A frontier in the use of camera traps: surveying terrestrial squamate assemblages

Abstract

There is an urgent need to improve methods for surveying snakes and lizards (squamates). Currently, fundamental data gaps exist about squamate distributions and abundance in numerous regions. Traditional squamate survey methods are useful, but they are also resource and labour intensive. In recent decades, camera traps have provided researchers an effective, cost‐efficient and minimally invasive survey tool; albeit primarily for birds, mammals and fish. The use of camera traps for reptiles generally, and squamates specifically, has been limited. Yet, recent developments in camera trapping methodology demonstrate how they could be used to survey a squamate assemblage. Although further research is required, these developments are encouraging. Thus, surveying squamates with camera traps is a primary frontier in camera trapping.

Introduction

Camera traps have become an important wildlife research tool. Where research questions do not require animals to be captured, camera traps have been used to answer a variety of research questions on vertebrates; albeit primarily for mammals, fish and birds (O'Connell et al. ; Mallet and Pelletier ; Meek et al. ). Early use of camera traps in terrestrial landscapes most often focused on monitoring bird nests (Cutler and Swann ). Due to technological and methodological advances in recent decades, the use of camera traps has expanded to address questions of mammal abundance (e.g. Karanth et al. ), activity patterns (e.g. de Almeida Jácomo et al. ), bait take (e.g. Glen and Dickman ), behaviour (e.g. Bauer et al. ) and occupancy (e.g. O'Connell et al. ) among other questions. In addition to having broad flexibility in the type of question camera traps can be used to address, they are also more effective and more cost efficient than numerous traditional methods (e.g. De Bondi et al. ; Paull et al. ).

Despite advances in camera trap use for many species, their use for monitoring reptiles, specifically terrestrial snakes and lizards (hereafter squamates), is in its infancy. Here, we argue that using camera traps to survey squamates is one of the next major frontiers for camera trap use. As we explore, there is a general need to improve fundamental knowledge of many squamate species. Although traditional squamate survey techniques are useful, improving the effectiveness and cost efficiency of survey methods can help reduce gaps in fundamental knowledge. Recent developments in the use of camera traps demonstrate that they can be both more effective and more cost efficient than traditional squamate survey methods. Although there are various methodological questions yet to examine, we expect that using camera traps to survey squamates is one of the next major frontiers of their use.

Surveying Squamates

The lack of fundamental ecological data for reptiles generally and squamates specifically is an immediate concern. As of August 2016, the number of recognized reptile species (n = 10,450; Uetz ) was approaching that of birds (n = 11,121) and much greater than either the number of amphibian (n = 7571) or mammalian (n = 5567) species (IUCN ). Of all reptiles, ~96% (n = 9882) are snakes or lizards (Uetz ). While the number of species is impressive, little is known of the natural history and ecology of many squamates (McDiarmid et al. ). In 2016 the IUCN () concluded that the threat level to reptiles globally could not be assessed since 49% of reptiles and 50% of squamates were data deficient. There are likely a number of reasons for this data shortfall; therefore, there are likely a number of solutions to address the shortfall. One approach is to improve the effectiveness and cost efficiency of methods for surveying squamates.

There are two key requirements for all survey methods. First, the survey method needs to effectively detect the target taxa. Some methods are limited by what they can detect due to the design and function of the technique; that is, they are technologically limited. For instance, pitfall traps are less effective at detecting long snakes than small lizards, as snakes can climb out of them (Todd et al. ). Due to limitations with any individual method, many researchers employ multiple complementary methods to survey squamate assemblages (Lindenmayer et al. ; Garden et al. ; Thompson and Thompson ). Second, the method needs to collect ecologically useful data (Sutherland ). Wildlife data can be collected at three levels of biological resolution: species level, where only species are identified; individual level, where individuals of a species are identified; and sub‐individual level, where morphological or demographic characteristics are recorded (Rodda and Guyer ). The fundamental ecological data that are required to survey a particular class or group of taxa at a particular location are a species list and, ideally, the abundances of those species (Williams et al. ; Lomolino et al. ; Shine ; Silvy ). Traditional squamate survey methods can achieve the required data resolutions.

