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The Accuracy of Behavioural Data Collected by Visitors in a Zoo Environment: Can Visitors Collect Meaningful Data?

The Accuracy of Behavioural Data Collected by Visitors in a Zoo Environment: Can Visitors Collect... Hindawi Publishing Corporation International Journal of Zoology Volume 2012, Article ID 724835, 13 pages doi:10.1155/2012/724835 Research Article The Accuracy of Behavioural Data Collected by Visitors in a Zoo Environment: Can Visitors Collect Meaningful Data? 1 2 1 1 Rachel L. Williams, Sue K. Porter, Adam G. Hart, and Anne E. Goodenough Department of Natural and Social Sciences, University of Gloucestershire, Cheltenham GL50 4AZ, UK Wildfowl and Wetlands Trust, Slimbridge, Gloucestershire GL2 7BT, UK Correspondence should be addressed to Rachel L. Williams, rachel.williams 31@hotmail.com Received 24 February 2012; Accepted 22 June 2012 Academic Editor: Simon Morgan Copyright © 2012 Rachel L. Williams et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Volunteer data collection can be valuable for research. However, accuracy of such data is often a cause for concern. If clear, simple methods are used, volunteers can monitor species presence and abundance in a similar manner to professionals, but it is unknown whether volunteers could collect accurate data on animal behaviour. In this study, visitors at a Wetlands Centre were asked to record behavioural data for a group of captive otters by means of a short questionnaire. They were also asked to provide information about themselves to determine whether various factors would influence their ability to collect data. Using a novel analysis technique based on PCA, visitor data were compared to baseline activity budget data collected by a trained biologist to determine whether visitor data were accurate. Although the response rate was high, visitors were unable to collect accurate data. The principal reason was that visitors exceeded the observation time stated in the instructions, rather than being unable to record behaviours accurately. We propose that automated recording stations, such as touchscreen displays, might prevent this as well as other potential problems such as temporal autocorrelation of data and may result in accurate data collection by visiting members of the public. 1. Introduction been collecting biodiversity data for wildlife organisations for several decades. For example, in 2011, over 600,000 members Animal behaviour data are important across the field of of the public took part in the Royal Society for the Protection biological sciences, from evolution and population biology of Birds’ “Big Garden Birdwatch” [7]. Several studies have to ethology in captive or domesticated animals. However, shown that volunteer-collected data on, for example, species collecting these data is time consuming. Given that the identification and quantifying abundance, can be as accurate duration of data collection for behavioural studies can range as basic biodiversity data recorded by scientists [4, 6, 8, 9], from several weeks [1, 2] to several years [3], funding especially when projects offer basic training and are closely professional researchers can be prohibitively expensive for supervised by scientists. Moreover, several methods have many studies, especially those conducted by zoological been developed to enhance the accuracy of volunteer-run parks and wildlife organisations [4, 5]. However, animal surveys, either in terms of the methods used to collect the behaviour is of considerable interest to the general public data or in subsequent analysis [4, 10–14]. Collection of (or at least a subset of the public with environmental and behavioural data, however, is subject to a certain degree of zoological interests), and many people spend considerable interpretation and may be more complex to record than time observing animals as a hobby (e.g., watching pets, counting or identifying species. It is not known whether wild birds, or animals in zoos). Professionals could use this the quality of volunteer-collected behavioural data would interest to recruit volunteers to record animal behaviour. be sufficient to calculate accurate activity budgets or to test There are many advantages of using volunteers to collect behavioural ecology hypotheses. data. Volunteers can collect data at little or no financial Monitoring animal behaviour is particularly important cost to the organisation running the project [4–6]; indeed in zoos because of the importance of animal welfare [15, large numbers of untrained members of the public have 16]. Zoos may encourage their zookeepers to participate in 2 International Journal of Zoology research [17] but data collection often cannot be a priority the enclosure allowed visitors to view the otters easily amongst the zookeepers’ daily husbandry activities [18]. from the walkway that spanned the front of the enclosure Research activities can be supplemented with undergraduate (Figure 1). There was also a small indoor sleeping chamber and postgraduate students under the supervision of lecturers in which visitors could see the otters through small glass and scientists, with no financial cost for the zoos involved windows in a walkthrough tunnel. Otters could access all [19, 20], but while this provides useful and reliable data, it parts of the enclosure at any time of the day, and no parts relies on the availability of students and on University course of the enclosure were closed during routine cleaning of the content. exhibit. An alternativeapproach couldbetouse zoovisitorsto collect data on a voluntary basis. The benefits of asking zoo visitors to collect data while they visit could be numerous. 2.2. Ethogram Data Zoos are popular attractions worldwide, attracting more than 700 million people each year [21], so there is no 2.2.1. Ethogram Construction and Scientific Data Collection. shortage of potential volunteers. Many visitors have a keen To determine whether visitors could record data that would interest in animals and wildlife conservation [22, 23], and accurately represent the otters’ behaviour, reliable baseline this could be a strong incentive to participate in research that data were required for comparison. A biologist with expe- may benefit the animals they are observing. Furthermore, rience in collecting behavioural data (RLW) created an behavioural data could be collected almost continuously ethogram as per Martin and Bateson [27] to record the throughout the day as and when visitors pass the animal otters’ behaviour based on prior observations in a pilot enclosures. This should create a database from which study. Behaviour categories were adapted from a behavioural daily activity budgets can be calculated. Finally, interactive study done by Anderson et al. [24] on a similar species activities create more positive experiences for visitors when (Asian small-clawed otters—Aonyx cinerea). Behaviours were compared to passive exhibit viewing [24], so an activity grouped into simple, easily definable, categories to ensure such as this could make the zoo more attractive to its that members of the public should be able to recognise visitors. them in the latter part of the study (Table 1). The study took place over 7 days during the opening hours of the While some research suggests that zookeepers’ casual park (10 am until 5 pm). Each hour was divided into six observations throughout the day provide a good indication of the overall activity budgets of the animals [18, 25, 26], 10 minute periods and the otters’ behaviour was recorded during two randomly selected 10-minute periods each hour and keepers are generally well acquainted with individual animals and their behaviours, they may not be acquainted [28]. An instantaneous scan sampling method [27–29]was with recording behaviour in a scientific and rigorous manner. used to record the behaviour of each of the 3 otters systematically every 10 s during the recording periods. This It also seems reasonable to assume that the vast majority of visitor-based “volunteers” would have no prior experience was the shortest interval in which data could be recorded by watching each otter consecutively. By using this sampling of collecting behavioural data and it would be logistically difficult, or impossible, to train and/or supervise them technique for each of the otters, the problem of missing while they collect data. However, if visitors are able to out individual behaviours was minimised and an overall collect accurate data on captive animals, there is a potential activity budget for all three otters could also be calculated. for volunteer projects to collect behavioural data on wild Subtle differences in size and coat colouration were used animals, especially where there are large concentrations of to distinguish each otter to calculate individual activity people and animals, such as in nature reserves or game parks. budgets. If an individual otter was out of view at any time The aim of this study is to determine whether visitors can during the recording period, it was noted as such. In total, collect accurate data on the behaviour of a small group 16.5 h of data were collected for each otter, with a data of animals in a captive environment. Visitor data were point collected from each otter simultaneously, giving 1,980 compared to data collected by a trained biologist. ethogram observations per otter (6 recordings per minute, that is, one every 10 seconds, ×20 minutes of observation per hour ×16.5 hours in total = 1, 980). This sample size 2. Methods is comparable to those used in studies of a similar nature [18, 30]. 2.1. Study Site. The study was conducted at the Wildfowl and Wetlands Trust (WWT) centre at Slimbridge, Glouces- tershire, UK (OS grid reference SO722047). A group of three female captive North American river otters (Lontra 2.2.2. Interobserver Variability. To examine the potential for canadensis) were selected for the study because of their interobserver variability in the collection of behavioural data, popularity with visitors and the fact that this species a second biologist (herein referred to as CK; not an author demonstrated a rich suite of behaviours during the daily of this study and independent from its planning and prior opening hours of the centre (R. L. Williams pers. obs.). It implementation but with the same level of experience as was important that visitors could see the otters in order RLW) collected ethogram data over one day, during exactly to record their behaviour, and the layout of the otter the same recording periods (14 × 10 min). The paired data enclosure facilitated this. Large panels of clear glass around were then compared. International Journal of Zoology 3 view” category from the ethogram was not included in the questionnaire because visitors did not know how many otters were in the enclosure. If they could not see any of the otters, they should have answered “no” to the questions asking whether they could see any otters inside or outside. Visitors were asked how long they spent at the otter enclosure overall to determine whether this was related to the number of behaviours recorded, and because this could be a potential indication that visitors might be spending longer than the requested 30 s recording data. Visitors were asked some anonymous personal information questions (e.g., their age group, whether they had volunteered before, whether they were a member of a wildlife organisation) to determine whether any of these factors influenced their ability to record Figure 1: Otter enclosure at Slimbridge, a photograph taken from accurate data. Finally, visitors were required to indicate how the front of the enclosure and showing the visitors’ viewpoint. many people had helped them fill in the questionnaire. The study took place over 8 consecutive days, for 7 hours each day. Visitor data were collected for a day more than the ethogram data because of logistical issues 2.3. Questionnaires when undertaking both activities was not possible. However, analysis of daily otter activity budgets after the data were 2.3.1. Otter Behaviour Questionnaire. The ethogram was collected showed that this did not affect the results. The simplified to a multiple-choice questionnaire to deter- study was advertised using A3-sized posters at the entrance mine whether visitors could collect accurate data on otter of the centre and near the otter enclosure, and was pro- behaviour. The instructions on the questionnaire were as moted by the mammal keeper during the twice daily otter clear, concise, and self-explanatory as possible, as recom- feeding demonstrations (11.30 am and 3.30 pm). Visitors mended by previous studies [6, 8, 10, 12, 31]. Visitors approaching the otter enclosure were asked whether they had to fill in basic information (e.g., write the time down, would be willing to fill in a questionnaire as part of a answer “yes” or “no” if they could see otters inside and/or research project on otter behaviour. No other details were outside), and tick the behaviours they saw when the otters given unless visitors asked questions, as the aim of the were outside (i.e., not in the sleeping chamber) during a study was to determine whether visitors could collect data 30 s period. This method was adapted from the one-zero without supervision. In order to compare ethogram- and sampling method in that all behaviours which were observed questionnaire-derived data, both were collected on the same within the interval were ticked once (1) and those that were days (in order to ensure consistent activity levels of the not observed were not ticked (0). It is recognised that the otters—Anderson et al. [24]). The study was carried out on two datasets differed not only in who had collected the data four days before the school holidays and on four days during (biologist or visitors) but how the data had been collected the school holidays. This allowed a comparison between (ethogram instantaneous scan sampling or questionnaire uptake of the questionnaire during quiet and busy periods at extended one-zero sampling, resp.). The differences