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Camera Traps Can Be Heard and Seen by Animals

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. Citation: Meek PD, Ballard G-A, Fleming PJS, Schaefer M, Williams W, et al. (2014) Camera Traps Can Be Heard and Seen by Animals. PLoS ONE 9(10): e110832. doi:10.1371/journal.pone.0110832 Editor: Zhigang Jiang, Institute of Zoology, China Received June 8, 2014; Accepted September 14, 2014; Published October 29, 2014 Copyright:  2014 Meek et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. Raw audio data have been deposited to the University of New England E-publications Library: une-20140917-091534. Funding: These authors have no support or funding to report. Competing Interests: The authors have declared that no competing interests exist. * Email: paul.meek@invasiveanimals.com tested, the effect on behaviour can scarcely be considered non- Introduction intrusive [8] if animals display behavioural responses to sampling Camera traps are being used widely throughout the world tools. although the limitations and constraints of these devices are rarely Observations of responses to mensurative devices strongly imply considered. The study of animal ecology, biology and behaviour that learning can occur as a consequence of exposure to the requires thorough planning, robust analysis and an element of devices. For examples, camera traps could be detected by animals good luck. Irrespective of the tools being used, there will always be for the following reasons: expected errors, variability, unknowns or biases, described as being similar to the ‘‘Observer Effect’’ or ‘‘Heisenberg’s Uncertainty 1. Auditory – by the emission of sounds from the electronic and Principle’’ [1]. The study of animals can only provide an insight mechanical components of the device: these could be in the into their life history; nothing is absolute and understanding the infra, audible and ultra-sound ranges. variability is an important component of research investigations. 2. Olfactory – metal, plastic and human scents on the device Camera trapping is a survey tool that has improved our capacity to [6,9], infer the life history of animals, especially where minimising 3. Learned association – avoidance of the camera trap through observer effects on animal behaviour is critical [2–4]. Some wariness of human presence at a site [6] or attraction to the consider that camera traps are a non-intrusive method of studying camera trap through lures and food baits, animals [5]. However, there is increasing evidence throughout the 4. Visual (day) – neophobia towards foreign objects introduced world that animal behaviour is affected by the presence of camera into their environment; regular-shaped objects (essentially traps [6–9]. In some circumstances this ‘effect’ may have little rectangular prisms) attached to trees or posts [12,13], impact on the investigation. In other studies, for example those 5. Visual (night) – the flash of xenon light, white LED or infrared using indices and mark-recapture estimators (e.g., [1,10,11]), it is LED illumination [7]. paramount that the technology used does not alter animal behaviour during or between monitoring sessions to ensure The hearing and vision [22] of animals varies depending on constancy of detectability [8]. Where bias occurs, it is crucial that their life history, hunting modis operandi, body size [23,24] and this effect is understood and measured when interpreting the favoured prey [25]. It is commonly accepted that the combination results of the observations; ‘‘the accuracy of an index is irrelevant; of hearing and vision is important for animal localisation acuity precision is paramount’’ [11]. Irrespective of the hypothesis being PLOS ONE | www.plosone.org 1 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps [22], for hunting and social interactions and to avoid predators perceive brightness and hue [39] or if colour vision is in fact [26]. important to cats and dogs [40]. Interestingly, apart from Mustela spp. [17] very little is known about the detection of infrared signals by animals. Auditory ranges In the three main species of interest to us (dogs, cats and foxes), Hearing ranges are broad in mammals, as an example; mice their night visual acuity as primarily nocturnal predators is high; in (Mus domesticus) have a range from 2.3–92 kHz [29], horses the case of the cat, and more than likely foxes and dogs, their (Equus cabalus) hear up to 33.5 kHz, cows (Bos taurus) to 35 kHz superior night vision is adapted for low visual stimuli [41]. Of most [32], kangaroo rat (Dipodomys merriami) to 74 kHz, while the interest is the animal’s ability to detect near infrared (700– rabbit (Oryctologus cuniculus) can only hear to 49 kHz., cotton rat 3000 nm) illumination: the part of the light spectrum used in infra- (Sugmondon hispidus) to 72 kHz [29], wood rat (Neotoma red camera traps. floridana) to 56 kHz, grasshopper mouse (Onychomys leucogaster) 69 KhZ [33], and fox squirrel (Sciurus niger) 49 kHz [34]. A small Australian predator, the northern quoll (Dasyurus hallucatus) hear Objectives best from 8–10 kHz although their hearing range is 0.5–40 kHz We were interested in two critical questions related to the effect [31]. Six Australian Brush-tailed possum (Trichosurus vulpecula) of camera trapping on predator behaviour; were trained to respond to frequencies of 88 kHz [35]. Only bats, dolphins and shrews have been reported to recognise and detect 1. Do camera traps produce an audible sound that animals can hear, and infrared flash illumination that they can see, and is high frequency signals [36], although the authors propose that ‘‘it is not impossible that all primitive mammals are capable of there variability between camera trap models and modes? echolocation’’. 2. What is the effect of the sound and illumination on animal Our associated research primarily focuses on the management behaviour? of introduced predators [1], wild dogs (Canis lupus ssp) and European red foxes (Vulpes vulpes) and to a lesser extent on feral To answer the first part of this question we tested a range of cats (Felis catus). Feral and domestic cats have one of the broadest commonly used camera traps to determine the frequency and hearing ranges of all mammals [27], ranging from 48 Hz to 85 loudness of audio outputs and whether they fell within the hearing kHz, although responses have been reported up to 100 kHz [28]. range of target mammals. We then tested whether the infra-red Dogs show variability in sensitivity to sound depending on breed illumination from a range of models produced outputs that were (6–45 kHz) (https://www.lsu.edu/deafness/HearingRange.html within the perceptible range of known animal vision. Conducting accessed 3 July 2013) and as high as 65 kHz [28], although this tests on these camera traps was made possible using sophisticated has been disputed [30]. Foxes have evolved with a wide ranging technology; the challenge was obtaining enough data on vision hearing capacity (0.9–34 kHz) with optimal hearing at 10–14 kHz and hearing in mammals. Our objectives were to determine and an upper limit of 34 kHz [25] and 65 kHz [28]. whether 1) camera traps emit any sounds in the audible, infra or ultrasonic ranges for humans; 2) camera traps emit infrared illumination above the observable range of mammals; 3) mammals Visual ranges see or hear camera traps, 4) if there is variability in sounds and Dogs are known to have dichromatic colour vision with an light emissions within and between camera trap models. upper limit of detection around 555 nm [16], while Mustelids have Two authors have suggested that human odour on camera traps been reported to have the capacity to detect infrared light up to may have been a deterrent to coyotes (Canis latrans) visiting 870 nm [17]. In the case of Australian marsupials there is clear camera trap sites [6,9]; we constrained our investigations here to evidence of colour vision [18–20] with taxa variability in regards sound and light emissions. Our investigations achieved all four to spectral sensitivity (dichromatic vs trichromatic) [21]. objectives in comprehensively reporting the sound and visual Camera traps that use xenon white flash to illuminate animals outputs of and between camera trap models, and how these have been widely used in hunting and wildlife research [7] even outputs compare to the known hearing and visual acuity of though there is concern that the bright flash affects the short and animals. long term behaviour of target animals. In a study of Kinkajous (Potos flavus) behavioural avoidance of ‘canopy-highway’ branch- es where white flash camera traps were placed has been reported Materials and Methods [8]. Tiger (Panthera tigris tigris) capture rates in Nepal decreased The main focus of this study was to evaluate the camera trap by 50% over 5 nights of camera trapping using xenon flash devices audio outputs (,20 kHz) in relationship to the known hearing [7] and similar concerns have been raised in studies of grey wolves ranges of animals; complementary to this was to quantify potential (Canis lupus) [14]. Technological advances have resulted in ultrasound outputs (20–60 kHz) and the infrared illumination infrared camera traps dominating the market based on claims that spectrums for a range of camera trap models in relation to the animals can’t see the infrared flash [15]. known vision spectral data of animals. Most of the mammal species being studied using camera traps are nocturnal-crepuscular animals, although not always [19], with Camera Traps, Set-up and Triggering some showing a slight preponderance for diurnal activity; so their We tested 12 models of camera traps for audio outputs using still eye physiology reflects this behaviour. It would not be accurate to and video functions; 7 models for infrared outputs and 5 models state that animals can ‘‘see in the dark’’; a more accurate for ultra-sonic outputs (Table 1); the camera trap settings varied description may be that they are able to ‘‘see what is in the dark’’ between models according to their specifications and functionality [37]. Knowledge on the vision capabilities of animals continues to (see Table 1 for some details). improve despite limitations in fully understanding how they view For all measurements during the audio and infra-red optical the world because of the challenges of measuring what they perceive [38]. In fact some believe that the perception of colour output tests, camera traps were fixed on a tripod, 100 cm above vision requires some form of learning, association and conscious- the surface and set so that the front of the camera was 50 cm from ness [39]. Moreover, there is uncertainty as to whether animals the measuring device to optimise signal detection. Every camera PLOS ONE | www.plosone.org 2 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps PLOS ONE | www.plosone.org 3 October 2014 | Volume 9 | Issue 10 | e110832 Table 1. The camera trap models and numbers used to evaluate the sound outputs in an anechoic chamber. Make Model Sample Acoustic Infra-red Ultrasonic Photos/trigger Video time Sensitivity Reconyx HC600 10 NN N 3NA H Scoutguard 550 10 NN 310 H Scoutguard SG680 V 8* NN 310 H Moultrie I65 5* NN 110 H Moultrie I60 1 N 3NA- H Cuddeback Capture 3 NN 1NA H Picxontroller DigitalEye 3 N 1NA H Bushnell 119466 1 NN 310 H Bushnell 119456C 1 N 310 H Moultrie I40 1 N 110 H Moultrie D40 1 NN 110 H Scoutguard 560D 1 NN N 3NA- H Uway NT50 1 NN N 310 H Uway NX50 1 N 310 H *Ten units of this model were tested but some failed to operate and were removed from the analysis. NA = not available. doi:10.1371/journal.pone.0110832.t001 Audio and Optical Emissions from Camera Traps Table 2. The approximate hearing ranges of 24 animals using data extracted from (https://www.lsu.edu/deafness/HearingRange. html) and additional data from papers cited in this study. Animal Scientific name Approximate Range (Hz) Upper Range (KHz) bat Unknown sp 2,000–110,000 110 cat Felis catus 45–64,000 64 chicken Gallus gallus 125–2,000 2 cow Bos taurus 23–35,000 35 dog Canis lupus 67–45,000 45 elephant Loxodonta sp 16–12,000 12 ferret Mustela putorius furo 16–44,000 44 guinea pig Cavia porcellus 54–50,000 50 hedgehog Erinaceinae sp 250–45,000 45 horse Equus caballus 55–33,500 33 human Homo sapien 64–23,000 23 house mouse Mus musculus 2300–92,000 92 opossum Didelphis sp 500–64,000 64 rabbit Oryctolagus cuniculus 96–49,000 49 raccoon Procyon lotor 100–40,000 40 rat Rattus rattus 200–76,000 76 sheep Ovis aries 100–30,000 30 cotton rat Sigmondon hispidusi 1000–72,000 72 brush tailed possum Trichosurus vulpecula *??