Table  lists 12 generic terrestrial squamate survey methods discussed in the literature (Bennett ; Blomberg and Shine ; Fitzgerald ; McDiarmid et al. ; Silvy ; Cogger ). This is not an exhaustive list and not every survey technique that exists is named, but most would fit within these generic methods. For example, a rock turning survey is a version of an ‘area search’. The survey methods are categorized into three archetypes. Visual methods involve searching or observing areas for fauna or signs of fauna and are a precursor to capture methods, which involve seizing and restraining specimens by hand or other device (e.g. noose pole). Trapping methods involve the use of equipment to capture specimens when the investigator is not immediately present. Camera traps are included for comparison under remote methods. Remote methods employ equipment to detect fauna while the investigator is not present in the field.

The primary downside to visual, capture and trapping methods is that all are considerably labour intensive. To execute a survey with these methods requires researchers to remain in the field for protracted periods as sampling usually needs to occur within a finite window during the day (Sutherland ; Silvy ). Even if one ignores the non‐sampling time in the field (i.e. overnight stays for logistic reasons) and only considers the actual sampling period (i.e. checking traps), labour‐intensive techniques can require hundreds to thousands of person hours to execute a survey. For example, Christy et al. () modelled detection probability of the brown tree snake (Boiga irregularis) at a 5 ha site in Guam. They used visual searches of 26 transects over a period of 109 search nights, checking each transect on every second occasion. Given the time required to search each transect per occasion (~30 min) and that searches were conducted in teams of two, Christy et al. () required 1417 h of person time for the visual search component of the survey alone. In contrast, camera traps have the capacity to increase the number of observers in the field with little additional cost. Thus, over the long term this advantage can make camera traps more cost efficient than traditional approaches (De Bondi et al. ; Welbourne et al. ).

A second major limitation with visual, capture and trapping methods is the presence of observer effects. Observer effects have two aspects. First, the term ‘observer effect’ is often used in the wildlife literature to refer to biases introduced into the data due to observer ability (Bekoff ; Sagarin and Pauchard ). Unless augmented with photography (see below), visual, capture and trapping methods require researchers to accurately record their observations in the field. Due to experiential differences between observers, variations in what is recorded can occur (Sagarin and Pauchard ). Camera traps minimize observer effects because the raw data (i.e. images) are available for interrogation long after data collection. The second aspect of ‘observer effects’ refers to changes in fauna behaviour due to the act of being observed (or captured or trapped). Tyrrell et al. () found the likelihood of trapping B. irregularis increased after the first trap event, whereas Ariefiandy et al. () observed trap avoidance in Komodo monitors (Varanus komodoensis). Remote methods can also suffer from this latter form of the observer effect (Sequin et al. ; Meek et al. , ), but it seems likely the magnitude compared with capture or trapping methods would be reduced. Beyond these two general disadvantages, each archetype has their own specific disadvantages (Table ).

Data resolution is the key advantage of capture and trapping methods. Along with incidence data, with specimens in‐hand investigators can measure morphological traits, determine sex, sample DNA and investigate diet (Blomberg and Shine ). The primary disadvantages of capture and trapping methods are that fauna can be negatively affected in ways not common with other survey methods. For example, during trapping surveys, despite researcher effort and good intentions, the probability of trap mortality is non‐zero. Both target and non‐target species die in traps for a variety of reasons such as exposure or predation (Hobbs and James ; Karraker ; Thompson and Thompson ; Ellis ). In addition, during capture and handling, although stress may negligibly affect long‐term survival of some species (Langkilde and Shine ; Fauvel et al. ; Holding et al. ), other species are clearly affected (Martin and Avery ; Bateman and Fleming ; Scroggie and Clemann ). Investigator safety is also of concern when using capture or trapping methods. Regardless of investigator experience and training, capturing or trapping large or venomous squamate species can result in investigators being seriously injured (Beaupre and Greene ; Fry ).