in data the centre, as well as increasing the range of different visitors collection methods were undertaken for good reason-one- filling in the questionnaire (e.g., more families during school zero sampling was the easiest type of sampling for visitors holidays). (and thus the most likely to be reliable) whereas instanta- neous scan sampling is a more robust method for generating data for activity budgets. Therefore, although it could be 2.3.2. Visitor Segmentation Questionnaire. The WWT devel- argued that different methods will give different results, the oped a questionnaire as part of a survey to learn more about study aimed to determine whether visitor-collected data (at their visitors, and this was used as a complementary tool its simplest) could be compared to maximally robust and in this study [33]. This questionnaire (named the visitor reliable data, validating the approach taken. segmentation questionnaire) was stapled behind the otter The layout of the questionnaire was an important con- behaviour questionnaire, but was optional so that length sideration [32]. Colour photographs were used to illustrate of the two combined questionnaires did not deter visitors each of the behaviours with the exception of “other”, which from participating. It consisted of a list of questions with the was represented by a question mark with space underneath instruction “tick the statement that best describes you”. The for visitors to write down what they had seen. Visitors were questions concerned topics such as motivations for visiting not asked to distinguish between individual otters, because the centre, personal interests and affinity for nature, and identifying them reliably would have been very difficult given preferences for various animals at the centre. Analysis of the short recording period and subtlety of the differences the results determined which “segment” a visitor belonged between otters. Consequently, they were requested to record to (Table 2) and, subsequently, allowed examination to test all of the behaviours they observed, regardless of which whether different segments of visitors could record otter individual was performing the behaviour. The “out of behaviour more effectively than others. 4 International Journal of Zoology Table 1: Ethogram used by a trained biologist to record simple otter behaviours. Behaviour Comments and additional information “Inside” is not a behaviour, but it was necessary to record this so that the period of time that the otters spent Inside inside was included in the activity budget (it was speculated that visitors may underrecord otters when they were inside—Section 4 ). Swimming In water, not interacting with other otters and/or showing signs of play. Eating This occurred mainly during twice-daily public demonstrations. Any playful interaction with another otter (such as chasing, play fighting) or playing alone (diving/rolling in the Playing water, playing with an object). Walking or running As stated. Self-grooming or mutual grooming (if mutual grooming occurred, all otters involved were recorded as Grooming grooming). Rolling Rolling on land. Sitting or lying Inactive animal (included pausing for a few seconds but also sleeping outside). down This was never recorded with the ethogram, though the otters did display aggressive behaviour over food on Fighting one occasion (outside a recording period), so it is possible that visitors could have recorded this. Other Any behaviour not mentioned above, for example, sprainting, climbing a tree, and drinking. If an otter was not observable at any point during a sampling interval such that its behaviour could not be Outofview recorded (i.e., under the pedestrian walkway or hidden in vegetation). See Section 4 for comments about the differentiation of swimming and playing. Table 2: Segmentation pen portraits—Modified and adapted from WWT visitor segmentation report [33]. Visitor segment Description and comments Learn together They believe in life-long learning for their family. Accessing the outside plays an important role in their leisure families time, and they are generally open to all forms of nature, rather than visiting specifically to see birds. Doing something that entertains and satisfies their children is the main priority in their day out. If their Fun time families children learn something along the way, then this is an added bonus. Their interest in nature is broad; it is not about acquiring detailed knowledge on specific species but more Social naturalists about simply enjoying any kind of wildlife. Interested naturalists are not active birdwatchers but visit to improve their knowledge and learn new things, Interested naturalists driven by a broad interest in the natural world. For interested birders, trips in the outside are a significant part of their life, and the majority are active Interested birders birdwatchers. Whilst they are mainly looking to develop their interests, their interest in birds is often tied into other hobbies such as walking, photography, and painting. Social birders are seeking to spend quality time with other people in natural surroundings where they are Social birders guaranteed to see interesting birds. Expert birders are applied birdwatchers who tend to take their hobby relatively seriously. This segment has the Expert birders most knowledge about the WWT’s wider conservation activities. Experiencing the outside is essential to sensualists’ lives; to them, it is food for the soul and is a space in which Sensualists they can relax and experience nature’s beauty. Wildlife and the outside are not of prime interest to them; their main focus is to spend quality time with others Social day-outers in a nice environment. 2.4. Data Processing and Analysis corrected dataset included writing the wrong time (pers. obs.), not answering all of the questions, and ticking all of the 2.4.1. Uncorrected and Corrected Data. When data were boxes haphazardly (such questionnaires were usually filled in entered into a spreadsheet, two copies were made: an by young children—pers. obs.). Questionnaires that could uncorrected version with data exactly as they were recorded be rectified were those in which visitors had interpreted a by visitors and a corrected version, whereby any mistakes behaviour as “other” when it could be reclassified as one of visitors had made that were noticed by RLW were rectified the categories listed, for example, “kissing” or “licking” = when possible or omitted from the dataset if the whole grooming; “going through tunnel” = playing, and so forth. questionnaire was unusable (c. 10% of the questionnaires These datasets are henceforth referred to as uncorrected were affected). Mistakes that resulted in exclusion from the visitor data and corrected visitor data. International Journal of Zoology 5 2.4.2. Calculating Activity Budgets. Ethogram data and ques- principal components in three dimensions with the radius of tionnaire data were converted into activity budgets to the resulting sphere, or “bubble”, indicating the confidence indicate the percentage occurrence of specific behaviours as radius. Plots were constructed using the RGL library and per Stafford et al. [30]. An activity budget was calculated rgl.sphere function for R [36]. Each bubble represented for each individual otter and for the whole group (using the overall activity budget, with the centre representing ethogram data), as well as for the group of otters using visitor the mean of the first three principal components and the data (using corrected and uncorrected data). In addition to radius representing the 95% confidence interval. Statistical the full questionnaire datasets, various subsets were extracted inferences were made on the basis that overlapping bubbles for separate analysis, for example, for each visitor segment signify no significant difference between the activity budgets and from adapted or standardised datasets (see below). represented by the bubbles while no overlap indicates signif- icant differences in the activity budgets (α = 0.05). In order for the plot to be reliable, the cumulative proportion of the 2.4.3. Adaptation of the Visitor Datasets and Extraction of variance explained by the first three principle components Subsets . In addition to the full activity budgets men- (i.e., those used to create the plots) needs to be greater than tioned above, activity budgets were also calculated with 0.95 [30]; in this study, all values exceeded 0.95. the behaviours playing and swimming combined into one A chi-square test for association was performed to category because these behaviours often overlapped. This test whether the number of behaviours recorded related was similar to the adaptations of Margulis and Westhus [18] to the length of time spent at the otter enclosure. The where “swim” and “stereotypic swim” were combined to corrected visitor data were used to calculate the number allow the comparison of keeper-collected data and scientist of behaviours recorded, and any questionnaires where the data on brown bear (Ursus arctos)behaviour. question regarding time spent at the enclosure was left There was a disparity in the number of visitors at blank were excluded. Number of behaviours recorded were different times of day, which could have led to an under- combined into 5 categories for the chi-square test (0, 1- representation of inside in the mornings when there were 2, 3-4, 5-6, and 7-8) and time periods were classed as less fewer questionnaires completed (because there were fewer than 2 mins, 2–5 mins, 6–10 mins, and over 10 mins. It is visitors in the centre) and an overrepresentation of eating worth noting that, although visitors could have recorded when many questionnaires were filled in during the otter up to 10 behaviours, this did not occur (one visitor did demonstrations. To reduce the effect of pseudoreplication record 9 behaviours, but this was excluded from the analysis and temporal autocorrelation (visitors recording the same because the visitor was a young child and data accuracy was behaviours at the same time) that may result from this, an questionable). average activity budget was calculated over each half hour period taking into account the number of questionnaires answered in each period. Given the varying length of time 2.5. Simulations to Test Accuracy of Visitor-Collected Data. that visitors had the questionnaire (including filling in the The selection of the time period in which the visitors were segmentation questionnaires) it was not logistically possible asked to collect data was based on the concept that a 30 s to calculate an average from the questionnaires over a shorter period would capture more data than a single instantaneous time interval than 30 min, and in some cases, autocorrelation scan, yet would not be likely to result in all behaviours between questionnaires was likely. The effects of this possible being observed; hence an estimate of frequency of behaviours autocorrelation are discussed below. could be obtained using this method. Given that preliminary Separate activity budgets were also calculated from sub- observations indicated that visitors vastly exceeded this time sets of questionnaires extracted from the complete dataset. period (see below), a computer simulation was developed These were based on the personal information questions at to determine if the 30 s sampling period would produce the end of the behaviour questionnaire. Activity budgets were comparable data to ethogram recordings given assumptions calculated based on the removal of all questionnaires that had that incorrect identification of behaviour and temporal been filled in by a child aged 10 or under from the initial autocorrelation of the data did not exist (i.e., data were dataset (because children may have difficulty giving accurate collected perfectly, except for the time of recording). The answers [34]), as well as separate subsets for the visitors simulation was constructed using R [35]. The simulation who had prior experience volunteering and for those who was parameterised according to the relative probability of the had none, and for visitors who were members of a wildlife behaviours, as collected from ethogram recordings, making organisation and for those who were not. the assumption that the ethogram data collected in this study were an accurate representation of the otters’ activity budget 2.4.4. PCA and Analytical Framework. To compare the (see results, Figure 2). ethogram activity budgets with the activity budgets cal- The simulation produced a random number (score) culated for the visitor datasets and subsets, bootstrapped between 1 and 100, which corresponded to a particular principal components analysis (PCA) was conducted in the behaviour based on the proportion of its occurrence (see R statistical package [35], following methods in Stafford results for details, but otters were seen swimming 11% of et al. [30]. Rather than plotting each activity budget on a the time, so a score between 1 and 11 would correspond two-dimensional scatterplot (as in conventional PCA), this to the behaviour “swimming”). After this initial score approach involved plotting the mean value of calculated had been set, the simulation ran with a timestep of the 6 International Journal of Zoology behaviours of 3.8, and when 5 (±2.5) produced an average of 3.2 behaviours). We next simulated data that represented 30 s of sampling by visitors. Although these simulated data were free from confounds such as temporal autocorrelation and misidentifi- cation of behaviours, they would give an accurate indication of whether the 30 s recording period would have allowed visitors to collect accurate data on the otters’ activity budget. As such, we simulated 574 visitor responses (the same number collected in the study). We compared simulated data and real visitor-collected data in terms of the number of behaviours recorded in a questionnaire to examine the (a) average length of time that visitors may have recorded data for. We also compared the 30 s simulated visitor data to ethogram data and real visitor data using modified PCA or “bubble” analysis, to determine whether recording behaviour for 30 s would result in significant differences to either of these recording methods. 