-88,000 88 fox squirrel Sciurus niger 113–49,000 49 northern quoll Dasyurus hallucatus 500–40,000 40 wood rat Neotoma floridana 940–56,000 56 grasshopper mouse Onychomys leucogaster 1850–69,000 69 kangaroo rat Dipodomys merriami 50–62,000 62 *lower hearing range is unknown for this species. doi:10.1371/journal.pone.0110832.t002 was tested separately and we conducted a countdown to infra-red sensor (PIR), resulting in stills and/or videos being taken. synchronise the measuring devices and to trigger the passive To trigger the camera traps, one of the authors stood in front and to one side of the device and waved a hand across the front of the camera four times at the end of the countdown. Every camera was tested for audio and optical outputs using still photos and where the function existed in a camera trap model, we tested video outputs. Acoustic Measurements Auditory outputs (.01–20 kHz). A Briel and Kjoer Type 2250 Hand held analyser was used in an anechoic chamber at the National Acoustics Laboratory in Chatswood, Sydney. The device was placed in front of the camera traps and automatically set to record camera outputs for 15 second periods. The equipment was calibrated to 94 db @1000 Hz using a Type 4230 Sound Level Calibrator. The data were generated by the analyser using an average amplification value for each of 17 frequencies over the 15 second recording period using five measurements (L ,L ,L , ZFmax ZSmax ZFmin L ,L ). Given our objective was to determine the maximum ZSmin Zeq audio outputs of the cameras, we only used L values in our ZFmax analysis. L is the maximum un-weighted audio level recorded ZFmax over the sampling period, so it is the highest level measured irrespective of frequency. Figure 1. Bootstrap estimates of the functional mean of the In order to calibrate the equipment to any background sound in anechoic chamber background sound envelope. doi:10.1371/journal.pone.0110832.g001 the anechoic chamber, we carried out ten ‘control’ recordings at PLOS ONE | www.plosone.org 4 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Figure 2. Bootstrap estimates of the functional mean (95% CI) of the sound emissions of the a) Reconyx HC600, b) Scoutguard SG 550, c) Scoutguard SG680 V, d) Moultrie I40, c) Moultrie I65, e) Pixcontroller DigitalEye and f) Cuddeback Capture taking still photos. doi:10.1371/journal.pone.0110832.g002 PLOS ONE | www.plosone.org 5 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Figure 3. Functional t-test results as a function of frequency for two select contrasts: a) Background sound- Cuddeback and b) HC600-Cuddeback. The red (solid) line indicates the permutation statistic (t ) results for 999 random permutations of the input data sequence max whilst the blue (dashed) line indicates the a = 0.05 critical level as a function of frequency. When the red (solid) line is equal or above the blue (dashed) line there was a significant difference at that frequency. doi:10.1371/journal.pone.0110832.g003 each of the 17 frequencies to derive the background sound envelope, with the decibels referenced to 20 micro Pascals (20610 Pa). Table 3. Comparisons between different camera outputs (still) and the background sound envelope. Model 1 Model 2 Statistic p-value Adjusted p-value Background HC600 t = 5.43 ,0.01* 0.056 max Background SG550 t = 2.73 0.22 1.00 max Background KG680 V t = 4.62 0.02* 0.53 max Background MI40 t = 5.14 0.02* 0.62 max Background MI65 t = 4.47 0.06 1.00 max Background Pixcontroller t = 4.27 0.13 1.00 max Background Cuddeback t = 13.53 ,0.01* 0.00 * max HC600 SG550 t = 3.44 0.07 1.00 max HC600 KG680 V t = 2.99 0.20 1.00 max HC600 MI40 t = 8.70 ,0.01* 0.00* max HC600 MI65 t = 3.60 0.17 1.00 max HC600 Pixcontroller t = 5.89 0.03* 0.76 max HC600 Cuddeback t = 18.03 ,0.01* 0.00* max SG550 KG680 V t = 3.10 0.17 1.00 max SG550 MI40 t = 6.74 0.01* 0.17 max SG550 MI65 t = 3.561835 0.16 1.00 max SG550 Pixcontroller t = 5.09 0.11 1.00 max SG550 Cuddeback t = 15.10 ,0.01* 0.00* max KG680 V MI40 t = 2.40 0.56 1.00 max KG680 V MI65 t = 3.53 0.17 1.00 max KG680 V Pixcontroller t = 5.01 0.04* 1.00 max KG680 V Cuddeback t = 15.10 ,0.01* 0.00* max MI40 MI65 t = 3.81 0.12 1.00 max MI40 Pixcontroller t = 4.16 0.21 1.00 max MI40 Cuddeback t = 11.00 0.03* 0.84 max MI65 Pixcontroller t = 4.38 0.08 1.00 max MI65 Cuddeback t = 12.99 ,0.01* 0.00* max Pixcontroller Cuddeback t = 21.97 ,0.01* 0.00* max Test statistics (t ) falling below the critical value are not significant at the particular frequency whilst those at or above were considered significant. (*denotes max significance at p,0.05). doi:10.1371/journal.pone.0110832.t003 PLOS ONE | www.plosone.org 6 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Figure 4. Bootstrap estimates of the functional mean and 95% Figure 5. Bootstrap estimates of the functional mean and 95% confidence envelopes for the Scoutguard SG550. confidence envelopes for the Scoutguard KG680. doi:10.1371/journal.pone.0110832.g004 doi:10.1371/journal.pone.0110832.g005 Ultrasonic outputs (4–200 kHz) To determine if ultrasonic frequencies were emitted by camera traps we used 10 Reconyx Hyperfire HC600, 3 Cuddeback Captures, 3 Pixcontroller DigitalEye, 1 Scoutguard 560D and 1 Uway NT50 camera traps. Control detections were also collected without a camera trap to measure any possible background sound outputs within the laboratory. As before, the camera traps were placed individually on a tripod 50 cm in front of two ANABAT Detectors connected to a ZCAIM unit. One detector was directly in front of the camera and the second at a 45 degree angle from the central axis of the camera. We tested both angles to assess whether signals were different when the devices were directly in front compared to off centre. Cameras were triggered by hand movements across the front of the camera and recordings were for 15 seconds each. Ultrasonic outputs were analysed using the acoustic analyser software, AnalookW. Light measurements Tests were conducted on 32 cameras comprising 7 models (Table 1) in a laboratory at the University of New England on th April 20 2011. Each camera was placed 80 cm from a hand-held Figure 6. Bootstrap estimates of the functional mean and 95% ASD Field Spectrometer (FS HH 325-1075) connected to a laptop confidence envelopes for the Moultrie MI40 camera. doi:10.1371/journal.pone.0110832.g006 computer to enable automated data storage. Flash outputs were recorded over a 17 millisecond per acquisition period using a 10 degree field of view lens. Ten measurements per camera motion frequencies (12.5 Hz–20 kHz) was established for a set of 10 (see above) were recorded. independent observations. Functional bootstrapping was applied to get the estimate of the mean curve and the associated 95% confidence curves [42]. Analysis boot Audio Outputs. Functional bootstrapping (n = 9999) [42] Due to the data collected by the sound analyser at 33 was used to estimate the mean curve and confidence curves (95% frequencies, we treated the audio spectrums as ‘‘functional’’, thus CI) using the L outputs for each camera trap model (stills and L was a function of frequency. Analysis of the infrared ZFmax ZFmax videos or both) where these features were available. Comparisons illumination and ultrasonic outputs were constrained to presenta- of still images within camera trap models were undertaken to tion of summary statistics and raw data because the data was evaluate variability using the functional mean to estimate average constrained by the unequal sample sizes of the camera trap models response for each camera trap model, and functional standard we had available. Furthermore, the ultrasonic data can only be deviation to assess variability within the same models. reported in ANALOOK format as ranges and not as raw data. Intra-and Inter Model Comparisons. Functional t-tests Background sound. The L variable was used for ZFmax [43] were used to compare outputs between camera traps, and analysing the audio outputs in our analysis. A background sound between camera trap models and to the background sound ‘envelope’ and the 95% confidence envelope across a range of PLOS ONE | www.plosone.org 7 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Table 4. Comparisons between different video camera outputs as well as the background (*: denotes statistical significance below the p = 0.05 level). Model 1 Model 2 Statistic p-value Adjusted p-value Background MI40 t = 4.15 0.08 0.75 max Background MI65 t = 4.89 0.03* 0.28 max Background SG550 t = 3.02 0.17 1.00 max Background KG680 V t = 2.88 0.41 1.00 max MI40 MI65 t = 4.33 0.13 1.00 max MI40 SG550 t = 10.24 ,0.01* 0.02* max MI40 KG680 V t = 3.71 0.21 1.00 max MI65 SG550 t = 4.32 0.05 0.52 max MI65 KG680 V t = 3.71 0.12 1.00 max SG550 KG680 V t = 3.50 0.21 1.00 max doi:10.1371/journal.pone.0110832.t004 envelope. Given there were 28 comparisons we predicted an compared to the published frequency hearing range of animals increased chance of ‘false positives’, as such we adjusted the p- using a Wilcoxon test (non-parametric). We plotted mean values using the ‘false discovery rate’ method [44] to account for frequency and 95% confidence intervals and used the reported this situation. hearing frequencies of 24 animals (Table 2) to determine likely Ultrasonic Outputs. Ultrasonic camera trap outputs were relationships between hearing and sound outputs. Data available recorded using an ANABAT Detector but this device does not on the University of Toledo ‘Behavioural Audiograms of provide raw data points and merely plots the data as a graph Mammals website (http://psychology.utoledo.edu/showpage. displaying the range of signals detected and the patterns. As such asp?name=mammal_hearing, accessed 6 June 2014) of known we were unable to accurately analyse variability within and hearing ranges of animals was compared to the audio output of the between models so the data has been collated to report on the camera traps. The hearing of one key species, the European Red ranges detected. Fox (Vulpes vulpes) has not been recorded in any investigations, so Infrared Outputs. Summary statistics were generated for the the known hearing range was unavailable. To overcome this light outputs across the range of infrared camera trap models, constraint we extracted the calling frequencies of red foxes from these are presented graphically; comparisons between infrared published research [28,45] using data extraction software ranges and animal range was not undertaken in detail due to a lack (PlotDigitizer http://plotdigitizer.sourceforge.net, accessed 6 June of data on animal infrared vision. 