While visual methods reduce impacts upon fauna, they are not impact free. Detecting cryptic species with visual‐only approaches can be difficult as individuals may scatter or hide when approached, thereby requiring intensive searches to locate fauna (Heatwole ). Burghardt ()p. 128 warns that “[j]ust observing an animal in the field, even for a short time…may be ethically suspect for many reasons”. The reasoning is as follows: squamates likely avoid humans in the same manner that they avoid predators, as predator avoidance reduces time for other activities and can lead to decreased body condition (e.g. Perez‐Tris et al. ); therefore, avoiding human researchers may also negatively impact fauna. Indeed, tourism has been widely reported to negatively affect numerous taxa, including squamates (Amo et al. ; Knapp et al. ). In addition, a limitation of visual methods is that they generally only achieve species‐level resolution of data, which limits their use to creating species’ lists (Guyer and Donnelly ).

To overcome observer biases, avoid invasive marking procedures (i.e. toe‐clipping) and improve data resolution, researchers are beginning to augment visual, capture and trapping approaches by photographing ornamental or scale patterns (Moro and MacAulay ; Treilibs et al. ). Identifying individuals of any species via their pattern relies upon the uniqueness and stability of said pattern (Ferner ; Pimm et al. ). By first capturing then photographing specimens, ornamental patterns of several squamate species have been found to be both unique and stable (Perera and Perez‐Mellado ; Edwards and Gardner ; Knox et al. ; Sreekar et al. ; Yang et al. ). Sacchi et al. () extended this technique by using the morphology and position of scales, in conjunction with Interactive Individual Identification System (I³S) software, to positively identify individuals of Lacerta bilineata and Podarcis muralis. Visual approaches have also been augmented with photographic techniques. For example, Gardiner et al. () used a telephoto lens to photograph free‐roaming eastern water dragons (Intellagama lesuerii) to identify individuals and estimate home ranges.

Augmenting traditional methods (Table ) with photographic approaches can improve their effectiveness and reduce some of their impacts. Still, capture and trapping approaches require fauna to be captured; capture and visual approaches are considerably restricted by the number of researchers; and all methods are generally labour intensive. These limitations provide strong motivation for researchers to adopt new techniques, provided they are effective, cost efficient and minimize impacts upon fauna. For mammals, camera traps have provided researchers with a tool that is both more effective and less costly than traditional methods, and minimizes impacts relative to many traditional approaches (Meek et al. ). Of course, camera traps are not going to be a panacea for all squamate survey requirements as they have their own limitations. But, provided camera traps can effectively detect squamates, they can provide a means to further enhance effectiveness and reduce impacts for collecting fundamental ecological data of squamates.

Using Camera Traps to Detect Herpetofauna: A Review

As we explore in the following review, camera traps have been used to detect squamates, but use has been limited. We conducted a thorough search of primary and secondary literature, last updated in December 2015, to identify studies that used camera traps to detect herpetofauna (amphibians and reptiles). Amphibian studies were included in the review as, given their ectothermy and often small size, they present similar detection problems to most squamates. Studies that reported incidental detections of herpetofauna were not included in the review as incidental detections during camera trapping studies are common. For example, in one of the earliest published camera trapping studies six squamate species were detected (Pearson ). Where two publications originated from the same study, for example, a thesis (e.g. Gibson ) and a journal article (e.g. Gibson et al. ), only the peer‐reviewed publication was included in the review. The procured studies were categorized according to several descriptors identified while reading the articles and used to identify general trends (Table ).

Descriptors used to categorize reptile and amphibian camera trapping studies

Descriptor	Description
Taxonomic group	Taxonomic group the study targeted. Categorized as ‘Amphibia’, ‘Reptile general’, ‘Crocodilia’, ‘Squamata’ or ‘Testudines’.
Species	Species targeted; if all species were targeted, study coded as ‘All’.
Objective	Identified the objective or key metric of the study; for example, behaviour or activity pattern.
Camera trap	Identified the brand of camera trap or type of camera used; studies that did not specify the type of camera were coded as ‘N/S’.
Trigger	The type of trigger mechanism used; categorized as ‘TL’ (time‐lapse), ‘Mech’ (mechanical), ‘AIR’ (active infrared sensor), or ‘PIR’ (passive infrared sensor).

