All of our past newsletters are archived here. We're aware that some of the links within them don't work in the archived versions and we're working to correct that. If you haven't yet subscribed to our monthly newsletters, you can do so here.
All of our past newsletters are archived here. We're aware that some of the links within them don't work in the archived versions and we're working to correct that. If you haven't yet subscribed to our monthly newsletters, you can do so here.
Thanks to everyone who contributed classifications over the past two weeks in pursuit of the prize-winning Easter photographs. Altogether, you submitted nearly 22,000 classifications in just 2 weeks - by far the most rapid rate of classification in the project's history! Congratulations to our prize-winners: Beth Smith, Reece Fowler and Julia Wilkinson. Each of them will receive a fabulous new Browning Command Ops Pro camera trap, courtesy of the generous support of NatureSpy! Thanks, also, to everyone else who contributed classifications. We hope you've enjoyed participating in the project. Please do carry on; every classification helps us to make sense of the data and to understand - as the project grows - how we can have confidence in what is being spotted in different parts of the country. Watch this news page for more initiatives coming soon ...
The Spotter homepage tells you how many image sequences you've classified. Some of you have noticed that it's rather slow to update after you've been spotting. Don't worry: the system is registering your efforts. However, last week, we had some site performance issues and we reduced the frequency with which statistics were updated (to once per day). We think we've identified the problem, so we'll be starting slowly to restore the frequency of calculations again. In the meantime, sorry for the frustration - but check back the following day to make sure that your statistics have all updated.
In March, we reached a major milestone. Specifically, for the first time since the MammalWeb UK project began, we reached a point at which every image sequence submitted to the MammalWeb UK project had been classified at least once! This is a great achievement and we’d like to thank everyone who has contributed classifications, as well as Helen, whose tireless work on the web platform has made Spotting such an effortless (and, we think, addictive) process!
Although MammalWeb UK is now just one of the projects on the site, it remains the project to which most people contribute data. At the point when all sequences had been classified at least once, it included almost 80,000 sequences from over 300 sites. As you can see from the detailed map (in which the MammalWeb UK sites are shown in red, overlying blue sites from other projects), survey efforts remain dominated by sites in the North East of England, where the project began. Zooming out to the UK map, however, you can see that MammalWeb UK is continuing to expand. If you are, or know, a camera trapper elsewhere in the country, please do upload your camera trap photos/encourage others to do so. This way we can continue to expand our coverage, and consequently learn more about mammal ecology across the UK.
At the point at which all image sequences had been classified at least once, the data suggest that about 62% of the sequences contained identifiable animal life. So, what do they contain? As you can see from the graph on the left below, the most frequently sighted animal is the grey squirrel which, as many of you will know, is an invasive non-native species. Nevertheless, there are a number of native species that appear frequently, including roe deer in about 1 in every 12 sequences you view, and badger or red fox in about 1 in 18 sequences. Bear in mind that these statistics are based on what species people have said are in sequences. As we get more classifications per sequence and more conviction regarding what is pictured, this could change.
A more intriguing picture arises when we consider the number of sites at which different species have been photographed (see graph on the right below). This suggests that roe deer and red fox are actually more geographically widespread in our data than are grey squirrels. This probably arises because they are more wide-ranging: when grey squirrels are active around a camera, they are usually very busy, generating lots of image sequences; roe deer and red foxes turn up at more cameras – but don’t linger by the camera for so long.
As contributors are increasingly trapping in other parts of the country, these patterns will almost certainly change. We have recently seen muntjac in the data set from a site in Worcestershire, as well as fallow deer from a site in South Wales. Who knows what other species we might see as the project continues to expand?
Probably our most requested feature is the ability for Spotters to zoom in to images to take a closer look. We're really excited to report that the ever-brilliant Helen at Rhombus Technology has just implemented that feature! When you're spotting, look out for the 'full screen tool' in the bottom right of the image display (where the red arrow is pointing in this picture).
We note that some versions of iOS and Safari don't have the full screen capability. In those cases, the tool should not display. You should, however, be able to zoom manually.
Another change in this release is that, on the projects page, you now click on the photo representing any project to find out more about that project and its subprojects. And, of course, in case you'd missed it, you can also navigate to any project of interest via the project pages and click "Classify this project", in order to specify exactly the collection of photos you wish to classify.