2014). We then used these data as a baseline hearing range for the Comparison with known animal hearing range. A mean red fox based on the assumption that foxes are calling to each audio output using ten HC600 Reconyx camera traps (chosen to other on this frequency and as such should hear these ranges. be representative of the quietest models) was produced and Figure 8. Functional t-statistics as a function of frequency for the MI40-SG550 V contrast in video mode. The test statistic (t ) max is displayed as a solid line and the a = 0.05 critical value as a function of Figure 7. Bootstrap estimates of the functional mean and 95% frequency is displayed as a dashed line. confidence envelopes for the Moultrie MI65 camera. doi:10.1371/journal.pone.0110832.g008 doi:10.1371/journal.pone.0110832.g007 PLOS ONE | www.plosone.org 8 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Table 5. Still vs Video comparisons using functional t-tests (*: denotes statistical significance below the p = 0.05 level). Model Statistic p-value Adjusted p-value MI40 t = 2.17 0.74 1.0 max MI65 t = 2.99 0.41 1.0 max SG550 t = 1.95 0.73 1.0 max KG680 V t = 2.98 0.35 1.0 max doi:10.1371/journal.pone.0110832.t005 suggesting that the values measured might be related to the Results frequency dependent accuracy of the measuring equipment. We found strong evidence that animals can hear the sound of, Intra-camera trap comparisons - Still Images. Both the and see the infra-red illumination of camera traps. background sound and the camera models displayed means and standard deviations that were frequency dependent. Each model Audio Outputs of Camera Traps of camera seemed to have their own unique signature (see Table Background sounds. Our data show that the functional S1 and Figure S1) with characteristic peaks and oscillations. There mean and standard deviation magnitudes of the background was a semi-regular pattern to the uncertainty within a camera sounds were highly frequency dependent (Fig. 1). Particular model, with particular sets of frequencies specific to camera model frequencies tended to be associated with a higher level of average although displaying the greatest variation within camera trap background sound (e.g. 12.5 Hz, 160 Hz, 250 Hz) with sound models. ranging from 8.8 dB to 28.4 dB. The variation in the sound In analysing 10 Reconyx HC600 we established that the mean measurements changed considerably as a function of frequency. values range from 7.6 dB to 27.1 dB across the frequency range The three largest standard deviations in sound outputs of camera (12.5 to 20,000 Hz) with a standard deviation ranging from 0.8 dB traps occur at 50 Hz, 12.5 Hz, and 500 Hz, with the total range of to 17.2 dB (Fig. 2). There was a substantial difference in the the standard deviation estimates across frequency being 0.9– magnitude of the camera output with the top three ‘loudest’ 14.3 Hz. The largest mean values and the greatest standard frequencies (12,500 Hz, 12.5 Hz, and 25 Hz) and the three deviation of sound components occurred at the lower frequencies Table 6. Ultrasonic outputs from five camera trap models including two control recordings, two ANABAT directions were utilised (directly in front and offset 45 degrees to the central axis of the camera). directly in front off-set 45 degrees Model and Code Lower (kHz) Upper (kHz) Lower (kHz) Upper (kHz) HC600–1 3 35 3 40 HC600–2 3 20 3 35 HC600–3 3 50 3 45 HC600–4 3 55 3 50 HC600–5 3 60 3 55 HC600–6 3 55 3 0 HC600–7 0000 HC600–8 3 55 3 50 HC600–9 0000 HC600–10 3 50 3 45 Cuddeback-1 3 40 3 55 Cuddeback-2 3 40 3 60 Cuddeback-3 3 60 3 40 Pixcontroller-1 0000 Pixcontroller-2 00345 Pixcontroller-3 3 35 0 0 Scoutguard560D-1 3000 Uway NT50–1 3 35 3 0 Control1 0000 Control2 0000 doi:10.1371/journal.pone.0110832.t006 PLOS ONE | www.plosone.org 9 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Figure 9. Dog (1), cat (2) and rat (3) hearing ranges in relation to the outputs of HC600 camera traps (1a, 2a, 3a) and as a function of frequency (1b, 2b, 2c). The black line is the mean audio output of the camera trap; the grey dotted lines are the 95% confidence limits. The red dotted lines represent the standard error around the known hearing range of the dog, cat and rat. Where the grey points and red dotted lines (SE) are below and closest to the mean audio output of the camera, the sound can be detected by the animal. doi:10.1371/journal.pone.0110832.g009 highest standard deviation values 10,000 Hz, 5,000 Hz, and the functional mean was from 11.0 dB to 34.3 dB, with the top 25 Hz. three highest values occurring at 2,500 Hz, 31.5 Hz, and 125 Hz. The Scoutguard SG 550 (still) functional mean was frequency The Scoutguard KG680 V had a unique ‘signature’ as well as dependent with spikes at 2500 Hz, 5000 Hz, and 10,000 Hz, frequency dependent characteristics in the functional mean. The although different to the HC600 (stills) and the background sound range of the functional mean was 8.1 dB to 30.2 dB with the three (Fig. 2). The functional standard deviation was also frequency highest values occurring at 8,000 Hz, 160 Hz, and 12.5 Hz. dependent and similar to the HC600. At 250, 5000 and 10000 Hz These frequencies show the greatest variability within a model and the variability in the output (L ) between cameras was greatest are quite different to the HC600 and SG 550. The functional ZFmax within a model (i.e., Reconyx still, Scoutguard still). The range of means of the Moultrie I40 display frequency dependency. The PLOS ONE | www.plosone.org 10 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Figure 10. The auditory threshold of 6 mammals represented as a function of frequency. doi:10.1371/journal.pone.0110832.g010 signature was also unique but due to the very small sample size 35.0 dB with the top three values occurring at 12.5 Hz, 4000 Hz, (n = 4) there is some uncertainty in the estimates. and 80 Hz. We found that there were sharp and sudden shifts in the The Pixcontroller DigitalEye also had a unique sound signature L statistic for different frequencies in this model. The range of and shared some similarities with the background sound profile. It ZFmax the functional mean was 10.3 dB to 37.8 dB whilst the functional also exhibited frequency dependent structure in both the standard deviation ranged from 0.4 dB to 16.3 dB. The three functional mean (10.7 dB–33.7 dB, maximal values at 160 Hz, greatest values of the functional mean occurred at 50 Hz, 40 Hz, 12.5 Hz, and 2000 Hz.) and standard deviation (0.5 dB–10.3 dB) and 12.5 Hz. The greatest variability occurred at 3150 Hz, with the top three values occurring at 800 Hz, 63 Hz, and 500 Hz, and 80 Hz in this order. Similarly, there was a frequency 12.5 Hz. dependence and unique sound signature in the Moultrie I65 Three Cuddeback cameras produced functional mean ranges camera trap The range of the functional mean was from 12.3 dB– from 14.3 dB to 41 dB with the top three values occurring at PLOS ONE | www.plosone.org 11 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps and Pixcontroller-Cuddeback were statistically significantly differ- ent. There were a further seven contrasts that seem to be statistically significant different but they did not pass the multiple comparisons adjustment. There was a significant difference in the background sound and the Cuddeback, which consistently produced louder sound outputs (16 Hz: Background – 15.9 dB Cuddeback- 23.7 dB, 80 Hz: Background- 14.9 dB Cuddeback- 29.0 dB, 400 Hz: Background – 8.8 dB, Cuddeback- 28.0 dB) (Fig. 3). The contrast between Reconyx HC600- Moultrie MI40 could either be a statistical anomaly or could indicate a difference in the operational frequency response for these two cameras, which is so minute that it is within the variation of the background sound envelope. These analyses confirm that different camera models exhibit unique sound profiles but not discernibly different to the variability within models. We found that for most frequencies, particularly the low to medium frequencies, significant differences exist. Intra camera trap comparisons - Video Of the four camera trap models tested, the Scoutguard SG550 Figure 11. Comparison of the predicted hearing range of the (Fig. 4) showed an overall decreasing trend with an occasional red fox in relation to the outputs of HC600 camera traps and as a function of frequency. minor peak where the operational sound or the uncertainty in the doi:10.1371/journal.pone.0110832.g011 estimate or uncertainty between models was higher. The operational sound characteristics appeared similar to that of the 400 Hz, 500 Hz (equal highest), and 2000 Hz (functional standard Moultrie MI40 but the functional standard deviation was higher at lower frequencies. deviation 0.5 dB–7.9 dB with the three largest values occurring at 12.5 Hz, 2000 Hz, and 8000 Hz. In the Scoutguard KG680, the functional mean exhibited a slow decrease in operational sound level with frequency (Fig. 5). Of note was the relative tight envelope around the estimate of the Comparisons between camera traps in still modes and mean indicating that this curve was estimated with far less background sounds uncertainty than the other models. There were several contrasts displaying significant differences In the Moultrie MI40 the functional mean of the sound is highly between models (Table 3). Specifically, comparisons between the frequency dependent (Figures 6 and Table 4). The operational Background-Cuddeback, HC600-MI40, HC600-Cuddeback, sound of the camera and the variation between models vary with SG550-Cuddeback, KG680 V-Cuddeback, MI65-Cuddeback, Figure 12. Mean infra-red wavelength illumination (nm) outputs for seven camera trap models showing the highest and lowest values. doi:10.1371/journal.pone.0110832.g012 PLOS ONE | www.plosone.org 12 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Figure 13. Infra red illumination of two opposing Reconyx HC600 camera traps simultaneously triggering. doi:10.1371/journal.pone.0110832.g013 frequency. The highest operational sound occurred at the lowest around 1000 Hz but it was still within the range of the background frequencies as well as the greatest variation and uncertainty sound (Fig. 8). between models. Except at very low frequencies and a slight (t <1–1.5) max A slight frequency dependent response was observed in the variation around 1000 Hz, there were no significant differences in response across frequencies. The secondary peak at 1000 Hz is Moultrie MI65 (Fig. 7) around the mean, but the standard deviation estimate was highly frequency dependent with a indicative of a difference in the functional mean estimates for these pronounced peak occurring in the 0–3 kHz band and a general two cameras in video mode. linear increase occurring from 4–20 kHz. The increasing width of the 95% confidence envelope as frequency increases reflects Comparisons between Still and Video Modes uncertainty with increasing frequency. This might be due to low There was no difference in still and video frequency response or sample sizes and our inability to establish whether or not the mean between the four camera models (Scoutguard and Moultrie) curve increases, remains stationary, or decreases at these (Table 5). frequencies. These data show that the sound level for the MI65 is higher than the MI40. Ultrasonic recordings Estimates of the mean audio output and standard deviation Ultrasound frequencies tests on the five camera trap models were estimated as a function of frequency for four different camera confirm that camera traps do produce ultrasonic outputs each time models operating in video mode. All cameras appear to have a photo is taken (Table 6). Frequency ranges for Reconyx HC600 frequency dependent operational characteristics and furthermore was 3–60 kHz with a median output of 52.5 kHz (SD = 13.4) there appears to be differences in the mean sound levels between directly in front of the device and 47.5 kHz (SD = 7.3) models. Importantly, the standard deviation curve estimates within perpendicular to the device. Other models emitted outputs within a model appear greater or on similar magnitude to the mean a similar range. There was some variability within models due to differences between cameras. This could be due to the limited the method of measuring the outputs; ANABAT detectors are number of camera traps models, although this is unlikely because designed to measure bat echolocation not low level ultrasonic the analysis suggested wide variation in magnitude and form. sound. Comparisons between Video Modes and Background Audio Outputs and Known Hearing Ranges of Animals Sound Our tests comparing Reconyx (HC600) camera trap outputs to Our functional tests with multiple comparison corrections for the existing hearing ranges of 21 species (see http://psychology. background sound in video mode showed no significant difference utoledo.edu/showpage.asp?name=mammal_hearing, accessed 6 (Table 4). There was however a difference in audio outputs June 2014) found compelling evidence that camera trap sound between the MI40 and SG550 with a difference in the response outputs fall within the hearing range of most of the species (Fig. 9– 11). In 9b, 9b and 9c we have presented data to show the PLOS ONE | www.plosone.org 13 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps relationship between the camera sound and the auditory threshold reported the frequency of a range of calls made by foxes to be less of the animal as a function of frequency. These data strongly than 2 kHz, which is consistent with one other study [45] that suggest that dogs, cats and rats have the capacity to detect low reported calls all under 2.5 kHz. The foxes hearing capacity has frequency outputs (,20 kHz) from camera traps. Data presented been reported to have a reduced capacity between 5–11 kHz with in Figure 10 provide evidence that a further six mammals, a discernible reduction around 8.5 kHz, but reported that they including humans, have