Camera traps have been a key part of the conservation toolkit for decades. Remotely triggered video or still cameras allow researchers and managers to monitor cryptic species, survey populations, and support enforcement responses by documenting illegal activities. Increasingly, machine learning is being implemented to automate the processing of data generated by camera traps.
A recent study published showed that, despite being well-established and widely used tools in conservation, progress in the development of camera traps has plateaued since the emergence of the modern model in the mid-2000s, leaving users struggling with many of the same issues they faced a decade ago. That manufacturer ratings have not improved over time, despite technological advancements, demonstrates the need for a new generation of innovative conservation camera traps. Join this group and explore existing efforts, established needs, and what next-generation camera traps might look like - including the integration of AI for data processing through initiatives like Wildlife Insights and Wild Me.
Group Highlights:
Our past Tech Tutors seasons featured multiple episodes for experienced and new camera trappers. How Do I Repair My Camera Traps? featured WILDLABS members Laure Joanny, Alistair Stewart, and Rob Appleby and featured many troubleshooting and DIY resources for common issues.
For camera trap users looking to incorporate machine learning into the data analysis process, Sara Beery's How do I get started using machine learning for my camera traps? is an incredible resource discussing the user-friendly tool MegaDetector.
And for those who are new to camera trapping, Marcella Kelly's How do I choose the right camera trap(s) based on interests, goals, and species? will help you make important decisions based on factors like species, environment, power, durability, and more.
Finally, for an in-depth conversation on camera trap hardware and software, check out the Camera Traps Virtual Meetup featuring Sara Beery, Roland Kays, and Sam Seccombe.
And while you're here, be sure to stop by the camera trap community's collaborative troubleshooting data bank, where we're compiling common problems with the goal of creating a consistent place to exchange tips and tricks!
Header photo: ACEAA-Conservacion Amazonica
- @mbkowalski11
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University of California Santa Cruz
PhD Student (UCSC, Wilmers Lab) interested in large carnivores, behavioral ecology, human-wildlife coexistence, and biologging
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Retired, living on South Africas Northern west coast tracking Brown hyena
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Dr. Kadambari Devarajan is an engineer-turned-ecologist working on biodiversity monitoring. (Website - http://kadambarid.in/)
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Description | Activity | Replies | Groups | Updated |
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Got it. We should definitely be able to handle those images. That said, if you're just looking for counts, then I'd recommend running Megadetector which is an object detection... |
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AI for Conservation, Camera Traps, Open Source Solutions, Software and Mobile Apps | 1 hour 52 minutes ago | |
Hi everyone!@LashaO and @holmbergius from the Wild Me team at ConservationX Labs gave a superb talk at last month's Variety Hour,... |
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AI for Conservation, Camera Traps | 10 hours 41 minutes ago | |
Hi everyone! @zhongqimiao was kind enough to join Variety Hour last month to talk more about Pytorch-Wildlife, so the recording might be of interest to folks in this thread. Catch... |
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AI for Conservation, Camera Traps, Open Source Solutions | 8 hours 38 minutes ago | |
Can't beat Dan's list! I would just add that if you're interested in broader protected area management, platforms like EarthRanger and SMART are amazing, and can integrate... |
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Data management and processing tools, Camera Traps, Conservation Tech Training and Education | 18 hours 17 minutes ago | |
Saul Greenberg is a great guy! He has made a few very useful videos regarding the Timelapse/Megadetector integration:https://grouplab.cpsc.ucalgary.ca/grouplab/uploads/... |
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Camera Traps | 3 days ago | |
That sure sounds interesting! Thank you for your input, @Colin_Cook |
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Camera Traps, Drones | 1 week 2 days ago | |
EcoAssist is an application designed to streamline the work of ecologists dealing with camera trap images. It’s an AI platform that... |
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Software and Mobile Apps, AI for Conservation, Camera Traps | 2 weeks ago | |
Hi @Alasdair Great to hear from you! Thanks for the comment and for those very useful links (very interesting). And for letting @Rob_Appleby know. I can't wait to hear... |
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Emerging Tech, Camera Traps, Conservation Tech Training and Education | 2 weeks 4 days ago | |
Hello everyone, I'm interested in gathering insights on how the behavior of different species impacts the development and efficacy of... |
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Biologging, Acoustics, Camera Traps, eDNA & Genomics, Emerging Tech, Marine Conservation | 3 weeks 4 days ago | |
Hi Andrew! Great to hear your friend, Scott working in Indonesia! I bet he is working on east region with lot of cool monitor lizards!I use Mavic 2 as well for my crocodile... |
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Camera Traps | 1 month 2 weeks ago | |
Ah yes. I didn’t notice that. Indeed it’s “near infrared”, 850nm lighting. |
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Camera Traps, Marine Conservation | 1 month 3 weeks ago | |
I've used AA rechargeable almost exclusively for many years now. I try to get rechargeables sourced from Japan (Panasonic Eneloop and Fujitsu), but have also used Eveready ... |
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Camera Traps | 1 month 3 weeks ago |
Instant Detect 2.0: A Connected Future for Conservation
17 January 2018 12:00am
Resource: Camelot - new camera trap software
1 November 2016 11:16am
18 December 2017 4:21pm
Thanks for the reply Chris!