Last summer many of you helped classify photos in the Highland Red Squirrel Project. The project focussed on the understanding of, and potential mitigation for, forest operations on red squirrels, and was run by a team based at the University of the Highlands and Islands in collaboration with Forest Enterprise Scotland. With your help, all images in the project were classified, and now the team have had chance to analyse the data, they would like to share with you the results! Click here to read the report.
One of our trappers, Roland, has written a report about his findings from camera trapping in his local woods over the past two years. In the report, he writes about the species that have been captured on his camera traps, which he has put out at 62 different locations in the Deerness woods, County Durham. This includes camera traps that he modified to be used to photograph small mammals, which you can read more about on our "Projects" page, under the "Small Mammal Camera Trapping" project. We'd like to say thank you to Roland for sharing this great report with us, and providing MammalWeb with many lovely photos, such as the ones below, to classify over the last few years! You can read the report by clicking here.
There are six species of deer in the UK: roe deer, red deer, fallow deer, Reeve's Muntjac deer, sika deer and chinese water deer. In County Durham, by far the most common deer species we capture on our camera traps is the roe deer. However, as MammalWeb starts to collect images from new camera trap sites across the country, you may come across some different deer species whilst spotting. Telling the difference between deer species can sometimes be tricky, so we've summarised some key facts for all six species in the graphic below.
When classifying camera trap photos here are some key things you can look for to help you decide which deer species it is.
If you would like more information on deer species in the UK, and the differences between them, here are some links to some great resources:
The Mammal Society's "Discover mammals" page: https://www.mammal.org.uk/species-hub/full-species-hub/discover-mammals/
The British Deer Society's "Deer Species" page: https://www.bds.org.uk/index.php/advice-education/species
NatureSpy's article on "What are the different British deer species?", which includes some lovely camera trap footage: https://www.naturespy.org/2016/07/what-are-the-different-british-deer-species/
Congratulations to Justine Thompson, who found the final seasonally-adjusted MammalWeb picture! This means that all three pictures have now been found, so congratulations to all our prize-winners: Elliot Tebbs, Clive Moulding and Justine Thompson. Their prizes will soon be in the mail!
More generally, thanks to everyone who has contributed massively to Spotting over recent weeks. Over the last month, a fantastic 12,000 sequences have been classified for the MammalWeb UK project! For the first time ever, we are now teasingly-close to having all MammalWeb sequences classified at least once. That's a huge achievement. Keep an eye on the project page to watch our progress towards that goal. You will also see that NatureSpy have uploaded a new batch of images from their cameras in the North York Moors. Their baited traps have yielded some beautiful pictures already, with red foxes a common visitor; what else might be in there?
We're pleased to report that two of the three modified photos have now been found. One was found on the evening of the 2nd of January, whilst another was found this morning. How long will it be before the third is tracked down? Keep spotting, and let's hope it turns up before the 12 days of Christmas are over! Two camera traps will soon be on their way to the lucky winners so far. Could you be the recipient of the third?
As we approach the end of 2018, we wanted to say a huge THANK YOU to everyone who has contributed to MammalWeb over the past year! It has been a tremendous year for Mammal monitoring in the north east of England – and increasingly further afield.
At the start of this year, 70 Trappers had deployed cameras at 227 sites, uploading 55,192 sequences, for which 257 Spotters had submitted 92,972 sequence-classifications (representing 40,374 unique sequences, or 73% of the sequences in the system).
As of today, 97 Trappers have now deployed cameras at 430 sites, uploading 122,742 sequences, for which 473 Spotters have submitted 208,229 sequence-classifications (representing 110,139 unique sequences, or 90% of the sequences in the system). This is tremendous growth in our efforts to find out more about where our wild mammals occur, what they do and what affects that. Next year promises to be much bigger!
This year has also seen the publication of our first paper, led by Pen, discussing how we can be confident about what species are pictured in the sequences you trap. This was a collective effort by everyone who has contributed to MammalWeb – so well done to all of you! Another major achievement was Sammy’s rigorous survey of the whole of County Durham. Thanks to everyone who made a huge effort to get so many of the images from that survey classified in such a short space of time! Thanks to you, Sammy was able to present her preliminary results at the recent meeting of the British Ecological Society. You can expect to hear more about that study over the coming year. We have also welcomed two new people – Sian Green and Jonathan Rees – to the MammalWeb team, as well as multiple new collaborating organisations, and you can expect to hear more about their work over coming months.
