Searching for rare and secretive snakes: are camera-trap and box-trap methods interchangeable?
Dalton B. Neuharth A B , Wade A. Ryberg
A I , Connor S. Adams A C , Toby J. Hibbitts A D , Danielle K. Walkup A , Shelby L. Frizzell A E , Timothy E. Johnson A F , Brian L. Pierce A , Josh B. Pierce G and D. Craig Rudolph H
A Natural Resources Institute, Texas A&M University, College Station, TX 77843, USA.
B Department of Biology, Texas State University, San Marcos, TX 78666, USA.
C Arthur Temple College of Forestry and Agriculture, Stephen F. Austin State University, Nacogdoches, TX 75962, USA.
D Biodiversity Research and Teaching Collections, Texas A&M University, College Station, TX 77843, USA.
E SWCA Environmental Consultants, Austin, TX 78749, USA.
F Department of Environmental Science, Florida Atlantic University, Boca Raton, FL 33431, USA.
G Southern Research Station, USDA Forest Service, Nacogdoches, TX 75965, USA.
H USDA Forest Service (Retired). Present address: 1147 Say Road, Santa Paula, CA 93060, USA.
I Corresponding author. Email: waryberg@tamu.edu
Wildlife Research 47(6) 476-484 https://doi.org/10.1071/WR19230
Submitted: 22 November 2019 Accepted: 25 April 2020 Published: 29 July 2020
Abstract
Context: Advancements in camera-trap technology have provided wildlife researchers with a new technique to better understand their study species. This improved method may be especially useful for many conservation-reliant snake species that can be difficult to detect because of rarity and life histories with secretive behaviours.
Aims: Here, we report the results of a 6-month camera-trapping study using time lapse-triggered camera traps to detect snakes, in particular the federally listed Louisiana pinesnake (Pituophis ruthveni) in eastern Texas upland forests in the USA.
Methods: So as to evaluate the efficacy of this method of snake detection, we compared camera-trap data with traditional box-trapping data collected over the same time period across a similar habitat type, and with the same goal of detecting P. ruthveni.
Key results: No differences in focal snake species richness were detected across the trap methods, although the snake-detection rate was nearly three times higher with camera traps than with the box traps. Detection rates of individual snake species varied with the trapping method for all but two species, but temporal trends in detection rates were similar across the trap methods for all but two species. Neither trap method detected P. ruthveni in the present study, but the species has been detected with both trap methods at other sites.
Conclusions: The higher snake-detection rate of the camera-trap method suggests that pairing this method with traditional box traps could increase the detection of P. ruthveni where it occurs. For future monitoring and research on P. ruthveni, and other similarly rare and secretive species of conservation concern, we believe these methods could be used interchangeably by saturating potentially occupied habitats with camera traps initially and then replacing cameras with box traps when the target species is detected.
Implications: There are financial and logistical limits to monitoring and researching rare and secretive species with box traps, and those limits are far less restrictive with camera traps. The ability to use camera-trap technologies interchangeably with box-trap methods to collect similar data more efficiently and effectively will have a significant impact on snake conservation.
Additional keywords: endangered, infrared, monitoring, remote detection, threatened.
References
Adams, C. S., Ryberg, W. A., Hibbitts, T. J., Pierce, B. L., Pierce, J. B., and Rudolph, D. C. (2017). Evaluating effectiveness and cost of time-lapse triggered camera trapping techniques to detect terrestrial squamate diversity. Herpetological Review 48, 44–48.Bathke, A. C., Schabenberger, O., Tobias, R. D., and Madden, L. V. (2009). Greenhouse–Geisser adjustment and the ANOVA-type statistic: cousins or twins? The American Statistician 63, 239–246.
| Greenhouse–Geisser adjustment and the ANOVA-type statistic: cousins or twins?Crossref | GoogleScholarGoogle Scholar |
Bennett, D., and Clements, T. (2014). The use of passive infrared camera trapping systems in the study of frugivorous monitor lizards. Biawak 8, 19–30.
Burgdorf, S. J., Rudolph, D. C., Conner, R. N., Saenz, D., and Schaefer, R. R. (2005). A successful trap design for capturing large terrestrial snakes. Herpetological Review 36, 421–424.
