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Hi everyone, do you know of any camera traps that are similar to the Reconyx UltraFire XR6, but that might have a higher response time?
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We used old bushnell HD, opened them, turned the lens by 180° to the left, and had a focus of about 25cm! You could also use a macro-lens (like in the citation). Not really necessary to use a different lens but a different focus!
The flash needs to be shaded...
another citation into that direction:
doi:10.1371/journal.pone.0067940
Sometimes it is just a simple trick ;-)
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I am working with a lot of timelapse data and I've been switching between Timelapse2 & just using VLC (strictly because it isn't as laggy with going back a few seconds like Timelapse2) to analyze these files, but its a very time consuming process. I was wondering if anyone here has a lot of experience going through timelapse files and tips on how to go through them in a more efficient matter?
The goal of my project is to compare detection rates for a slow moving species with a few different camera trapping designs
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Have you tried theImageJ? We usually use imageJ or Fiji to analyze the Timelapse data of embryo development under microscope. Sry, I am not very sure you're mean of going through data more efficiently. I attach a link that help me analyze my photos.
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Hello colleagues, in the coming months I will be investigating the presence of drills (Mandrillus leucophaeus) in an area where they have not been seen for years (Pico Basilé Natural Park, Bioko, Equatorial Guinea). It is a rainforest, with altitudes of about 1000-2000 meters. Obviously, I have considered line transect surveys, as they have been widely used for estimating abundance of primate populations. However, there are some issues to consider.
1. It is a very steep area, which will prevent me from drawing completely straight transects.
2. I will perhaps not even find the species. Therefore, as it has been done with the species in other areas, indirect evidence such as fecal remains will be sought. I also thought it appropriate to incorporate signs of human activity into the data (cartridges, rubbish,...) as bushmeat hunting is the main cause of biodiversity loss on the island.
3. I will also have trap cameras, which I intended to strategically place in front of fig trees, a key food in the diet of the species.
I am just starting in the field. I have done fieldwork before, but related to other very different taxa in a very different environment. I've been checking the literature but still, I wanted to ask you to recommend me a study that has used similar methods (nonlinear transects), or that has considered fecal remains to assess the presence of a primate species (I don't even want to say density, because I do not know or if we find them). Or maybe some other publication that explains how to propose different sampling methods according to the field conditions, how to calculate the distance between transects, etc. Or any other key issues they deem appropriate to explain to me.
Thank you so much!
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Hello Oriol,
I think you are approaching your fieldwork strategically. You are right to consider the extent to which (or even if) so-called "standard", or "classic", field methodologies can be applied in Pico Basilé NP on Bioko:
1. "It is a very steep area, which will prevent me from drawing completely straight transects."
My doctoral research on black lemur socioecological responses to anthropogenic habitat disturbance was similarly in a protected area (a small mountain) where the topography was quite challenging. So, in establishing my study site's path system, and during my initial surveys to select a specific field site on the massif, I used the topography to my advantage as much as I could. For example, linear transects could be adapted to the observer(s) (i.e., you and any assistant(s)!) using ridge-lines or the upper edges of ravines to move in a linear fashion. Of course, this approach would make your survey transits generally altitudinal in nature -- not a bad thing, and there is a comparative literature on altitudinal sampling (but, not what one reads about in the majority of literature on conducting survey transects of primate populations). Trying to move along natural elevational "pathways" in the landscape would largely avoid the logistical challenges of having to try and "bush-whack" your way horizontally/latitudinally up and down across a landscape where steep slopes predominate.
2. "I will perhaps not even find the species. Therefore, as it has been done with the species in other areas, indirect evidence such as fecal remains will be sought. I also thought it appropriate to incorporate signs of human activity into the data (cartridges, rubbish,...) as bushmeat hunting is the main cause of biodiversity loss on the island."
Yes -- you should look for multiple signs that might indicate presence of drills and/or the activity of bushmeat hunters in the ares. In addition to cartridges, *any* evidence of temporary hunting camps should be recorded (and mapped, or pinpointed with GPS) -- e.g., evidence of shelters such as lean-tos and/or campfires; evidence of bush-knives (i.e., 'panga', 'coup-coup") being used to clear brush or paths; etc.
3. "I will also have trap cameras, which I intended to strategically place in front of fig trees, a key food in the diet of the species."
In addition to placing camera traps at large fig trees, if there are any streams or natural clearings that drills might cross where the width of the crossing would permit the possibility of gaining group count data (if drills are present), it would be worthwhile to place a camera trap in any such setting (at least for a brief period to see what might be caught on camera).
4. "... fecal remains to assess the presence of a primate species...".
This would be very tricky at best. Unless you see a drill defecate, and can then locate those fecal droppings, you don't know what species deposited the feces. Then there are the technical issues -- if you were to collect fecal samples, that sets up a situation where you would need the necessary lab materials & equipment to fix and store the fecal samples. Otherwise, they would simply grow mold. I suppose fecal samples could be dried in the sun (and then later re-hydrated using distilled water for whatever testing you envision). But, in a rainforest habitat, trying to sun-dry fecal samples might simply be futile!
Hope some of this feedback proves useful. Good luck with your project!
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After quick research on the web, I've not found anything of my interest. I know nowadays there are many software used to analyse camera-trap data, which are very useful to automatically extrapolate metadata such as date and time, as well as quickly identify the species, number of animals, sex, age and so on. Furthermore, some of them use Artificial Intelligence (AI) to recognize blank images and/or species.
However, most of them work only with photos, likely due to their low memory demands and facility to be processed. At least, this is what I found.
And here comes my question: Do you know any software or R package that works with VIDEOS? I'm looking for something which can automatically help to collect some metadata (date, format, species) instead of filling manually in excel tables.
Thank you in advance for any suggestions.
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We use agouti (https://www.agouti.eu/), works also with videos.
good support! delivers anything you mentioned! Also an AI (but needs to be checked)!
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Climate change is a prolonged process and does not affect an ecosystem suddenly. Camera traps do not provide any information regarding how precipitation and temperature is fluctuating daily, seasonal, or yearly. In this case, which alternate method could be more effective to monitor the impact of climate change on hibernation in mammals?
But If camera traps could also be used two questions arise here:
what should be the duration of the study? I don't think 3-4 years of monitoring could be enough to get reliable results. Secondly, only camera traps are enough to monitor the animals?
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Dear Kurt
I think no. Relying on temperature recorded by camera traps can not provide provide the climate change data. Camera traps could only record temperature when capture an animal while passing in front of it. Climate change is something els. Its an overall change and needs long term data
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I’m looking for a camera trap that can be set out in the field to function as a camera trap but can simultaneously be programmed to take a video with audio for a set time each day. Does anyone know of a camera trap that has this capability?
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It might be easier to just have one camera set for timelapse video and another camera for motion detection.
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Many of us are now using cameratrapping all over the forests, for many purposes. Most of time, we all collect (I guess) an extraordinary amount of informations what are out of our scopes. But what could be usefull for someone somewhere ... Related to my experience in French Guiana, I'm thinking about a Monodelphis making a nest, a 45 min long sequence of 8 bushdogs bathing, grooming, a vampire "running" after a Priodontes, a baby Myrmecophaga digging with his mother .. among many others, all sleeping in computers.
Is there any webplatform that could allow to share those "moments of cryptic life" ? A journal where we could depose such thousands of anecdotal behaviors ?
Maybe something to propose, create ?
Suggestions and comments welcome !
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Yes, Benoit de Thoisy . I think iNaturalist is the right place for what you are looking for. Check this:
I have also thousand of mammals and birds photo captures in Northern Quebec region. We should share all these to increase field observations. If not, they would disappear in our computers and that's a real shame.
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We are studying circadian rhythm in longhorn beetles within the genus Cerambyx, which includes diurnal and nocturnal species, in order to understand the  selective forces involved in such a striking evolutionary divergence. We would like to know if those genus including both diurnal and nocturnal species are frequent in insects
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For coleoptera: Pimelia, Scarabaeus, Anthia, ... Some species can also change the period of activity depending on the season (especially in deserts like Anthia sexmaculata)
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For many camera trap studies it is a problem that it is not possible to distinguish individuals, therefore consecutive visits may be the same individual. Either an individual triggers a burst of captures during one visit, or the individual moves consecutively in an out of the camera view during a short time period.