3. Results 3.1. Interobserver Variability. The activity budgets collected by the two biologists were very similar except for the categories of playing (35% for RLW and 25% for CK) and swimming (14% for RLW and 22% for CK). Because playing and swimming were sometimes difficult to differentiate RLW (playing often occurred in water), the differences between the CK two activity budgets were less apparent when these categories (b) were combined as a single category (Figures 2(a) and 2(b)). There was no significant difference between activity budgets Figure 2: (a) Comparison of otters’ activity budgets calculated collected by the two biologists. However, when playing and from ethogram data collected by two biologists (RLW and CK) over swimming were combined, the bubbles overlapped more, one day. Note: categories “fighting” and “other” are not displayed indicating greater similarity (Figures 3(a) and 3(b)). on the graph because neither occurred on that day. (b) As above, swimming and are playing combined as one category. 3.2. Uptake of Questionnaires and Potential Errors. In total, 574 questionnaires were collected during the study. A very simulation of 5 s. At each timestep, the score was modified low number of visitors declined to fill in the questionnaire by adding or subtracting a second, randomly generated when they were asked (estimated at <5%), and the main number (between 3 and −3 from a uniform distribution), reason given for this was that they did not have time. Of from the current score. This new score then indicated the the questionnaires collected, 39.2% were collected outside behaviour of the otter at the next timestep. In practise, of school holidays and 60.8% during the school holidays, this meant that successive time steps normally resulted in reflecting the increase in visitor numbers in the centre. the same behaviours being recorded, which corresponded to Some visitors left various questions unanswered in the observations on behaviour (i.e., behavioural inertia is more otter behaviour questionnaire (Table 3). The segmentation likely than behavioural change). questionnaire was completed by 62.4% of visitors who had To parameterise this alteration (named the “change by” filled in the otter behaviour questionnaire, but of these, 5.6% variable), results from the ethogram recordings were used. could not be used because visitors had not followed the Results indicated that the otters performed on average 3.6 instructions and had ticked more than one answer, meaning behaviours in a 10 min period. Therefore, we systematically that they could not be classified into a visitor segment. changed the “change by” variable, and for each value, While the questionnaires were being filled in, personal we simulated 100,000 individuals 10 min periods (with observations indicated that visitors were watching the otters sampling every two 5 s timesteps—equating to the 10 s for longer than 30 s. This was reflected in the responses recording periods that were used in this study) to produce to the question concerning the length of time visitors had a number of behaviours as close as possible to 3.6. The spent at the enclosure. A chi-square test showed that the “change by” variable of 6 (i.e., between −3and 3) produced length of time a visitor spent at the enclosure affected the the most accurate representation, producing an average of number of behaviours recorded (χ = 41.7, df = 12, P< 3.5 behaviours over 10 min. (when the “change by” variable 0.001). This was because visitors who stayed at the otter was 7 (±3.5), the model produced an average number of enclosure for shorter lengths of time recorded significantly Otters’ activity budget (%) Otters’ activity budget (%) Inside Inside Swimming Swimming + playing Eating Eating Playing Walking Walking Grooming Grooming Rolling Rolling Sitting Sitting International Journal of Zoology 7 (a) (b) Figure 3: Results of bootstrapped PCA examining differences between ethogram data collectedby two biologists for the group of otters over one day. Black = RLW, red = CK. Cumulative proportionof variance explained by first 3 principal components > 0.999. (b) as above but with playing and swimming combined. Table 3: Percentage of questions not answered in the otter behaviour questionnaire. Questionnaires where this Question was left unanswered What time is it? 0.2% Approximately how long have you spent at the otter enclosure in total today? 5.7% Are you, or someone who helped fill in this questionnaire a member of any wildlife charities? 8.3% Have you or anyone who helped fill in this questionnaire volunteered or done something to help any wildlife charities? (e.g., habitat improvement, wildlife surveys, helped at events, raised money, 11.6% etc.) What age are you/the people who helped fill in this questionnaire? Write down the number of 9.9% people in each age group. fewer behaviours than those who stayed at the enclosure for 30 longer (mean number of behaviours recorded: <2 mins = 2.14; 2–5 mins = 2.34; 6–10 mins = 2.93, >10 mins = 3.33). 3.3. Comparing Ethogram Activity Budgets with Activity Bud- gets Calculated from Visitor Data. The otters’ activity budget calculated using ethogram data consisted mainly of time spent inside (28%), followed by playing (21%) (Figure 4). 0 “Other” behaviours (e.g., sprainting, drinking, climbing...), and rolling amounted to the smallest proportion of the activity budget (2%). Fighting is not represented in the ethogram activity budget, but visitors did record fighting (1%), and it was observed during the study (outside of Uncorrected visitor data Corrected visitor data the randomly allocated observation periods). Compared Ethogram data to the ethogram data, visitors underrecorded sitting, time spent inside and playing and overrecorded all of the other Figure 4: Differences in otters’ activity budgets calculated using behaviours, with the exception of “other” in the corrected corrected and uncorrected visitor data and ethogram data. visitor data, which was identical to the ethogram data. The most noticeable differences between ethogram and visitor data lie between time spent inside (28% for ethogram data and 11% for visitor data) and swimming (10% for ethogram There were significant differences between ethogram data data and 25% for visitor data). and visitor data, but there were no significant differences Otters’ activity budget (%) Inside Swimming Eating Playing Walking Grooming Rolling Sitting Fighting Other 8 International Journal of Zoology between uncorrected visitor data and corrected visitor data (Figure 5). Additionally, there were no significant differences between each individual otter and the average taken for the group, so to simplify subsequent analyses, only corrected visitor data and ethogram data for the group of otters were used. Significant differences also occurred between ethogram data and data collected by different visitor segments, but there were no significant differences between the behavioural data recorded by different types of visitor (as quantified using the visitor segments used in the analysis: learn together families, fun time families, sensualists, social naturalists and expert birders, note: other segments could not be used because of small sample sizes) (Figure 6). There was a significant difference between ethogram Figure 5: Results of bootstrapped PCA examining differences data and visitor data, but no significant difference between between ethogram and visitor data. Black = ethogram data for corrected visitor data before and after questionnaires filled group of otters, red = ethogram data for otter 1, green = ethogram in by children were excluded from the dataset. There was data for otter 2, dark blue = ethogram data for otter 3, light no significant difference between visitors who had prior blue = corrected visitor data, and pink = uncorrected visitor data. experience volunteering, or were a member of a wildlife Cumulative proportion of variance explained by first 3 principal organisation and those who were not. All visitor datasets components = 0.995. were still significantly different to the ethogram dataset (Figures 7(a) and 7(b)). There were still significant differ- ences between ethogram and visitor data when playing and of collecting scientific data on birds may be more likely to swimming were combined in the activity budgets and when collect accurate data than a “fun time family” that is on a visitor data was reclassified taking into account time periods recreational trip, but this was not the case in this study. in which the data had been collected (Figures 7(c) and 7(d)). 4.2. Where Did They Go Wrong? 3.4. Simulation of Test Accuracy of Visitor Data Collection Methods. The average number of behaviours recorded by 4.2.1. Ignoring the Instructions. One of the most important visitors in the study was 2.9, whereas the average number instructions on the questionnaire was the length of time of behaviours recorded in the simulation running for 30 s required to observe the otters for. This length of time was 1.4. Changing the length of time that visitors took to was chosen because it was thought to be short enough record behaviours in the simulation indicated that visitors not to deter visitors from participating and would allow may have watched the otters for up to 8 min, instead of the recording data as and when visitors walked past the following the instructions and recording behaviour for 30 s. enclosure. Ease of data collection and reliability were both Comparing the overall behaviour of all three otters combined a key aspect of this study because visitors were assumed to be using bootstrapped PCA demonstrated that there was no untrained. Therefore, 30 s was considered to be a reasonable significant difference in overall behaviour when observations length of time for visitors to scan the otter enclosure and be took place for 30 s (from simulated data) and the real able to identify behaviours while imposing a time limit so ethogram data, but when compared with the longer 8 min that all visitors should spend approximately the same length observation period or the visitor collected data, significant of time recording data. Results of the simulation model of differences to the ethogram data occurred (Figure 8). visitors undertaking 30 s sampling periods when filling in questionnaires showed that this length of time should have resulted in the accurate representation of the otters’ activity 4. Discussion budgets. 4.1. Visitors Cannot Accurately Collect Behavioural Data. The Despite the instruction to watch for 30 s being underlined ethogram method used to determine otter activity budgets and in bold font, most visitors did not follow this and was repeatable between trained biologists, and this suggests recorded data for much longer than 30 s (pers. obs.). When that it is a reliable way of determining activity budgets. visitors stayed longer at the otter enclosure, they ticked However, visitors were unable to collect accurate data on significantly more behaviours. This is probably one of the the otters’ behaviour regardless of which visitor segment main reasons why their activity budgets were incorrect. In they were in, their age, prior experience volunteering or some cases, visitors admitted watching for longer. One visitor whether they were a member of a wildlife organisation. This ticked rolling and wrote “when arrived,” indicating that they did not differ when behaviours that overlapped (playing felt this was an interesting behaviour and that they should and swimming) were combined in the analysis, nor when record it, even though it was not in their 30 s recording much of the potential pseudoreplication caused by varying period. Another visitor wrote “the otters came out at 10.36,” numbers of visitors throughout the day was removed. It which also indicates that they watched for longer than 30 s may seem intuitive that an “expert birder” with experience but may have thought that adding extra detail would benefit International Journal of Zoology 9 in each age group” could not be analysed because visitors misunderstood the question. Most visitors wrote down the number of people in their party, regardless of whether or not they had helped fill in the questionnaire. The fact that visitors underrecorded sitting and time spent inside may be because these could be ignored if they appeared less interesting for visitors than more active behaviours. Sitting generally occurred for short periods of time (with otters pausing for a few seconds), in which case visitors could have missed this. The underrecording of time spent inside may have been caused by visitors missing otters inside if some of the otters were outside. If this was the case, visitors often observed the otters that were outside and did not check the sleeping chamber (pers. obs.). Another contributing factor could be that otters spent more time inside during quiet times when there were no visitors around to record this (early morning and late afternoon). Figure 6: Results of bootstrapped PCA examining differences The underrecording of playing is probably correlated with between ethogram data and different visitor segments. Black = the overrecording of swimming; it is likely that some ethogram data for group of otters, red = fun time families, green = visitors confused the two behaviours and ticked swimming sensualists, dark blue = social naturalists, light blue = expert birders, instead of playing when otters were playing in the water and pink = learn together families. No other visitor segments were (Figures 2(a) and 2(b)). Playing may have been difficult for included, since in total they contained <20 responses. Pairwise some visitors to interpret. Indeed, most “other” behaviours comparisons between social naturalists and sensualists also indi- that were reclassified in the corrected dataset were reclassified cated no significant differences occurred between these categories. as playing. However, removing mistakes