When you state:
"Camelot has two modes for importing data: a bulk import, and a per-session import. It sounds like you have many images up-front, and so bulk import may be the way to go. In this case Camelot can create the camera trap stations based on the location of the images, and their metadata."
When you mention 'location' you refer to the location of the images from where they are imported from? And not the gps location from the EXIF data if it's available, right? In my case no gps data would be available. But if I've downloaded the images to a hard drive in the field, and then back in the office import them into Camelot I can tell Camelot that the pictures from folder X belong to camera station 1?
You're right about the two points for optimizing. If photos can be ordered by station, date, time, and reference images ordered by 'distance to station', it greatly reduces the number of reference images to look through as the vast majority of individuals will be recorded at only a few stations, effectively trimming down the number of individuals to look through from 100's to a few dozen.
Cascading the drop down lists Species > individuals (or even area > species > individuals, or species > area > individuals, or in some cases species > group > individuals) would be beneficial too in the process of identifying individuals. In a SQL database this isn't hard to code into the fields on a form, but might not be that easy in Camelot as you would have to chose if the field you add depends on another field on the form.
19 December 2017 8:10am
Hi Egil,
When you mention 'location' you refer to the location of the images from where they are imported from? And not the gps location from the EXIF data if it's available, right?
Yes, that's right -- I should have said the 'directory of those images'.
But if I've downloaded the images to a hard drive in the field, and then back in the office import them into Camelot I can tell Camelot that the pictures from folder X belong to camera station 1?
Yes, that's right. Images can be dragged & dropped into existing camera trap stations, which have GPS coordinates associated. For the bulk import case, the data scanned from the image would need to be joined with GPS data to produce the final CSV for upload.
And thanks for the confirmation on how you'd expect that functionality should behave.
-Chris
FIT Cheetahs
4 December 2017 12:00am
HWC Tech Challenge Update: Meet the Judges
20 October 2017 12:00am
Research: Trail Camera Comparison Testing (results)
3 October 2017 12:53pm
19 October 2017 11:14am
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Best Practices: Camera trap survey guide released
12 October 2017 12:17pm
Recommendations Needed: Best camera traps for Central African rainforests?
10 October 2017 4:13pm
12 October 2017 11:34am
Hi John,
They will want a camera with good tolerance to humidity + precipitation (so a camera with a proper O-ring seal, and pack it with regularly-dried silica gel). Elephants will likely have a go at the cameras - so they will want to think about protecting their cameras with heavy-duty steel security boxes (perhaps with welded on spikes, which has worked in Thailand) and minimising smell left on and around their cameras during setup (e.g. use gloves, don't smoke or leave food).
Apart from that, the usual considerations apply: good detection circuitry (less of a problem if targeting elephants though, as they are massive) and battery life always helps.