Reviews of the camera trapping literature demonstrate that, compared with mammals or birds, camera traps have been used infrequently to detect herpetofauna generally and squamates specifically (Cutler and Swann ; Diment ; O'Connell et al. ; McCallum ; Meek et al. ). Burton et al. (), for instance, reviewed 266 camera trapping studies published between 2008 and 2013 and identified only five studies had targeted herpetofauna. We identified 55 published studies that had used camera traps to address reptile (n = 51) or amphibian (n = 4) questions (Figure ; Table ). While the earliest study was published in 1991 (Hunt and Ogden ), the majority (56%, n = 31) were published since the start of 2012. Of the reptile camera trapping studies, 22 addressed squamates only, 19 addressed turtles only, 9 studies were on crocodilians and only Baxter‐Gilbert et al. () considered all reptiles as target species.

Amphibian and reptile studies that used camera traps including the study objective, the brand or type of camera trap used (N/S = not specific) and type of trigger mechanism

Study	Species	Objective	Camera trap	Trigger
Amphibia
Crosby ()	All	Area use	Reconyx RC55, PC800	PIR, TL
Engbrecht and Lannoo ()	Lithobates areolatus	Activity pattern	Bushnell TrophyCam	TL
Pagnucco et al. ()	Ambystoma macrodactylum	Area use	Reconyx PC85	PIR, TL
Hoffman et al. ()	Lithobates areolatus	Activity pattern	Cuddeback, Video camera	TL
Reptile general
Baxter‐Gilbert et al. ()	All	Area use	Bushnell TrophyMAX	PIR, TL
Crocodilia
Campos and Mourao ()	Caiman crocodilus	Nest predation	Bushnell, Tigrinus	PIR
Chowfin and Leslie ()	Gavialis gangeticus	Abundance	N/S	TL
Charruau and Henaut ()	Crocodylus acutus	Nesting ecology	Moultrie	PIR
Somaweera and Shine ()	Crocodylus johnstoni	Nesting ecology	Bushnell TrophyCam	PIR
Somaweera et al. ()	Crocodylus johnstoni	Nest predation	Bushnell TrophyCam	PIR
Da Silveira et al. ()	Caiman crocodilus, Melanosuchus niger	Nest predation	Moultrie	PIR
Villamarin‐Jurado and Suarez ()	Melanosuchus niger	Nesting ecology	CamTrakker	PIR
Thorbjarnarson et al. ()	Caiman crocodilus, Crocodylus acutus, Melanosuchus niger	Nesting ecology	CamTrakker	PIR
Hunt and Ogden ()	Alligator mississippiensis	Nest predation	Kodak, Canon	AIR, Mech
Squamata
Ariefiandy et al. ()	Varanus komodoensis	Abundance (index)	ScoutGuard SG‐560 V	PIR
Broeckhoven and Mouton ()	Karusasaurus polyzonus, Ouroborus cataphractus	Behaviour	Reconyx PC900	TL
Gibson et al. ()	Woodworthia spp.	Behaviour	TimelapseCam 8.0, UoVision UV565	TL
Welbourne et al. ()	All	Occupancy	Reconyx HC600	PIR
Ariefiandy et al. ()	Varanus komodoensis	Abundance (index)	ScoutGuard SG‐560 V	PIR
Bennett and Clements ()	Varanus olivaceus	Area use	TrailMaster	PIR
Johnston ()	Oligosoma spp.	Incidence	Kinopta Blackeye	TL
Richardson ()	All	Occupancy	Reconyx HC600	PIR
Ariefiandy et al. ()	Varanus komodoensis	Occupancy	ScoutGuard SG‐560 V	PIR
Jessop et al. ()	Varanus varius	Bait take	ScoutGuard SG‐560 V	PIR
Welbourne ()	All	Occupancy	Reconyx HC600	PIR
Barbour and Clark ()	Crotalus spp.	Behaviour	Video camera	TL
Barbour and Clark ()	Crotalus oreganus oreganus	Behaviour	Video camera	TL
Clark et al. ()	Crotalus spp.	Behaviour	Video camera	TL
Fenner et al. ()	Liopholis slateri	Behaviour	Video camera	TL
McGrath et al. ()	Tympanocryptis pinguicolla	Incidence	Moultrie	PIR
Cochran and Schmitt ()	Crotalus horridus	Area use	Bushnell, Cuddeback	PIR, TL
Clark ()	Crotalus horridus	Behaviour	Video camera	TL
Clark ()	Crotalus horridus	Behaviour	Video camera	TL
Clark ()	Crotalus horridus	Behaviour	Video camera	TL
Milne et al. ()	Tiliqua adelaidensis	Behaviour	Video camera	TL
Sadighi et al. ()	Crotalus horridus	Area use	TrailMaster	AIR
Testudines
Agha et al. ()	Gopherus agassizii	Area use	Reconyx	PIR
Bluett and Schauber ()	Trachemys scripta	Abundance	Plantcam	TL
Bluett and Cosentino ()	Trachemys scripta, Chrysemys picta	Occupancy	Plantcam	TL
Micheli‐Campbell et al. ()	Elusor macrurus	Nesting ecology	Reconyx PM75	TL
Geller ()	Graptemys spp.	Nest predation	Reconyx HC600, RM30	PIR, TL
Geller ()	Graptemys ouachitensis	Nesting ecology	Reconyx HC600, RM30	PIR, TL
Guyer et al. ()	Gopherus polyphemus	Abundance	N/S	Mech
Vilardell et al. ()	Testudo hermanni	Nest predation	Bushnell Trail Sentry	PIR
Bieber‐Ham ()	Chrysemys picta	Nest predation	Reconyx PC800	PIR
Doody et al. ()	Carettochelys insculpta	Nesting ecology	TrailMaster	AIR
Gonçalves et al. ()	Trachemys dorbigni	Nest predation	N/S	N/S
Johnson et al. ()	Gopherus polyphemus	Behaviour	N/S	Mech
Alexy et al. ()	Gopherus polyphemus	Area use	TrailMaster	AIR
Boglioli et al. ()	Gopherus polyphemus	Behaviour	N/S	Mech
Maier et al. ()	Chelydra serpentina	Nest predation	N/S	Mech
Marchand et al. ()	Simulated turtle nests	Nest predation	N/S	Mech
Doody et al. ()	Carettochelys insculpta	Nesting ecology	TrailMaster	AIR
Doody and Georges ()	Carettochelys insculpta	Nesting ecology	TrailMaster	AIR
Guyer et al. ()	Gopherus polyphemus	Area use	N/S	Mech