We look forward to a very exciting 2019. There are some great developments in the pipeline, and you can expect to see some fabulous site improvements very soon …
For every classification you do on the County Durham Survey project between Mon 12/11/2018 17:00 and Mon 26/11/2018 17:00, you’ll get one ‘ticket’ in a prize draw to win either a £100 Amazon voucher, or one of two £50 Amazon vouchers! The more classifications you do during this time, the more chance you’ll have to win a prize!
You can read more information about the project over on our Projects page. To start classifying, simply log in as a MammalWeb spotter, and select "County Durham Survey" from the dropdown "Select a project box".
We've got a diverse array of new spotting opportunities for you to enjoy! Should be something for everyone - so thanks in advance for anything you can do to help uncover what's out there! Here are our new spotting opportunities:
1). PhD student Sammy has started to upload her daunting (half a million!) set of pics from this summer's survey of County Durham. You can read more about the project on the Projects page. To help classify the photos select 'County Durham Survey' from the dropdown box when spotting.
2). For something truly different, check out long-term MammalWeb contributor Roland's new project. How well do you know the small mammals of Britain? Time to find out! Read more about the project on our Projects page, and select 'Small Mammal Camera Trapping' when spotting to help classify some images!
Over recent months, we've had several news articles about new projects available via the MammalWeb site. With huge thanks to Helen, who's been developing them, the project listings pages are now available.
If you click on "More" under any project, you will find a short description of each project and an indication of progress with uploading and classifying its image sequences. The summary charts draw on what is becoming a very large data base and, as a result, they currently take a little while to appear. Those will be optimised in due course to speed them up. We also plan to make it possible to link straight through to classifying sequences for any specific project. Private projects are not listed on these pages but some projects that are currently private will soon be made available for public viewing.
Summary charts for a project are based on submitted classifications (rather than on strictly validated data) but should, in any case, give a reasonable sense of the relative numbers of image sequences in which different species appear. They certainly suggest striking differences between the species most commonly photographed in a range of settings (including predominantly urban, entirely rural, arboreal, or with the assistance of baiting).
Notice that the "progress bars" (as depicted in the image above) identify the proportion of image sequences that have been classified at least once. In reality, we often need more than one classification to develop a reasonable sense of what's in a sequence (see further here). Consequently, if the progress bar suggests that 100% of the project's sequences have been classified but pictures are still available for you to classify, please keep spotting!
I would say, "We've all done it!" - but it's probably mostly just me. Yes, once again I'm howling in anguish because I forgot that my camera trap uses a US time format (MM-DD-YYYY), rather than the more familiar (to me at least) DD-MM-YYYY format. That means that photos from a camera trap I put out in early July, are all proudly stamped with the claim that they were taken at various times after the 7th of May! If I was cataloguing and analysing my own camera trap photos, I'd have work-arounds for this error. However, because MammalWeb takes information directly from the image EXIF data (Exchangeable image file format data, for those of you who care), I can't upload the images until I've sorted out the dodgy "Photo taken" dates and times. This problem has been hanging over me for a while but, today, I decided to look into a solution. Happily, I found one!
The software allows you to choose the source folder containing the files you want to correct, as well as the output folder in which you want to store the corrected files. That's particularly useful if - like me - it takes you a while to work out the difference between two dates (so you don't want to overwrite the originals until you've checked that you're correct). There are a variety of options for changing the dates and times - but the most straightforward is just to set the numbers of days, hours, minutes and seconds by which you were out when you set the camera. One thing to check is the "options" tab, which might suggest renaming the images. You can easily change that, if you'd prefer that it left the names unchanged. Of course, if you have a camera trap that puts the date and time on each photo, that will still be in error - but at least the dates and times recorded in the database will be correct!
Well, I'm pleased to have found this simple solution - and I hope that some of you find it useful too.
Many of you will have been pleased to see the news, a couple of weeks ago, that pine marten appear to be spreading into Northumberland (e.g., see this article in The Guardian). The recovery of pine marten in England is an exciting development for nature enthusiasts, and could help to alleviate pressure on our native red squirrels.
We're really excited to announce a new partnership with NatureSpy, a non-profit organisation that - like MammalWeb - aims to engage people with the wildlife around them, and to research and conserve wildlife and habitats through study and monitoring. NatureSpy run a variety of projects and, at present, they are organising an intensive, 3-year project to study pine marten in the North York Moors. With the aid of volunteers, they are currently rotating camera traps around a variety of sites in the North York Moors, and a proportion of those traps are set to record still images. The traps yield large numbers of images and those will help to inform NatureSpy about the ecology of the area, aiding the development of a long-term conservation plan for pine marten in the area. If we're lucky, we might even see a picture or two of a pine marten!
