Would you be willing to talk about your experience as part of a Skype or phone interview? At the UCL Interaction Centre, Dr Charlene Jennett and Zoya Ajani are hoping to understand more about the experiences of Bat Detective volunteers – how did you find out about the project and what motivates you to take part? By understanding your experience at Bat Detective, Charlene and Zoya are hoping to gain valuable insights into ways to improve online citizen science projects in the future.
This work is being conducted as part of the Citizen Cyberlab project, a three-year EU project that aims to study and enhance the opportunities for learning and creativity available to participants in online citizen science projects.
Interviews are between 30 mins to 1 hour, and participants will be rewarded with an Amazon gift voucher. If you think you would like to be interviewed, please email Charlene for more information.
By Kate E. Jones and Kim Mroz
The Bat Detective project has passed its one-month anniversary! Since the launch, everyone who’s gotten involved has been fantastic. We’ve also had quite a lot of press coverage including that on the BBC News website; interviews on BBC Radio 4’s Material World Programme, Irish Radio, BBC World News; and a podcast for The Guardian.
Since our launch (up until Halloween), we’ve had 671 of you register with the site to explore the data our iBats volunteers recorded from Bulgaria. In total you helped us look at 18,729 snapshots and you provided 73,421 classifications – amazing! You found 12,653 bat calls in our Bulgarian data and also 22,275 insect calls and 23,003 machine sounds. We expected that a lot of the bat calls found would those ‘searching’ calls made when a bat is navigating around, and that is indeed the case (8,821 calls or 70% of the total). However the rest of them were classified as feeding calls (1,591) and a really impressive 2,239 calls were social. This is really exciting as comparatively little is known about social calls and this is first time that they have been recorded over such a large area.
We have been really amazed by how much support you have given us and many of you have done thousands of classifications each, for example one person provided over 9,000 classifications! On Halloween we released the Romanian data which of course includes those recordings made in Transylvania (home of Bram Stoker’s Dracula)! Despite what you may have heard about the legend of Dracula, you will not hear any vampire bats (bats that feed on blood) in the recordings. In fact there are only 3 species of ‘vampire’ bats out of over 1200 bat species in total with only one species known to associated with humans and they all live in South America. However, some exciting species that you might hear in the recordings include the Schreiber’s bent-wing bat (Miniopterus schreibersii), which is one of most threatened species in Europe and the European free-tailed bat (Tadarida teniotis) which might possibly be one of the smelliest!
A huge thank you for those of you that agreed to become moderators on the Bat Detective talk and helped field all the questions! There is a constant demand for more information, and you have given us lots of useful feedback about the site. We’ve noticed particular questions about the recordings (and the bats within them) keep cropping up and we have answered some of the most commonly asked questions below, which we would be happy to hear your thoughts about! That’s it for now, watch out for the Transylvanian report coming in a few weeks!
- How can we hear the high frequencies?
Rob covered in his blog how the volunteers used ultrasound microphones to record the sounds beyond our hearing. These are then played back at a much slower speed to be recorded to the hard-drive, which is what we’re classifying here on BatDetective.org… So 0.3 seconds of sound beyond our feeble hearing becomes 3 seconds of audible calls!
- Why can I hear frogs, birds and tigers, but no button to tag them?
The recordings were all made across Europe shortly after sunset, and have been time-expanded (see FAQ #1). This means that it’s very unlikely you’re actually hearing tigers or birds, and if you were then they wouldn’t sound like you’d expect! Instead, we have chirpy bats and roaring insects, whose calls have been lowered in pitch and lengthened in time. So if you hear a noise that sounds familiar, you have to think about whether it would sound as familiar if it was 10 times higher and quicker!
- More examples? I’m not seeing many bats!
The examples we’ve included in the field guide are particularly loud, clean sounds to help with your classifications. However, there isn’t enough room to include all variations of bat, insect and machine sounds! It could be that you’re over-looking the different, slightly obscured or quiet calls … you might like to check out the collections that users have made for more (possibly noisier) examples of interesting sounds!
- Is this a bat or an insect?
There are certain insects sounds (see Fig. 1) that masquerade as bat feeding calls (scroll down in the link) in the spectrograms, and there’s a general rule to help with these. Does the sound have a clicky or a chirpy quality? If it’s a clicky sound, then this is almost certainly an insect!
- If you’re only interested in bats, should I bother with labelling insects and machine sounds?
Yes, please! We’re hoping to branch out into insects too; it would be a shame to waste all of this fantastic data. On the other hand, flagging machine noise can help tremendously with data quality control.
- What happens if I realise I’ve made mistakes? No back button?!
It’s okay! Don’t worry! We obviously appreciate the care you’re taking with the tagging, but if you happen to miss something or you later disagree with your own tag then in the long-run it shouldn’t matter. Hopefully other users will spot these things too and everyone’s opinion will balance out to good classifications!
- What should I do with harmonics?
Most naturally-made sound will contain more than one harmonic. Bat calls and insect sounds are no different!
Sometimes these harmonics are very quiet, and may not even reach the microphone at all (see Tim’s blog) but if there is a nice distinct harmonic (e.g., Fig. 2) then there’s no harm in marking it. Feel free to make a separate frequency range to let us know about harmonics.
- What are these odd un-cut recordings?
Rob’s blog discusses how the processing of an evening’s recordings is meant to work, but sometimes our automated methods break down. Instead of only getting lovely 3 second snippets, there are also a few crazy recordings floating around … you can see some examples here! Don’t worry about these; just ask for another sound (sorry!).
