Watercolor camera in gray frame

Shutterbugs & Scientists: How digital cameras enhance our relationship with nature

The digital camera has become a staple tool in the modern travel suitcase. Today, you will see novice photographers attempting to capture stunning wildlife and landscapes at all National Parks and World Heritage Sites. So many of us haul around cumbersome DSLR cameras accompanied by their various accessories, lenses and filters so that we can remember our travel experiences through vivid 4K resolution. If you fall into this category of traveling shutterbugs, consider yourself a potential citizen scientist because you are using a powerful tool that has led to global conservation initiatives and environmental research.

Photographing ants along the Kabini River

A recent trip to the state of Karnataka, India introduced me to a tangible example of how digital still cameras are changing the future for big cats. During a morning safari through Nagarahole National Park, naturalist guide Arvind Gowda shared that DSLR camera traps were originally introduced to monitor tiger populations by capturing still photos for stripe analyzation. A secondary result of camera traps in Nagarahole National Park addressed the devastating issue of poaching. Soon after digital cameras were implemented, multiple forest offense cases involving poaching were solved using evidence from captured images. Now, due to the constant watchful eye of digital camera surveillance combined with strict wildlife regulations, poachers are less likely to act out of fear of being convicted. As a result, poaching has drastically decreased due to the fact that scientists and National Park rangers have 24/7 eyes on wildlife in the park (A. Gowda, personal communication, February 25, 2020).

Arvind is also a phenomenal wildlife photographer. Take a look at his work through his Instagram handle @arvind_gowda7.

Tiger photographed in Nagarahole National Park

Big cats and little cats alike are being monitored with countless noninvasive hidden camera traps. In 2015, scientists in India reviewed field surveys conducted with digital cameras to explore leopard cat distribution in Bhadra, BRT Tiger Reserve, Nagarahole, and Bandipur. Results demonstrated that leopard cat densities were higher in Bhadra where more annual precipitation fell. Further analysis revealed that leopard cats were frequenting coffee plantations and human settlements, possibly because of prey abundance in these areas. Results of this study can guide future infrastructure projects within India’s reserves to maintain landscapes that support small carnivore habitat (Srivathsa et al, 2015).

Digital cameras are used to monitor herbivore populations as well. In the United States, black-tailed deer have experienced decreasing populations in western states as compared to the eastern states. To analyze population densities and better understand the decline, 13 motion-activated camera traps were set up on a private ranch in California. Captured images allowed biologists to successfully identify 50 individuals and estimate a summer density of 7.7 deer/km^2 and a fall density of 8.6 deer/km^2. The important findings from this research showed again that camera traps can serve as a great help in monitoring species populations and in turn help humans make decisions about land management while accounting for wildlife habitat (Macualay, Sollmann & Barrett, 2020).

A question for all amateur and professional photographers: Have you ever returned home from a trip with hundreds to thousands of photos showing blurry and overexposed compositions? Personally, I consider a 10% clear capture rate to be a great success. Scientists using camera traps are not immune to the time-consuming tasks required to painstakingly asses thousands of individual photos, many of which contain undetectable data. While digital photographing technology has rapidly progressed, solutions to analyze and categorize the countless data images has been slow to develop (Ahumada et al, 2019). Solutions are finally evolving, and in recent years new technological functions have been released to eliminate the issue of data overload. Blurred images can now be assessed using an algorithm that computes blur percentage and automatically omits unclear images. Histogram-based analysis is used for eliminating too bright and too dark images while convolutional neural networks (CNN) uses anchor boxes and points to detect objects, specifically animals, in captured photos. These algorithms have been used to produce software programs which help wildlife researches categorize their thousands of images to discern which are useful (Tekeli & Bastanlar, 2019).

Clear example of visible tiger stripes for identification

Today, photo managing software is available for the scientific community as well as the public sector. All of us have now have access to a website called Widlife Insights, a platform that supports the global sharing of wildlife data. This software uses artificial intelligence to categorize images based on species, and the audience includes anyone with access to internet (Ahumada et al, 2019). I encourage you to explore the website through the link below.

Wildlife Insights: https://www.wildlifeinsights.org/home

eMammal is an online archive of wildlife images taken through camera traps. Like Wildlife Insights, this data is available to the public and YOU can be a citizen scientist and participate in this far reaching wildlife study.

eMammal: https://emammal.si.edu/

Now consider that you have finally arrived at your favorite National Park in the hopes of seeing the most elusive wildlife. I experienced this anticipation and uncertainty while visiting Nagarahole National Park. Multiple safari tours went out for the morning shift, but only a select few vehicles were lucky enough to spot a tiger. Again, wildlife researches share in this frustration and often must rely on luck and hope that their species of study will just so happen to meander in front of their digital camera trap. Though not a useful tool for us tourists and photographers, attractants and edible bait are sometimes used in scientific research to better study elusive carnivores that are misrepresented. It should be noted that attractants can have adverse affects on wildlife and deter animals because of human scent. Camera trap bait should only be used when the benefits of understanding a species through detection outweighs the negatives of exposing wildlife to human placed attractants (Mills et al, 2019). So, us novice photographers should remain in designated safari vehicles and cross our fingers for such rare and exhilarating wildlife sightings. Let’s keep the excitement alive!