If you are registered as a Spotter, the NatureSpy images will be available to classify by selecting "Classify All" from your Spotter home screen. To focus your efforts on helping the NatureSpy team, you can select "NatureSpy - North York Moors" and choose "Classify Selected Project Only".
You can also read a post about this project on the NatureSpy blog, here.
Much of the monitoring conducted by NatureSpy (as well as many other individuals and organisations) uses video, rather than still images. We know that a capacity to handle video (rather than just image sequences) is an aspect of the platform that many of you would like to see us develop. Over coming months, we will be looking for ways to resource this (both the development and the subsequent hosting of large video files); we'll keep you posted regarding progress!
We (the project team, plus all of our participating volunteers) have published our first paper based on MammalWeb! The paper is in the journal Remote Sensing in Ecology and Conservation, and can be found here. When we think of Remote Sensing, we often think of satellite observations (a source of data that can be remarkably handy for ecologists, as well as many land managers, plus other scientists and social scientists). However, Remote Sensing can cover many types of data collection for which the presence of people is not necessary at the time of data acquisition. Camera trapping is, thus, a good example of a remote sensing approach.
A pre-requisite for making use of the data collected by all of MammalWeb's participants is knowing what's in the images. By comparing user-submitted classifications to a set of over 10,000 image sequences that have been looked at by "experts" to determine their subjects, we can learn about how confident we can be about those classifications. Happily, it turns out that participants are very good at identifying what's in an image sequence. We need lots of examples to get a good idea of how accurate participants usually are, so we focused on 16 of the most commonly-occurring species (or species designations). When those species occurred in a sequence, we looked at all the submitted classifications and asked how many of them correctly said that the species was pictured. For almost all of the commonly-occurring species, that figure was 80% or more. For several species, it was closer to 95%! Given the risk, with all trail cameras, of getting blurry, dark, partial, or otherwise indistinct images, we think this is a real testament to the skill and dedication of those using the website!
Fig. 1. In general, spotters show high levels of accuracy.
Two "species" for which accuracy is notably lower are small rodents and brown hares. Further analyses looking at the inaccurate classifications in those cases show that they arise for different reasons. In particular, small rodents are often overlooked altogether, because they are often visible only from their eye-shine. We hope that our site developments (especially the new approach to being able to move backwards and forwards through a sequence, which can help to identify any sort of movement) will reduce this problem. By contrast, brown hares show lower accuracy than most other species because they are often misidentified as rabbits. This is understandable, given their many similarities. However, we would encourage anyone who is uncertain to take a look at web tutorials, such as this page or this one.
Fig. 2. Reasons for incorrect classifications by species or species group. Where blue predominates, the species is more often missed than misclassified; green indicates the proportion of errors that arise from misclassification.
Clearly, based on these numbers alone, we can be much more confident of classifications regarding some species than others. This might mean that we could remove many image sequences, allowing users to focus on the less distinct, the more unusual, or those that prove harder to reach consensus about. However, that might result in a far less rewarding time for Spotters. At present, we are keeping a close eye on techniques for automatic image analysis. These might, at the very least, allow us to remove sequences very likely to contain no wildlife, which - based on comments received - would probably be very popular with many of our contributors!
Toby Atkinson-Coyle recently graduated from the biology department at Durham University: congratulations Toby! For his final year project, Toby worked with the MammalWeb team on a camera trapping project looking at the impact of urbanisation on mammals in Durham. Here, he writes about some of the findings from his project:
For my masters’ project, I used distance sampling with camera traps to assess the impact of urbanisation on mammals in Durham, UK. As discussed in previous posts, this method involves measuring the distance of animals from the camera which can then be used to calculate their density. I deployed cameras in both rural and urban habitats across a 3x4km area of Durham from 12th February through to 9th March 2018.
Over the study period, a total of 2,646 images of wild mammals were obtained, 1,285 in rural and 1,361 in urban habitats (see Figure 1). Six species were regularly detected in both habitats, including European rabbit, European badger, red fox, grey squirrel, roe deer and small rodents. European rabbit and grey squirrel were the most frequently photographed species, so I report on them in greater detail. To assess the overall impact of urbanisation on mammals, I was also able to calculate broader community-level metrics such as species richness.
Figure 1 A subset of mammals photographed in Durham, UK.