Burton, A. C., Neilson, E., Moreira, D., Ladle, A., Steenweg, R., Fisher, J. T., Bayne, E., and Boutin, S. (2015). Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes. Journal of Applied Ecology 52, 675–685.
| Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes.Crossref | GoogleScholarGoogle Scholar |
Desmarais, B. A., and Harden, J. J. (2013). Testing for zero inflation in count models: bias correction for the Vuong test. The Stata Journal 13, 810–835.
| Testing for zero inflation in count models: bias correction for the Vuong test.Crossref | GoogleScholarGoogle Scholar |
Garden, J. G., McAlpine, C. A., Possingham, H. P., and Jones, D. N. (2007). Using multiple survey methods to detect terrestrial reptiles and mammals: what are the most successful and cost-efficient combinations? Wildlife Research 34, 218–227.
| Using multiple survey methods to detect terrestrial reptiles and mammals: what are the most successful and cost-efficient combinations?Crossref | GoogleScholarGoogle Scholar |
Hsing, P. Y., Bradley, S., Kent, V. T., Hill, R. A., Smith, G. C., Whittingham, M. J., Cokill, J., Crawley, D., MammalWeb volunteers Stephens, P. A. (2018). Economical crowdsourcing for camera trap image classification. Remote Sensing in Ecology and Conservation 4, 361–374.
| Economical crowdsourcing for camera trap image classification.Crossref | GoogleScholarGoogle Scholar |
Hunter, M. E., Oyler-McCance, S. J., Dorazio, R. M., Fike, J. A., Smith, B. J., Hunter, C. T., Reed, R. N., and Hart, K. M. (2015). Environmental DNA (eDNA) sampling improves occurrence and detection estimates of invasive Burmese pythons. PLoS ONE 10, e0121655.
| Environmental DNA (eDNA) sampling improves occurrence and detection estimates of invasive Burmese pythons.Crossref | GoogleScholarGoogle Scholar | 25874630PubMed |
Hyslop, N. L., Cooper, R. J., and Meyers, J. M. (2009). Seasonal shifts in shelter and microhabitat use of Drymarchon couperi (eastern indigo snake) in Georgia. Copeia 2009, 458–464.
| Seasonal shifts in shelter and microhabitat use of Drymarchon couperi (eastern indigo snake) in Georgia.Crossref | GoogleScholarGoogle Scholar |
Hyslop, N. L., Meyers, J. M., Cooper, R. J., and Stevenson, D. J. (2014). Effects of body size and sex of Drymarchon couperi (eastern indigo snake) on habitat use, movements, and home range size in Georgia. The Journal of Wildlife Management 78, 101–111.
| Effects of body size and sex of Drymarchon couperi (eastern indigo snake) on habitat use, movements, and home range size in Georgia.Crossref | GoogleScholarGoogle Scholar |
Kays, R. W., and Slauson, K. M. (2008). Remote cameras. In ‘Noninvasive Survey Methods for Carnivores’. pp. 110–140. (Eds R. A. Long, P. MacKay, W. J. Zielinski, and J. C. Ray.) pp. 110–140. (Island Press: Washington, DC, USA.)
Mauchly, J. W. (1940). Significance test for sphericity of a normal n-variate distribution. Annals of Mathematical Statistics 11, 204–209.
| Significance test for sphericity of a normal n-variate distribution.Crossref | GoogleScholarGoogle Scholar |
Meek, P. D., Ballard, G., Claridge, A., Kays, R., Moseby, K., O’Brien, T., O’Connell, A., Sanderson, J., Swann, D. E., Tobler, M., and Townsend, S. (2014). Recommended guiding principles for reporting on camera trapping research. Biodiversity and Conservation 23, 2321–2343.
| Recommended guiding principles for reporting on camera trapping research.Crossref | GoogleScholarGoogle Scholar |
Meek, P. D., Ballard, G. A., and Fleming, P. J. (2015). The pitfalls of wildlife camera trapping as a survey tool in Australia. Australian Mammalogy 37, 13–22.
| The pitfalls of wildlife camera trapping as a survey tool in Australia.Crossref | GoogleScholarGoogle Scholar |
O’Connell, A. F., Nichols, J. D., and Karanth, K. U. (Eds) (2011). ‘Camera Traps in Animal Ecology: Methods and Analyses.’ (Springer: Tokyo, Japan.)