and omissions and Cumulative proportion of variance explained by first 3 principal grouping behaviours did not change the overall results. This components = 0.997. suggests that misidentification of behaviours by visitors was not the prime reason for the differences between ethogram and visitor activity budgets. the study. At the end of one questionnaire that had been filled in by a parent and child (where all but one of the boxes had been ticked), the parent wrote, “hence saw all of 4.2.3. Item Nonresponse. Item nonresponse, in which a the above because watched for a long time.” Another visitor questionnaire is returned with one or more questions wrote that they “saw the otters outdoors earlier” so had unanswered, can have an impact on results of a survey filled their questionnaire in for a previous time (based on but these impacts are difficult to measure [37–39]. There their memory of what they saw the otters do) as well as the could be various reasons why some visitors left questions present (when the otters were indoors), thus confounding blank (Table 3). For example, the visitor who missed out their results. Some visitors demonstrated attention to detail the question asking for the time may not have been able to by adding detailed notes on their questionnaires. However, find out what the time was as they did fill in all of the other these details are often impossible to analyse unless they questions. Boredom or rushing to finish the questionnaire can be reclassified, and this process can be time consuming may have been reasons why 1.6% of visitors filled in the (pers. obs). It seems that attention to detail and enthusiasm, time and ticked behaviours but did not answer any other while generally considered key attributes for volunteering, questions that appeared later in the questionnaire [40]. It is can hinder the quality of behavioural data collected. also possible that some of the visitors who did not answer questions on the second page did not realise they were there, 4.2.2. Making Mistakes and Adding Extra Details. Occa- despite the staple and instruction “please turn over” in bold sionally, visitors admitted that they were wrong on their and underlined at the bottom of the first page: some visitors questionnaires, despite understanding the instructions. One only realised this when another visitor pointed it out to them visitor ticked rolling but wrote “in water” next to the box (pers. obs.). Another possibility is that visitors may not have despite the fact that the behaviour was entitled “rolling— wanted to fill in the questionnaire but felt obliged to do so e.g. on soil or rocks”, another ticked sitting but specified out of politeness and as a result, may have rushed through that the otters were indoors. However, only the obvious the questions, missing some out. mistakes could be removed from the corrected dataset, and This lack of attention to detail could be caused by the fact it is highly likely that some mistakes remained undetected that the questionnaire was impromptu: visitors were on a day (i.e., if visitors wrongly interpreted behaviours or deliberately out not expecting to have to concentrate on a task. They may ticked boxes even though they had not seen a particular also have been distracted by the surrounding environment behaviour). It was impossible to measure this. Furthermore, (e.g., by their children or by other visitors). Slightly more the question “What age are you/the people who helped fill visitors avoided answering the question about volunteering in this questionnaire? Write down the number of people than the question about being a member of a wildlife 10 International Journal of Zoology (a) (b) (c) (d) Figure 7: (a) Results of bootstrapped PCA examining differences between ethogram data, corrected visitor data, and uncorrected visitor data when all questionnaires filled in by children were removed from the dataset. Black = ethogram data for group of otters, red = children’s questionnaires removed from corrected visitor data, and green = corrected visitor data. Cumulative proportion of variance explained by first 3 principal components >0.999. (b) As above but examining visitor segments. Black = ethogram data for group of otters, red = corrected visitor data, green = visitors who had previous experience volunteering, dark blue = visitors who did not have prior experience volunteering, light blue = visitors who were members of a wildlife organisation, and pink = visitors who were not members of a wildlife organisation. Cumulative proportion of variance explained by first 3 principal components = 0.995. (c) As above but examining ethogram data for group of otters and corrected visitor data when playing and swimming were combined. Black = ethogram data for group of otters and red = corrected visitor data. Cumulative proportion of variance explained by first 3 principal components >0.999. (d) As above but examining ethogram data and visitor data with standardised time periods. Black = ethogram data for group of otters and red = corrected visitor data. Cumulative proportion of variance explained by first 3 principal components = 0.987. organisation or charity (Table 3). This may be because the they could not participate. In a zoo environment, it would membership question can be more easily interpreted, as be very difficult to fully control the spread of questionnaires membership to the WWT is well advertised throughout over time because of the irregular flow of visitors, not only the centre and 57% of all visitors to the centre during the at different times of day (e.g., when the centre first opens or study were members of WWT. The volunteering question when visitors are hurrying to leave before the closing time), may confuse those who are unfamiliar with the idea of but also in adverse weather conditions when visitors would volunteering; one visitor said that she considered visiting the be less likely to want to fill in a questionnaire. Additionally, centre as volunteering (pers. comm.). there were often more visitors at the enclosure when the otters were active, with large crowds often attracting passers by because the formation of a crowd could indicate that the 4.2.4. Temporal Autocorrelation of the Data. Questionnaires otters were doing something interesting or unusual (pers. were handed to visitors as and when they arrived at the obs.). In this study, the averaging of data over 30 min periods otter enclosure. As such, it is highly likely that some of the helped reduce autocorrelation effects due to the effects otters’ behaviours were simultaneously recorded by many mentioned previously, but would not completely eliminate visitors, especially at busy times such as during the feeding them if there was a difference in recorder effort within a 30 min period. demonstrations. While it would have been possible to hand out only one questionnaire at a time, such an approach However, the effects of temporal autocorrelation on the would reduce the uptake of the questionnaire, and also would results of this study appear minimal. Firstly, “standardised” have a negative influence on visitor experience, with visitors data (where an average activity budget was calculated over either waiting a long time to participate or feeling left out if each 30 min period taking into account the number of International Journal of Zoology 11 Uptake rate maybelesshighwhenanimalsare outof view or in an indoor area. As discussed previously, otters were less popular with visitors when they were inside, visitors walked past and/or did not see the point of filling in the questionnaire until it was explained that it was important to find out how much time the otters were spending inside. This has been discussed in previous studies. Indeed, Altman [45]and Anderson et al.[24] found that zoo visitors paid more attention to an animal’s behaviour when the animals were most active compared to when theywerelessactiveor inactive. Jackson [46] and Johnston [47] found that visitors spent less time in front of enclosures where animals were inactive. Additionally, mammals are the most popular class in zoos [48], and larger animals may be preferred by visitors over smaller animals [49]. It is possible that a behavioural study would not prove as popular with visitors if it involved less appealing classes or species. Indeed, Hoff and Maple [50] found that some visitors deliberately avoided going to reptile Figure 8: Results of bootstrapped PCA examining differences exhibits. between real data and simulated data. Black = real visitor data, red = real ethogram data, green = simulated visitor data where data were collected for 8 min, and blue = simulated visitor data where data were collected for 30 s. Cumulative proportion of variance explained by first 3 principal components = 99.8. 4.4. Recommendations for Further Study. A visitor who had completed the questionnaire made the following comment: “you could tell us more about the otters than we could tell you”. This statement underlies the concept of volunteer data collection: a scientist’s work can be more reliable than that of questionnaires answered) and “unstandardised” data both a volunteer, as was the case in this study. However, it is the differed significantly from ethogram data. Secondly, when large number of volunteers that can make them a powerful data were simulated (and autocorrelation effects were elimi- tool for research. Although the method in this study did nated) results corresponding to visitors collecting data for a not allow visitors to collect accurate activity budgets, it did long period of time (8 min) were highly significantly different have some success. The high uptake rate suggests that getting from ethogram recordings. Hence, it appears that it was visitors to collect data on active and entertaining animals the length of time in which visitors recorded behaviour can be successful. Public engagement and distributing the that was the largest source of error, rather than potential questionnaires by hand also undoubtedly had a major errors inherent to the sampling design used. Nevertheless, influence on the uptake rate. methods to eliminate temporal autocorrelation and enhance Several improvements could be made in future research. the visitor experience are given in the Recommendations When asking volunteers to collect behavioural data, it is Section. important that behaviours are simple enough that volunteers can distinguish them without confusion. Clear instructions 4.3. A Success: The High Questionnaire Uptake Rate. The are needed when designing questionnaires, but in situations questionnaire uptake rate may not have been so high if where a time limit is necessary, it is important to try to the questionnaires had not been handed out in person facilitate this to ensure that methods are followed as closely [41]. Indeed, very few visitors were observed picking up a as possible, perhaps by providing a large clock in front of the questionnaire themselves when the questionnaires were laid enclosure. A time limit could also be imposed with the use of out on a wall next to the otter enclosure, despite posters technology, for example, through multimedia or interactive advertising the study. In this situation, children were more video screens, which have previously been used in zoos and curious than adults, often picking up questionnaires and aquaria to convey information to visitors [51–53]. This type filling them in of their own accord. Curiosity is a strong of technology has also been used by the National Marine motivational force in children [42–44] and it is often believed Aquarium in Plymouth, UK to allow visitors to collect data that curiosity decreases with age [44], which may explain on fish in an exhibit (pers. obs). Visitors could also collect why fewer adults picked questionnaires up. Distributing data with the use of smart phone technology as this has questionnaires in the manner described in this study could already been used for other types of volunteer data collection cause logistical problems for zoos (for financial and temporal [54]. Technology such as this may also reduce the number reasons discussed in Section 1). However, it may be possible of questions that are unanswered by imposing a response, that handing questionnaires upon entry to the park along or could be used to eliminate any temporal autocorrelation with a quick explanation or instruction leaflet could be of responses by either only having a single display, or by a suitable method to increase participation, similar to the accurately recording the time of the response, so replication method described in Dillman [41]. in time can be removed. 12 International Journal of Zoology Overall, many of the aims of volunteering were com- [9] C. Kremen, K. S. Ullman, and R. W. Thorp, “Evaluating the quality of citizen-scientist data on pollinator communities,” pleted in this study as visitors were keen to participate, Conservation Biology, vol. 25, no. 3, pp. 607–617, 2011. enjoyed observing the otters, gave positive feedback, and [10] W. R. T. Darwall and N. K. Dulvy, “An evaluation of the asked questions about the study. Visitors were generally suitability of non-specialist volunteer researchers for coral reef able to recognise different behaviours and recorded a rare fish surveys. Mafia Island, Tanzania—a case study,” Biological behaviour that the scan sampling method did not detect [27]. Conservation, vol. 78, no. 3, pp. 223–231, 1996. They were also often eager to provide detailed notes on their [11] S. R. Engel and J. R. Voshell, “Volunteer biological monitoring: observations. The “ad libitum” behaviour sampling method can it accurately assess the ecological condition of streams?” maybemoresuitedtovolunteersasitwould remove the American Entomologist, vol. 48, pp. 164–177, 2002. need for a restrictive time limit and would allow volunteers [12] C. Newman, C. D. Buesching, and D. W. Macdonald, “Val- to record behaviours as they wished. 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The Accuracy of Behavioural Data Collected by Visitors in a Zoo Environment: Can Visitors Collect Meaningful Data?