To minimize double counting many studies are using a time gap (hit window), which is the length of time used to group consecutive images/videos together as single detections (given that the data are from the same camera and featuring the same species). This will vary between study designs, for example bait site will cause individuals to stay within the detections zone for a longer period compared to non-baited sites. Further, some species will be more likely to stay at the site than others.
Is there a good procedure to estimate an optimal time gap (hit window) for an existing data set?
Best regards,
Ronny
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This depends mostly on the methodology (baited/non-baited; random samples/non random) and especially the analysis method.
For most of the more recent density estimate methods very short (2s etc) or no time delay have been used.
If you have enough saving capacity and battery life (which has improved in newer models) I would say you should go for the shortest interval possible. If required you can remove/filter multiple triggers in analysis. Otherwise you may miss critical data during the time interval where the camera stays innactive. And I personally prefer video captures instead of snapshots (which helps better identification).
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Hi all,
It's rare to come across papers that calculates both and some states that they are the same.
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Hi Nur,
Yes as far as I know, both terms are synonymous. The formula for calculating both the indices is same.
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To avoid pseudo-replication, only images taken 30 min of a previous photo to the same event are considered as independent records. I think 30 minutes seems excessive to avoid pseudo-replication between photographs. I am sure that at times, different individuals (animals) could pass the same camera trap within 30 mins. Can anyone give reasoning a little more?
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30 minutes can be excessive or can be too little (in fact, in some cases, we have also used 60 minutes). It depends on the species and its behavior and other factors. For example, if you set up your camera next to the main den of a species that uses it frequently, you are going to get a lot of photos of the same individual in a brief time that may introduce a bias in your results, depending on the objective, of course.
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How can I use R to extract the time interval between visits of different species from camera trap images?
For example, Species A arrives at 07:00 (6 photos, each 1 min apart)
Species B arrives at 07:45 (so a 45 min time interval, or more precisely a 39 min time interval).
I have 10's of thousands of images, and I have used camtrapR to extract the record table, but the deltatime just tells me the time interval between photos of the same species same visit, not inter-species. I want to investigate the effect of species A's presence on species B.
Any advice?
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An important update (which I learned the hard way).
Do not simply calculate difference between the times like in the code I provided above. Problem is that R will change the unit of that time difference, it will be days when it is over 24h or hours when under 24, so 2.5 days and 2.5 hours will have the same value, obviously distorting the results.
Instead, use:
tte$timeDifference[i] <- difftime(tte$date[i], tte$date[i-1], units= "hours")
with any unit you like. hours made most sense in my case.
Courtney Marneweck and Ilona Papp, did you have any luck with this kind of analysis? I was able to get the results but I am still cautious about how to interpret them.
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I collectd data by using camera trap on a wild animal. It consisted at 130 photos. I have placed data in Excel with multiple columns of image no., year, month, date, time, temperature, lunar phase, no. of animals, behavior of animal. Now i want to know that how i can analyze the data? and which statistical tools will b used regarding to find out good results.
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Hello every one,
I am working on the activity pattern of the 3 mammal species. can you please tell me how to arrange the data on an excel sheet/CSV file for the daily activity pattern of a species (within 24 hours) in a season/ year using R software. As I am using R.
Thanks
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Almost no information on seed fate has been reported for Asian pheasants (Phasianidae), although they certainly eat fruits and are attracted to fruit baits at camera traps. They are typically the largest birds in forest understories in the tropics and subtropics, unless hunted, so they are potentially significant in seed dispersal if seeds survive gut passage.
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Large seeds are more likely to survive.
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Dear all,
I am visualising videos from our great tit-nestboxes (nests were recorded when the chicks were 9-10 days old, hatching date = 1) and I figured out that, sometimes, one of the parents remained inside the nestbox and foraged the chicks, while the other one brought the prey items to the nest (without accessing the nestbox). Due to a ringed bird in a couple, I could confirm that the bird inside the nestbox was the female (as expected). However, I need stronger evidence about it at this stage: does anyone have any paper to suggest about this specific behaviour when chicks are 9-10 days old? Something proved by using PIT tags and cameras, for example?
Thanks a lot in advance!
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Evolutionary conflicts of interest between family members are expected to influence patterns of parental investment. In altricial birds, despite providing the same kind of parental care, patterns of investment in different offspring can differ between parents, a situation termed parentally biased favoritism. Previous explanations for parentally biased favoritism have received mixed theoretical and empirical support.
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I'm trying to assess how useful camera trapping would be to compare forest fragments of <4km2. The focal species are carnivores within each fragment with range sizes of no more than 0.5km2.
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Only wildlife photography can help.
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We have a large camera trap database of multiple carnivores species (from long-term camera trap data). We want to to examine the activity patterns to examine potential temporal aspects of co-occurrence and want to find a solid R-package that can help in that effort.
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Рекомендую!
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Hi,
I am interested in estimating feline PV through camera-trapping. However, it is really hard to classify the individuals of my target species found on the records in different age groups. Also, it is rare to find cubs in the camera-trapping records. For these reasons, I would like to know if there is any proxy I can use for these two parameters.
Thank you in advance.
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I also agree with Andrew .. good comment .
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Looking to connect with any research, papers or groups using remotely triggered stereo cameras to create 3 dimensional pictures of wildlife and gather data on cryptic species. Wanting to set up a system similar to the BRUV (baited remote underwater video) but for terrestrial systems, possible using a downward facing camera?
I'm thinking someone out there is probably already doing this?
Cheers,
Jamie
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Hi Jamie Mcaulay Here's an example with tapir in South America. But no idea if this research continues or if the group is still active. Published using 2D only but the group may be interested in participating in this fascinating idea of advancing with 3D ...
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Hello,
I am currently working on a wildlife monitoring project that relies entirely on camera trapping, over different habitats and approximately 9500 square km (not entirely covered). The data is going to be used for both populations estimate and species distribution.
All trapped species are considered, and I am having some issues with species such as Rupicapra rupicapra and Sus scrofa, which enjoy spending more time on a single spot and are not easily individually recognisable. I am merging the events of the these species which are separated by less than 20 minutes, keeping a (conservative) total count of, for example, the individuals during one day.
But I was wondering, is there a rule of thumb to account for possible double counting of the same individuals, or shall I just keep my assessment of 20 minutes as a "statistically good enough" time gap?
Thank you very much and best regards,
Michelle
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Over counting may produce biased data, for this you have to installed camera traps at a good distance to each. Then only comparing the time dynamics of the photocapture you can do this kind of analysis.
Hope this will help.
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Does anyone know of current research on livestock predator mitigation strategies (Wolf, Bears, Puma, Dingos, etc …)
I am interested in evalution and techniques with fence, IOT sensors, camera trapping, change in strategies, etc ?
Kind regards
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Please take a look at this useful PDF attachment.
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In the past years, I've been doing a lot of camera trapping in rainforests, and there is recurring issue I've been having for a while: daytime IR images. 
As the rainforest understory tends to be low-light environment, all camera trap models I've used (Reconyx Hyperfire HC500 and Browning Dark Ops Pro) often switch automatically to the IR flash mode, even during the daytime. Since color is an important attribute for the differentiation of otherwise similar species, I find this problematic. Is anyone else having the same problem, and if so, have you found a way around it?
I was wondering whether it would be possible to change the light threshold at which the camera decides to switch to infrared. Browning addresses this issue on their webpage (https://browningtrailcameras.zendesk.com/hc/en-us/articles/360009748473-...), but does not provide any solutions. 
All insights are welcome :). 
Cheers,  Thomas
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There is no solution. In rain forest there is not enough light to take pictures without infrared flash. Pictures would come out very dark. You can try to manage the camera parameters or maybe use one low glow model.