the capacity to detect camera traps in hear sounds well at 10–14 kHz [25]. Given red fox calling the lower frequency bandwidths. The hearing ranges in compar- frequencies, they would certainly hear some of the infra and ultra ison to camera trap outputs for a further 12 mammals are sounds emitted by camera traps. We report the first evidence that provided in Figure S2. animals can detect the presence of camera traps due to the audio Given the paucity of data on the known hearing range of red and optical outputs from these devices. This study determined that foxes we carried out a comparison on the minimal hearing range at certain frequencies, animal hearing (Table 2 and see http:// for this species based on their calling frequencies [25,45] (Fig. 11). www.lsu.edu/deafness/HearingRange.html, accessed 6 June This was based on the assumption that foxes must be able to hear 2014) can easily detect these sounds. the frequency of fox calls recorded at a minimum. From this The results of our testing also provide conclusive evidence that analysis we derived an optimum hearing range for the red fox of camera traps do emit ultrasonic outputs, especially when battery around 8–12 kHz although this would be an under-estimation of levels are low. In a pilot trial we found that low powered batteries their true range. Despite having to use call frequencies to model resulted in the ANABAT detecting an output but in subsequent hearing range, the results show that red foxes can easily hear tests with fully charged batteries, there was no audible signal camera trap outputs. suggesting that camera trap outputs vary with battery life. The use The data presented provide robust evidence that mammals can of a bat call monitoring device has been used previously to test detect the sound outputs of camera traps. LED lights being used in research on Mustella vision [17]. The authors were unable to detect any outputs by the lights, however in Infra-red Wavelength Outputs the case of camera traps there are a range of electrical and The infra-red illumination ranges varied between models mechanical components apart from the LED circuitry that may be (Fig. 12) but there was no difference in wavelength outputs within emitting sound. models for the Reconyx HC600 (Mean = 940.5, SD = 1.8, 95% CI = 1.3), Scoutguard 550 (Mean = 828.3, SD = 4.7, 95% Animal Vision CI = 3.4) and Scoutguard 680 V (mean = 844.1, SD = 0.6, 95% Information on the extent of infrared detection by other CI = 0.5) camera traps. mammals is scant in the literature. There have been some Based on the data in Figure 12, camera traps that are advertised investigations using behavioural methods that report some animals as ‘‘no glow’’ (HC600) or ‘‘black ops’’ (NT50) are clearly using can see infrared light in the range 539–870 nm although the infrared technology with wavelengths operating above 850 nm. evidence is limited across the taxa. As such we were unable to These infrared LED’s are emitting light that is nearly invisible to conduct any comparative analysis of infrared flash light outputs the human eye, but not some animals. with animal vision to test our hypotheses. Research has established that Honey Possums (Tarsipes rostrata) Discussion are able to see light in the 557 nm range [18] while ferrets (Mustela furo) can see around 870 nm [17] and Tamar Wallaby In this study we tackled the first part of a two staged question; (Macropus eugenii) peaked at 539 nm [20]. do camera traps have the capacity to project audio and optical These data probably underestimate the extent of an animal’s stimuli to wildlife? Moreover, are these outputs different between ability to detect infrared light since they are based on behavioural and within models and recording modes (still or video)? We studies [38], not physiological analysis, because such technology is present these data on the audio and visual outputs of camera traps unavailable. As such, we are unable to state exactly what the limits to highlight the importance of identifying the effects camera of animal vision might be, and we believe that the range of trapping may have on animal behaviour. infrared light presented in Figure 12 are likely seen by many species of animal. In support of this claim, one of the authors (PM) Animal Hearing was able to see a faint red glow of a Reconyx HC600 in absolute A wide range of comparisons were conducted to investigate the darkness. Reports of humans detecting infrared (1064 nm) well possibility of differences in operating audio outputs of different above the illumination currently used in camera traps have been camera models in both still and video mode. In the vast majority of recorded [47,48]. This being the case, there is no doubt that cases (except the Cuddeback) the operational sound was little nocturnal animals with vision sensitive to night light can see different from the background sound in the sound laboratory. In infrared illumination. The responses of animals to infrared flash some cases slight differences were found between models (e.g. are highly variable between species and individuals (Meek Unpub MI40 and SG550 video) but were of such a low level that they data; Ballard Unpub data). While we cannot measure exactly what were within the magnitude of the background sound. The noise animals see, they most likely see a similar image to the flash created by two people being present in the anechoic chamber recorded by two camera traps triggered simultaneously, as shown conducting the experiments probably produced sounds and in Figure 13. affected the background sound envelope. If we were able to Cats appear to detect the presence of camera traps more than conduct the tests remotely there may have been a more significant other animals (Meek Unpub data; Ballard Unpub data), which is difference between camera trap noise and background noise. probably due to their retina sensitivity at 826 nm [49] and total In comparing the auditory range of animals in contrast to our vision field of view being 287u with binocular over lap of 130u recorded outputs, we sourced sonagraph data for a range of [37]. This peripheral view combined with the very high sensitivity species. There have not been any sonagraphs to determine the hearing ranges of foxes although it has been reported that red fox to infrared light at the higher end of the near infrared spectrum would make cats more than capable of easily detecting camera have an upper limit of 65 kHz [37]. While studies of 75 foxes [46] PLOS ONE | www.plosone.org 14 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps trap flashes; especially in models with light emissions below multiple frequencies and background scatter exist are less likely to 800 nm (see Fig. 12). be detected by animals [55]. The effects of white flash camera traps on animal behaviour In some studies the target species’ ability to detect a camera trap have been recognised as an intrusive survey method because it has may not be important because the requirement is to detect been shown to startle and cause animals to flee (7). Some authors presence only, so irrespective of whether the animal baulks and have suggested that using infrared illumination may reduce this runs from a camera trap is of no importance. Where repeat visits flight response [7,8,14], especially where infrared wavelengths to a site are imperative for analysis, i.e., mark recapture, exceed ,870 nm [17]. While there is little information on the photographic indexes, CPUE and activity indexes, the interference detectable range of infrared wavelengths by most animals, one to behaviour and potential avoidance of the camera trap may study did find that ferrets’ (Mustelo furo) maximum observable introduce a bias on the probability of detection. An issue also range was about 870 nm [17]. Multiple images and corresponding raised by in one study [17] in regard to the potential for infrared footprint detecting plots from our research on feral cats, wild dogs light emitting surveillance devices or traps to cause avoidance by and foxes in Australia over several years indicates that all three animals. species can detect flash illumination from Reconyx HC600 camera There is a convincing argument presented in this study to traps (Meek Unpub data; Ballard Unpub data). In field trials confirm that most mammals can hear the operational sounds where two HC600 were facing each other, we were able to generated by camera traps in both the infrasound and ultrasound accidentally trigger the cameras to simultaneously trigger showing ranges. Moreover, given the strong relationship between vision visually what nocturnal animals may see when infra red and hearing acuity [22], this study concludes that most mammals illumination occurs (Fig. 13) [50]. can see the infra-red illumination used in camera traps. Anecdotal reports of ship rats (Rattus rattus) and brush-tailed possums (Trichosurus vulpecula) from three unpublished studies Supporting Information describe avoidance of infrared illumination in these species (see [17]). Although there has not been any effect found on predator Figure S1 The noise frequency outputs of twelve camera behaviour around ground-nesting bird nests from infrared camera trap models and the background control. traps used to detect visitation [51]. (TIF) Despite wide spread belief that humans cannot see near infrared Figure S2 The hearing range of an additional twelve light, many authors have reported being able to detect infrared animals in comparison to the noise outputs of a camera light during experiments and these descriptions have been trap. described [17]. On the evidence presented in the literature and (TIF) summarised here, we conclude that most nocturnal or arrhythmic (nocturnal with some diurnal activity) mammals can see the Table S1 The mean audio outputs of 12 camera trap infrared illumination (flash) emitted by camera traps. models at different frequencies. (DOCX) Conclusions Hearing and vision work together to form what is referred to as Acknowledgments auditory localisation acuity [22]; where an animal hears a sound Thanks to the Schultz Foundation for their support and provision of some and turns towards the sound using eye sight to focus in on the camera traps to use in our experiments. We greatly appreciate the technical stimuli. This is probably the case in camera trapping, where a assistance of Greg Stewart of the National Acoustic Laboratory and Keryn sound is heard by a passing animal and the device is further Lapidge of the Invasive Animals CRC. Thank you to Damien Byrne from recognised by vision, thus enabling animals to detect the device. Outdoor Cameras Australia and Nick Dexter of Jervis Bay National Park With the constant sounds of the forest animals are unlikely to be for lending us some camera traps. We appreciate the technical support and hearing the camera traps constantly as the frequency and advice provided by Matt Dobson in recording the ultrasonic outputs. amplitude values are very similar. Furthermore, the audio outputs Thank you to Julian Partridge, Christa Neumeyer, Nathan Hart, Lyn collected in the anechoic chamber were recorded at 50 cm, and it Beazley, Catherine Arresse and Henry Heffner for their invaluable advice and opinions on animal hearing and vision. is reported that with every metre away from the camera a loss of 6 dB is expected [52]. Sound levels are affected by distance from the source, atmospheric attenuation, terrain, ground cover, wind Author Contributions and weather [53], forest density (a function of limb and trunk Conceived and designed the experiments: PM GB PF WW MS. Performed density) and foliage [54] and as such we acknowledge that this the experiments: PM GB PF WW MS. Analyzed the data: PM GF WW attenuation may reduce sounds from camera traps under field MS. Contributed reagents/materials/analysis tools: PM GB PF WW MS conditions. This is because unlike the pure sounds recorded by GF. Contributed to the writing of the manuscript: PM GB PF WW MS audiograms, complex sounds like those in a natural setting where GF. References 1. Caughley G (1977) Analysis of Vertebrate Populations. London: John Wiley & 6. Se´quin ES, Jaeger MM, Brussard PF, Barrett RH (2003) Wariness of coyotes to Son. camera traps relative to social status and territory boundaries. Canadian Journal 2. Swann DE, Hass CC, Dalton DC, Wolf SA (2004) Infrared-triggered cameras of Zoology 81: 2015–2025. for detecting wildlife: an evaluation and review. Wildlife Society Bulletin 32: 7. Wegge P, Pokheral CP, Jnawali SR (2004) Effects of trapping effort and trap 357–365. shyness on estimates of tiger abundance from camera trap studies. Animal Conservation 7: 251–256. 3. 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Camera Traps Can Be Heard and Seen by Animals