Trigger mechanisms were AIR, active infrared; PIR, passive infrared; Mech, mechanical or TL, time‐lapse.

The use of camera traps to detect herpetofauna has been similar to the use of camera traps to detect birds. In bird studies, camera traps have been primarily used to examine behaviour or nesting related questions; such as, feeding or predation (Cutler and Swann ). Similarly, for crocodilian or turtle‐related studies camera traps were often used to answer nesting‐related questions. For amphibians and squamates camera traps were often used at locations of known activity to monitor behaviour or use of a particular area. For example, to understand various rattlesnake (Crotalus spp.) behaviours, authors of several studies first radio‐tracked target specimens to refuge locations (Clark , ,b; Barbour and Clark ,b; Clark et al. ). When individual snakes were located, behaviour was captured with a video camera. Such studies are valuable, but successful use of camera traps in this manner does not necessarily translate to using camera traps to detect squamates in an assemblage, or make them useful for determining squamate occupancy or abundance.

Attempting to detect herpetofauna with camera traps at ostensibly random locations has occurred on few occasions (Table ). Most success has come from using camera traps with concentration methods. Concentration methods have been widely used to improve the efficacy of many survey techniques; for example, using drift fences with pitfall traps (McDiarmid et al. ). McGrath et al. () trialled passive infrared (PIR) triggered camera traps to detect the grassland earless dragon (Tympanocryptis pinguicolla). To focus the activity of individual dragons, camera traps were placed at artificial arthropod burrows that T. pinguicolla use for shelter. Unfortunately, the authors are yet to publish further research demonstrating the comparative effectiveness or reliability of their camera trapping approach. Ariefiandy et al. (, , ) used meat baits to attract V. komodoensis to camera trap locations and found they were more effective than using cage traps to determine relative abundance.