Species varied in density between habitats. Four out of the six detected mammal species decreased from rural to urban habitats whilst two increased. The largest differences in density were in rabbit and grey squirrel populations. Rabbit density in urban habitats was twice that in rural ones (see Figure 2A). Conversely, squirrel density was much greater in rural habitats (see Figure 2B).
Figure 2 Estimated density per km2 of European rabbit and grey squirrel populations in rural and urban habitats.
I calculated species richness per deployment by counting the number of different species detected by each camera. Species richness was higher in rural habitats with an average of 1.60 (0.29 SE) species detected per deployment whilst in urban only 1.12 (0.23 SE) species were detected (see Figure 3).
Figure 3 Species richness per deployment of mammals in rural and urban habitats.
Urbanisation has a range of impacts on mammals at both the species and community levels. Broader ecological metrics indicate an overall decline of mammals with urbanisation but, at the species level, some appeared to benefit. Therefore, it is important to consider a range of species and community-level metrics when assessing the response of wildlife to disturbance.
Many of you have asked us to increase the range of species that you can choose from when spotting. We will soon be implementing changes to give this much greater flexibility, without forcing you to wade through long species lists each time you classify what’s in an image sequence. Specifically, when you are spotting, you should soon see something like the screenshot below. At the top will be 3 or more “filters”, which will allow you to navigate rapidly between lists of common species, and full lists of either mammals or birds. In some cases, there might also be a list of species that are most likely to turn up among images associated with the project you are Spotting. For the vast majority of image sequences you look at, the pictured species will be in the “Common” list (which will usually be the default display). If you are lucky, however, sometimes you might see an unusual species. In those cases, you can click on the “Mammals” or “Birds” filters to find what you are looking for. Those lists are arranged alphabetically and you can use the page selectors to jump to a different page of the list. Bear in mind that it might take a little while before you find those rarer species in the lists. For example, if you are looking for a mink under “M”, you might need to check whether we have discriminated between mink species (in which case, the American mink will be under “A”). For some species, we have also retained less certain designations for when you know what sort of animal it is but you can’t identify it to species-level. For example, you can find “Unidentified bird” under “U” in the birds list, and "Small rodent (unknown species)" under “S” in the mammals list. If possible, however, do identify to species level.
Some of you might have noticed that there are new projects available to classify. Specifically, at present, we have the “Highland Red Squirrel Project” and the “North Pennines NNRs” projects visible under the “Classify Selected Project Only” menu.
The North Pennines NNRs project has yet to upload data; we will tell you more about that project when images have been uploaded. However, the Highland Red Squirrel Project has uploaded data. In case you fancy helping out with their project, here’s a quick overview of what they’re up to and why.
Red squirrels are charismatic members of the UK’s native fauna but have been highlighted as one of our more threatened native mammals (e.g., see here). Although they occur in various parts of the UK, the majority of red squirrels (c. 75% of the UK population) are found in Scotland. A range of work is required throughout the UK to mitigate threats to red squirrels, and to boost their chances of re-establishment. However, it is important that we manage remaining populations to ensure a strong base from which the population can expand when conditions have improved.
Red squirrels and their dreys are protected under UK and Scottish legislation, and there is a requirement to mitigate for any forest operations that could disturb the squirrels or damage their dreys. Forest Enterprise Scotland manages over 400,000 ha of Scotland’s multi-functional forests and need to plan mitigation for their forest operations. There is, however, very limited information about the impact of disturbance caused by forest operations on red squirrels. Without knowing the impacts of those operations, if any, it’s difficult to know what mitigation, if any, is needed.
This project is being run by a team based at the University of the Highlands and Islands in collaboration with Forest Enterprise Scotland. They aim to determine the impact on red squirrel breeding success, ranging behaviour and drey usage of habitat fragmentation and habitat loss caused by forest operations. They are also looking into the use of nest boxes as a potential mitigation measure for forest operations taking place during the breeding season. This latter aspect of the project is being assessed, in part, by determining the use of nest boxes at different heights and in different tree types. The team have set up their monitoring so that camera traps will capture animals investigating or going into and out of the nest boxes. Owing to the possibilities of false triggers and to the frequency with which other species (especially birds) will use the nest boxes, the monitoring has yielded large numbers of images. The team need as much help as possible to classify what (if anything) is using the nest boxes.