Laila Bahaa-el-din et al. used Panthera and Scoutguard in Gabon; the Goualougo Triangle Ape Project in Rep Congo uses Reconyx I think; Julia Gessner et al. used Reconyx in Rep. Congo and Cameroon. The latter reported that (of 47 cameras), 4 were taken out by elephants and one by a leopard!
Ollie
Download New Conservation Tech Guidelines: Camera Traps, Acoustics and LiDAR
11 October 2017 12:00am
How to lose a BRUV in 10 days
26 September 2017 12:00am
Survey: Camera Trap Survey with WWF-UK
20 September 2017 9:48pm
Recommendations Needed: GSM Camera Traps
24 May 2017 1:42pm
10 July 2017 1:24pm
Hi Chloe,
I've had promising results with the Scoutguard MG983G-30M, and I believe a 4G version has just been released. The 3G version has some useful features, like two-way communication to change settings/get images and a audio call feature (which I haven't used). I'd be very pleased to hear how your tests go.
Cheers,
Rob
10 July 2017 4:04pm
Thanks everyone,
@TopBloke @Kai - I've not come across the Ltl Acorn ones - will take a look. So does that mean if it was purchased in the UK it would be locked to a UK SIM then? That might be problemativ as we tend to purchase here to test and set up before sending out when staff are heading back to the country of deployment.
@Rob+Appleby - That's good to know about the Scoutguard MG983G-30M too, thanks.
A supplier is going to send me a new model by the same people who make Scoutguard to test but he hasn't said what it is. Maybe it's the 4G one. Whatever it is if it is any good I will feed back on here
Chloe
10 July 2017 4:42pm
@@Chloe+Aust - pls google “ltl acorn uk”, you will get a lot info. No, no limited, just the company's sale rules. You could use it anywhere, but for example, if you wants to use it in kenya, you need a local sim card, such as safaricom... when you check photos from china, you will find most of them photoed by are ITI acorn. Panda,tiger, snow leopord, cloud leopard, leopard, golden cat....
Scoutguard is also a good china camrea traps. oldest company. only company have espano menu. but they are focus on US hunting market. not special for wildlife researching use.
The LOREDA is also good, the only brand focus on wildlife-bio researching camra traps in china. Might be do not have dealers/stock in uk.
From the Field: Developing a new camera trap data management tool
7 July 2017 12:00am
Article: Google's cloud vision for automated identification of camera trap photos
12 April 2016 1:04pm
7 August 2016 11:25pm
An update to the automated species identification debate:
A paper has recently come out which used deep learning ("very deep convolutional networks") and managed 89% accuracy for the Snapshot Serengeti Zooniverse dataset, IF the image was first manually cropped around the animal. Seriously, who has time to do that? If the image remained uncropped they managed a woeful 35% accuracy.
Perhaps we have a long wait ahead of us for this to become a practical reality?
22 June 2017 7:22am
Note that paper isn't actually a journal article, hasn't gone through peer review, its a preprint.
24 June 2017 12:50am
Fair point, it isn't a peer reviewed article as yet. I had a poke around out of curiosity and wasn't able to track down a fully published paper yet (thought it's been a while since this preprint was released...). On reading, were there any issues that stood out to you that others should be aware of? And, as Ollie pointed out, the research wasn't getting a great response rate from uncropped images - I wonder if perhaps, given the time since the original publication, the results may have actually improved by now? It seems (from my interested but unqualified observer perspective) that the field is moving forward in leaps and bounds, such that a paper pre-published in march 2016 may very well be out of date by this stage...
Resources: Panthera Camera Trap information
5 April 2017 8:47pm
26 May 2017 12:39am
My understanding is that the Panthera cameras are only available to people or groups in Panthera's network. I tried to get some a few years back and had no luck, even for a project that had received Pathera funding in the past.
Regarding the poacher cam, I know @ColbyLoucks at WWF has developed a system using infrared thermal cameras that worked in the field trials.
Putting on my black thinking hat, the design as shown of the poacher cam will not be effective long-term once poachers know to look for it. Eric Dinerstein had worked on a project where such cameras would be concealed in a vine or some other organic-looking encasement.
26 May 2017 12:04pm
black thinking hat ! Interesting and honest.
