the duration of the smoothing window for Blanding’s and Painted turtle terrestrial and aquatic motion, using accelerometer data sampled at 1 Hz.

Maximum ODBA value (solid line) and 95% of the maximum ODBA value (dashed) are indicated.

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Fig 2 Expand

Fig 3.

Qualitative selection of the most suitable threshold value (vertical line) relative to accuracy, sensitivity and specificity for Blanding’s turtles and Painted turtles, using accelerometer data sampled at 1 Hz.

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Fig 3 Expand

Table 1.

Overall classification performance for the testing data used to classify Blanding’s turtle and Painted turtle activity based on only accelerometry data, sampled at 1 Hz.

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Table 1 Expand

Table 2.

Overall classification performance for the testing data used to classify Blanding’s turtle and Painted turtle activity based on accelerometry and water sensor data, sampled at 1 Hz.

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Table 2 Expand

Table 3.

Classification performance for the testing data used to classify Blanding’s turtle and Painted turtle activity based on accelerometry data, using the other species’ threshold values.

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Table 3 Expand

Fig 4.

Daily activity-budget for Blanding’s (n = 16) and Painted turtles (n = 23) in the South March Highlands, Ottawa.

Shown are mean proportion (± SD) of time spent doing each of the four main states during a 24-hour period.

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Fig 4 Expand