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Pubmed Central
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© 2014 Meek et al
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1932-6203
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1932-6203
DOI
10.1371/journal.pone.0110832
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Abstract

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. Citation: Meek PD, Ballard G-A, Fleming PJS, Schaefer M, Williams W, et al. (2014) Camera Traps Can Be Heard and Seen by Animals. PLoS ONE 9(10): e110832. doi:10.1371/journal.pone.0110832 Editor: Zhigang Jiang, Institute of Zoology, China Received June 8, 2014; Accepted September 14, 2014; Published October 29, 2014 Copyright:  2014 Meek et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. Raw audio data have been deposited to the University of New England E-publications Library: une-20140917-091534. Funding: These authors have no support or funding to report. Competing Interests: The authors have declared that no competing interests exist. * Email: paul.meek@invasiveanimals.com tested, the effect on behaviour can scarcely be considered non- Introduction intrusive [8] if animals display behavioural responses to sampling Camera traps are being used widely throughout the world tools. although the limitations and constraints of these devices are rarely Observations of responses to mensurative devices strongly imply considered. The study of animal ecology, biology and behaviour that learning can occur as a consequence of exposure to the requires thorough planning, robust analysis and an element of devices. For examples, camera traps could be detected by animals good luck. Irrespective of the tools being used, there will always be for the following reasons: expected errors, variability, unknowns or biases, described as being similar to the ‘‘Observer Effect’’ or ‘‘Heisenberg’s Uncertainty 1. Auditory – by the emission of sounds from the electronic and Principle’’ [1]. The study of animals can only provide an insight mechanical components of the device: these could be in the into their life history; nothing is absolute and understanding the infra, audible and ultra-sound ranges. variability is an important component of research investigations. 2. Olfactory – metal, plastic and human scents on the device Camera trapping is a survey tool that has improved our capacity to [6,9], infer the life history of animals, especially where minimising 3. Learned association – avoidance of the camera trap through observer effects on animal behaviour is critical [2–4]. Some wariness of human presence at a site [6] or attraction to the consider that camera traps are a non-intrusive method of studying camera trap through lures and food baits, animals [5]. However, there is increasing evidence throughout the 4. Visual (day) – neophobia towards foreign objects introduced world that animal behaviour is affected by the presence of camera into their environment; regular-shaped objects (essentially traps [6–9]. In some circumstances this ‘effect’ may have little rectangular prisms) attached to trees or posts [12,13], impact on the investigation. In other studies, for example those 5. Visual (night) – the flash of xenon light, white LED or infrared using indices and mark-recapture estimators (e.g., [1,10,11]), it is LED illumination [7]. paramount that the technology used does not alter animal behaviour during or between monitoring sessions to ensure The hearing and vision [22] of animals varies depending on constancy of detectability [8]. Where bias occurs, it is crucial that their life history, hunting modis operandi, body size [23,24] and this effect is understood and measured when interpreting the favoured prey [25]. It is commonly accepted that the combination results of the observations; ‘‘the accuracy of an index is irrelevant; of hearing and vision is important for animal localisation acuity precision is paramount’’ [11]. Irrespective of the hypothesis being PLOS ONE | www.plosone.org 1 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps [22], for hunting and social interactions and to avoid predators perceive brightness and hue [39] or if colour vision is in fact [26]. important to cats and dogs [40]. Interestingly, apart from Mustela spp. [17] very little is known about the detection of infrared signals by animals. Auditory ranges In the three main species of interest to us (dogs, cats and foxes), Hearing ranges are broad in mammals, as an example; mice their night visual acuity as primarily nocturnal predators is high; in (Mus domesticus) have a range from 2.3–92 kHz [29], horses the case of the cat, and more than likely foxes and dogs, their (Equus cabalus) hear up to 33.5 kHz, cows (Bos taurus) to 35 kHz superior night vision is adapted for low visual stimuli [41]. Of most [32], kangaroo rat (Dipodomys merriami) to 74 kHz, while the interest is the animal’s ability to detect near infrared (700– rabbit (Oryctologus cuniculus) can only hear to 49 kHz., cotton rat 3000 nm) illumination: the part of the light spectrum used in infra- (Sugmondon hispidus) to 72 kHz [29], wood rat (Neotoma red camera traps. floridana) to 56 kHz, grasshopper mouse (Onychomys leucogaster) 69 KhZ [33], and fox squirrel (Sciurus niger) 49 kHz [34]. A small Australian predator, the northern quoll (Dasyurus hallucatus) hear Objectives best from 8–10 kHz although their hearing range is 0.5–40 kHz We were interested in two critical questions related to the effect [31]. Six Australian Brush-tailed possum (Trichosurus vulpecula) of camera trapping on predator behaviour; were trained to respond to frequencies of 88 kHz [35]. Only bats, dolphins and shrews have been reported to recognise and detect 1. Do camera traps produce an audible sound that animals can hear, and infrared flash illumination that they can see, and is high frequency signals [36], although the authors propose that ‘‘it is not impossible that all primitive mammals are capable of there variability between camera trap models and modes? echolocation’’. 2. What is the effect of the sound and illumination on animal Our associated research primarily focuses on the management behaviour? of introduced predators [1], wild dogs (Canis lupus ssp) and European red foxes (Vulpes vulpes) and to a lesser extent on feral To answer the first part of this question we tested a range of cats (Felis catus). Feral and domestic cats have one of the broadest commonly used camera traps to determine the frequency and hearing ranges of all mammals [27], ranging from 48 Hz to 85 loudness of audio outputs and whether they fell within the hearing kHz, although responses have been reported up to 100 kHz [28]. range of target mammals. We then tested whether the infra-red Dogs show variability in sensitivity to sound depending on breed illumination from a range of models produced outputs that were (6–45 kHz) (https://www.lsu.edu/deafness/HearingRange.html within the perceptible range of known animal vision. Conducting accessed 3 July 2013) and as high as 65 kHz [28], although this tests on these camera traps was made possible using sophisticated has been disputed [30]. Foxes have evolved with a wide ranging technology; the challenge was obtaining enough data on vision hearing capacity (0.9–34 kHz) with optimal hearing at 10–14 kHz and hearing in mammals. Our objectives were to determine and an upper limit of 34 kHz [25] and 65 kHz [28]. whether 1) camera traps emit any sounds in the audible, infra or ultrasonic ranges for humans; 2) camera traps emit infrared illumination above the observable range of mammals; 3) mammals Visual ranges see or hear camera traps, 4) if there is variability in sounds and Dogs are known to have dichromatic colour vision with an light emissions within and between camera trap models. upper limit of detection around 555 nm [16], while Mustelids have Two authors have suggested that human odour on camera traps been reported to have the capacity to detect infrared light up to may have been a deterrent to coyotes (Canis latrans) visiting 870 nm [17]. In the case of Australian marsupials there is clear camera trap sites [6,9]; we constrained our investigations here to evidence of colour vision [18–20] with taxa variability in regards sound and light emissions. Our investigations achieved all four to spectral sensitivity (dichromatic vs trichromatic) [21]. objectives in comprehensively reporting the sound and visual Camera traps that use xenon white flash to illuminate animals outputs of and between camera trap models, and how these have been widely used in hunting and wildlife research [7] even outputs compare to the known hearing and visual acuity of though there is concern that the bright flash affects the short and animals. long term behaviour of target animals. In a study of Kinkajous (Potos flavus) behavioural avoidance of ‘canopy-highway’ branch- es where white flash camera traps were placed has been reported Materials and Methods [8]. Tiger (Panthera tigris tigris) capture rates in Nepal decreased The main focus of this study was to evaluate the camera trap by 50% over 5 nights of camera trapping using xenon flash devices audio outputs (,20 kHz) in relationship to the known hearing [7] and similar concerns have been raised in studies of grey wolves ranges of animals; complementary to this was to quantify potential (Canis lupus) [14]. Technological advances have resulted in ultrasound outputs (20–60 kHz) and the infrared illumination infrared camera traps dominating the market based on claims that spectrums for a range of camera trap models in relation to the animals can’t see the infrared flash [15]. known vision spectral data of animals. Most of the mammal species being studied using camera traps are nocturnal-crepuscular animals, although not always [19], with Camera Traps, Set-up and Triggering some showing a slight preponderance for diurnal activity; so their We tested 12 models of camera traps for audio outputs using still eye physiology reflects this behaviour. It would not be accurate to and video functions; 7 models for infrared outputs and 5 models state that animals can ‘‘see in the dark’’; a more accurate for ultra-sonic outputs (Table 1); the camera trap settings varied description may be that they are able to ‘‘see what is in the dark’’ between models according to their specifications and functionality [37]. Knowledge on the vision capabilities of animals continues to (see Table 1 for some details). improve despite limitations in fully understanding how they view For all measurements during the audio and infra-red optical the world because of the challenges of measuring what they perceive [38]. In fact some believe that the perception of colour output tests, camera traps were fixed on a tripod, 100 cm above vision requires some form of learning, association and conscious- the surface and set so that the front of the camera was 50 cm from ness [39]. Moreover, there is uncertainty as to whether animals the measuring device to optimise signal detection. Every camera PLOS ONE | www.plosone.org 2 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps PLOS ONE | www.plosone.org 3 October 2014 | Volume 9 | Issue 10 | e110832 Table 1. The camera trap models and numbers used to evaluate the sound outputs in an anechoic chamber. Make Model Sample Acoustic Infra-red Ultrasonic Photos/trigger Video time Sensitivity Reconyx HC600 10 NN N 3NA H Scoutguard 550 10 NN 310 H Scoutguard SG680 V 8* NN 310 H Moultrie I65 5* NN 110 H Moultrie I60 1 N 3NA- H Cuddeback Capture 3 NN 1NA H Picxontroller DigitalEye 3 N 1NA H Bushnell 119466 1 NN 310 H Bushnell 119456C 1 N 310 H Moultrie I40 1 N 110 H Moultrie D40 1 NN 110 H Scoutguard 560D 1 NN N 3NA- H Uway NT50 1 NN N 310 H Uway NX50 1 N 310 H *Ten units of this model were tested but some failed to operate and were removed from the analysis. NA = not available. doi:10.1371/journal.pone.0110832.t001 Audio and Optical Emissions from Camera Traps Table 2. The approximate hearing ranges of 24 animals using data extracted from (https://www.lsu.edu/deafness/HearingRange. html) and additional data from papers cited in this study. Animal Scientific name Approximate Range (Hz) Upper Range (KHz) bat Unknown sp 2,000–110,000 110 cat Felis catus 45–64,000 64 chicken Gallus gallus 125–2,000 2 cow Bos taurus 23–35,000 35 dog Canis lupus 67–45,000 45 elephant Loxodonta sp 16–12,000 12 ferret Mustela putorius furo 16–44,000 44 guinea pig Cavia porcellus 54–50,000 50 hedgehog Erinaceinae sp 250–45,000 45 horse Equus caballus 55–33,500 33 human Homo sapien 64–23,000 23 house mouse Mus musculus 2300–92,000 92 opossum Didelphis sp 500–64,000 64 rabbit Oryctolagus cuniculus 96–49,000 49 raccoon Procyon lotor 100–40,000 40 rat Rattus rattus 200–76,000 76 sheep Ovis aries 100–30,000 30 cotton rat Sigmondon hispidusi 1000–72,000 72 brush tailed possum Trichosurus vulpecula *??