Machine learning, meet the ocean
10 May 2017 12:00am
From the Field: Dr Raman Sukumar and Technology Developments Needed to Conserve Elephants
5 April 2017 12:00am
Camera Trap Pictures Wanted
6 March 2017 11:38am
31 March 2017 10:18am
Paul,
I can get some when I do my next deployment (sometime next week at this stage).
Colin
31 March 2017 10:21am
Nice, thanks Colin! Are you deploying cameras as part of the phascogale project?
Paul - are you quite sure you don't need some camera trap photos of some gorgeous Australian mammals for your guidelines as well?
31 March 2017 10:28am
Steph,
Not quite. I'm coordinating a fauna monitoring project for a Landcare network and, of course, we hope to get phascogales. I've just retrieved a batch of cameras from nest box monitoring duty for the phascogale project and their next role will be to investigate a possible sighting of a Squirrel Glider in the area.
Colin
How to stop the thieves when all we want to capture is wildlife in action
23 March 2017 12:00am
Recommendations Needed: Real-time enabled camera traps
17 August 2016 2:56pm
9 March 2017 7:32am
Hi Kai,
thanks for the links. Interesting. I requested them for pricing details.
The Panthera Anti-Poaching Cam makes use of existing networks and costs about 350 USD. That is not very expensive, is it?
Cheers,
Jan Kees
9 March 2017 9:51am
Hi Jankees
Thanks for your reply,
If there have existing network like RoyalKPNN.V. provide mobile phone service, there will be no problem, 3G/4G camera traps will works well. each cam 250 USD at the moment.
Now days hundreds of chinese tech team are working on LoRa and NB-IoT solutions as well. All of them want to be successfull like HUAWEI,ZTE and DJI. Nice people, good team, team work ,working 12 hours each day like machine, like arms race.
I am sure they are willing to support anti-poaching. I am not techman,but we are chinese, we have the duty to solve problems, be responsible for it. If you come to china oneday, let me know.
Thanks, and your sensingclues is great.
Regards
Kai
14 March 2017 6:13pm
A number of good points have been made. In terms of remote-enable camera traps, you will mainly find one that use cellular data signals to transmit images. Typically these are thumbnails rather full resolution, so you will likely still need to retrieve teh emory cards for analysis. Also, traps that transmit images tend to have a lionger time lag between shots, which can be a problem. Hunting web sites tend to have the most complete reviews and discussions of the various models.
If you want to use citizen science in the data analysis process, I would suggest looking at Zooniverse (www.zooniverse.org). It has a pretty well-thought-out platform.
Survey: Camera trap effects on people
2 March 2017 4:25pm
5 March 2017 3:34pm
Thanks, i send the it to my chinese friends, i am sure some of them finished the survey.
cheers
Kai
#Tech4Wildlife Photo Challenge: Our favourites from 2016
1 March 2017 12:00am
Remote Camera Data Processing - Counting Individual Animals?
10 November 2016 12:30am
20 January 2017 12:04am
Hi Kate, It all depends on the specie and data set accuracy you are trying to collect. If you are purely documenting frequency of visits, this is straight forward. However, if you are recording numbers then further analysis of photos may be needed. Some animals like foxes have distinctive marks or shapes, whilst smaller mammals can be a lot harder. If this is impossible, then a time limit should be defined across all camera traps. From all the papers I have read and projects we have worked with, there doesn’t seem to be clear standard. Hope this helps. Mike - handykam
3 February 2017 2:00am
Hi Kate, this may be a bit late for your analysis but I will put here for future reference. The case you mention would be to detemine independent events, not necesarily different individuals. Unless there is conspicuous colour, pattern, size, sex or other scars/markings then you shouldn't label them as different individuals. I haven't found much analysis or discussion on this point so it seems prior experience or a "best-guess" is used to determine the time between independent events. Within the R package "camtrapR" vignette it is mentioned (https://cran.r-project.org/web/packages/camtrapR/vignettes/DataExploration.html) "The criterion for temporal independence between records ... will affect the results of the activity plots" and you may have other data to correlate activity with abundance or density.