But If you want color for sure you have to use a model with white light flash. And value the inconvenience to wildlife. In some spices there is no discomfort
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Hi, I am planning to set up a long term monitoring study using camera traps in Peru. In terms of choosing station location, number of cameras, distance within stations and orientation of the camera, could you offer any advice? Is there any paper you have used in the past as guidance?
My aim is to observe how species assemblages react to wet/dry season and how they will vary in the next years.
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There are several questions that need to be answered before a plan to set up a camera trap monitoring grid.
1. BUDGET - how many cameras can you afford? What is your budget for servicing these camera traps and processing the images.How large an area do you need to survey?
2. SPECIES - what are your target species? How large are their territories, home ranges? Do home ranges differ between sexes? Is there a preferred habitat for these species?
3. Given these two previous points, the grid itself needs to recognize that mobile animals used the avalable habitat in non-random ways. Some species prefer ridges, other prefer low-lands and riverbanks. Others will use existing game trails or human - made trails for the same reason as you or I - it is easier to walk on an established trail. You also need to think about camera placement. The successful camera traps I have seen and used have a wide field of view. In a tight spot all you might get is a shot of the flank or tail of a jaguar. Therefore an open space around the camera is preferred. I would suggest a preliminary survey of the area that you have available for use in this project to make the best use of your resources. Look for tracks, scat or other evidence of habitat use before you make decisions about where the traps are placed. If you are doing a general survey of say mammals in a particluar area you may have to use a mixed strategy covering a variety of habitat sub-sets and camera heights. It all depends on the objectives of the planned survey. Best of luck and good hunting.
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Hello,
I am new with occupancy models, and I am working on selecting a model-fitting function for an occupancy model to use for a camera trap study that incorporates abundance and multiple seasons into detection. I hope to use unmarked in R, though I am open to other options. The Royle and Nichols 2003 function (occuRN) seems to be best for using abundance models, while the MacKenzie et al. 2003 (colext) function seems to be used for multi-seasons. My study design is as follows:
  • 3 summers of data collection, camera traps deployed in backyards
  • Cameras deployed 2X per season in each backyard for 7 days at a time
  • 2 cameras in each yard per deployment (at the same time)
I realize that I will have to account for the spatial and temporal autocorrelation, and that they can't be treated as independent samples, but having 2 cameras per deployment may give me a unique advantage to modeling detection. They were always deployed in roughly the same areas of the yard with roughly the same amount of cover and other habitat metrics. Should I be utilizing the multiple season functions, the abundance-informed functions, or another type of function?
Thank you for your assistance!
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I am also looking same question description for my camera trapping data.multiple species and multiple season.
each camera duration of each species divide in a week.each week let's five presence of bears.you need consided 1.its means for first week your dectection is one..then check red fox week one..let's suppose five detention.but you need consided 1.then second week for each species and each season..RPRENCE or presence you can uses.Gamm. model you can used
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I just read that AA lithium batteries last longer than Alkaline ones. Thus, I want to check my camera traps ones every six months so as to cut cost. Hence I'm interested to know how long they can last?
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Thank you very much guys! I will consider your recommendations.
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Hi all,
I'm just wondering about ebird. Everyone can see this initiative has been very successful gathering together information from different people about the location of bird species. Considering that... why ebird does not include other classes?
I have seen many citizen science projects like emmamal, mammal web, liveandes, etc... that try to follow what ebird does, but I'm not sure if they will be able to have the impact that the first has, well ebird has years working this.
I know it's easier to see birds than other species, but people who work with other classes should have sightings about the species that they work with. So at least we could start gathering that information together, in only ONE project, for both increasing the impact of our research and involving citizens.
so... when ebird will include other classes? why not using same platform for gathering together information about other taxa? By the way I know "naturalist" tries to do that, but I'm not sure if they have the impact of ebird
(I hope a nice discussion will emerge from this)
cheers
nicolas
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There are many other options than eBird for a wider species range. Here in Europe Observation.org (www.observation.org) is the most popular after 15 years, with 100 millions observations and 100.000.000 users. It is international, and it is growing fastly. Its mobile apps are amazing for professional and amateur naturalists, with much more data quality than eBird.
Regards
Julio Rabadán González
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What would be the best grid size for pres/abs survey of snow leopard using camera trapping in the Himalayas?
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Ganga Ram Regmi, an old question, but it popped up on my feed.
Defining your grid relative to average home range size for an occupancy study is one option, but it doesn't have to be. It's something that has crept into the literature (particularly for big cats) and stems from a desire to interpret the level of occupancy as proportional to abundance. There's no theoretical reason why you have to do this.
You can define your grid cell size however you want, and I often think it's actually better to define your cell to be smaller than a home range size, as I describe in the video Jeffrey J. Thompson mentioned (thanks for the plug;-) ).
If resources allow using camera traps, then in the first instance I'd be considering using SCR for snow leopards, in which case you want multiple cameras per home range to get information about spatial movemement.
Hope that helps.
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We have two large camera trap data sets (tropical and temperate forest), which I would like to use for estimating animal density. Which are the available methods? Strengths and weaknesses? Thanks
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A good place to start is Chapter 6 here:
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We want to study the pollination of a tropical liana species by bats. In order to estimate the visitation rate of bats at the flowers, we would like to use camera traps. Does anyone have experience with using camera traps for trapping small and fast bat species and can recommend a brand (bushnell, cuddleback, Reconyx etc)?
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It's incredibly hard to work with bats in the wild using camera traps. Most successful field researchers prefer to use custom-made systems composed of cameras, triggers, and sensors. I suggest talking to Prof. Tschapka, from Ulm University (Germany), who gets very nice results: https://www.uni-ulm.de/en/nawi/bio3/apl-prof-dr-marco-tschapka/.
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Dear People,
I have data, recorded by a set of 12 cameras in a 5x5km grid, with 1 camera position in each cell for every month (July-December, 4 positions in total/per grid cell). These positions are spatially dependent because of the small grid size and greater homerange size of the target species: Ursus arctos.
My question is, if I can conduct a single season occupancy model for that kind of data, although a requirement seems to be spatially independent sample sites,
or if I should use spatial capture-recapture models (SCR) to analyse habitat selection and spatial behaviour instead?
Another question is: how many trap days should be considered as one repeated visit (occasion- K) for the occupancy model? (3-7?)
Last but not least: does anybody know, where to get daily temperature and precipitation data for Greece :)?
Thank you so much
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I like this discussion
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Humbly seeking methods of analysing the data collected through camera trapping.
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Hello Jigme,
Considering the fact that clouded leopards are quite elusive, I would encourage you to go for occupancy modelling; if you have site and survey covariates, that would be amazing.
And yes as @Ashish mentioned you could use your location data to plot MCPs to look at the distribution pattern
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I've done some camera trap work as an undergrad and I'm looking for a postgrad project. This looks interesting.
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Thanks :)
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Hi,
we have placed numerous camera traps in an African savanna to monitor wildlife diversity. Although we tried to avoid such situations, in some locations we have quite a lot of grass in the background, triggering the trap constantly. I wonder if there's someone with experience in savanna camera trapping and whether this can be eliminated in some way, or should I just accept the thought of going through millions of pictures of grass :) My main concern is not so much the amount of empty photographs as the problems linked to that - full SD cards and batteries running out, therefore loss of data. Does anyone know whether lowering the sensitivity setting could influence the probablility of capturing some animals?
I will be happy for any thoughts and advices on this, many thanks!
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Hi,
My experience is in forests, not savanna, but there is always that twig with high self esteem that thinks it deserves to be photographed, a lot.
Altering the area (cutting grass or whatever) might alter behavior and area usage.
Lowering picture quality might jeopardize positive ID.
Best thing to do, get the SD card with the maximum capacity supported by the camera and change it as often as needed. If possible, connect camera to a car battery, if allowed, instead of using regular batteries.
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For my project, I want to calculate relative abundance for a range of different species. I am using camera traps (10 sec video, minimum 10 sec interval) to collect data.