Asiatic elephant photographed from inside safari vehicle

Finally, scientists must always consider the cost of research. Compared to more invasive tools such as pitfall traps, motion-activated digital cameras offer a cost effective approach to surveying rarely sighted wildlife. In a survey study of squamates, when extrapolated to represent a realistic scenario, a camera trap approach was estimated to cost only 23% of what more labor-intensive trapping methods require (Welbourne et all, 2019). Photography technology has certainly had an affect on how environmental research is progressing, changing the physical way in which we engage with nature as well as altering the economic status and availability of scientific research data.

I consider myself no more than an amateur photographer, just capable enough to use my Canon EOS Rebel T5i as a tool to capture images of wildlife and nature that I plan to paint. As an artist, I use digital photography to aid in seeing small details and quickly fleeting moments. For my purpose, cameras help me observe, appreciate and develop a relationship with the natural environment. Photographs allow me to study the anatomical proportions of animals, and recreating them through observational painting leaves a lasting impression on my mind so that I retain the details. An oriental magpie-robin is quick to hop about while a male Asiatic elephant must be viewed from inside a safari vehicle as he moves through the consuming forest. Likewise, a peacock’s colors and details cannot be captured by the human eye from a distance. Camera technology helps us overcome our human handicap of limited sight so that we are exposed to all the details nature has to offer. Therefore, my digital camera has become an integral piece in my ability to paint and share what matters to me most; nature and wildlife. I also use photos for wildlife identification. Admittedly, I can never remember all the bird and wildlife species seen during my travels, but with photos, I can identify them and retain the information at a later date. A final positive of digital cameras is that we can all observe animals from a safe and respectful distance as evident in the paintings below. 

Paintings completed using reference photographs

Access to digital photography also supports the global sharing of accurate and detailed wildlife images. Kait Hanson, Hawaii based travel writer and owner of CommuniKait blog, has provided me with wildlife photos she captured in Africa. While I have not yet visited Kenya, her photography has granted me detailed insight into the appearance of African wildlife. While photos cannot replace the experience of watching an animal move in the wild landscape, they can accurately share the most minute characteristics and textures of their exterior anatomical makeup. Digital photography grants non-invasive global access to the beauty of wildlife.

African elephant painted from image provided by Kait Hanson

Let us not forget the emotional impact that images leave with us. Though not necessarily quantifiable, wildlife photographers are altering the future of conservation by engaging their audience with awe inspiring images of details otherwise unseen. According to Chris Helzer, writer for The Praire Ecologist, conservation photography demands that photographers share images which tell stories and directly benefit and conserve the shared subject (2013). He shares the work of entomologist Piotr (Peter) Naskrecki as an example of how impactful photography can be. After reviewing Naskrecki’s work, I agree that his photos stimulate curiosity and wonder that will forever change the way I see some of the world’s smaller wildlife creatures. You can view his work at the link below.

The Smaller Majority: https://thesmallermajority.com/

If you have wildlife and nature photos you’re willing to share, please post a link in the comments below. Happy snapping!


Ahumada, J., Fegraus, E., Birch, T., Flores, N., Kays, R., O’Brien, T., Palmer, J., Schuttler, S., Zhao, J., Jetz, W.,  Kinnaird, M., Kulkarni, S., Lyet, A., Thau, D., Duong, M., Oliver, R., Dancer, A. (2019). Wildlife insights: a platform to maximize the potential of camera trap and other passive sensor wildlife data for the planet. Environmental Conservation, 47(1). doi: 10.1017/S0376892919000298

Helzer, C. (2012, January 22). Conservation photography in the digital age. The Prairie Ecologist. https://prairieecologist.com/2013/01/22/conservation-photography-in-the-digital-age/

Macaulay, L., Sollmann, R., Barrett, R. (2020). Estimating deer populations using camera traps and natural marks. Journal of Wildlife Management, 84(2), 301-310. doi: 10.1002/jwmg.21803

Mills, D., Fattebert, J., Hunter, L., Slotow, R. (2019). Maximising camera trap data: using attractants to improve detection of elusive species in multi-species surveys. PLoS ONE, 14(5), 1-16. doi: 10.1371/journal.pone.0216447

Srivathsa, A., Parameswaran, R., Sharma, S., Karanth, K. (2015). Estimating population sizes of leopard cats in the Western Ghats using camera surveys. Journal of Mammalogy, 96(4), 742-750. doi: 10.1093/jmammal/gyv079

Tekeli, U. & Bastanlar, Y. (2019). Elimination of useless images from raw camera-trap data. Turkish Journal of Electrical Engineering & Computer Sciences, 27(4), 2394-2411. doi: 10.3906/elk-1808-130

Welbourne, D., Claridge, A., Paull, D., Ford, F. (2019). Camera-traps are a cost-effective method  for surveying terrestrial squamates: A comparison with artificiall refuges and pitfall traps. PLoS ONE, 15(1), 1-17. doi: 10.1371/journal.pone.0226913