- Audio doesn’t work … help?
The site currently relies on Flash to play the audio recordings. If you’re having problems while using a major browser (e.g., Firefox, IE, Chrome) you may need to update your browser or Flash install to use the latest version. If you’re still having problems, then please let us know on the Help boards.
- I’m not sure about something, what should I do?
Ask us! If you have a general topic in mind, you can start a discussion on the Science, Chat or Help boards or see if someone else beat you to it. If a particular sound has you stumped then Talk about it! The science team, moderators and other users may be just as stumped as you, but (hopefully) they might just have an answer!
We’re very appreciative of all of the feedback you’ve provided, which mostly concerns the mechanics of the Bat Detective site. We’re now at the stage of having a think on what changes we can make to allow you all to help us more easily.
- Improve the tutorial and guide terminology … and the tutorial itself!
The tutorial is at the top of our list of improvements. Hopefully a dedicated page containing a tutorial video, call guide and site-guide will make it easier for new and old users alike to find answers to their questions, and feel more confident while helping Bat Detective. Watch this space!
- Add frequency scales on talk images.
This is also something that we’re very keen to add ourselves. Discussing recordings in Talk will certainly be a lot easier with some reference to frequencies!
- Confirmation button after selecting ‘Next Sound’.
Several users have noted how other Zooniverse projects (e.g., MoonZoo) have some form of confirmation request when the ‘Next Sound’ button is hit while classifying. This would prevent slightly over-enthusiastic clicking leading to missed recordings, and is definitely something that’s possible.
- ‘Did you spot this?’ sounds.
So you can check how well you’re spotting the bats and insects, it has been suggested that every now and then we could give you an already classified sound to look at, and then point out the calls to see if we agree. Another great idea that we can filch (thanks Planet Hunters)!
By Tim Lucas
Knowing whether bat populations are growing or shrinking tells us about the health of the bat population (see Dr Kate Barlow’s blog). It also gives us information about the health of the ecosystem in general, as discussed by Dr Robin Freeman. However, these are relative measures; are there more bats this year than last year? Sometimes we want to know an actual number. Are there a thousand bats? Ten thousand? A million?
For example, if we are trying to conserve a rare bat species we need to estimate the actual number of bats. At very low population sizes inbreeding starts to become a significant problem for conservation. Ten percent fewer bats than last year could mean a decrease from 100,000 bats to 90,000 bats or it could mean a decrease from 1,000 to 900 bats. While both situations are worrying, only in the later case do we need to start considering genetic inbreeding.
So how do we estimate the size of a bat population from our acoustic surveys? This is not a simple problem. If I go out with my bat detector and count 200 bats, what does this mean? Maybe I actually detected every single bat making the population size only 200. Maybe I detected one percent of all bats making the population size 20,000.
In essence the problem is to work out how many bats you expect to detect per hour of surveying. This depends on a number of factors. The flight speed of a species is important. You are more likely to come into contact with bats that fly quickly. If you sit by a motorway you will see more cars than if you sat by a country lane even if the total number of cars is the same on each road.
Secondly the actual area of land that you are surveying is clearly important and this depends on the distance within which you can detect a bat. Louder bats can be detected from further away, just as larger animals can be seen from further away. This means you are surveying a larger area if you are looking for loud species than if you were looking for quiet species.
The frequency of the bat call also matters as high frequency sounds travel less far than low frequency sounds.
As an example, the spectrogram shown has a loud ‘hockey stick’ call at about 25kHz but also a quieter harmonic above it, at about 60 kHz. Even without considering through use of seo services that the harmonic is quieter (it is less bright on the spectrogram) it will travel about half the distance of the lower frequency call. The maths to work out these distances is long and boring so I hope you don’t mind me not showing my working!
So, if we can make a good guess of how large an area we are actually surveying we can work out what proportion of the bat population we saw. Did we survey 1% of land in Europe, or 0.001% and so did we see 1% of the bat population, or 0.001%. Using this information and information about how fast bats fly we can try to work out how many bats there are in total and use this information to conserve them as best we can.
As you know, we have a huge number of audio snippets and we want to know what’s in them! We would certainly never be able to find the bats all by ourselves — There are just that many recordings.
This is where the Bat Detective project steps in. We’re really hoping that citizen scientists will help us to locate and identify bat tweets and insect clicks that have been captured across the globe by the lovely volunteers.
Once we gather your votes on the contents of a snippet, this will highlight the recordings of interest and provide us with labels. On top of hunting for the bats, your labelled sequences of searching, feeding and social tweets will also allow us to analyse the different sounds.
As the number of your identifications grows, the more information we will have; it doesn’t even matter if a recording is given a range of different labels! By pointing out the controversial sounds, we can gain an insight into the calls that are hard to distinguish.
If the majority of your votes on a snippet’s contents agree, then this recording can be compared to other snippets that have been similarly labelled. By finding the features they have in common, and what sets them apart from other sounds, we can begin to automate our quest for interesting sounds.
To help us decide on useful identifying features as an seo company for bats, which could be wildly obvious or devilishly subtle, we can use machine learning. This involves designing a computer program that we can hand our snippets and your voted labels to, for it to then return different ways the sounds can be grouped together. Analysing these resulting clusters will then pave the way for automatically detecting the different bat tweets (and insect buzzes) within any number of snippets!