THE PROBLEM
I know that usually with camera trapping, a video is independent if the animal is not counted again within 30 minutes.
This works very well with all the solitary animals. But now i have a problem with peccary (collared and white lipped). They are very important for this project. And they are also the only two species that live in (sometimes large) groups.
Now I have times where within 5 minutes I have multiple videos of a few peccary traveling from one side of the frame to the other side, so to me it is clear that this is a large group passing by my trap but based on the 30 minute rule I can only count 4 because that is the maximum of peccaries in one video. So I am worried, like this I will underestimate peccaries.
MY QUESTION
My idea is now, to apply the 30 minute rule but to make an exemption when I can see they are all traveling past and not stopping.
Would you agree with this idea or do you think I should do something different?
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I understand you want to count each solitary species in an image as one individual. At the end you have total animals observed for that species.
Any collared peccary (one or more) in an image can be counted as one collared peccary *group*. Same for white lipped. At the end you have *total groups* and you multiply by mean number in a group for that peccary species.
Then you also need an estimate of peccary group size. This cannot be obtained from your camera traps because they 'see' only part of a group and it is not possible to determine if it was a large or a small group.
Perhaps you can get mean group size from published research, or 'typical group size' from visual observations. Alternatively, you could set up some separate cameras with wide view and longer recording duration, then count the number in each peccary group that passes the camera and take the mean.
Good luck with your project.
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Hi, I'm looking for camera traps most suitable for my research in the African savanna ecosystem (in South Africa). I need a trap with white flash, fast trigger speed and preferably long battery life. The higher the image quality the better. The price can be higher if it has all these specifications.. Does anybody have any experience with camera traps in savannas or have any recommendations in general?
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Hi Klára
You are very right that with IR cameras individual recognition is painful and you may need to discard many photographs. If you are still using Reconyx, please try the following setting:
Sensitivity: High
Night Mode: Fast shutter
We were using Reconyx Hyperfire HC500 for tigers, but as I mentioned many pictures will be blurred and difficult to identify.
Considering your requirements, you can try Cuddeback C or Ambush models (white flash). The shutter lag is very less (0.25 sec), and they have a considerable flash range (40-45 feet). But in higher temperatures (>50 degrees C) battery might get exhausted faster than usual (4-5 days depending on the number of night photographs).
Cheers,
Ayan
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Hello everyone,
I am planning to perform a camera trap study to observe wild boar activity patterns in an agricultural landscape. In the attachment you see the forested areas (n=136) within the study region which is where I want to place the cameras following a grid pattern. But area sizes vary between 0.000015 and 440 ha. 68 areas are smaller than 5 ha, 34 smaller than 2 ha.
And here come my questions: How to treat all those small areas? Take them into account or maybe not? Cluster them to a certain total size? Step away from systematic camera trapping and check each small forest patch on the ground regularly for signs of wild boar presence instead? What would then be a suitable minimum area size to use camera traps?
Are there studies that figured out something like a minimum size of a permanent wild boar forest habitat?
Thank you very much in advance for your input!
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As others have alluded to - the threshold size of resources wild boar need to survive includes food and shelter, and as a mobile species they can assemble their needs across disperate elements of the landscape. A bit of food here, a bit of shelter there. All this I'm sure you know. More complicatedly you'll need to define the unit you're trying to measure - probably not indidiuals so sounders? - or larger? If larger (i.e. some consistent unit of space) some sort of biased flexible grid is probably your only hope unless you have prior information about how they use space - with some species this can be presence of particular food plants or maturity of woodlnad patches - boar use everything so when we've modelled boar in real landscapes we use irreglarly shaped randomised units which capture aggregations of wood and woodlot and scrub parcels - in our case ususally at the scale of 2-5 sounders (i.e. 20 non-juvenile females when we predict population growth). As I'm sure your work will indicate - units with more wood have more activity (i.e. are better?!) - the basis of infering carrying capacity - but that all units could sustain boar. If you want to map density/quality/activity at the scale of individual sounders you might need alot of fefort.
Word of caution - your boundaries are real to you but not the boar - buffer out by a sensible distance to capture valuable resources just the other side of your red line - unless it is some real geography that you think may constrain the daily movements you ascribe to home-range formation - roads - big rivers etc
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Do any of you know literature/ evidence for this? In a small scale test with camera traps on carcasses, those of predatory birds were untouched. This is only an anecdotical observation, but I was wondering if there is something more to it, and I couldn't find any studies.
Thanks in advance
Kristijn
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Hello,
This seem to be true: you can have a look at these studies.
Kind regards
Damien
- Carnivore carcasses are avoided by carnivores. June 2017. Journal of Animal Ecology 86(5). DOI 10.1111/1365-2656.12714
- Invasive carnivores alter ecological function and enhance complementarity in scavenger assemblages on ocean beaches (http://onlinelibrary.wiley.com/doi/10.1890/15-0027.1/abstract)
- Abernethy, E. F., Turner, K. L., Beasley, J. C., DeVault, T. L., Pitt, W. C., & Rhodes, O. E. (2016). Carcasses of invasive species are predominantly utilized by invasive scavengers in an island ecosystem. Ecosphere, 7(10), https://doi.org/10.1002/ecs2.1496
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I want to compare the detection frequency of various mammal species across 4 surveys. The survey effort ranges from 1-8 months. Should I only use the same amount of survey effort from all surveys for the comparison (i.e. the first 30 days) or if I am using the detection rate/100 trap days, is it acceptable to compare variable survey periods (excluding seasonal changes)?
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If you are using a population estimation technique such as occupancy, distance, or mark/recapture sampling you could add survey effort and/or seasonality as covariates influencing detection probability.
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I´m planning to evaluate abundance of this terrestrial bird by camera trapping. Any help will be very useful.
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Were you ever able to find home range estimates for Crax rubra?
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When calculating the number of independent events and trapping rates for a camera trap study, I used a specific time interval between sequences to determine independence for single individuals of the same species. However, what to do with gregarious species? If in a sequence there is more than 1 individual of the same species (even if I cannot ID them individually), should I count this as 1 event or count the total of events according to the number of individuals?
This is important when calculating trapping rates as they can vary a lot for large groups like Mangabeys and chimpanzees. I have only found 1 paper that mentions specifically this issue: Monroy-Vilchis Octavio et al., Fototrampeo de mamíferos en la Sierra Nanchititla, México: abundancia relativa y patrón de actividad. Rev. biol. Trop., 2011 Mar; 59(1): 373-383.
Usually the type of definition for independent event I find are similar to this one: “Consecutive photographs of the same species at the same site were deemed independent when there was at least 1-h interval between them” without specifying what happens when more than 1 individual is recorded in the same sequence.
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Hello Rosa,
What kind of software do you use to analyse the data? In my team, we use Camera Base (http://www.atrium-biodiversity.org/tools/camerabase/), which allows you to specify the number of observed individuals for each photo/video and if it is a social group. So regarding your question - we would count it a single independent registration of a group of n individuals.
If the species is gregarious then you're essentially working with group trapping rates, rather than individual trapping rates. Having recorded the size of the observed groups you can then analyse this data further depending on your question/s (e.g. are smaller or larger groups captured more frequently).
Hope this helps!
Elitsa
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I am trying to calculate whether my sampling effort was enough based on a species accumulation curve for a camera-trap study using the software R. Any tips on what script to use or how to organize my data accordingly?
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In the book "Camera Trapping for Wildlife Research" ( chapter 5. Presence/absence and species inventory) we developed an R script to calculate species accumulation curve. R script can be downloaded from https://www.dropbox.com/sh/5w4y6u7uq2mc2i3/AADjdBCrN_7tAg-UHAbhf8sFa?dl=0
best regards
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I have gathered around 30 videos/images of unique cats around my campus using camera traps that were placed randomly based on a grid system. Is there a way to turn this data into an estimate of population abundance/density? I've found this article below that lists over 10 different models that can possibly be used for this purpose in a very organized table, however I am not a statistics guy. Any guidance would be greatly appreciated!