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Hindawi Publishing Corporation
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Copyright © 2012 Rachel L. Williams et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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1687-8477
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1687-8485
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10.1155/2012/724835
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Hindawi Publishing Corporation International Journal of Zoology Volume 2012, Article ID 724835, 13 pages doi:10.1155/2012/724835 Research Article The Accuracy of Behavioural Data Collected by Visitors in a Zoo Environment: Can Visitors Collect Meaningful Data? 1 2 1 1 Rachel L. Williams, Sue K. Porter, Adam G. Hart, and Anne E. Goodenough Department of Natural and Social Sciences, University of Gloucestershire, Cheltenham GL50 4AZ, UK Wildfowl and Wetlands Trust, Slimbridge, Gloucestershire GL2 7BT, UK Correspondence should be addressed to Rachel L. Williams, rachel.williams 31@hotmail.com Received 24 February 2012; Accepted 22 June 2012 Academic Editor: Simon Morgan Copyright © 2012 Rachel L. Williams et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Volunteer data collection can be valuable for research. However, accuracy of such data is often a cause for concern. If clear, simple methods are used, volunteers can monitor species presence and abundance in a similar manner to professionals, but it is unknown whether volunteers could collect accurate data on animal behaviour. In this study, visitors at a Wetlands Centre were asked to record behavioural data for a group of captive otters by means of a short questionnaire. They were also asked to provide information about themselves to determine whether various factors would influence their ability to collect data. Using a novel analysis technique based on PCA, visitor data were compared to baseline activity budget data collected by a trained biologist to determine whether visitor data were accurate. Although the response rate was high, visitors were unable to collect accurate data. The principal reason was that visitors exceeded the observation time stated in the instructions, rather than being unable to record behaviours accurately. We propose that automated recording stations, such as touchscreen displays, might prevent this as well as other potential problems such as temporal autocorrelation of data and may result in accurate data collection by visiting members of the public. 1. Introduction been collecting biodiversity data for wildlife organisations for several decades. For example, in 2011, over 600,000 members Animal behaviour data are important across the field of of the public took part in the Royal Society for the Protection biological sciences, from evolution and population biology of Birds’ “Big Garden Birdwatch” [7]. Several studies have to ethology in captive or domesticated animals. However, shown that volunteer-collected data on, for example, species collecting these data is time consuming. Given that the identification and quantifying abundance, can be as accurate duration of data collection for behavioural studies can range as basic biodiversity data recorded by scientists [4, 6, 8, 9], from several weeks [1, 2] to several years [3], funding especially when projects offer basic training and are closely professional researchers can be prohibitively expensive for supervised by scientists. Moreover, several methods have many studies, especially those conducted by zoological been developed to enhance the accuracy of volunteer-run parks and wildlife organisations [4, 5]. However, animal surveys, either in terms of the methods used to collect the behaviour is of considerable interest to the general public data or in subsequent analysis [4, 10–14]. Collection of (or at least a subset of the public with environmental and behavioural data, however, is subject to a certain degree of zoological interests), and many people spend considerable interpretation and may be more complex to record than time observing animals as a hobby (e.g., watching pets, counting or identifying species. It is not known whether wild birds, or animals in zoos). Professionals could use this the quality of volunteer-collected behavioural data would interest to recruit volunteers to record animal behaviour. be sufficient to calculate accurate activity budgets or to test There are many advantages of using volunteers to collect behavioural ecology hypotheses. data. Volunteers can collect data at little or no financial Monitoring animal behaviour is particularly important cost to the organisation running the project [4–6]; indeed in zoos because of the importance of animal welfare [15, large numbers of untrained members of the public have 16]. Zoos may encourage their zookeepers to participate in 2 International Journal of Zoology research [17] but data collection often cannot be a priority the enclosure allowed visitors to view the otters easily amongst the zookeepers’ daily husbandry activities [18]. from the walkway that spanned the front of the enclosure Research activities can be supplemented with undergraduate (Figure 1). There was also a small indoor sleeping chamber and postgraduate students under the supervision of lecturers in which visitors could see the otters through small glass and scientists, with no financial cost for the zoos involved windows in a walkthrough tunnel. Otters could access all [19, 20], but while this provides useful and reliable data, it parts of the enclosure at any time of the day, and no parts relies on the availability of students and on University course of the enclosure were closed during routine cleaning of the content. exhibit. An alternativeapproach couldbetouse zoovisitorsto collect data on a voluntary basis. The benefits of asking zoo visitors to collect data while they visit could be numerous. 2.2. Ethogram Data Zoos are popular attractions worldwide, attracting more than 700 million people each year [21], so there is no 2.2.1. Ethogram Construction and Scientific Data Collection. shortage of potential volunteers. Many visitors have a keen To determine whether visitors could record data that would interest in animals and wildlife conservation [22, 23], and accurately represent the otters’ behaviour, reliable baseline this could be a strong incentive to participate in research that data were required for comparison. A biologist with expe- may benefit the animals they are observing. Furthermore, rience in collecting behavioural data (RLW) created an behavioural data could be collected almost continuously ethogram as per Martin and Bateson [27] to record the throughout the day as and when visitors pass the animal otters’ behaviour based on prior observations in a pilot enclosures. This should create a database from which study. Behaviour categories were adapted from a behavioural daily activity budgets can be calculated. Finally, interactive study done by Anderson et al. [24] on a similar species activities create more positive experiences for visitors when (Asian small-clawed otters—Aonyx cinerea). Behaviours were compared to passive exhibit viewing [24], so an activity grouped into simple, easily definable, categories to ensure such as this could make the zoo more attractive to its that members of the public should be able to recognise visitors. them in the latter part of the study (Table 1). The study took place over 7 days during the opening hours of the While some research suggests that zookeepers’ casual park (10 am until 5 pm). Each hour was divided into six observations throughout the day provide a good indication of the overall activity budgets of the animals [18, 25, 26], 10 minute periods and the otters’ behaviour was recorded during two randomly selected 10-minute periods each hour and keepers are generally well acquainted with individual animals and their behaviours, they may not be acquainted [28]. An instantaneous scan sampling method [27–29]was with recording behaviour in a scientific and rigorous manner. used to record the behaviour of each of the 3 otters systematically every 10 s during the recording periods. This It also seems reasonable to assume that the vast majority of visitor-based “volunteers” would have no prior experience was the shortest interval in which data could be recorded by watching each otter consecutively. By using this sampling of collecting behavioural data and it would be logistically difficult, or impossible, to train and/or supervise them technique for each of the otters, the problem of missing while they collect data. However, if visitors are able to out individual behaviours was minimised and an overall collect accurate data on captive animals, there is a potential activity budget for all three otters could also be calculated. for volunteer projects to collect behavioural data on wild Subtle differences in size and coat colouration were used animals, especially where there are large concentrations of to distinguish each otter to calculate individual activity people and animals, such as in nature reserves or game parks. budgets. If an individual otter was out of view at any time The aim of this study is to determine whether visitors can during the recording period, it was noted as such. In total, collect accurate data on the behaviour of a small group 16.5 h of data were collected for each otter, with a data of animals in a captive environment. Visitor data were point collected from each otter simultaneously, giving 1,980 compared to data collected by a trained biologist. ethogram observations per otter (6 recordings per minute, that is, one every 10 seconds, ×20 minutes of observation per hour ×16.5 hours in total = 1, 980). This sample size 2. Methods is comparable to those used in studies of a similar nature [18, 30]. 2.1. Study Site. The study was conducted at the Wildfowl and Wetlands Trust (WWT) centre at Slimbridge, Glouces- tershire, UK (OS grid reference SO722047). A group of three female captive North American river otters (Lontra 2.2.2. Interobserver Variability. To examine the potential for canadensis) were selected for the study because of their interobserver variability in the collection of behavioural data, popularity with visitors and the fact that this species a second biologist (herein referred to as CK; not an author demonstrated a rich suite of behaviours during the daily of this study and independent from its planning and prior opening hours of the centre (R. L. Williams pers. obs.). It implementation but with the same level of experience as was important that visitors could see the otters in order RLW) collected ethogram data over one day, during exactly to record their behaviour, and the layout of the otter the same recording periods (14 × 10 min). The paired data enclosure facilitated this. Large panels of clear glass around were then compared. International Journal of Zoology 3 view” category from the ethogram was not included in the questionnaire because visitors did not know how many otters were in the enclosure. If they could not see any of the otters, they should have answered “no” to the questions asking whether they could see any otters inside or outside. Visitors were asked how long they spent at the otter enclosure overall to determine whether this was related to the number of behaviours recorded, and because this could be a potential indication that visitors might be spending longer than the requested 30 s recording data. Visitors were asked some anonymous personal information questions (e.g., their age group, whether they had volunteered before, whether they were a member of a wildlife organisation) to determine whether any of these factors influenced their ability to record Figure 1: Otter enclosure at Slimbridge, a photograph taken from accurate data. Finally, visitors were required to indicate how the front of the enclosure and showing the visitors’ viewpoint. many people had helped them fill in the questionnaire. The study took place over 8 consecutive days, for 7 hours each day. Visitor data were collected for a day more than the ethogram data because of logistical issues 2.3. Questionnaires when undertaking both activities was not possible. However, analysis of daily otter activity budgets after the data were 2.3.1. Otter Behaviour Questionnaire. The ethogram was collected showed that this did not affect the results. The simplified to a multiple-choice questionnaire to deter- study was advertised using A3-sized posters at the entrance mine whether visitors could collect accurate data on otter of the centre and near the otter enclosure, and was pro- behaviour. The instructions on the questionnaire were as moted by the mammal keeper during the twice daily otter clear, concise, and self-explanatory as possible, as recom- feeding demonstrations (11.30 am and 3.30 pm). Visitors mended by previous studies [6, 8, 10, 12, 31]. Visitors approaching the otter enclosure were asked whether they had to fill in basic information (e.g., write the time down, would be willing to fill in a questionnaire as part of a answer “yes” or “no” if they could see otters inside and/or research project on otter behaviour. No other details were outside), and tick the behaviours they saw when the otters given unless visitors asked questions, as the aim of the were outside (i.e., not in the sleeping chamber) during a study was to determine whether visitors could collect data 30 s period. This method was adapted from the one-zero without supervision. In order to compare ethogram- and sampling method in that all behaviours which were observed questionnaire-derived data, both were collected on the same within the interval were ticked once (1) and those that were days (in order to ensure consistent activity levels of the not observed were not ticked (0). It is recognised that the otters—Anderson et al. [24]). The study was carried out on two datasets