Reed, R. N., Hart, K. M., Rodda, G. H., Mazzotti, F. J., Snow, R. W., Cherkiss, M., Rozar, R., and Goetz, S. (2011). A field test of attractant traps for invasive Burmese pythons (Python molurus bivittatus) in southern Florida. Wildlife Research 38, 114–121.
| A field test of attractant traps for invasive Burmese pythons (Python molurus bivittatus) in southern Florida.Crossref | GoogleScholarGoogle Scholar |
Richardson, E., Nimmo, D. G., Avitabile, S., Tworkowski, L., Watson, S. J., Welbourne, D., and Leonard, S. W. (2017). Camera traps and pitfalls: an evaluation of two methods for surveying reptiles in a semiarid ecosystem. Wildlife Research 44, 637–647.
| Camera traps and pitfalls: an evaluation of two methods for surveying reptiles in a semiarid ecosystem.Crossref | GoogleScholarGoogle Scholar |
Rovero, F., Zimmermann, F., Berzi, D., and Meek, P. (2013). ‘Which camera trap type and how many do I need?’ A review of camera features and study designs for a range of wildlife research applications. Hystrix 24, 148–156.
Rudolph, D. C., Pierce, J. B., and Koerth, N. E. (2018). The Louisiana pinesnake (Pituophis ruthveni): at risk of extinction? Herpetological Review 49, 609–619.
Stevenson, D. J., Dyer, K. J., and Willis-Stevenson, B. A. (2003). Survey and monitoring of the eastern indigo snake in Georgia. Southeastern Naturalist 2, 393–408.
| Survey and monitoring of the eastern indigo snake in Georgia.Crossref | GoogleScholarGoogle Scholar |
Treilibs, C. E., Pavey, C. R., Hutchinson, M. N., and Bull, C. M. (2016). Photographic identification of individuals of a free-ranging, small terrestrial vertebrate. Ecology and Evolution 6, 800–809.
| Photographic identification of individuals of a free-ranging, small terrestrial vertebrate.Crossref | GoogleScholarGoogle Scholar | 26865967PubMed |
Welbourne, D. J., MacGregor, C., Paull, D., and Lindenmayer, D. B. (2015). The effectiveness and cost of camera traps for surveying small reptiles and critical weight range mammals: a comparison with labour-intensive complementary methods. Wildlife Research 42, 414–425.
| The effectiveness and cost of camera traps for surveying small reptiles and critical weight range mammals: a comparison with labour-intensive complementary methods.Crossref | GoogleScholarGoogle Scholar |
Welbourne, D. J., Claridge, A. W., Paull, D. J., and Lambert, A. (2016). How do passive infrared triggered camera traps operate and why does it matter? Breaking down common misconceptions. Remote Sensing in Ecology and Conservation 2, 77–83.
| How do passive infrared triggered camera traps operate and why does it matter? Breaking down common misconceptions.Crossref | GoogleScholarGoogle Scholar |
Welbourne, D. J., Paull, D. J., Claridge, A. W., and Ford, F. (2017). A frontier in the use of camera traps: surveying terrestrial squamate assemblages. Remote Sensing in Ecology and Conservation 3, 133–145.
| A frontier in the use of camera traps: surveying terrestrial squamate assemblages.Crossref | GoogleScholarGoogle Scholar |
Welbourne, D. J., Claridge, A. W., Paull, D. J., and Ford, F. (2019). Improving terrestrial squamate surveys with camera-trap programming and hardware modifications. Animals (Basel) 9, 388.
| Improving terrestrial squamate surveys with camera-trap programming and hardware modifications.Crossref | GoogleScholarGoogle Scholar |
Willson, J. D., Pittman, S. E., Beane, J. C., and Tuberville, T. D. (2018). A novel approach for estimating densities of secretive species from road-survey and spatial-movement data. Wildlife Research 45, 446–456.
| A novel approach for estimating densities of secretive species from road-survey and spatial-movement data.Crossref | GoogleScholarGoogle Scholar |
Yousif, H., Yuan, J., Kays, R., and He, Z. (2019). Animal Scanner: software for classifying humans, animals, and empty frames in camera trap images. Ecology and Evolution 9, 1578–1589.
| Animal Scanner: software for classifying humans, animals, and empty frames in camera trap images.Crossref | GoogleScholarGoogle Scholar | 30847057PubMed |