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Hi Mike. If your camera are located in a "correct" distance (allowing you can detect the same individual in several camera-trap) you can use spatial capture-recapture. You can use MLE (secr: http://www.otago.ac.nz/density/SECR.html) or Bayesian approach (https://www.elsevier.com/books/spatial-capture-recapture/royle/978-0-12-405939-9). Attached you can find a paper (also about cats!). If you need the codes, please let me known.
Best,
Jose
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I'm in the early stages of investigating the role of a particular small tree in forest, comparing animal use of it with close by areas (30 to 50 m away in the same forest). Home ranges of the animals far exceeds this this distance. Estimates of animal populations, density, occupancy etc. are peripheral to my study. I'm interested in how many visits each tree gets by different species each day. I don't care which animals visit just how often they interact with my target trees. Struggling to find relevant CT literature and methods.
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Please you need read a recent review of methods by Caravalli et al. 2017. A review of camera trapping for conservation behaviour research. Remote Sensing in Ecology and Conservation. DOI: 10.1002/rse2.48.
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Hello everyone,
I want to relate environmental variables and human factors to presence data obtain with camera traps, would it work to randomly generate pseudo absences from the available environmental variables?
Thank you for your input
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If you are using site occupancy models to deal with detection probability, what is the reason to create pseudo absences? If you want to include some environmental variables and human factors in your model, you can do it using covariates (eg with unmarked, presence or even in BUGS).
Best,
Jose
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Hi all, 
We have many thousand of empty pictures triggered by grass/tree movement in our database and we are simply looking for a way to filter them out.
We don't need software that can identify species or deal with metadata, just something that can detect empty pictures for us. It would safe about 95% of our time...
Thanks!
Stephanie
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Hi there!
Ok cool thanks for the info! I'll see of someone is keen to try it on Windows.
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We are building a specialized wildlife camera to detect various small mammals (focusing on mustelids and dormice). We have included No Glow IR / black flash into the camera in order to minimize the influence on the animals.
We are pretty convinced that the animals mentioned cannot detect our flash emitting light at 920 nanometres, but we cannot find any literature on this subject. Can anybody give us a hint?
Thanks in advance,   
Nils
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Hi Nills
Best of luck
df
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We will start soon a 1 year (at least) camera trap project, where the main target will be mesocarnivores. Unfortunately, some animals like mongooses don´t have spots or truly individual marks and many pictures might be blurred, especially at night.
The idea is to use tags (e.g. hear tags, hair cuts, etc.) that will increase the chance of individual identification, even in worst conditions!
At the same time, we will be conducting box trapping sessions to capture several individuals.
Can someone suggest any easy and durable method to mark animals with the lowest impact possible?
Thanks a lot in advance
Best Regards
Filipe Carvalho
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Hi,
In my experience, there is not a good way to mark the animals like mongoose. Hair cuts are temporal, and not very useful. Hear tags would be great, but they come off very soon. Maybe the best way is a plastic collar with geometrical marks. In this paper I've used spatial counts and I've marked (telemetry tag) only one Egyptian mongoose, but was enough to estimate the density.
Best,
Jose
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I am studying a threatened species of mammal (Philippine mouse-deer) and capturing and marking them is not advisable because they are prone to trauma and stress. I proposed studying their population by camera trapping but I need to individually recognize them so I wont commit a double counting of individuals. Are there any non-invasive ways on how to estimate their population ? and is there anything I can do to avoid double counting? Thank you.
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Kindly see the ideas suggested here in this informative abstract by Gursky,  Salibay and Cuevas.
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I have some Cuddleback camera traps and a problem with theft (the Reserve gets a lot of foot traffic). Does anyone have tips on cheaply discouraging thieves? I can't use heavy lockboxes as we have few sturdy trees around. 
Thanks! 
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 You might find some inspiration in the link provided below.
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I am looking for Reconyx HC600-like, infrared and movement triggered camera traps (weather proof) that record video. The idea is to set them up at focal plants to observe/record frugivory events. Has anyone tried particular models with success in the field?
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Oliwia,
I am trying to research feeding of berries on frangula alnus using camera traps. I used browning strike force elite trail camera. Got some video of robins at 6ft distance from tree crown but I suspect videos of robin were incidental to other trigger events eg wind triggering branch movement. This has had big implications for my research.
Whatever model you purchase it would be worthwhile testing it at feeding stations that attract robins or other similar sized birds at different distances . Same goes for any species of interest eg if its a mammal try testing with permission at a pet farm that may have it.  I am now testing for detection rate using this method post field work. It would have been better if I had done it before hand but circumstances didn't allow. Sometimes you only know about pitfalls after you spend time and money on equipment and effort.
Also you should be aware that my 'incidental' footage shows robins flying into frame and picking berries on the wing and flying out of frame in less than 2 secs. The time in and out of a field of view that the robin enters may (depending on the activity) be too short  for your trail camera to capture video or photos. Your photo that is blank may have just missed the action or activity by the robin. This could be the case especially if you need to be close to the species for the camera to detect it which will mean a small field of view.
Also you may like to  search for the following useful papers. the first two are particularly useful I think.
 "Identifying Performance Differences Among Trail Cameras Used to Monitor Forest Mammals" and
"Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes"
and
Management and Analysis of Camera Trap Data: Alternative Approaches
and
An Open Standard for Camera Trap Data
and
Random versus Game Trail-Based Camera
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I am trying to get a handle on the thousands of photos I have on our camera traps, and need to include an extension rule for the naming files on ReNamer. Our camera stations are set to take a photo when triggered, and then another two pictures at two second intervals. If an animal lingers in front of the camera the first picture of the new set is taken at the same time as the last photo from the previous set. I would like to make a rule where the photos are all named with the photo number (1 2 or 3) to avoid having file names duplicated.
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Hi Laura,
I haven't used this tool. But in general I use python scripts running at the background to rename the files. Anyways, please use the Scripting and Timestamp method to accomplish your task. Maybe you have to write a batch file that does the task you want. 
Timestamp will help you to take pics with Date/Time/Year and each file will be uniquely named,
If this is what you are looking for, 
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I am currently working in Cameroon on wildlife assessment with camera-traps, aim to compare faunal biodiversity between 4 different land tenures regimes. The objective is to quantify afterwards diversities indices between 4 sites. After discussions with specialists, I would like to have your opinion. I plan to divide my 44 cameras into 4 grids, corresponding to my 4 land tenures regimes, during 3 months. Cameras will be placed with a distance of 1.4 km between each other (TEAM protocol). I have 11 cameras available for each grid, but I have an important question about one of them: one of our land tenures regimes is composed of 3 distinct community forests of 5,000 hectares each.
We have three possibilities concerning the distribution of cameras for this land tenure: (i) we can use 3-4 cameras in each community forest during 3 months, (ii) we can set up 11 cameras in each community forest one by one and each during 1 month (but it will not be possible to keep the 1.4km distance between cameras, considering the small size of community forests), or (iii) we can put the all 11 cameras in only one community forest during 3 months, but taking maybe then less heterogeneity of landscape patterns.
Would it be better to maximize the sampled zone with a maximum of time and a minimum of cameras, or to reduce the time and put more cameras in each sub-zone? Are 700-800 camera-trap days ( < 1000 camera-trap days) enough to obtain valuable data ?
Thanks a lot!
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Many thanks for all of your feedbacks!
Hein, forest elephants are not our only studied species. We focus more broadly on forest large mammals, such as forest antelopes, small primates, gorillas, chimpanzees and forest elephants. We point our cameras to animal tracks.
Mary, your recommendations exactly correspond to our first sampling plan for the “community forests” land tenure! We are just still wondering if it is not a problem to use a different design of camera grid for this land tenure (split in 3 sub-grids), compared with the three others where we will use regular grids of 11 cameras.