differed not only in who had collected the data four days before the school holidays and on four days during (biologist or visitors) but how the data had been collected the school holidays. This allowed a comparison between (ethogram instantaneous scan sampling or questionnaire uptake of the questionnaire during quiet and busy periods at extended one-zero sampling, resp.). The differences in data the centre, as well as increasing the range of different visitors collection methods were undertaken for good reason-one- filling in the questionnaire (e.g., more families during school zero sampling was the easiest type of sampling for visitors holidays). (and thus the most likely to be reliable) whereas instanta- neous scan sampling is a more robust method for generating data for activity budgets. Therefore, although it could be 2.3.2. Visitor Segmentation Questionnaire. The WWT devel- argued that different methods will give different results, the oped a questionnaire as part of a survey to learn more about study aimed to determine whether visitor-collected data (at their visitors, and this was used as a complementary tool its simplest) could be compared to maximally robust and in this study [33]. This questionnaire (named the visitor reliable data, validating the approach taken. segmentation questionnaire) was stapled behind the otter The layout of the questionnaire was an important con- behaviour questionnaire, but was optional so that length sideration [32]. Colour photographs were used to illustrate of the two combined questionnaires did not deter visitors each of the behaviours with the exception of “other”, which from participating. It consisted of a list of questions with the was represented by a question mark with space underneath instruction “tick the statement that best describes you”. The for visitors to write down what they had seen. Visitors were questions concerned topics such as motivations for visiting not asked to distinguish between individual otters, because the centre, personal interests and affinity for nature, and identifying them reliably would have been very difficult given preferences for various animals at the centre. Analysis of the short recording period and subtlety of the differences the results determined which “segment” a visitor belonged between otters. Consequently, they were requested to record to (Table 2) and, subsequently, allowed examination to test all of the behaviours they observed, regardless of which whether different segments of visitors could record otter individual was performing the behaviour. The “out of behaviour more effectively than others. 4 International Journal of Zoology Table 1: Ethogram used by a trained biologist to record simple otter behaviours. Behaviour Comments and additional information “Inside” is not a behaviour, but it was necessary to record this so that the period of time that the otters spent Inside inside was included in the activity budget (it was speculated that visitors may underrecord otters when they were inside—Section 4 ). Swimming In water, not interacting with other otters and/or showing signs of play. Eating This occurred mainly during twice-daily public demonstrations. Any playful interaction with another otter (such as chasing, play fighting) or playing alone (diving/rolling in the Playing water, playing with an object). Walking or running As stated. Self-grooming or mutual grooming (if mutual grooming occurred, all otters involved were recorded as Grooming grooming). Rolling Rolling on land. Sitting or lying Inactive animal (included pausing for a few seconds but also sleeping outside). down This was never recorded with the ethogram, though the otters did display aggressive behaviour over food on Fighting one occasion (outside a recording period), so it is possible that visitors could have recorded this. Other Any behaviour not mentioned above, for example, sprainting, climbing a tree, and drinking. If an otter was not observable at any point during a sampling interval such that its behaviour could not be Outofview recorded (i.e., under the pedestrian walkway or hidden in vegetation). See Section 4 for comments about the differentiation of swimming and playing. Table 2: Segmentation pen portraits—Modified and adapted from WWT visitor segmentation report [33]. Visitor segment Description and comments Learn together They believe in life-long learning for their family. Accessing the outside plays an important role in their leisure families time, and they are generally open to all forms of nature, rather than visiting specifically to see birds. Doing something that entertains and satisfies their children is the main priority in their day out. If their Fun time families children learn something along the way, then this is an added bonus. Their interest in nature is broad; it is not about acquiring detailed knowledge on specific species but more Social naturalists about simply enjoying any kind of wildlife. Interested naturalists are not active birdwatchers but visit to improve their knowledge and learn new things, Interested naturalists driven by a broad interest in the natural world. For interested birders, trips in the outside are a significant part of their life, and the majority are active Interested birders birdwatchers. Whilst they are mainly looking to develop their interests, their interest in birds is often tied into other hobbies such as walking, photography, and painting. Social birders are seeking to spend quality time with other people in natural surroundings where they are Social birders guaranteed to see interesting birds. Expert birders are applied birdwatchers who tend to take their hobby relatively seriously. This segment has the Expert birders most knowledge about the WWT’s wider conservation activities. Experiencing the outside is essential to sensualists’ lives; to them, it is food for the soul and is a space in which Sensualists they can relax and experience nature’s beauty. Wildlife and the outside are not of prime interest to them; their main focus is to spend quality time with others Social day-outers in a nice environment. 2.4. Data Processing and Analysis corrected dataset included writing the wrong time (pers. obs.), not answering all of the questions, and ticking all of the 2.4.1. Uncorrected and Corrected Data. When data were boxes haphazardly (such questionnaires were usually filled in entered into a spreadsheet, two copies were made: an by young children—pers. obs.). Questionnaires that could uncorrected version with data exactly as they were recorded be rectified were those in which visitors had interpreted a by visitors and a corrected version, whereby any mistakes behaviour as “other” when it could be reclassified as one of visitors had made that were noticed by RLW were rectified the categories listed, for example, “kissing” or “licking” = when possible or omitted from the dataset if the whole grooming; “going through tunnel” = playing, and so forth. questionnaire was unusable (c. 10% of the questionnaires These datasets are henceforth referred to as uncorrected were affected). Mistakes that resulted in exclusion from the visitor data and corrected visitor data. International Journal of Zoology 5 2.4.2. Calculating Activity Budgets. Ethogram data and ques- principal components in three dimensions with the radius of tionnaire data were converted into activity budgets to the resulting sphere, or “bubble”, indicating the confidence indicate the percentage occurrence of specific behaviours as radius. Plots were constructed using the RGL library and per Stafford et al. [30]. An activity budget was calculated rgl.sphere function for R [36]. Each bubble represented for each individual otter and for the whole group (using the overall activity budget, with the centre representing ethogram data), as well as for the group of otters using visitor the mean of the first three principal components and the data (using corrected and uncorrected data). In addition to radius representing the 95% confidence interval. Statistical the full questionnaire datasets, various subsets were extracted inferences were made on the basis that overlapping bubbles for separate analysis, for example, for each visitor segment signify no significant difference between the activity budgets and from adapted or standardised datasets (see below). represented by the bubbles while no overlap indicates signif- icant differences in the activity budgets (α = 0.05). In order for the plot to be reliable, the cumulative proportion of the 2.4.3. Adaptation of the Visitor Datasets and Extraction of variance explained by the first three principle components Subsets . In addition to the full activity budgets men- (i.e., those used to create the plots) needs to be greater than tioned above, activity budgets were also calculated with 0.95 [30]; in this study, all values exceeded 0.95. the behaviours playing and swimming combined into one A chi-square test for association was performed to category because these behaviours often overlapped. This test whether the number of behaviours recorded related was similar to the adaptations of Margulis and Westhus [18] to the length of time spent at the otter enclosure. The where “swim” and “stereotypic swim” were combined to corrected visitor data were used to calculate the number allow the comparison of keeper-collected data and scientist of behaviours recorded, and any questionnaires where the data on brown bear (Ursus arctos)behaviour. question regarding time spent at the enclosure was left There was a disparity in the number of visitors at blank were excluded. Number of behaviours recorded were different times of day, which could have led to an under- combined into 5 categories for the chi-square test (0, 1- representation of inside in the mornings when there were 2, 3-4, 5-6, and 7-8) and time periods were classed as less fewer questionnaires completed (because there were fewer than 2 mins, 2–5 mins, 6–10 mins, and over 10 mins. It is visitors in the centre) and an overrepresentation of eating worth noting that, although visitors could have recorded when many questionnaires were filled in during the otter up to 10 behaviours, this did not occur (one visitor did demonstrations. To reduce the effect of pseudoreplication record 9 behaviours, but this was excluded from the analysis and temporal autocorrelation (visitors recording the same because the visitor was a young child and data accuracy was behaviours at the same time) that may result from this, an questionable). average activity budget was calculated over each half hour period taking into account the number of questionnaires answered in each period. Given the varying length of time 2.5. Simulations to Test Accuracy of Visitor-Collected Data. that visitors had the questionnaire (including filling in the The selection of the time period in which the visitors were segmentation questionnaires) it was not logistically possible asked to collect data was based on the concept that a 30 s to calculate an average from the questionnaires over a shorter period would capture more data than a single instantaneous time interval than 30 min, and in some cases, autocorrelation scan, yet would not be likely to result in all behaviours between questionnaires was likely. The effects of this possible being observed; hence an estimate of frequency of behaviours autocorrelation are discussed below. could be obtained using this method. Given that preliminary Separate activity budgets were also calculated from sub- observations indicated that visitors vastly exceeded this time sets of questionnaires extracted from the complete dataset. period (see below), a computer simulation was developed These were based on the personal information questions at to determine if the 30 s sampling period would produce the end of the behaviour questionnaire. Activity budgets were comparable data to ethogram recordings given assumptions calculated based on the removal of all questionnaires that had that incorrect identification of behaviour and temporal been filled in by a child aged 10 or under from the initial autocorrelation of the data did not exist (i.e., data were dataset (because children may have difficulty giving accurate collected perfectly, except for the time of recording). The answers [34]), as well as separate subsets for the visitors simulation was constructed using R [35]. The simulation who had prior experience volunteering and for those who was parameterised according to the relative probability of the had none, and for visitors who were members of a wildlife behaviours, as collected from ethogram recordings, making organisation and for those who were not. the assumption that the ethogram data collected in this study were an accurate representation of the otters’ activity budget 2.4.4. PCA and Analytical Framework. To compare the (see results, Figure 2). ethogram activity budgets with the activity budgets cal- The simulation produced a random number (score) culated for the visitor datasets and subsets, bootstrapped between 1 and 100, which corresponded to a particular principal components analysis (PCA) was conducted in the behaviour based on the proportion of its occurrence (see R statistical package [35], following methods in Stafford results for details, but otters were seen swimming 11% of et al. [30]. Rather than plotting each activity budget on a the time, so a score between 1 and 11 would correspond two-dimensional scatterplot (as in conventional PCA), this to the behaviour “swimming”). After this initial score approach involved plotting the mean value of calculated had been set, the simulation ran with a timestep of the 6 International Journal of Zoology behaviours of 3.8, and when 5 (±2.5) produced an average of 3.2 behaviours). We next simulated data that represented 30 s of sampling by visitors. Although these simulated data were free from confounds such as temporal autocorrelation and misidentifi- cation of behaviours, they would give an accurate indication of whether the 30 s recording period would have allowed visitors to collect accurate data on the otters’ activity budget. As such, we simulated 574 visitor responses (the same number collected in the study). We compared simulated data and real visitor-collected data in terms of the number of behaviours recorded in a questionnaire to examine the (a) average length of time that visitors may have recorded data for. We also compared the 30 s simulated visitor data to ethogram data and real visitor data using modified PCA or “bubble” analysis, to determine whether recording behaviour for 30 s would result in significant differences to either of these recording methods. 