If you are using and occupancy analysis this may be trivial as you will likely be lumping multiple nights of survey into a single detection period for each camera anyway (we have used six 10-day detection periods for cats in central Aus).
SECR methods may also be more useful for calculating density. Timing of events BETWEEN cameras can be used to show that photos are of different indivduals as they cannont exist in two places simultaneously or travel at fast enough rate to be captured in that time frame (clocks must be synchronised).
I hope you have had as good a season in Bon Bon as we have in Alice Springs. Cheers, Al
5 February 2017 8:58am
The facts are simple. If you violate the assumption of independence of sampling events you will bias the result. In the event of multiple observations by overestimating occupancy due to counting the same animal twice. There is therefore no answer to your problem. People try to overcome it by chosing a particular random number to try and standardise the method across sampling sessions. Let us say we decide to use one hour between new samples in all our sampling sessions. If abundance changes between sessions our ability to detect an animal may change and our result may therefore be biased up or down depending on the trend. So we allow detectability to vary between samples to try and reduce this bias. This is done through assessing the results of the replicate samples i.e. n days.
However, the session time determines how many counts are reduced to presence only and as session time increases the variance of the occupancy estimate may grow. But we don't know if this increasing variance/ loss of accuracy is based on a real loss of information or not because we don't know if we are correctly throwing away information portraying the same individual or information on the presence of multiple individuals. Therefore selection of session time may effect our ability to detect a change in occupancy even with accounting for varying detection. i.e. detection may be equal if our session time is too short. In other words if in both one hour AND two hours we detect multiple animals on the same number of plots, convert this to the binomial (presence/absence), then detectability will be equal for both sessions. But if in one hour we detect half the number of animals as in two hours what does this say about occupancy?
Spatially explict (SE) models will also not help because as far as I know they are based on allowing multiple detections across plots, not within plots. Or cameras in this case.
Having said this there is apparently some hope in marking a portion of individuals to increase the accuracy of SECR or SE unmarked in this case. So my only advice would be to run an experiment with marking some foxes and use a SE model with predominantly unmarked indiviudals.
On a more jovial note you could simply mine the data by assessing the power to detect a change between pre/post baiting using a variety of different session times. The reality of such a result is highly dubious but it might inspire more thought on the behaviour of this particular situation. Failing all this youy could run away and join the circus.
Discussion: Wildlife Institute of India to conduct first tiger estimation in nine countries
28 November 2016 1:55pm
28 November 2016 2:07pm
@wildtiger @Shashank+Srinivasan @NJayasinghe Do you have thoughts on this?
31 January 2017 7:05pm
What species monitoring protcols do you know of that explicitly focus on one species?
-John
Discussion: Opinion of TEAM network and Wildlife Insights
7 June 2016 5:36am
24 June 2016 6:08am
Thank you. I had not seen TRAPPER.
I had seen Snoopy, CameraBase, the Sanderson & Harris executables, and TEAM. And none of them had seemed suitable for the work that I was doing.
I will investigate TRAPPER further.
30 June 2016 4:38am
I like TRAPPERs video capability.
I am yet to test it out though.
13 December 2016 12:47am
Hi Heidi,
You might also consider becoming involved in the eMammal project (emammal.si.edu) that the Smithsonian has recently developed. It has tools for both uploading and coding camera trap images, with the bonus that they are ultimately archived and made available by the Smithsonian for future researchers. My opinion is that moving toward open-access data will make all of our efforts more valuable into the future. I'm using eMammal, but not one of the developers or associated with the Smithsonian.
Cheers,
Robert
Conservation Leadership Programme 2017 Award
21 November 2016 12:00am
Standardization Discussion: Nomenclature
5 October 2016 4:48am
31 October 2016 2:18pm
Camera trapping is the new kid on the block, and it is still talking like a 5-year old ! It will take some time, and some journal editors insisting on uniform and properly used terms before everyone can be sure what everyone else is talking about.
For what it's worth, here is what I understand when I read the terms you list;
Survey - the process of designing the study, putting out and servicing the camera traps, collating and analysing data and writing it up. So much much more than just the time that the camera traps were in the field.