Fructueux, oui chaque forêt communautaire fait entre 4000 et 5000 ha, mais elles ne sont pas contigües. L’idée de diviser l’échantillonnage des 11 caméras entre trois forêts communautaires distinctes relève d’une perspective d’échantillonnage relative au régime foncier étudié (en acceptant une certaine variabilité due aux différences intrinsèques entre ces trois forêts communautaires), et non une étude du terroir au sens propre. Effectivement, c’est un problème d’installer une grille de 11 caméras dans chaque forêt communautaire durant un mois chacune en alternance, et nous éliminons donc cette possibilité. Il reste donc à voir si l’utilisation de 11 caméras dans une seule grille dans une seule des forêts communautaires serait plus pertinent ou non que d’utiliser 4 caméras par forêt communautaire avec une logique « agrégation par régime foncier ».
Kalinga, thanks for this confirmation and those recommendations! I agree with your comment!
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Hi everyone
We would like to use trail cameras to record the behaviour of small carnivores at night. No need to say that we have a limited budget. The latest entry-level Bushnell model (Essential E2) does not allow to take video-clips longer than 15 s at night with 3 s trigger interval, whereas the Essential allowed up to 1 min with 1 s interval (this is what we call progress...). We are therefore looking for cheap but reliable alternatives. I found good reviews on the Bestguarder DTC-880V/SG009:
N.B. Apparently this model (or a slightly modified version) is also marketed under other brand names such as TEC.BEAN (and maybe XIKEZAN).
I also read some positive feedbacks from buyers on Amazon but noticed that a few people mentioned that the nocturnal video-clips and pics were not necessarily of good quality (i.e. "grainy").
We were wondering whether any of you have used this trail camera and if so, what is your opinion on/assessment of the quality of nocturnal video-clips?
Also, do you have any feedback on the reliability of this brand(s)/model(s)?
Thanks in advance for your precious assistance.
Emmanuel
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Hi Emmanuel
Small carnivore behaviour is a specialist and challenging application where nobody has done much camera trapping - the big markets are deer hunters in the USA and researcher want still pictures to do population estimates. There are some papers from Australia and New Zealand, and recent papers on interspecific scent marking, in Santa Cruz, Panama and Botswana that I can send you if you have not seen them already.
I have done some small carnivore camera trapping with mixed results. In my experience the most important feature is trigger speed - at ranges where the image of a small carnivore is a sensible size; out to about 5 or 6 m from the camera, a 1 s trigger delay, added to PIR sensitivity being lower at the edges of the detection zone means that videos begin with the animals already leaving the field of view. Fortunately faster triggers (0.5s) are now standard. If you want to record behaviour that goes on for a while you need long videos (with the disadvantage that they chew memory and take along time to review) and a fast recovery between videos or sod's law will determine that the camera will miss the critical bit !.
Among older cameras Bushnell Trophycams struggle with detection when it is hot, and the video quality is marginal. Stealthcams are way too slow.
Reconyx Ultrafires produce very good videos for a very high price, and have a slow response and recovery. Spypoint 11Ds, at abut 1/3 the price of the Reconyx have very fast triggers and recovery, but their video is not as good. Browning have three new models out that look interesting. Their Strike Force Elite HD is mid range with mid range perfomance but seemed to have a dead spot about 5m out.
Putting it diplomatically; the two review sites you link are not as objective as could be wished.The most reliable reviews are those of TrailcamPro's site; http://www.trailcampro.com/, but even they too are in the business of selling trail cameras, so they tend to look on the bright side.
There is a sudden explosion of mid-range camera traps like the on you are considering. It is likely that they are being produced by the same Chinese manufacturers as make the established brands, so in principal there is no reason why they will not work as well as the established brands. What I do notice is that the price on Amazon is about the same as for Bushnell's, Brownings and Spypoints with similar performance, so you are not saving money by going for a new brand.
They quote a very long detection range, but they could have achieved it with a nice cold background and a large target like a human. It is not relevant to recording small carnivores against a hot African background, - I have seen a family of Selous mongoose playing for 5 min or so 4 m from a Bushnell Trophycam (the old model) in the early evening with not a single image captured !! At 20 m a small carnivore will be a tiny speck anyway, especially with the 90 degree field of view. Unless there is autoexposure control, very bright IR lights are actually a drawback for small targets close up because all you get is burned out images. 
Price and performance specifications are not good predictors of actual performance in the field - you really need to try out an actual camera, but that gets very expensive very quickly. It would be encouraging if the suppliers had enough faith in their products to make them available for testing for research applications.
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Hi All,
I'm setting up an experiment following this design: a 10x10m arena divided in 4 quarters (with sticks delimiting all quarters), and would like to record videos of who (kangaroos marked with carved color collars and colour eartags) feed on the area, and for how long...
What do you think would be the best device to get such recordings? I was thinking of using camera traps (potentially one at each corner of the arena) but I'm thinking of the following limitations: battery life (cameras would stay on site for 8 to 16h), quality of the video (that would allow animal identification), and especially trigger/detection sensitivity, as I would need it to record continuously as long as an animal has its nose within the area, even if it doesn't move much...
Any suggestion?
Thanks a lot!
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If you look at some of my previous answers on this subject. I have used a small CCTV system where several cameras are connected to a single hard disk recorder (DVR). It can be run in the field from batteries but is not ultra portable (DIY hook-up). However a fairly basic CCTV such as the one I have used is based on video motion detect (i.e. it detects an on screen movement in the image, not a PIR sensor as with many trail cameras), you can have two (or more) cameras running and have one set to motion detect and another to record constantly.
The motion detect would enable you to count the number of times it was triggered by an animal (visits) and the constant record would enable you to obtain the full footage for however long the animal was present. Alternative just do constant record and then watch it to count visits and observe, although I think using the two in combination might be more useful.
Set up the cameras so that the area of interest is all within the field of view and you can also potentially mask the areas outside using the DVR software so that they do not trigger the motion detect. As a guide two cameras and a DVR should run constantly for several days on a couple of 12v leisure batteries (100Ah). The size of your area suggests you might need more than two cameras to ensure good coverage, but I'd suggest that a single wide angle camera set further back could do the motion detect and you could have several other cameras covering sections of the study area on constant record. DVR's tend to come in 4 camera and 8 camera versions and occasionally more. Logistically it's the batteries that are the big problem in terms of portability and practicality, if AC mains electricity is available then that problem is solved.
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I intend to begin live trapping efforts on a carnivorous lizard that has yet to be consistently trapped. Some efforts have been made to determine bait preferences with live traps, but successful trapping is so low and with no statistical significance.
Has anyone used baited camera traps to determine bait preferences? Would the animal need to consume the bait for it to be considered a success?
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I'm currently looking at a range of baits to attract animals to a specific model of kill trap. As well as being interested in whether animals find one bait more attractive than an other I also want to know which species show an interest in the bait so we can assess potential risk to non-target species. One problem with not catching an animal is that in the absence of any other information you don't know if you didn't catch it because the bait wasn't attractive enough or because the animal wasn't there in the first place. We have used motion triggered CCTV to record animal activity in the vicinity of the trap. It is surprising how many animals of even the target species walk straight past the trap/bait as if it is not there or give it a brief sniff before walking away. Taking this approach for an initial trial might give you a better idea of the encounter rate vs the capture rate and might reveal some aspects of animal behaviour that could help you improve trap performance.
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I am having difficulty finding ways of getting camera traps set up at canopy level (looking for primates) without tree climbing equipment. Any suggestions? 
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Thanks for your answers. The camera traps will be fixed in place and left for multiple days. Do you possible have any papers which have used these techniques?
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Hello there,
I am struggling to compare the results of the Shannon Wiener Index between two seasons. I have done the indices between camera trap locations and two seasons (i.e. Location1;  Wet = 1.92 vs Dry = 1.66, Location2; Wet = 1.94 vs Dry = 1.88 etc). How can I compare the statistical significance between these two seasons and locations? I am using R albeit a novice... The same question goes for the Simpson's Index. Any help would be greatly appreciated!   
Many thanks
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I don't think statistical comparisons of Shannon Weiner indices are biological useful, since you can get the same value in multiple different ways, e.g. high species richness and low evenness may give you the same index value as low richness but high evenness. I'd compare richness and evenness separately so you know where the difference is.