Only three studies published during the review period have successfully used camera traps to survey a squamate assemblage (Welbourne ; Richardson ; Welbourne et al. ). Using PIR‐triggered camera traps with drift fences, Welbourne () developed the Camera Overhead Augmented Temperature (COAT) method (Fig. ). The COAT method positions the camera trap above a target area facing towards the ground. As the PIR sensor triggers the camera when something with a higher or lower surface temperature than the background surface temperature enters the detection area (Welbourne et al. ), a cork floor tile was positioned directly beneath the camera trap to create a thermal contrast between the background and target fauna. Despite the majority of squamate species that occurred on the study area being detected, Welbourne () identified several limitations with the method. Specifically, images were blurry due to the focal settings of the camera trap, and orientation of the camera trap itself affected detections of squamates.

Further comparisons and refinement of the COAT method has occurred since Welbourne (). Richardson () compared the COAT method to pitfall trapping in an arid environment and found the COAT method to be just as effective for diurnal species, but less effective for nocturnal species. Given the difficulty of surveying monitor lizards (Varanus spp.) in arid environments, Richardson () noted that camera traps could potentially revolutionize detection of monitor lizards. Welbourne et al. () then compared the COAT method with traditional methods for detecting both mammals and squamates simultaneously. They found the COAT method was more effective for mammals and as effective for squamates. Equally important, Welbourne et al. () demonstrated that the COAT method was less costly than the traditional methods used. More recently, and beyond the review period, Welbourne () improved the effectiveness of the COAT method and demonstrated it was more effective than pitfall trapping, area searches and artificial refuges for detecting squamates.

Studies led by Richardson and Welbourne above were methodological in nature and were not carried out to answer a specific ecological question. Still, the reviewed studies demonstrate that camera traps can meet the characteristics required of a squamate survey method. Welbourne () and Richardson () noted that a range of sizes of squamate species was detected; including Lampropholis spp., which have a snout–vent length of ~50 mm (Wilson and Swan ). Beyond detection, camera traps also need to collect ecologically relevant data. Camera traps can generate species‐level data provided sympatric species are differentiable. Several authors noted that, due to blurry images, some species were indistinguishable from one another (McGrath et al. ; Welbourne ; Richardson ; Welbourne et al. ). Blurry images are caused either from the camera being poorly focused or slow shutter speeds. In the above studies, blurry images were caused due to the fixed focal length of the camera trap being used. Reconyx camera traps have a standard fixed focal length of ~3 m (Reconyx ). Thus, when positioned < 1 m from the target area, images are not perfectly sharp. Nevertheless, Welbourne () has shown how to modify the cameras focal length, which has allowed differentiation between very similar squamate species (i.e. Lampropholis delicata and L. guichenoti).

Identifying individual specimens from camera trap images is more difficult than identifying species alone. Ornamental patterns of squamate species have been used to positively identify individuals (Sacchi et al. ; Yang et al. ). Yet, those approaches used images collected by human photographers who ensured the appropriate diagnostic features were captured. Camera traps do not afford such luxury as often only one aspect of the detected animal is recorded; still individuals can be identified. Both Bennett and Clements () and Milne et al. () were able to identify individual squamates from particular body and head, patterns and markings. Bennett and Clements () noted the approach was not necessarily reliable as defining marks were sometimes only visible on one side of the individual. With the camera trap positioned overhead, as in the COAT method, Welbourne () was able to identify 14 individual jacky dragons (Amphibolurus muricatus) from their dorsal ornamental patterns. Thus, for species that exhibit ornamental patterns that are individually distinctive, individual‐level data resolution may be obtainable with camera traps. Alternatively, individual‐level data resolution may be obtained using the approach discussed by Sacchi et al. (), whereby scale morphology and position are used with I³S software to identify individuals.