Site - a spot on the ground. Usually these days specified as a GPS location. What you describe as a site I would call a study area.
Station - I do not recall having read this in connection with camera traps, and I would not use it. I admit that this is not consistent; I have read and I would use "bait station" or "feeding station" interchangebly with "baiting site" or "feeding site". It is of course possible to station a camera trap at a baiting site, or site a camera trap at a feeding station !!
Camera - is certainly a physical device that takes photos, but you cannot record animals with just a camera, you need someting to trigger it. A self-triggering camera is a camera trap (or trail camera, game camera etc).
A station session (see above about station) would be OK is site was substituted for station.
Peter
12 November 2016 2:39pm
Hi folks,
for Site - in our camera trap data base we use the mountain or National/Nature park
Survey - is connected to the time scale - i.e. This mountain2015 or 2016
Station is the actual place of the cameras (1 or 2) with GPS coordinates
Diana
Article and Discussion: Scale of camera trap studies
25 August 2016 11:50am
5 October 2016 3:37pm
@heidi.h Definitely a valid question. It looks like they have it connected to a zooniverse project, which means they are using citizen science to not only set up and maintain the cameras, but to process the data. Pretty neat.
What we do
Our main task is to get our trail camera volunteers up and running with equipment and training. Volunteers can now apply to host a camera in Wisconsin survey blocks where they have access to land (visit dnr.wi.gov, keyword "Snapshot Wisconsin" for more information). Trail camera volunteers are in charge of setting up a camera and retrieving its SD card (containing saved photos) at least four times per year. Volunteers then send the photos to WDNR to be posted on Zooniverse. By the end of 2017, we expect to have enough cameras for > 2000 volunteers to participate in the project -- these cameras will produce millions of photos each year!
While we get our trail camera volunteers set up, we have plenty of other photos to show the Zooniverse community. WDNR staff have placed over 300 trail cameras in two areas of the state now home to a species of elk (Cervus elaphus) formerly abundant throughout North America. Elk were extirpated from Wisconsin in the 1800s due to overhunting and habitat loss. Reintroduction efforts began in 1995 and continue today, and we're curious to know how the elk are doing! Classifying the photos from the elk reintroduction areas will give us great information about population size and distribution, and examine how elk presence overlaps with that of wolves--natural predators of elk.
5 October 2016 3:42pm
But in answer to your question, @P.Glover.Kapfer , I haven't heard of any near this large. TEAM Network would be the closest - 17 sites, 14 countries and approximately 1000 camera traps deployed over 2000km 2 that are monitored annually. @efegraus - does TEAM Network have ambitions to be expand to this sort of scale?
@ollie.wearn perhaps you might know of some other big scale camera trapping projects?
8 November 2016 1:15pm
Bringing over some of the comments we're getting on Twitter:
@WILDLABSNET Our @UAlberta lab deploys ARUs at 1000s of sites in Alberta each year in collaboration with @ABbiodiversity #bioacoustics
— Elly Knight (@ellycknight) November 7, 2016
@WILDLABSNET yeah, @TEAMNetworkOrg does that...pretty sure thousands of cameras across 15 or sites
— Asia Murphy (@am_anatiala) November 4, 2016
Neotropical Migratory Bird Conservation Act grants via USFWS
8 November 2016 12:00am
How many cameras in a camera trap?
4 July 2016 4:32am
11 July 2016 2:55pm
Hi
In some cases you need to recognize individuals, such as in capture-recapture analysis for abundance/density estimations, or you might want an index of individuals that are detected (instead of number of detection).
If you need to recognize individuals is better if you have both flanks of the animal photographed, and even better if the animal has natural marks (such as rosettes or stripes like jaguars or tigers), but you can also use scars and general body complexion to help.
You can still make a capture-recapture study with one camera trap, but you have to choose only pictures of one side of the animal to use, and discard all the other pictures of the other side (since you won't know if are the same animal), doing that you decrease the detection probability, because now it would be the product of the likelihood of the animal walking trough the camera and the likelihood of going in the direction that you need.