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Hi. I have count data from camera traps and want to assess if there is a relationship between capture rate and a covariable. When i standardize counts per number of trap nights, the variable gets continuous. Is it okay to run GLM with Poisson or negative binomial dist even my count data is now continuous? If not, is there a way around this problem?
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Dear Ramiro,
If your raw data is count data with zeros included, I would not advice you to transform it into continuous data before analysis. Instead, as you say, the Poisson and negative binomial GLMs are excellent  starting points for modelling your data. I would neither (at this point) start thinking about zero-inflated models or hurdle models - zeros are a common and perfectly sensible outcome for Poisson and neg. bin. processes with low expectation.
There most common way to properly go around the problem of varying effort between different data point (here counts) is the use of a so-called "offset variable", which by definition has an effect (regression coefficient) equal to 1. In log-linear models (with log-link; such as the Poisson and neg. bin GLM) you put the natural logarithm of a measure of effort as the offset. In your case it would be offset = log(trap.nights).
Hope this helps!
Best wishes,
Andreas
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I wish to use trail cameras in my teaching. The course is about vertebrates and the images from the trail cameras will be a learning resource among others. The main goal is that the students learn species identification. 
I would like to get suggestion for trail camera software for photo management and sharing with students.
Most important features: 
  • Simple structure with camera trap as main folder and with subfolders for each species.
  • Accessible for the students online
  • Password protected (only viewing). 
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Camera Base by Mathias Tobbler is free and works quite well . Has some minor details.... but Im sure he will be quite happy to receive feedback.
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I sampled a community of terrestrial mammals through camera traps in eight different sites and I would like to calculate functional beta diversity using a relative abundance index of species. I am using analysis suggested by Leprieur et al 2012, but I think that it is not accounting for abundance.
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See: Carlo Ricotta & Sabina Burrascano, Prestia 80: 61–71, 2008 
Beta diversity for functional ecology :-)
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Camera trapping has been used extensively for individually identifiable animals such as Tigers, Leopards etc. But is there any possibility to use camera trap data of non-identifiable animals such as sloth bear can be used for abundance estimation?  
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Hi Ramiro. Of course you can use N-mixture or RN models, but you need to take in account the key assumptions:
1- Closure assumption
2- No false positive errors
3- Independence of detection (are your CT correlated considering the target species?)
4-Homogeneity of detection among individuals
In RN models you also assume that the abundance is the main source of heterogeneity in detection
I recommend you this paper:
Dénes, F. V., Silveira, L. F., & Beissinger, S. R. (2015). Estimating abundance of unmarked animal populations: accounting for imperfect detection and other sources of zero inflation. Methods in Ecology and Evolution, 6(5), 543–556. http://doi.org/10.1111/2041-210X.12333
Best regards,
Jose
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I am looking to collaborate with a project that involve topics in my study field as mammal ecology, camera traps, management, invasive species, ecosystem restoration and conservation. I have a few weeks in May 2017 and I am open to collaborate in any country of southeast Asia.
Thank you.
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Hello Sebastian,
I am a marine mammal researcher based in the University of St. La Salle in Negros Island, Philippines and a friend of Dr. Liao. I've been involved in some terrestrial fauna research as well, and I have colleagues working for a foundation involved in terrestrial fauna conservation. Unfortunately our website has little information as of the moment, but you can e-mail me at makoy28_delapaz@yahoo.com.  
Regards,
Manuel
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We are recording the behavior of large bats in caves with IR cameras, but this includes a lot of cables and batteries to be able to record them for at least 10 hours. I would like to know if it possible to use camera traps (bushnell, cuddleback, Reconyx etc). What I understand is that the they (some) are able to record for half a minute and reset for a few seconds. Does anybody have experience with using camera traps for continuous video recording?
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Hi Ivar,
as it was previously stated, trap-cams are not intended for this use. Instead they are made for long term "monitoring" a field recording events triggered by the presence of an animal moving across. However, I recommend you to just select some trap-cams based on the quality of their video (main issue since they tend to be low on resolution), and download their manuals to check the recording modes. I am familiar with Bushnell, and their cameras have a "Field Scan Feature" that allows to do what you look for. This is to record video/or stills, during a preset range of hours each day, for a preset interval and duration (video) without requiring the trigger from an active animal. If there is an animal, during the "interval" it can trigger as well the record.
To my knowledge you could setup the camera to work between a start and stop time, with a short interval (1') and a duration as long as possible (60").  This would provide a cheaper and simple solution, but again you have to check if the video quality of these cameras is enough for your study.
Another solution may be to use an action camera (e.g. GoPro or cheaper clones), replacing the lens and removing the IR filter that covers the sensor (there are some companies that do this / or check tutorials on youtube). This would allow the camera to record IR, getting high resolution in a smaller factor than a modified DSLR or CCTV setup. You still would need to provide external IR light (plenty of cheap options on eBay / e.g. IR led ring).
EDIT: another option that may help you is to move from IR into Thermal video. Doing it, would avoid any need of external lighting. A very simple way to implement this (and avoiding "Flir" costs) is to use an android phone (easy to supply with additional energy + microSD mem cards) with a thermal camera. I recommend you to check the small Seek CompactXR camera (about 200 USD) for this purpose.
kind regards!
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I am interested in using cellular equipped camera traps to monitor live traps set for carnivores in a Bornean rainforest with partial telephone coverage. My current thoughts are to use cameras with a timelapse function, as opposed to relying on images sent following a triggering event, to help avoid false negatives. Has anyone tried this approach, or does anyone have experience using any of the current cell equipped camera models in rainforest conditions? 
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Thanks Rafael for you offer to spread my question among your network - that would be helpful. Many thanks for your info, Dave. I will definitely need to test these cameras in situ to see if the approach is feasible.  
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My objective is individual recognition in camera-monitoring of nest attendance by Pied Imperial-pigeons. I've tried placing cotton pads with temporary hair colour in the nest. This produced faint marks at best, sometimes no mark. Marks were hard to see, mostly hidden under the sitting bird, quickly lost in rainy weather. I'd really appreciate information on suitable color products. Also keen to get other ideas for mark application without capture. Thanks!
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The type is termed "neopastel", should be available at any arts store
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We are thinking on using camera traps to monitor pollinator visits? Does anyone have experience with using them? Do they work well?
Any advisable model at a nice cost?
Many thanks!
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Dear Joao, check for the papers of Kenji Suetsugu, he is also present here on Research Gate; you might find some technical help, while here is an excerpt of references from my database (key word "video surveillance") I find useful:
  • Azarcoya-Cabiedes, W., et al. 2014. Automatic detection of bumblebees using video analysis. - Dyna 81: 81-84.
  • Brechbühl, R., et al. 2010. Impact of flower-dwelling crab spiders on plant-pollinator mutualisms. - Basic and Applied Ecology 11: 76-82.
  • Bumrungsri, S., et al. 2008. The pollination ecology of two species of Parkia (Mimosaceae) in southern Thailand. - Journal of Tropical Ecology 24: 467-475.
  • Lihoreau, M., et al. 2016. Monitoring Flower Visitation Networks and Interactions between Pairs of Bumble Bees in a Large Outdoor Flight Cage. - PLoS ONE 11: e0150844.
  • Lortie, C. J., et al. 2012. From birds to bees: applying video observation techniques to invertebrate pollinators. - Journal of Pollination Ecology 6: 125-128.
  • Micheneau, C., et al. 2010. Orthoptera, a new order of pollinator. - Annals of Botany 105: 355-364.
  • Steen, R. 2009. A Portable Digital Video Surveillance System to Monitor Prey Deliveries at Raptor Nests. - Journal of Raptor Research 43: 69-74.
  • Steen, R. 2012. Pollination of Platanthera chlorantha (Orchidaceae): new video registration of a hawkmoth (Sphingidae). - Nordic Journal of Botany 30: 623-626.
  • Steen, R. and Thorsdatter Orvedal Aase, A. L. 2011. Portable digital video surveillance system for monitoring flower-visiting bumblebees. - Journal of Pollination Ecology 5: 90-94.