-88,000 88 fox squirrel Sciurus niger 113–49,000 49 northern quoll Dasyurus hallucatus 500–40,000 40 wood rat Neotoma floridana 940–56,000 56 grasshopper mouse Onychomys leucogaster 1850–69,000 69 kangaroo rat Dipodomys merriami 50–62,000 62 *lower hearing range is unknown for this species. doi:10.1371/journal.pone.0110832.t002 was tested separately and we conducted a countdown to infra-red sensor (PIR), resulting in stills and/or videos being taken. synchronise the measuring devices and to trigger the passive To trigger the camera traps, one of the authors stood in front and to one side of the device and waved a hand across the front of the camera four times at the end of the countdown. Every camera was tested for audio and optical outputs using still photos and where the function existed in a camera trap model, we tested video outputs. Acoustic Measurements Auditory outputs (.01–20 kHz). A Briel and Kjoer Type 2250 Hand held analyser was used in an anechoic chamber at the National Acoustics Laboratory in Chatswood, Sydney. The device was placed in front of the camera traps and automatically set to record camera outputs for 15 second periods. The equipment was calibrated to 94 db @1000 Hz using a Type 4230 Sound Level Calibrator. The data were generated by the analyser using an average amplification value for each of 17 frequencies over the 15 second recording period using five measurements (L ,L ,L , ZFmax ZSmax ZFmin L ,L ). Given our objective was to determine the maximum ZSmin Zeq audio outputs of the cameras, we only used L values in our ZFmax analysis. L is the maximum un-weighted audio level recorded ZFmax over the sampling period, so it is the highest level measured irrespective of frequency. Figure 1. Bootstrap estimates of the functional mean of the In order to calibrate the equipment to any background sound in anechoic chamber background sound envelope. doi:10.1371/journal.pone.0110832.g001 the anechoic chamber, we carried out ten ‘control’ recordings at PLOS ONE | www.plosone.org 4 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Figure 2. Bootstrap estimates of the functional mean (95% CI) of the sound emissions of the a) Reconyx HC600, b) Scoutguard SG 550, c) Scoutguard SG680 V, d) Moultrie I40, c) Moultrie I65, e) Pixcontroller DigitalEye and f) Cuddeback Capture taking still photos. doi:10.1371/journal.pone.0110832.g002 PLOS ONE | www.plosone.org 5 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Figure 3. Functional t-test results as a function of frequency for two select contrasts: a) Background sound- Cuddeback and b) HC600-Cuddeback. The red (solid) line indicates the permutation statistic (t ) results for 999 random permutations of the input data sequence max whilst the blue (dashed) line indicates the a = 0.05 critical level as a function of frequency. When the red (solid) line is equal or above the blue (dashed) line there was a significant difference at that frequency. doi:10.1371/journal.pone.0110832.g003 each of the 17 frequencies to derive the background sound envelope, with the decibels referenced to 20 micro Pascals (20610 Pa). Table 3. Comparisons between different camera outputs (still) and the background sound envelope. Model 1 Model 2 Statistic p-value Adjusted p-value Background HC600 t = 5.43 ,0.01* 0.056 max Background SG550 t = 2.73 0.22 1.00 max Background KG680 V t = 4.62 0.02* 0.53 max Background MI40 t = 5.14 0.02* 0.62 max Background MI65 t = 4.47 0.06 1.00 max Background Pixcontroller t = 4.27 0.13 1.00 max Background Cuddeback t = 13.53 ,0.01* 0.00 * max HC600 SG550 t = 3.44 0.07 1.00 max HC600 KG680 V t = 2.99 0.20 1.00 max HC600 MI40 t = 8.70 ,0.01* 0.00* max HC600 MI65 t = 3.60 0.17 1.00 max HC600 Pixcontroller t = 5.89 0.03* 0.76 max HC600 Cuddeback t = 18.03 ,0.01* 0.00* max SG550 KG680 V t = 3.10 0.17 1.00 max SG550 MI40 t = 6.74 0.01* 0.17 max SG550 MI65 t = 3.561835 0.16 1.00 max SG550 Pixcontroller t = 5.09 0.11 1.00 max SG550 Cuddeback t = 15.10 ,0.01* 0.00* max KG680 V MI40 t = 2.40 0.56 1.00 max KG680 V MI65 t = 3.53 0.17 1.00 max KG680 V Pixcontroller t = 5.01 0.04* 1.00 max KG680 V Cuddeback t = 15.10 ,0.01* 0.00* max MI40 MI65 t = 3.81 0.12 1.00 max MI40 Pixcontroller t = 4.16 0.21 1.00 max MI40 Cuddeback t = 11.00 0.03* 0.84 max MI65 Pixcontroller t = 4.38 0.08 1.00 max MI65 Cuddeback t = 12.99 ,0.01* 0.00* max Pixcontroller Cuddeback t = 21.97 ,0.01* 0.00* max Test statistics (t ) falling below the critical value are not significant at the particular frequency whilst those at or above were considered significant. (*denotes max significance at p,0.05). doi:10.1371/journal.pone.0110832.t003 PLOS ONE | www.plosone.org 6 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Figure 4. Bootstrap estimates of the functional mean and 95% Figure 5. Bootstrap estimates of the functional mean and 95% confidence envelopes for the Scoutguard SG550. confidence envelopes for the Scoutguard KG680. doi:10.1371/journal.pone.0110832.g004 doi:10.1371/journal.pone.0110832.g005 Ultrasonic outputs (4–200 kHz) To determine if ultrasonic frequencies were emitted by camera traps we used 10 Reconyx Hyperfire HC600, 3 Cuddeback Captures, 3 Pixcontroller DigitalEye, 1 Scoutguard 560D and 1 Uway NT50 camera traps. Control detections were also collected without a camera trap to measure any possible background sound outputs within the laboratory. As before, the camera traps were placed individually on a tripod 50 cm in front of two ANABAT Detectors connected to a ZCAIM unit. One detector was directly in front of the camera and the second at a 45 degree angle from the central axis of the camera. We tested both angles to assess whether signals were different when the devices were directly in front compared to off centre. Cameras were triggered by hand movements across the front of the camera and recordings were for 15 seconds each. Ultrasonic outputs were analysed using the acoustic analyser software, AnalookW. Light measurements Tests were conducted on 32 cameras comprising 7 models (Table 1) in a laboratory at the University of New England on th April 20 2011. Each camera was placed 80 cm from a hand-held Figure 6. Bootstrap estimates of the functional mean and 95% ASD Field Spectrometer (FS HH 325-1075) connected to a laptop confidence envelopes for the Moultrie MI40 camera. doi:10.1371/journal.pone.0110832.g006 computer to enable automated data storage. Flash outputs were recorded over a 17 millisecond per acquisition period using a 10 degree field of view lens. Ten measurements per camera motion frequencies (12.5 Hz–20 kHz) was established for a set of 10 (see above) were recorded. independent observations. Functional bootstrapping was applied to get the estimate of the mean curve and the associated 95% confidence curves [42]. Analysis boot Audio Outputs. Functional bootstrapping (n = 9999) [42] Due to the data collected by the sound analyser at 33 was used to estimate the mean curve and confidence curves (95% frequencies, we treated the audio spectrums as ‘‘functional’’, thus CI) using the L outputs for each camera trap model (stills and L was a function of frequency. Analysis of the infrared ZFmax ZFmax videos or both) where these features were available. Comparisons illumination and ultrasonic outputs were constrained to presenta- of still images within camera trap models were undertaken to tion of summary statistics and raw data because the data was evaluate variability using the functional mean to estimate average constrained by the unequal sample sizes of the camera trap models response for each camera trap model, and functional standard we had available. Furthermore, the ultrasonic data can only be deviation to assess variability within the same models. reported in ANALOOK format as ranges and not as raw data. Intra-and Inter Model Comparisons. Functional t-tests Background sound. The L variable was used for ZFmax [43] were used to compare outputs between camera traps, and analysing the audio outputs in our analysis. A background sound between camera trap models and to the background sound ‘envelope’ and the 95% confidence envelope across a range of PLOS ONE | www.plosone.org 7 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Table 4. Comparisons between different video camera outputs as well as the background (*: denotes statistical significance below the p = 0.05 level). Model 1 Model 2 Statistic p-value Adjusted p-value Background MI40 t = 4.15 0.08 0.75 max Background MI65 t = 4.89 0.03* 0.28 max Background SG550 t = 3.02 0.17 1.00 max Background KG680 V t = 2.88 0.41 1.00 max MI40 MI65 t = 4.33 0.13 1.00 max MI40 SG550 t = 10.24 ,0.01* 0.02* max MI40 KG680 V t = 3.71 0.21 1.00 max MI65 SG550 t = 4.32 0.05 0.52 max MI65 KG680 V t = 3.71 0.12 1.00 max SG550 KG680 V t = 3.50 0.21 1.00 max doi:10.1371/journal.pone.0110832.t004 envelope. Given there were 28 comparisons we predicted an compared to the published frequency hearing range of animals increased chance of ‘false positives’, as such we adjusted the p- using a Wilcoxon test (non-parametric). We plotted mean values using the ‘false discovery rate’ method [44] to account for frequency and 95% confidence intervals and used the reported this situation. hearing frequencies of 24 animals (Table 2) to determine likely Ultrasonic Outputs. Ultrasonic camera trap outputs were relationships between hearing and sound outputs. Data available recorded using an ANABAT Detector but this device does not on the University of Toledo ‘Behavioural Audiograms of provide raw data points and merely plots the data as a graph Mammals website (http://psychology.utoledo.edu/showpage. displaying the range of signals detected and the patterns. As such asp?name=mammal_hearing, accessed 6 June 2014) of known we were unable to accurately analyse variability within and hearing ranges of animals was compared to the audio output of the between models so the data has been collated to report on the camera traps. The hearing of one key species, the European Red ranges detected. Fox (Vulpes vulpes) has not been recorded in any investigations, so Infrared Outputs. Summary statistics were generated for the the known hearing range was unavailable. To overcome this light outputs across the range of infrared camera trap models, constraint we extracted the calling frequencies of red foxes from these are presented graphically; comparisons between infrared published research [28,45] using data extraction software ranges and animal range was not undertaken in detail due to a lack (PlotDigitizer http://plotdigitizer.sourceforge.net, accessed 6 June of data on animal infrared vision. 