Of course, camera traps do not need to be used to the exclusion of existing methods. Using camera traps in combination with traditional methods may be one way to leverage the advantages of multiple techniques. Bluett and Schauber (), for instance, examined the effectiveness of camera traps and capture and marking techniques to estimate abundance of a known population size of adult red‐eared slider turtles (Trachemys scripta). Individual turtles were first captured and marked with a defining mark then the study site was monitored for 20 days using camera traps. Bluett and Schauber () found that camera traps were effective survey tools for estimating abundance of prior marked fauna. Such an approach would likely be broadly applicable to other fauna without individually identifiable features such as ornamental patterns. That is, where capture–mark–recapture studies are ordinarily employed it might be possible to conduct the capture and marking phase of a study then, provided those marks are observable with camera traps, use camera traps to create detection histories. In fact, combing camera traps with other sensors generally, such as temperature or light data loggers, would further increase the utility of data collected by camera traps.

Although camera traps offer advantages over existing methods, there are several disadvantages pertinent to this discussion. First, the effectiveness of one camera trap model at detecting fauna is not necessarily equivalent to another camera trap model (Swann et al. ; Damm et al. ; Meek et al. ). Differences in performance generally require a single camera trap model to be employed throughout a survey programme. While ordinarily achievable, commercial pressures cause camera trap manufacturers to periodically discontinue older designs for new models. Thus, natural attrition of survey equipment may result in too few camera trap units of the same model being available to carry out a survey. It is feasible to calibrate the effectiveness of a new camera trap model against an existing model, but it is a step not required with traditional techniques. Two additional disadvantages of using camera traps are that they are more likely to malfunction or be targets of theft than most traditional survey approaches. Although camera trap manufacturers continue to improve the reliability of their equipment, and despite researchers developing new approaches to reduce theft (Meek et al. ), these latter concerns are likely the most financially costly.

Future Research

Recent advances in camera trapping methodology coupled with the need for more effective and cost‐efficient squamate survey methods makes surveying squamates with camera traps a key frontier. The COAT method “is potentially ground‐breaking in its approach to inventory and monitoring” of squamates (Swann and Perkins ,p. 6). Still, further research is necessary before camera traps become more widely adopted. First, camera traps need to be tested in a greater variety of habitats. Successful use of camera traps to survey a squamate assemblage has hitherto occurred in only a temperate (Welbourne ; Welbourne et al. ) and an arid (Richardson ) environment. While results are encouraging, alternative habitats will provide different squamate assemblages and different environmental features, such as, temperature, substrate and vegetation structures, which may affect the method's efficacy. In conjunction with examining the effectiveness of camera traps in alternative habitats, further comparisons need to be made with other squamate survey methods. Direct comparisons are required to understand the complete utility of camera traps for surveying squamates.

If the COAT method is the most promising avenue for monitoring squamates with camera traps, then the second major avenue for future research is further improving the COAT method's effectiveness. Although numerous improvements could be made, the most immediate issues to address are detection of nocturnal species, further evaluation of concentration methods and camera trap array design (Welbourne ). Detecting nocturnal squamate species with the COAT method is limited (Welbourne ; Richardson ). Effective detection of nocturnal species might be achieved by using the time‐lapse trigger throughout the night and/or by using a battery‐powered heated tile to create the necessary thermal contrast and attract nocturnal species. More generally, further investigation is required into how concentration techniques affect the method's efficacy. It is not clear whether the cork tile actually attracts fauna or whether the tile only functions to create thermal contrast between fauna and the background. If the tile attracts squamates then its use may affect squamae behaviours; thus, its use needs to be more carefully considered. Furthermore, whether squamate‐specific baits can improve detections requires investigation. An aspect of the COAT method that could likely draw heavily from pitfall trapping research is array design. Initial experiments used linear drift fence arrays. Using more complicated trapping arrays with longer drift fences should almost certainly increase the COAT method's effectiveness (Fisher and Rochester ).

Conclusion

Given the lack of fundamental data for squamates, there is an urgent need to develop more effective squamate survey methods. Camera traps have become an important tool in wildlife research. They provide researchers a means to address existing questions, often more effectively and cost efficiently than traditional approaches, and provide a means to ask new types of questions. For herpetofauna generally and squamates specifically, camera traps have received little use. Recent methodological developments, specifically those using the COAT method, suggest that surveying squamates with camera traps is both possible and can be cost effective. Camera traps are not a panacea. There will likely always be a need for traditional squamate survey methods. Yet, for many types of squamate survey, camera traps will likely become an important tool for squamate researchers.