Camera trap, line transect census and track surveys: a comparative evaluation

1. What they did

Conservation planning often needs a quick picture of which mammals live in an area and how common they are. The authors compared three ways of doing this in the grasslands of Emas National Park, central Brazil:

• Camera traps. During January and March 2002 they placed 29 automatic cameras (Cam Trakker) beside a dirt road, 1.5 km apart. Each camera was treated as one sampling unit covering a radius of 750 m.
• Track census. Each camera unit was also a 1.5 km track sampling unit. Every day for 44 days, a vehicle drove the road at 20 km/h, dragging a brush of palm leaves behind it to wipe out old tracks, so that only fresh tracks were counted on each pass.
• Line transect (sighting) census. Two observers rode on the back of the pick-up during the track census and recorded every mammal they saw. Further sighting surveys, by day and night, were run on other park roads to match the effort of the other two methods, so this method could not be compared with the others site by site.

They looked at how quickly each method built up the species list, and calculated photographic and track rates (records per day) for each species. They then compared camera and track results across the 29 units, allowing for the fact that nearby units tend to give similar results (spatial autocorrelation), and asked whether the two methods agreed better for larger species.

2. What they found

Species richness

• Of the 28 medium to large terrestrial mammal species known from the park’s grasslands, track surveys detected 19 (68%), camera traps 17 (reported as 64%) and direct sightings 16 (57%).
• Track census found species fastest, reaching its full count after only 12 days. All three methods arrived at similar species totals after about 30 days.
• 14 species were recorded by both camera traps and tracks; these are mainly species of open habitats.

Comparing camera traps and tracks across the 29 units

• Species richness and total abundance were not significantly correlated between the two methods (richness r = 0.312, P = 0.167; abundance r = 0.422, P = 0.078).
• For some species the two methods did agree significantly from place to place: white-lipped peccary (r = 0.703), giant armadillo (r = 0.230) and giant anteater (r = 0.403). For others, such as maned wolf (r = 0.006), they did not.
• Track rates were usually higher than photographic rates. For example, the maned wolf had a track rate of 0.154 records per day against 0.052 for photographs, and the tapir 0.121 against 0.024. The jaguar was similar by both methods (0.022 and 0.024).
• Across species, photographic and track rates were strongly correlated (r = 0.798), but photographic rates were consistently lower.
• The two methods agreed better for larger animals: agreement rose with body mass (r = 0.792 in the text, 0.74 in the figure).

3. What they concluded

• Track counts were the most efficient quick method for detecting species and relative abundance in Emas Park, but they need at least two people (a driver and an observer) and a vehicle, and the field staff need considerable experience with the signs of the local animals.
• Weather and ground conditions limit track surveys: ground that is too wet or too dry affects whether tracks can be seen and identified, and can make a survey valid or invalid. Game trails are good places for tracks but may not represent the wider area.
• Both track and photographic rates can overestimate abundance because the same animal can be counted more than once. Tracks are more prone to this, since photographs taken at very short intervals (probably of the same animal) can be discarded. The authors suggest this may partly explain the higher track rates.
• Direct counts along transects were the most limited method: they depend on good field conditions and well trained observers, and can favour large species active by day.
• Despite high start-up costs, the authors judge camera trapping the most appropriate method for mammal inventories in all conditions. It is cheaper in the long run, identifies species accurately, disturbs the environment little, detects night and day species equally (at least compared with direct counts), can be run by untrained staff, covers large areas at once, and can also show activity patterns and support population studies.

4. How tracking was or was not used

Tracks were counted daily on a dirt road divided into 29 units of 1.5 km, from a vehicle driving at 20 km/h. A palm-leaf brush dragged behind the vehicle wiped the road so that each day’s count held only fresh tracks. Tracks were identified to species and turned into track rates (records per day). Tracking was one of the three methods being compared.

5. Tracker or observer certification

Not reported. The paper does not say who identified the tracks or how experienced they were, although the authors state that track surveys need field staff with considerable experience of local signs. Several people and “all the volunteers” are thanked for help with data collection.

6. Other technologies, skills or innovations

• Cam Trakker automatic cameras (CamTrak South, Watkinsville, Georgia, USA).
• A brush of palm leaves dragged behind the vehicle to wipe old tracks off the road before each count.
• Statistical correction for spatial autocorrelation (Dutilleul’s method) when comparing methods across nearby sites.

7. Implications for conservation (from the paper)

• Fast, reliable ways to measure species richness and abundance are crucial for setting conservation priorities, especially given urgent conservation needs worldwide.
• Camera trapping can estimate both richness and abundance in a short time, and long-term monitoring could track changes in abundance, activity, breeding and habitat use. These data can serve as a rapid assessment of wildlife conservation status and guide conservation priorities and management.