2014). We then used these data as a baseline hearing range for the Comparison with known animal hearing range. A mean red fox based on the assumption that foxes are calling to each audio output using ten HC600 Reconyx camera traps (chosen to other on this frequency and as such should hear these ranges. be representative of the quietest models) was produced and Figure 8. Functional t-statistics as a function of frequency for the MI40-SG550 V contrast in video mode. The test statistic (t ) max is displayed as a solid line and the a = 0.05 critical value as a function of Figure 7. Bootstrap estimates of the functional mean and 95% frequency is displayed as a dashed line. confidence envelopes for the Moultrie MI65 camera. doi:10.1371/journal.pone.0110832.g008 doi:10.1371/journal.pone.0110832.g007 PLOS ONE | www.plosone.org 8 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Table 5. Still vs Video comparisons using functional t-tests (*: denotes statistical significance below the p = 0.05 level). Model Statistic p-value Adjusted p-value MI40 t = 2.17 0.74 1.0 max MI65 t = 2.99 0.41 1.0 max SG550 t = 1.95 0.73 1.0 max KG680 V t = 2.98 0.35 1.0 max doi:10.1371/journal.pone.0110832.t005 suggesting that the values measured might be related to the Results frequency dependent accuracy of the measuring equipment. We found strong evidence that animals can hear the sound of, Intra-camera trap comparisons - Still Images. Both the and see the infra-red illumination of camera traps. background sound and the camera models displayed means and standard deviations that were frequency dependent. Each model Audio Outputs of Camera Traps of camera seemed to have their own unique signature (see Table Background sounds. Our data show that the functional S1 and Figure S1) with characteristic peaks and oscillations. There mean and standard deviation magnitudes of the background was a semi-regular pattern to the uncertainty within a camera sounds were highly frequency dependent (Fig. 1). Particular model, with particular sets of frequencies specific to camera model frequencies tended to be associated with a higher level of average although displaying the greatest variation within camera trap background sound (e.g. 12.5 Hz, 160 Hz, 250 Hz) with sound models. ranging from 8.8 dB to 28.4 dB. The variation in the sound In analysing 10 Reconyx HC600 we established that the mean measurements changed considerably as a function of frequency. values range from 7.6 dB to 27.1 dB across the frequency range The three largest standard deviations in sound outputs of camera (12.5 to 20,000 Hz) with a standard deviation ranging from 0.8 dB traps occur at 50 Hz, 12.5 Hz, and 500 Hz, with the total range of to 17.2 dB (Fig. 2). There was a substantial difference in the the standard deviation estimates across frequency being 0.9– magnitude of the camera output with the top three ‘loudest’ 14.3 Hz. The largest mean values and the greatest standard frequencies (12,500 Hz, 12.5 Hz, and 25 Hz) and the three deviation of sound components occurred at the lower frequencies Table 6. Ultrasonic outputs from five camera trap models including two control recordings, two ANABAT directions were utilised (directly in front and offset 45 degrees to the central axis of the camera). directly in front off-set 45 degrees Model and Code Lower (kHz) Upper (kHz) Lower (kHz) Upper (kHz) HC600–1 3 35 3 40 HC600–2 3 20 3 35 HC600–3 3 50 3 45 HC600–4 3 55 3 50 HC600–5 3 60 3 55 HC600–6 3 55 3 0 HC600–7 0000 HC600–8 3 55 3 50 HC600–9 0000 HC600–10 3 50 3 45 Cuddeback-1 3 40 3 55 Cuddeback-2 3 40 3 60 Cuddeback-3 3 60 3 40 Pixcontroller-1 0000 Pixcontroller-2 00345 Pixcontroller-3 3 35 0 0 Scoutguard560D-1 3000 Uway NT50–1 3 35 3 0 Control1 0000 Control2 0000 doi:10.1371/journal.pone.0110832.t006 PLOS ONE | www.plosone.org 9 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Figure 9. Dog (1), cat (2) and rat (3) hearing ranges in relation to the outputs of HC600 camera traps (1a, 2a, 3a) and as a function of frequency (1b, 2b, 2c). The black line is the mean audio output of the camera trap; the grey dotted lines are the 95% confidence limits. The red dotted lines represent the standard error around the known hearing range of the dog, cat and rat. Where the grey points and red dotted lines (SE) are below and closest to the mean audio output of the camera, the sound can be detected by the animal. doi:10.1371/journal.pone.0110832.g009 highest standard deviation values 10,000 Hz, 5,000 Hz, and the functional mean was from 11.0 dB to 34.3 dB, with the top 25 Hz. three highest values occurring at 2,500 Hz, 31.5 Hz, and 125 Hz. The Scoutguard SG 550 (still) functional mean was frequency The Scoutguard KG680 V had a unique ‘signature’ as well as dependent with spikes at 2500 Hz, 5000 Hz, and 10,000 Hz, frequency dependent characteristics in the functional mean. The although different to the HC600 (stills) and the background sound range of the functional mean was 8.1 dB to 30.2 dB with the three (Fig. 2). The functional standard deviation was also frequency highest values occurring at 8,000 Hz, 160 Hz, and 12.5 Hz. dependent and similar to the HC600. At 250, 5000 and 10000 Hz These frequencies show the greatest variability within a model and the variability in the output (L ) between cameras was greatest are quite different to the HC600 and SG 550. The functional ZFmax within a model (i.e., Reconyx still, Scoutguard still). The range of means of the Moultrie I40 display frequency dependency. The PLOS ONE | www.plosone.org 10 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Figure 10. The auditory threshold of 6 mammals represented as a function of frequency. doi:10.1371/journal.pone.0110832.g010 signature was also unique but due to the very small sample size 35.0 dB with the top three values occurring at 12.5 Hz, 4000 Hz, (n = 4) there is some uncertainty in the estimates. and 80 Hz. We found that there were sharp and sudden shifts in the The Pixcontroller DigitalEye also had a unique sound signature L statistic for different frequencies in this model. The range of and shared some similarities with the background sound profile. It ZFmax the functional mean was 10.3 dB to 37.8 dB whilst the functional also exhibited frequency dependent structure in both the standard deviation ranged from 0.4 dB to 16.3 dB. The three functional mean (10.7 dB–33.7 dB, maximal values at 160 Hz, greatest values of the functional mean occurred at 50 Hz, 40 Hz, 12.5 Hz, and 2000 Hz.) and standard deviation (0.5 dB–10.3 dB) and 12.5 Hz. The greatest variability occurred at 3150 Hz, with the top three values occurring at 800 Hz, 63 Hz, and 500 Hz, and 80 Hz in this order. Similarly, there was a frequency 12.5 Hz. dependence and unique sound signature in the Moultrie I65 Three Cuddeback cameras produced functional mean ranges camera trap The range of the functional mean was from 12.3 dB– from 14.3 dB to 41 dB with the top three values occurring at PLOS ONE | www.plosone.org 11 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps and Pixcontroller-Cuddeback were statistically significantly differ- ent. There were a further seven contrasts that seem to be statistically significant different but they did not pass the multiple comparisons adjustment. There was a significant difference in the background sound and the Cuddeback, which consistently produced louder sound outputs (16 Hz: Background – 15.9 dB Cuddeback- 23.7 dB, 80 Hz: Background- 14.9 dB Cuddeback- 29.0 dB, 400 Hz: Background – 8.8 dB, Cuddeback- 28.0 dB) (Fig. 3). The contrast between Reconyx HC600- Moultrie MI40 could either be a statistical anomaly or could indicate a difference in the operational frequency response for these two cameras, which is so minute that it is within the variation of the background sound envelope. These analyses confirm that different camera models exhibit unique sound profiles but not discernibly different to the variability within models. We found that for most frequencies, particularly the low to medium frequencies, significant differences exist. Intra camera trap comparisons - Video Of the four camera trap models tested, the Scoutguard SG550 Figure 11. Comparison of the predicted hearing range of the (Fig. 4) showed an overall decreasing trend with an occasional red fox in relation to the outputs of HC600 camera traps and as a function of frequency. minor peak where the operational sound or the uncertainty in the doi:10.1371/journal.pone.0110832.g011 estimate or uncertainty between models was higher. The operational sound characteristics appeared similar to that of the 400 Hz, 500 Hz (equal highest), and 2000 Hz (functional standard Moultrie MI40 but the functional standard deviation was higher at lower frequencies. deviation 0.5 dB–7.9 dB with the three largest values occurring at 12.5 Hz, 2000 Hz, and 8000 Hz. In the Scoutguard KG680, the functional mean exhibited a slow decrease in operational sound level with frequency (Fig. 5). Of note was the relative tight envelope around the estimate of the Comparisons between camera traps in still modes and mean indicating that this curve was estimated with far less background sounds uncertainty than the other models. There were several contrasts displaying significant differences In the Moultrie MI40 the functional mean of the sound is highly between models (Table 3). Specifically, comparisons between the frequency dependent (Figures 6 and Table 4). The operational Background-Cuddeback, HC600-MI40, HC600-Cuddeback, sound of the camera and the variation between models vary with SG550-Cuddeback, KG680 V-Cuddeback, MI65-Cuddeback, Figure 12. Mean infra-red wavelength illumination (nm) outputs for seven camera trap models showing the highest and lowest values. doi:10.1371/journal.pone.0110832.g012 PLOS ONE | www.plosone.org 12 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps Figure 13. Infra red illumination of two opposing Reconyx HC600 camera traps simultaneously triggering. doi:10.1371/journal.pone.0110832.g013 frequency. The highest operational sound occurred at the lowest around 1000 Hz but it was still within the range of the background frequencies as well as the greatest variation and uncertainty sound (Fig. 8). between models. Except at very low frequencies and a slight (t <1–1.5) max A slight frequency dependent response was observed in the variation around 1000 Hz, there were no significant differences in response across frequencies. The secondary peak at 1000 Hz is Moultrie MI65 (Fig. 7) around the mean, but the standard deviation estimate was highly frequency dependent with a indicative of a difference in the functional mean estimates for these pronounced peak occurring in the 0–3 kHz band and a general two cameras in video mode. linear increase occurring from 4–20 kHz. The increasing width of the 95% confidence envelope as frequency increases reflects Comparisons between Still and Video Modes uncertainty with increasing frequency. This might be due to low There was no difference in still and video frequency response or sample sizes and our inability to establish whether or not the mean between the four camera models (Scoutguard and Moultrie) curve increases, remains stationary, or decreases at these (Table 5). frequencies. These data show that the sound level for the MI65 is higher than the MI40. Ultrasonic recordings Estimates of the mean audio output and standard deviation Ultrasound frequencies tests on the five camera trap models were estimated as a function of frequency for four different camera confirm that camera traps do produce ultrasonic outputs each time models operating in video mode. All cameras appear to have a photo is taken (Table 6). Frequency ranges for Reconyx HC600 frequency dependent operational characteristics and furthermore was 3–60 kHz with a median output of 52.5 kHz (SD = 13.4) there appears to be differences in the mean sound levels between directly in front of the device and 47.5 kHz (SD = 7.3) models. Importantly, the standard deviation curve estimates within perpendicular to the device. Other models emitted outputs within a model appear greater or on similar magnitude to the mean a similar range. There was some variability within models due to differences between cameras. This could be due to the limited the method of measuring the outputs; ANABAT detectors are number of camera traps models, although this is unlikely because designed to measure bat echolocation not low level ultrasonic the analysis suggested wide variation in magnitude and form. sound. Comparisons between Video Modes and Background Audio Outputs and Known Hearing Ranges of Animals Sound Our tests comparing Reconyx (HC600) camera trap outputs to Our functional tests with multiple comparison corrections for the existing hearing ranges of 21 species (see http://psychology. background sound in video mode showed no significant difference utoledo.edu/showpage.asp?name=mammal_hearing, accessed 6 (Table 4). There was however a difference in audio outputs June 2014) found compelling evidence that camera trap sound between the MI40 and SG550 with a difference in the response outputs fall within the hearing range of most of the species (Fig. 9– 11). In 9b, 9b and 9c we have presented data to show the PLOS ONE | www.plosone.org 13 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps relationship between the camera