  • Suetsugu, K. and Hayamizu, M. 2014. Moth floral visitors of the three rewarding Platanthera orchids revealed by interval photography with a digital camera. - Journal of Natural History 48: 1103-1109.
  • Ueta, M. and Tanaka, K. 2006. Nest observation analysis with a motion detecting software for recorded video images. - Bird Research 2: T1-T7.
I tried the following while recording pollinator assemblage and behavior on Satureja: I recorded insect visitors for 8 hours a day (several days) with Sonny HD camera with additional battery pack and two memory cards using my tripod. Afterwards, videos were digested with iSpy software with option "motion capture" when the software recognized visitor movements and segregates video clips... For me it worked, but it takes some time to evaluate the recordings.
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Hi all,
I have a dataset from a camera trapping grid that has a low number of sites but spans a long period of time.  
The cameras have been in the same sites since 2013, and there are 64 sites over 200 square miles. The number of sites is very low when compared to other camera trapping studies, but we have over 100,000 photos.  I am interested in whether this dataset could be used to compare species diversity over time, but most of the camera trapping literature I've read has hundreds of sampling locations.  The data has already been collected and it isn't possible to add more sites.
I'm looking for advice on the best statistical approaches to use for a dataset like this. Has anyone worked with a camera trapping dataset that has a very low site sample size and what analytical methods did you use?  
Thank you,
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For species distribution modelling, the number of camera sites is optimal. Evidently, the camera sites should be unbiased. The more critical question is whether your set of environmental covariates is comprehensive and of a matching spatial and attribute accuracy (WorldClim not always is).
Our paper on predicting a post-fire tree diversity is attached for your inspiration. In the mean-time we have seen deer impacting on the post-fire development.
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any good suggestions for Camera Trap data software that can work on a Mac?
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Hi Katrina,
It depends on what you want to study. For density estimation (using my mac) I use SPACECAP and can recommend it. I have also heard great things about SCRbayes (https://sites.google.com/site/spatialcapturerecapture/scrbayes-r-package) for the same purpose. I will probably switch to camtrapR for managing camera trap data. 
Good luck, hope this helps. 
Sam
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Hi all, I've found that almost all literature relating to camera trap calculated the animals' relative abundance index (RAI) as the formula: RAI=independent event / traping days *100. My question is, why not to use the individuals concluded in each independent event as the numerator here? e.g. if we got 25 independent events concluding 30 sambar individuals of during 40 days , can we calculate the RAI of sambar here like: 30/40*100=75, instead of 25/40*100=62.5 ?
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The method you are using is a form of presence-absence sampling. If samples are no longer independent then the estimates will be biased. The degree of bias will be dependent on the degree to which the samples are not independent. If the degree of bias is the same at all sample sites then the sites should still be comparable. If not, then how am I to believe that there are site differences and your results are not an artifact of a shifting level of bias between study sites?
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I am carrying out camera trapping surveys to estimate the abundance and space use relationship of the medium sized carnivore in a protected area. I have done vegetation and ground cover surveys around each camera trap point. I have used 2 sq km grid design for deploying camera traps following the closure assumption of 60 days. I divided the study area into 4 blocks and performed camera traps for 15 days in each block containing 50 camera trap grids each. I have estimated the abundance of individual species for the entire study area using Royle-Nichole’s heterogeneity model using the program PRESENCE. Now to correlate with the habitat or ground cover data with the photographic record of these medium sized carnivores, which parameter should I use? May I use the photo captured rate of individual species captured at individual camera trap points with this habitat values or any other parameter should be considered.
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I think exactly as Christian. The occupancy and detection probability can explain the influence of habitat and antrophogenic variables upon distribution and abundance, and at the same time, it could permit detect some survey biases.
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I need to purchase some camera traps to be used at high altitude on Mt Kenya where it also rains a lot.  The traps will be used to try and photograph owls that are very shy, so I need to ensure they don't flash or emit any other light that would disturb the birds.  The photos may be taken during daytime or nighttime, but even during the day the lighting conditions are poor as it is in the forest.  I'd prefer to spend in the range of $250/camera.  I hear the battery life on most models now is good, ideally the batteries would last at least one month.  We have to carry them in backpacks up the mountain, so weight to some extent is also a consideration. I have no experience with camera traps so there may be other important features I'm not considering?  Thanks, Darcy 
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Hallo Darcy, we use ScoutGuard camera traps to photograph mammals inside and outside Kurger National Park (South Africa). We have 30+ out in the field. We have not seen the need to change brand type as we get good results from our cams. The image quality during daytime photos is great (8 megapixel cameras we actually set to 5 MP for storage purposes).
ScoutGuard (and most other brands) fall within your price range and are light to carry. There are many ScoutGuard varieties incl. ones that emit EITHER a slightly conspicuous red-coloured IR flash OR that are completely invisible. The thing with IR flashes is that they blur moving objects at night!
We put SanDisk 4 GB SD cards into ours (I think they come with the cams.) and 4x AA Energizer batteries (not incl.). These batts. can last more than one month taking hundreds of photos. If you want to check them even less often then add 8x AA batteries and the camera will remain on for more than 2 months (just check SD card size, maybe upsize to 8 GB?). An important point: the ALKALINE BATTERIES OUTLAST THE RECHARGEABLES. Another trick is to set the sensitivity of the motion sensor to "Low" as "tree triggers" (moving branches, leaves, grasses) become a problem but, still capture larger objects such as animals under this setting. We also order the protective casing that is made for these cams. Unfortunately, we had some cameras leaking with our last batch. The seals must have been faulty however, none actually stopped working: just a build-up of moisture inside battery and screen compartment. As a solution we open the rubber port hole at the bottom of the camera so moisture can drain.
Regards and I hope this finds you well,
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Especially in remote areas? Or is camera trapping sufficient?
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Hello Hannah,
when I got it right, you want detect the cats by scanning the landscape with a thermografic device? I did some experiments with thermografic cameras (FLIR and Optris) to track ground (mice, shrews) and tree (squirrels) living small mammals. My experiences are that you get sufficent images when you have the animal right in front of you (max. several meteres). When you are scanning the landscape its is very difficut to detect mammals by thermography. The most heat emitting parts of a mammalian body are the eyes, nose and sometimes the ears. When they are hidden by twigs, leaves etc. you wont see the animal. In insulating roosts it is impossible to see any heat emission (e.g. squirrels in dreys).
To demonstrate you the problems I attach some images I made last evening showning our cat in the room, under the table and on the pillow at her roosting place (all images taken in a max. distances of 2 meteres). The two-leged mammals on the sofa (distance 8-10 m) are difficult to detect: the right one working at the laptop, the left one is hidden by a newspaper... Shurely it depends on the temperature gradient between animal and his sorroundings but I think thermography wont help you. To detect present animals I would prefer camera traps or hair traps.
All the best
Stefan
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Any one with scientific papers or any leading information on carnivore density estimation using camera traps preferably data analysis ? kindly assist thank you. 
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I'm rather new to using occupancy modelling and PRESENCE, and I've come accross with this situation:
I have 12 sites where we have used camera trapping to analyse mammalian occupancy and measured several variables such as vegetation structure, patch size etc.
For one species detected, number of detections varied from 0 to 3 per site (totalling 15, which I assume should be enough for a total of 18 trapping days). After incorporating varying numbers of covariates my psis for all the sites are one of two (e.g. o.4 or 0.8), even in sites that never detected this species.Several of the AICs between models are also exactly the same, even though my covariate data varies, which I'd think should be about one in a billion chance...
With other species, my AIC between models do vary, but the psis are still very similar if only one covariate is used.
I would appreciate very much if anyone could give any indication as of why this happens.
Thank you already in advance!
regards,
Nina
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 Dear Guilaume: Interesting paper, but I see that this is very different..and SCR study that used 33 trap locations to estimate the total number of activity centers in the state space. This is completely different from occupancy estimation, which, I reiterate, does require much larger sample sizes (= sites visited) to derive meaningful estimates.
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