Remember: if you are working on a desktop computer, you can use the cursor left and cursor right keys to speed up scanning through a sequence. We are working on ways to improve the set of species that are shown for any project. For now, however, if you are working on the red squirrel project, you can find the red squirrel on the second page of the species options and the great tit on the fifth page. You can navigate rapidly to any page of options by clicking directly on the relevant page indicator. As always, we only want your classifications for what appears in an entire sequence, not what appears in individual images. Please make sure you’ve looked at the whole sequence before submitting your classifications and moving to the Next Sequence.
We're delighted to announce that Pen has scooped another award! This time it's Durham University's inaugural "Science Postgraduate Excellence in Outreach Award". As many of you know, Pen is passionate about science and passionate about getting more people involved in science. The award recognises the broad range of outreach activities that Pen has been involved in. These include his work on MammalWeb (including his work with Belmont Community School), his activities as an organiser of Ustinov College's "Café Scientifique" outreach programme, and his work on the College's Global Citizenship Programme. The latter included many innovative events, such as a public science day, university visits for primary school children, and a "speed-dating" event for teachers to meet with postgraduate researchers from the university, making new contacts and arranging new outreach events.
More on Pen's activities with outreach via MammalWeb can be found in this short video on his work with Belmont Community School, and this video of his prize-winning talk at the 2017 "Ecology Across Borders" meeting in Ghent, Belgium (the largest Ecology meeting in the European calendar).
We thought you might be interested to see this picture of a pine marten mother and her kits, clearly making the most of a den box provided by John Martin as part of a project to monitor pine martens in Dumfries and Galloway. The project involves a range of collaborators, including both John and Shirley, who (among other pine marten-related activities) produce pine marten den boxes, pine marten expert Johnny Birks, and Gareth Ventress of Forest Enterprise Scotland.
Roland, a MammalWeb trapper, sent in this photo which seems to capture the native/non-native squirrel conflict rather well! The photo was taken in southwest Scotland, as part of a squirrel monitoring project with which Roland is involved. Roland notes that the photo was taken in a wood in which red squirrels are abundant but grey squirrels are actively controlled. Contact between the species is highly undesirable because of the risk of transmission of squirrel parapox viris, which the grey squirrels carry but are apparently unaffected by. Red squirrels, by contrast, are highly vulnerable to the disease. There was an outbreak recently near Dumfries, not far from where this image was captured.
The photo was taken using a Xikezan R20 camera trap, which is one of the cheaper camera traps that Roland has tried out.
In response to your requests, we’re making some changes to the website. The first of those changes will mainly affect the way that you view and classify images to make the process quicker and more efficient. That change is scheduled for next Monday, the 23rd of April.
Further exciting updates are planned for coming weeks, and will include changes to allow you to view basic data showing what species you’re finding and where.
In line with new data protection legislation, we will soon be unable to send you emails unless you give us explicit permission to do so. To ensure that we can continue to communicate with you, to let you know about what we’re finding, and to keep you informed about exciting changes to the website, please subscribe to our newsletter here.
Have you thought about being a Trapper but haven't got around to it yet? One of our existing Trappers has pointed out that there are currently some highly-affordable camera traps available via Amazon. In particular, there are several camera traps in the £40 - £60 range with excellent customer reviews - e.g., see here. If you already own one of these traps, or if you do buy one and have thoughts on its performance, let us know. We can then share that information with other Trappers. Happy Trapping!
You may have read, in a previous news post, about a distance sampling method we are trialling here at MammalWeb to try to estimate animal density from camera trap images. In order to test out the accuracy of this method, and some other recently published methods, we’re doing a little test which involves counting lots of deer at Raby Castle.
The aim is to put out some camera traps to get images of the deer and then to use available methods to calculate a deer population density and see how accurate it is. Before we do all this though, the first step is to work out how many deer there are, a task less simple than it sounds!
Although it may not sound all that scientific, the best way to do a thorough count of the deer herd was to take photos of the herd as they followed a tractor which projects tasty carrots! Here are just some of the photographs I got from doing that:
After counting dozens of photographs multiple times, I eventually concluded that there are 253 Red deer and 263 Fallow deer at Raby Castle! Now we just need to put out the camera traps and see how close to that figure we can get.
MammalWeb trapper Roland Ascroft has been camera trapping in his local area of Deerness Woods ever since he borrowed his first camera from us in 2015. Since then, he has contributed a huge number of images to MammalWeb, as well as going even further by conducting his own studies on some of the species in Deerness Woods, such as the Roe Deer. He has been kind enough to write a short article about his experiences as a MammalWeb trapper and some of the findings of his studies! To read the article please click the link below.