Using one camera per site is a good setup for a site occupancy study, and you can even estimate abundance with the Royle-Nichols method, if your data fits it.
I hope this helps
Bests
Juan
12 July 2016 7:42pm
We have just started testing an array of three cameras recording video at an African wild dog marking site. The idea is to give seamless coverage of an area larger than can be monitored by one camera, with maximum chance of detecting animals approaching from any direction. As a bonus it produces pictures of both sides. The cameras have only been out for a week, so it is too early to assess how well the arrangement works.
1 November 2016 1:38pm
We have a set of three Bushnells covering an African wild dog scent-marking site. They are at the apices of a triangle, with each camera just at the edge of the field of view of one of the others. This gives us a higher probability of detecting animals at the site, a better view of the action on at least one of the cameras, and no dead spots below each camera.
I was hoping to use two Reconyx Ultrafire XR6s on game trails at each of ten scent stations, but the cameras cannot detect animals walking towards or away from them.
Peter
Internet Cats Just Got Bigger
26 October 2016 12:00am
18 December 2017 12:16pm
Hi Egil, I think Camelot has a reasonable story around most of these things. Here's how I see it:
I set up a survey and I add the information about all the camera trapping stations (including camera IDs).
I import the photos. The database reads the data, time and camera ID from the photos so photos are linked to a camera trap location.
Camelot has two modes for importing data: a bulk import, and a per-session import. It sounds like you have many images up-front, and so bulk import may be the way to go. In this case Camelot can create the camera trap stations based on the location of the images, and their metadata.
http://camelot-project.readthedocs.io/en/latest/bulkimport.html
Then I do a quick first pass where I assign a species (tiger, leopard, etc) to each photo.
Yes, I expect you'll find the library UI suitable for this.
In a second round I want to identify the tigers. So I get all photos labelled with 'tiger'. Obviously the first one is a new animal thus I want a 'button' which allows me to add a new animal. Then in following pictures there is a drop-down menu with identified tigers. The order of the pictures presented is by camera trap location, data, time and then the next nearest camera trap location.
The sighting added in the first pass can be edited to add-in the individual, and new individuals can be added straight from the dropdown menu. Camelot does not have the ability to define a custom ordering of images: the ordering is always by camera trap station, by capture time (broadly; it's a bit more nuanced than this in reality). However does have the notion of "reference images", where images flagged in this way can be displayed, in another window (which can handy where multiple monitors are available), based on the currently selected sighting field data.
If things go as planned I'll likely be running into 100,000's of pictures, so I need to be able to do the first round pretty quickly. Then there will be 4-5 species I need to identify at the level of the individual. There will probably up to about 200 individuals of a species, but never more than about 20 at each camera trapping station, and the vast majority of individuals won't show up at more than 4-5 camera trapping stations either.
Camelot does support this sort of raw scale (x00,000 images) and has a reasonably efficient UI for identification. The information here may be relevant, depending on how many multiples of 100,000 it turns out to be.
However Camelot does not currently offer the ability to limit individuals in a field depending on the selected species (it is always the same individuals available in a dropdown regardless of the selected species). Potentially this limation could be worked around by having a dropdown available for each species, which will at least highlight in an export where a data-entry error may have arisen. (e.g., individual chosed in the "individuals" for species X field, but the selected species is Y.)
At 200 individuals the workflow for reference images could start to break down too, depending on the level of familiarity with the individuals. (i.e., repeatedly searching through all reference-quality images of a species, or images for a couple dozen individuals to make an identification could be onerous.)
I've looked around and I think Camelot is closest to what I want, but I wonder if I could get it really close to what I want. I have quite a bit of experience with SQL and building access databases, but I thought, with the prevalence of camera traps these days, that there would be more packages out there.
I agree Camelot really only goes part-way to meeting the requirements. It should be workable to use Camelot for the purpose, though support for individuals is relatively new and really hasn't been optimised for this sort of scale. It seems like the two places where Camelot is most lacking for this workflow are (and correct me if I'm wrong):
It'll likely be some time before these features are available in Camelot, but I'll add them to the development backlog.
-Chris