sound and the auditory threshold reported the frequency of a range of calls made by foxes to be less of the animal as a function of frequency. These data strongly than 2 kHz, which is consistent with one other study [45] that suggest that dogs, cats and rats have the capacity to detect low reported calls all under 2.5 kHz. The foxes hearing capacity has frequency outputs (,20 kHz) from camera traps. Data presented been reported to have a reduced capacity between 5–11 kHz with in Figure 10 provide evidence that a further six mammals, a discernible reduction around 8.5 kHz, but reported that they including humans, have the capacity to detect camera traps in hear sounds well at 10–14 kHz [25]. Given red fox calling the lower frequency bandwidths. The hearing ranges in compar- frequencies, they would certainly hear some of the infra and ultra ison to camera trap outputs for a further 12 mammals are sounds emitted by camera traps. We report the first evidence that provided in Figure S2. animals can detect the presence of camera traps due to the audio Given the paucity of data on the known hearing range of red and optical outputs from these devices. This study determined that foxes we carried out a comparison on the minimal hearing range at certain frequencies, animal hearing (Table 2 and see http:// for this species based on their calling frequencies [25,45] (Fig. 11). www.lsu.edu/deafness/HearingRange.html, accessed 6 June This was based on the assumption that foxes must be able to hear 2014) can easily detect these sounds. the frequency of fox calls recorded at a minimum. From this The results of our testing also provide conclusive evidence that analysis we derived an optimum hearing range for the red fox of camera traps do emit ultrasonic outputs, especially when battery around 8–12 kHz although this would be an under-estimation of levels are low. In a pilot trial we found that low powered batteries their true range. Despite having to use call frequencies to model resulted in the ANABAT detecting an output but in subsequent hearing range, the results show that red foxes can easily hear tests with fully charged batteries, there was no audible signal camera trap outputs. suggesting that camera trap outputs vary with battery life. The use The data presented provide robust evidence that mammals can of a bat call monitoring device has been used previously to test detect the sound outputs of camera traps. LED lights being used in research on Mustella vision [17]. The authors were unable to detect any outputs by the lights, however in Infra-red Wavelength Outputs the case of camera traps there are a range of electrical and The infra-red illumination ranges varied between models mechanical components apart from the LED circuitry that may be (Fig. 12) but there was no difference in wavelength outputs within emitting sound. models for the Reconyx HC600 (Mean = 940.5, SD = 1.8, 95% CI = 1.3), Scoutguard 550 (Mean = 828.3, SD = 4.7, 95% Animal Vision CI = 3.4) and Scoutguard 680 V (mean = 844.1, SD = 0.6, 95% Information on the extent of infrared detection by other CI = 0.5) camera traps. mammals is scant in the literature. There have been some Based on the data in Figure 12, camera traps that are advertised investigations using behavioural methods that report some animals as ‘‘no glow’’ (HC600) or ‘‘black ops’’ (NT50) are clearly using can see infrared light in the range 539–870 nm although the infrared technology with wavelengths operating above 850 nm. evidence is limited across the taxa. As such we were unable to These infrared LED’s are emitting light that is nearly invisible to conduct any comparative analysis of infrared flash light outputs the human eye, but not some animals. with animal vision to test our hypotheses. Research has established that Honey Possums (Tarsipes rostrata) Discussion are able to see light in the 557 nm range [18] while ferrets (Mustela furo) can see around 870 nm [17] and Tamar Wallaby In this study we tackled the first part of a two staged question; (Macropus eugenii) peaked at 539 nm [20]. do camera traps have the capacity to project audio and optical These data probably underestimate the extent of an animal’s stimuli to wildlife? Moreover, are these outputs different between ability to detect infrared light since they are based on behavioural and within models and recording modes (still or video)? We studies [38], not physiological analysis, because such technology is present these data on the audio and visual outputs of camera traps unavailable. As such, we are unable to state exactly what the limits to highlight the importance of identifying the effects camera of animal vision might be, and we believe that the range of trapping may have on animal behaviour. infrared light presented in Figure 12 are likely seen by many species of animal. In support of this claim, one of the authors (PM) Animal Hearing was able to see a faint red glow of a Reconyx HC600 in absolute A wide range of comparisons were conducted to investigate the darkness. Reports of humans detecting infrared (1064 nm) well possibility of differences in operating audio outputs of different above the illumination currently used in camera traps have been camera models in both still and video mode. In the vast majority of recorded [47,48]. This being the case, there is no doubt that cases (except the Cuddeback) the operational sound was little nocturnal animals with vision sensitive to night light can see different from the background sound in the sound laboratory. In infrared illumination. The responses of animals to infrared flash some cases slight differences were found between models (e.g. are highly variable between species and individuals (Meek Unpub MI40 and SG550 video) but were of such a low level that they data; Ballard Unpub data). While we cannot measure exactly what were within the magnitude of the background sound. The noise animals see, they most likely see a similar image to the flash created by two people being present in the anechoic chamber recorded by two camera traps triggered simultaneously, as shown conducting the experiments probably produced sounds and in Figure 13. affected the background sound envelope. If we were able to Cats appear to detect the presence of camera traps more than conduct the tests remotely there may have been a more significant other animals (Meek Unpub data; Ballard Unpub data), which is difference between camera trap noise and background noise. probably due to their retina sensitivity at 826 nm [49] and total In comparing the auditory range of animals in contrast to our vision field of view being 287u with binocular over lap of 130u recorded outputs, we sourced sonagraph data for a range of [37]. This peripheral view combined with the very high sensitivity species. There have not been any sonagraphs to determine the hearing ranges of foxes although it has been reported that red fox to infrared light at the higher end of the near infrared spectrum would make cats more than capable of easily detecting camera have an upper limit of 65 kHz [37]. While studies of 75 foxes [46] PLOS ONE | www.plosone.org 14 October 2014 | Volume 9 | Issue 10 | e110832 Audio and Optical Emissions from Camera Traps trap flashes; especially in models with light emissions below multiple frequencies and background scatter exist are less likely to 800 nm (see Fig. 12). be detected by animals [55]. The effects of white flash camera traps on animal behaviour In some studies the target species’ ability to detect a camera trap have been recognised as an intrusive survey method because it has may not be important because the requirement is to detect been shown to startle and cause animals to flee (7). Some authors presence only, so irrespective of whether the animal baulks and have suggested that using infrared illumination may reduce this runs from a camera trap is of no importance. Where repeat visits flight response [7,8,14], especially where infrared wavelengths to a site are imperative for analysis, i.e., mark recapture, exceed ,870 nm [17]. While there is little information on the photographic indexes, CPUE and activity indexes, the interference detectable range of infrared wavelengths by most animals, one to behaviour and potential avoidance of the camera trap may study did find that ferrets’ (Mustelo furo) maximum observable introduce a bias on the probability of detection. An issue also range was about 870 nm [17]. Multiple images and corresponding raised by in one study [17] in regard to the potential for infrared footprint detecting plots from our research on feral cats, wild dogs light emitting surveillance devices or traps to cause avoidance by and foxes in Australia over several years indicates that all three animals. species can detect flash illumination from Reconyx HC600 camera There is a convincing argument presented in this study to traps (Meek Unpub data; Ballard Unpub data). In field trials confirm that most mammals can hear the operational sounds where two HC600 were facing each other, we were able to generated by camera traps in both the infrasound and ultrasound accidentally trigger the cameras to simultaneously trigger showing ranges. Moreover, given the strong relationship between vision visually what nocturnal animals may see when infra red and hearing acuity [22], this study concludes that most mammals illumination occurs (Fig. 13) [50]. can see the infra-red illumination used in camera traps. Anecdotal reports of ship rats (Rattus rattus) and brush-tailed possums (Trichosurus vulpecula) from three unpublished studies Supporting Information describe avoidance of infrared illumination in these species (see [17]). Although there has not been any effect found on predator Figure S1 The noise frequency outputs of twelve camera behaviour around ground-nesting bird nests from infrared camera trap models and the background control. traps used to detect visitation [51]. (TIF) Despite wide spread belief that humans cannot see near infrared Figure S2 The hearing range of an additional twelve light, many authors have reported being able to detect infrared animals in comparison to the noise outputs of a camera light during experiments and these descriptions have been trap. described [17]. On the evidence presented in the literature and (TIF) summarised here, we conclude that most nocturnal or arrhythmic (nocturnal with some diurnal activity) mammals can see the Table S1 The mean audio outputs of 12 camera trap infrared illumination (flash) emitted by camera traps. models at different frequencies. (DOCX) Conclusions Hearing and vision work together to form what is referred to as Acknowledgments auditory localisation acuity [22]; where an animal hears a sound Thanks to the Schultz Foundation for their support and provision of some and turns towards the sound using eye sight to focus in on the camera traps to use in our experiments. We greatly appreciate the technical stimuli. This is probably the case in camera trapping, where a assistance of Greg Stewart of the National Acoustic Laboratory and Keryn sound is heard by a passing animal and the device is further Lapidge of the Invasive Animals CRC. Thank you to Damien Byrne from recognised by vision, thus enabling animals to detect the device. Outdoor Cameras Australia and Nick Dexter of Jervis Bay National Park With the constant sounds of the forest animals are unlikely to be for lending us some camera traps. We appreciate the technical support and hearing the camera traps constantly as the frequency and advice provided by Matt Dobson in recording the ultrasonic outputs. amplitude values are very similar. Furthermore, the audio outputs Thank you to Julian Partridge, Christa Neumeyer, Nathan Hart, Lyn collected in the anechoic chamber were recorded at 50 cm, and it Beazley, Catherine Arresse and Henry Heffner for their invaluable advice and opinions on animal hearing and vision. is reported that with every metre away from the camera a loss of 6 dB is expected [52]. Sound levels are affected by distance from the source, atmospheric attenuation, terrain, ground cover, wind Author Contributions and weather [53], forest density (a function of limb and trunk Conceived and designed the experiments: PM GB PF WW MS. Performed density) and foliage [54] and as such we acknowledge that this the experiments: PM GB PF WW MS. 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