3. Results 3.1. Interobserver Variability. The activity budgets collected by the two biologists were very similar except for the categories of playing (35% for RLW and 25% for CK) and swimming (14% for RLW and 22% for CK). Because playing and swimming were sometimes difficult to differentiate RLW (playing often occurred in water), the differences between the CK two activity budgets were less apparent when these categories (b) were combined as a single category (Figures 2(a) and 2(b)). There was no significant difference between activity budgets Figure 2: (a) Comparison of otters’ activity budgets calculated collected by the two biologists. However, when playing and from ethogram data collected by two biologists (RLW and CK) over swimming were combined, the bubbles overlapped more, one day. Note: categories “fighting” and “other” are not displayed indicating greater similarity (Figures 3(a) and 3(b)). on the graph because neither occurred on that day. (b) As above, swimming and are playing combined as one category. 3.2. Uptake of Questionnaires and Potential Errors. In total, 574 questionnaires were collected during the study. A very simulation of 5 s. At each timestep, the score was modified low number of visitors declined to fill in the questionnaire by adding or subtracting a second, randomly generated when they were asked (estimated at <5%), and the main number (between 3 and −3 from a uniform distribution), reason given for this was that they did not have time. Of from the current score. This new score then indicated the the questionnaires collected, 39.2% were collected outside behaviour of the otter at the next timestep. In practise, of school holidays and 60.8% during the school holidays, this meant that successive time steps normally resulted in reflecting the increase in visitor numbers in the centre. the same behaviours being recorded, which corresponded to Some visitors left various questions unanswered in the observations on behaviour (i.e., behavioural inertia is more otter behaviour questionnaire (Table 3). The segmentation likely than behavioural change). questionnaire was completed by 62.4% of visitors who had To parameterise this alteration (named the “change by” filled in the otter behaviour questionnaire, but of these, 5.6% variable), results from the ethogram recordings were used. could not be used because visitors had not followed the Results indicated that the otters performed on average 3.6 instructions and had ticked more than one answer, meaning behaviours in a 10 min period. Therefore, we systematically that they could not be classified into a visitor segment. changed the “change by” variable, and for each value, While the questionnaires were being filled in, personal we simulated 100,000 individuals 10 min periods (with observations indicated that visitors were watching the otters sampling every two 5 s timesteps—equating to the 10 s for longer than 30 s. This was reflected in the responses recording periods that were used in this study) to produce to the question concerning the length of time visitors had a number of behaviours as close as possible to 3.6. The spent at the enclosure. A chi-square test showed that the “change by” variable of 6 (i.e., between −3and 3) produced length of time a visitor spent at the enclosure affected the the most accurate representation, producing an average of number of behaviours recorded (χ = 41.7, df = 12, P< 3.5 behaviours over 10 min. (when the “change by” variable 0.001). This was because visitors who stayed at the otter was 7 (±3.5), the model produced an average number of enclosure for shorter lengths of time recorded significantly Otters’ activity budget (%) Otters’ activity budget (%) Inside Inside Swimming Swimming + playing Eating Eating Playing Walking Walking Grooming Grooming Rolling Rolling Sitting Sitting International Journal of Zoology 7 (a) (b) Figure 3: Results of bootstrapped PCA examining differences between ethogram data collectedby two biologists for the group of otters over one day. Black = RLW, red = CK. Cumulative proportionof variance explained by first 3 principal components > 0.999. (b) as above but with playing and swimming combined. Table 3: Percentage of questions not answered in the otter behaviour questionnaire. Questionnaires where this Question was left unanswered What time is it? 0.2% Approximately how long have you spent at the otter enclosure in total today? 5.7% Are you, or someone who helped fill in this questionnaire a member of any wildlife charities? 8.3% Have you or anyone who helped fill in this questionnaire volunteered or done something to help any wildlife charities? (e.g., habitat improvement, wildlife surveys, helped at events, raised money, 11.6% etc.) What age are you/the people who helped fill in this questionnaire? Write down the number of 9.9% people in each age group. fewer behaviours than those who stayed at the enclosure for 30 longer (mean number of behaviours recorded: <2 mins = 2.14; 2–5 mins = 2.34; 6–10 mins = 2.93, >10 mins = 3.33). 3.3. Comparing Ethogram Activity Budgets with Activity Bud- gets Calculated from Visitor Data. The otters’ activity budget calculated using ethogram data consisted mainly of time spent inside (28%), followed by playing (21%) (Figure 4). 0 “Other” behaviours (e.g., sprainting, drinking, climbing...), and rolling amounted to the smallest proportion of the activity budget (2%). Fighting is not represented in the ethogram activity budget, but visitors did record fighting (1%), and it was observed during the study (outside of Uncorrected visitor data Corrected visitor data the randomly allocated observation periods). Compared Ethogram data to the ethogram data, visitors underrecorded sitting, time spent inside and playing and overrecorded all of the other Figure 4: Differences in otters’ activity budgets calculated using behaviours, with the exception of “other” in the corrected corrected and uncorrected visitor data and ethogram data. visitor data, which was identical to the ethogram data. The most noticeable differences between ethogram and visitor data lie between time spent inside (28% for ethogram data and 11% for visitor data) and swimming (10% for ethogram There were significant differences between ethogram data data and 25% for visitor data). and visitor data, but there were no significant differences Otters’ activity budget (%) Inside Swimming Eating Playing Walking Grooming Rolling Sitting Fighting Other 8 International Journal of Zoology between uncorrected visitor data and corrected visitor data (Figure 5). Additionally, there were no significant differences between each individual otter and the average taken for the group, so to simplify subsequent analyses, only corrected visitor data and ethogram data for the group of otters were used. Significant differences also occurred between ethogram data and data collected by different visitor segments, but there were no significant differences between the behavioural data recorded by different types of visitor (as quantified using the visitor segments used in the analysis: learn together families, fun time families, sensualists, social naturalists and expert birders, note: other segments could not be used because of small sample sizes) (Figure 6). There was a significant difference between ethogram Figure 5: Results of bootstrapped PCA examining differences data and visitor data, but no significant difference between between ethogram and visitor data. Black = ethogram data for corrected visitor data before and after questionnaires filled group of otters, red = ethogram data for otter 1, green = ethogram in by children were excluded from the dataset. There was data for otter 2, dark blue = ethogram data for otter 3, light no significant difference between visitors who had prior blue = corrected visitor data, and pink = uncorrected visitor data. experience volunteering, or were a member of a wildlife Cumulative proportion of variance explained by first 3 principal organisation and those who were not. All visitor datasets components = 0.995. were still significantly different to the ethogram dataset (Figures 7(a) and 7(b)). There were still significant differ- ences between ethogram and visitor data when playing and of collecting scientific data on birds may be more likely to swimming were combined in the activity budgets and when collect accurate data than a “fun time family” that is on a visitor data was reclassified taking into account time periods recreational trip, but this was not the case in this study. in which the data had been collected (Figures 7(c) and 7(d)). 4.2. Where Did They Go Wrong? 3.4. Simulation of Test Accuracy of Visitor Data Collection Methods. The average number of behaviours recorded by 4.2.1. Ignoring the Instructions. One of the most important visitors in the study was 2.9, whereas the average number instructions on the questionnaire was the length of time of behaviours recorded in the simulation running for 30 s required to observe the otters for. This length of time was 1.4. Changing the length of time that visitors took to was chosen because it was thought to be short enough record behaviours in the simulation indicated that visitors not to deter visitors from participating and would allow may have watched the otters for up to 8 min, instead of the recording data as and when visitors walked past the following the instructions and recording behaviour for 30 s. enclosure. Ease of data collection and reliability were both Comparing the overall behaviour of all three otters combined a key aspect of this study because visitors were assumed to be using bootstrapped PCA demonstrated that there was no untrained. Therefore, 30 s was considered to be a reasonable significant difference in overall behaviour when observations length of time for visitors to scan the otter enclosure and be took place for 30 s (from simulated data) and the real able to identify behaviours while imposing a time limit so ethogram data, but when compared with the longer 8 min that all visitors should spend approximately the same length observation period or the visitor collected data, significant of time recording data. Results of the simulation model of differences to the ethogram data occurred (Figure 8). visitors undertaking 30 s sampling periods when filling in questionnaires showed that this length of time should have resulted in the accurate representation of the otters’ activity 4. Discussion budgets. 4.1. Visitors Cannot Accurately Collect Behavioural Data. The Despite the instruction to watch for 30 s being underlined ethogram method used to determine otter activity budgets and in bold font, most visitors did not follow this and was repeatable between trained biologists, and this suggests recorded data for much longer than 30 s (pers. obs.). When that it is a reliable way of determining activity budgets. visitors stayed longer at the otter enclosure, they ticked However, visitors were unable to collect accurate data on significantly more behaviours. This is probably one of the the otters’ behaviour regardless of which visitor segment main reasons why their activity budgets were incorrect. In they were in, their age, prior experience volunteering or some cases, visitors admitted watching for longer. One visitor whether they were a member of a wildlife organisation. This ticked rolling and wrote “when arrived,” indicating that they did not differ when behaviours that overlapped (playing felt this was an interesting behaviour and that they should and swimming) were combined in the analysis, nor when record it, even though it was not in their 30 s recording much of the potential pseudoreplication caused by varying period. Another visitor wrote “the otters came out at 10.36,” numbers of visitors throughout the day was removed. It which also indicates that they watched for longer than 30 s may seem intuitive that an “expert birder” with experience but may have thought that adding extra detail would benefit International Journal of Zoology 9 in each age group” could not be analysed because visitors misunderstood the question. Most visitors wrote down the number of people in their party, regardless of whether or not they had helped fill in the questionnaire. The fact that visitors underrecorded sitting and time spent inside may be because these could be ignored if they appeared less interesting for visitors than more active behaviours. Sitting generally occurred for short periods of time (with otters pausing for a few seconds), in which case visitors could have missed this. The underrecording of time spent inside may have been caused by visitors missing otters inside if some of the otters were outside. If this was the case, visitors often observed the otters that were outside and did not check the sleeping chamber (pers. obs.). Another contributing factor could be that otters spent more time inside during quiet times when there were no visitors around to record this (early morning and late afternoon). Figure 6: Results of bootstrapped PCA examining differences The underrecording of playing is probably correlated with between ethogram data and different visitor segments. Black = the overrecording of swimming; it is likely that some ethogram data for group of otters, red = fun time families, green = visitors confused the two behaviours and ticked swimming sensualists, dark blue = social naturalists, light blue = expert birders, instead of playing when otters were playing in the water and pink = learn together families. No other visitor segments were (Figures 2(a) and 2(b)). Playing may have been difficult for included, since in total they contained <20 responses. Pairwise some visitors to interpret. Indeed, most “other” behaviours comparisons between social naturalists and sensualists also indi- that were reclassified in the corrected dataset were reclassified cated no significant differences occurred between these categories. as playing. However, removing mistakes and omissions and Cumulative proportion of variance explained by first 3 principal grouping behaviours did not change the overall results. This components = 0.997. suggests that misidentification of behaviours by visitors was not the prime reason for the differences between ethogram and visitor activity budgets. the study. At the end of one questionnaire that had been filled in by a parent and child (where all but one of the boxes had been ticked), the parent wrote, “hence saw all of 4.2.3. Item Nonresponse. Item nonresponse, in which a the above because watched for a long time.” Another visitor questionnaire is returned with one or more questions wrote that they “saw the otters outdoors earlier” so had unanswered, can have an impact on results of a survey filled their questionnaire in for a previous time (based on but these impacts are difficult to measure [37–39]. There their memory of what they saw the otters do) as well as the could be various reasons why some visitors left questions present (when the otters were indoors), thus confounding blank (Table 3). For example, the visitor who missed out their results. Some visitors demonstrated attention to detail the question asking for the time may not have been able to by adding detailed notes on their questionnaires. However, find out what the time was as they did fill in all of the other these details are often impossible to analyse unless they questions. Boredom or rushing to finish the questionnaire can be reclassified, and this process can be time consuming may have been reasons why 1.6% of visitors filled in the (pers. obs). It seems that attention to detail and enthusiasm, time and ticked behaviours but did not answer any other while generally considered key attributes for volunteering, questions that appeared later in the questionnaire [40]. It is can hinder the quality of behavioural data collected. also possible that some of the visitors who did not answer questions on the second page did not realise they were there, 4.2.2. Making Mistakes and Adding Extra Details. Occa- despite the staple and instruction “please turn over” in bold sionally, visitors admitted that they were wrong on their and underlined at the bottom of the first page: some visitors questionnaires, despite understanding the instructions. One only realised this when another visitor pointed it out to them visitor ticked rolling but wrote “in water” next to the box (pers. obs.). Another possibility is that visitors may not have despite the fact that the behaviour was entitled “rolling— wanted to fill in the questionnaire but felt obliged to do so e.g. on soil or rocks”, another ticked sitting but specified out of politeness and as a result, may have rushed through that the otters were indoors. However, only the obvious the questions, missing some out. mistakes could be removed from the corrected dataset, and This lack of attention to detail could be caused by the fact it is highly likely that some mistakes remained undetected that the questionnaire was impromptu: visitors were on a day (i.e., if visitors wrongly interpreted behaviours or deliberately out not expecting to have to concentrate on a task. They may ticked boxes even though they had not seen a particular also have been distracted by the surrounding environment behaviour). It was impossible to measure this. Furthermore, (e.g., by their children or by other visitors). Slightly more the question “What age are you/the people who helped fill visitors avoided answering the question about volunteering in this questionnaire? Write down the number of people than the question about being a member of a wildlife 10 International Journal of Zoology (a) (b) (c) (d) Figure 7: (a) Results of bootstrapped PCA examining differences between ethogram data, corrected visitor data, and uncorrected visitor data when all questionnaires filled in by children were removed from the dataset. Black = ethogram data for group of otters, red = children’s questionnaires removed from corrected visitor data, and green = corrected visitor data. Cumulative proportion of variance explained by first 3 principal components >0.999. (b) As above but examining visitor segments. Black = ethogram data for group of otters, red = corrected visitor data, green = visitors who had previous experience volunteering, dark blue = visitors who did not have prior experience volunteering, light blue = visitors who were members of a wildlife organisation, and pink = visitors who were not members of a wildlife organisation. Cumulative proportion of variance explained by first 3 principal components = 0.995. (c) As above but examining ethogram data for group of otters and corrected visitor data when playing and swimming were combined. Black = ethogram data for group of otters and red = corrected visitor data. Cumulative proportion of variance explained by first 3 principal components >0.999. (d) As above but examining ethogram data and visitor data with standardised time periods. Black = ethogram data for group of otters and red = corrected visitor data. Cumulative proportion of variance explained by first 3 principal components = 0.987. organisation or charity (Table 3). This may be because the they could not participate. In a zoo environment, it would membership question can be more easily interpreted, as be very difficult to fully control the spread of questionnaires membership to the WWT is well advertised throughout over time because of the irregular flow of visitors, not only the centre and 57% of all visitors to the centre during the at different times of day (e.g., when the centre first opens or study were members of WWT. The volunteering question when visitors are hurrying to leave before the closing time), may confuse those who are unfamiliar with the idea of but also in adverse weather conditions when visitors would volunteering; one visitor said that she considered visiting the be less likely to want to fill in a questionnaire. Additionally, centre as volunteering (pers. comm.). there were often more visitors at the enclosure when the otters were active, with large crowds often attracting passers by because the formation of a crowd could indicate that the 4.2.4. Temporal Autocorrelation of the Data. Questionnaires otters were doing something interesting or unusual (pers. were handed to visitors as and when they arrived at the obs.). In this study, the averaging of data over 30 min periods otter enclosure. As such, it is highly likely that some of the helped reduce autocorrelation effects due to the effects otters’ behaviours were simultaneously recorded by many mentioned previously, but would not completely eliminate visitors, especially at busy times such as during the feeding them if there was a difference in recorder effort within a 30 min period. demonstrations. While it would have been possible to hand out only one questionnaire at a time, such an approach However, the effects of temporal autocorrelation on the would reduce the uptake of the questionnaire, and also would results of this study appear minimal. Firstly, “standardised” have a negative influence on visitor experience, with visitors data (where an average activity budget was calculated over either waiting a long time to participate or feeling left out if each 30 min period taking into account the number of International Journal of Zoology 11 Uptake rate maybelesshighwhenanimalsare outof view or in an indoor area. As discussed previously, otters were less popular with visitors when they were inside, visitors walked past and/or did not see the point of filling in the questionnaire until it was explained that it was important to find out how much time the otters were spending inside. This has been discussed in previous studies. Indeed, Altman [45]and Anderson et al.[24] found that zoo visitors paid more attention to an animal’s behaviour when the animals were most active compared to when theywerelessactiveor inactive. Jackson [46] and Johnston [47] found that visitors spent less time in front of enclosures where animals were inactive. Additionally, mammals are the most popular class in zoos [48], and larger animals may be preferred by visitors over smaller animals [49]. It is possible that a behavioural study would not prove as popular with visitors if it involved less appealing classes or species. Indeed, Hoff and Maple [50] found that some visitors deliberately avoided going to reptile Figure 8: Results of bootstrapped PCA examining differences exhibits. between real data and simulated data. Black = real visitor data, red = real ethogram data, green = simulated visitor data where data were collected for 8 min, and blue = simulated visitor data where data were collected for 30 s. Cumulative proportion of variance explained by first 3 principal components = 99.8. 4.4. Recommendations for Further Study. A visitor who had completed the questionnaire made the following comment: “you could tell us more about the otters than we could tell you”. This statement underlies the concept of volunteer data collection: a scientist’s work can be more reliable than that of questionnaires answered) and “unstandardised” data both a volunteer, as was the case in this study. However, it is the differed significantly from ethogram data. Secondly, when large number of volunteers that can make them a powerful data were simulated (and autocorrelation effects were elimi- tool for research. Although the method in this study did nated) results corresponding to visitors collecting data for a not allow visitors to collect accurate activity budgets, it did long period of time (8 min) were highly significantly different have some success. The high uptake rate suggests that getting from ethogram recordings. Hence, it appears that it was visitors to collect data on active and entertaining animals the length of time in which visitors recorded behaviour can be successful. Public engagement and distributing the that was the largest source of error, rather than potential questionnaires by hand also undoubtedly had a major errors inherent to the sampling design used. Nevertheless, influence on the uptake rate. methods to eliminate temporal autocorrelation and enhance Several improvements could be made in future research. the visitor experience are given in the Recommendations When asking volunteers to collect behavioural data, it is Section. important that behaviours are simple enough that volunteers can distinguish them without confusion. Clear instructions 4.3. A Success: The High Questionnaire Uptake Rate. The are needed when designing questionnaires, but in situations questionnaire uptake rate may not have been so high if where a time limit is necessary, it is important to try to the questionnaires had not been handed out in person facilitate this to ensure that methods are followed as closely [41]. Indeed, very few visitors were observed picking up a as possible, perhaps by providing a large clock in front of the questionnaire themselves when the questionnaires were laid enclosure. A time limit could also be imposed with the use of out on a wall next to the otter enclosure, despite posters technology, for example, through multimedia or interactive advertising the study. In this situation, children were more video screens, which have previously been used in zoos and curious than adults, often picking up questionnaires and aquaria to convey information to visitors [51–53]. This type filling them in of their own accord. Curiosity is a strong of technology has also been used by the National Marine motivational force in children [42–44] and it is often believed Aquarium in Plymouth, UK to allow visitors to collect data that curiosity decreases with age [44], which may explain on fish in an exhibit (pers. obs). Visitors could also collect why fewer adults picked questionnaires up. Distributing data with the use of smart phone technology as this has questionnaires in the manner described in this study could already been used for other types of volunteer data collection cause logistical problems for zoos (for financial and temporal [54]. Technology such as this may also reduce the number reasons discussed in Section 1). However, it may be possible of questions that are unanswered by imposing a response, that handing questionnaires upon entry to the park along or could be used to eliminate any temporal autocorrelation with a quick explanation or instruction leaflet could be of responses by either only having a single display, or by a suitable method to increase participation, similar to the accurately recording the time of the response, so replication method described in Dillman [41]. in time can be removed. 12 International Journal of Zoology Overall, many of the aims of volunteering were com- [9] C. Kremen, K. S. Ullman, and R. W. Thorp, “Evaluating the quality of citizen-scientist data on pollinator communities,” pleted in this study as visitors were keen to participate, Conservation Biology, vol. 25, no. 3, pp. 607–617, 2011. enjoyed observing the otters, gave positive feedback, and [10] W. R. T. Darwall and N. K. Dulvy, “An evaluation of the asked questions about the study. 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