# Substrate and species constraints on the use of track incidences to estimate African large carnivore abundance

> Can counting fresh tracks on dirt roads tell you how many lions, leopards, cheetahs and hyaenas live in an area? Across 18 sites from Namibia to the Serengeti, with trackers riding on the vehicle bonnet over 15 306 km, researchers found that on sandy soils one simple model fits all these large carnivores. Clay soils behave differently, and they show how many track finds a survey needs to be precise.

Summary by Kersey Lawrence, Original Wisdom. Updated 9 November 2026. Page: https://www.originalwisdom.com/tracking-literature/2010-funston-frank-substrate-species-constraints-use/

## Citation and access

- **Authors:** P. J. Funston, L. Frank, T. Stephens, Z. Davidson, A. Loveridge, D. M. Macdonald, S. Durant, C. Packer, A. Mosser and S. M. Ferreira
- **Year published:** 2010
- **Journal or source:** Journal of Zoology
- **Full citation:** Funston, P. J., Frank, L., Stephens, T., Davidson, Z., Loveridge, A., Macdonald, D. M., Durant, S., Packer, C., Mosser, A. and Ferreira, S. M. 2010. Substrate and species constraints on the use of track incidences to estimate African large carnivore abundance. Journal of Zoology 281(1): 56–65.
- **DOI:** 10.1111/j.1469-7998.2009.00682.x
- **Access status:** Publisher link only
- **Where to find it:** https://doi.org/10.1111/j.1469-7998.2009.00682.x

## Tags

- **Species:** Mammals > Brown hyena; Mammals > Cheetah; Mammals > Leopard; Mammals > Lion; Mammals > Spotted hyena
- **Region:** Africa > Botswana; Africa > Kenya; Africa > Namibia; Africa > South Africa; Africa > Tanzania; Africa > Zimbabwe
- **Tracking:** Track counts; Tracking; Tracks; Tracks and signs identification
- **Methods and technology:** Analysis of variance (ANOVA); Global Positioning System (GPS); Linear regression; Population estimation; Power analysis; Radio telemetry; Road transects; Simulation
- **Data type:** Existing data; New field data
- **Observer qualification:** Reported but not validated
- **Discipline:** Population trends; Wildlife tracking
- **Year published:** 2010

## Detailed keywords

- **Species:** Studied: lion (Panthera leo), cheetah (Acinonyx jubatus), leopard (Panthera pardus), spotted hyaena (Crocuta crocuta) and brown hyaena (the paper gives no scientific name for the brown hyaena). Lions are the case study for survey design and confidence intervals. Other examples discussed: pumas, also called mountain lions (Felis concolor), in the earlier track-count literature.
- **Location and habitat:** Seven study areas with 18 study sites. Tsumkwe District and Kaudum Game Reserve, Namibia (closed woodland or dense shrubs on deep Kalahari sandy soils; data from Stander 1998). Kgalagadi Transfrontier Park, South Africa and Botswana (vegetated dunes and shrubby grassland; sparse to open tree savanna with grassy plains): Dune-north, Dune-south, Mabuasehube, Sesatswe, Mosimane and Other-tree sites. Hwange National Park, Zimbabwe, Main camp (closed woodland with dense shrubs on deep Kalahari sands and basalt clays). Venetia-Limpopo Nature Reserve, South Africa (closed woodland with dense shrubs on granites and sedimentary sandy soils). Laikipia District, Kenya: El Karama, Mugie and Mpala (semi-arid rangelands and shrubby grassland on clay and sandy soils). Serengeti National Park, Tanzania: short-grass and long-grass plains on deep clay soils, each surveyed in the wet and dry seasons.
- **Topics:** track counts (spoor counts) as an index of large carnivore abundance; calibrating track density against known carnivore density; effect of substrate (sandy versus clay soils); species differences; saturation of the index at high density (spotted hyaenas on clay); road transects driven with a tracker on the bonnet; sweeping roads with a brush drag; survey design and required survey effort; how many track finds are needed for a precise estimate; confidence intervals for density estimates; detecting population trends; human–carnivore conflict as background.
- **Statistics or models:** Linear models of track density against carnivore density (combined sandy-soil model: track density = 3.15 × carnivore density + 0.40, R² = 0.96; combined lion and cheetah clay-soil model: track density = 0.55 × density − 0.28, R² = 0.71); exponential saturation model for spotted hyaenas on clay (R² = 0.93, n = 4); analysis of variance (ANOVA) of residuals and linear comparisons of slopes and intercepts; non-linear decay models fitted by log-transformed linear regression (track density against distance between track finds; coefficient of variation against number of track finds; survey distance against lion density); simulation of 10 000 draws to build confidence intervals; 95% minimum convex polygon home ranges to calculate density from radio-collared animals; Gerrodette’s (1987) inequality (power analysis, power 0.8) to plan survey intervals for detecting a 10% change per year.
- **Data type:** New field data (track surveys and long-term monitoring of known or radio-collared individuals) combined with published track data (Stander 1998) and published or unpublished density estimates (Knight, Bothma et al. 1997, Mills 1990, Durant et al. 2002 and 2003). In total 15 306.4 km driven on 339 transects. Dates of data collection are not given. Inconsistencies in the paper: (1) the text says the estimated confidence interval included the density from other methods in three of the nine lion sites, but Table 3 shows this for only two (Mosimane and Short-grass wet); (2) the Results give track densities from 0.27 to 161.70 per 100 km and carnivore densities from 0.54 to 215.00 per 100 km², but Table 2 lists track densities as low as 0 and 0.05 and carnivore densities as low as 0.21 and 0.27; (3) in Figure 3, the parameter box for the track density to carnivore density step repeats the values of the first box (1.75 and −0.66) rather than the sandy-soil model values in the text; (4) Table 3 prints two confidence intervals with typing errors (“15–62-25.88” and “12–67-18.47”, probably 15.62 to 25.88 and 12.67 to 18.47); (5) the Table 2 note says 15 study sites, while the table lists 18.

## Synopsis

### 1. What they did

Managers of lions and other large carnivores need to know how many animals there are and whether numbers are going up or down, but counting them directly is slow, costly and hard to repeat. Track counts are a cheaper alternative: the more animals there are, the more tracks people should find. Earlier work (Stander 1998) warned that such indices might only hold for the species and site where they were calibrated, so the authors tested whether one relationship could work across many places, species and soils.

- Track surveys. At 18 study sites in seven study areas in Namibia, South Africa and Botswana, Zimbabwe, Kenya and Tanzania (including published Namibian data from Stander 1998), teams drove sections of road or off-road routes (transects) on soils fine enough to show tracks. They left out routes with more than 50% vegetation cover. A tracker sat on the bonnet of a four-wheel-drive vehicle moving at about 10 to 20 km per hour and scanned for tracks ahead. When tracks were found, the vehicle stopped and the trackers identified the species, leaving out any they could not identify reliably. Only tracks from the previous 24 hours were counted; roads were swept with a brush drag when transects were driven on consecutive days. In total they drove 15 306.4 km on 339 transects. The Serengeti sites were surveyed in both wet and dry seasons.

- Known densities. They compared track counts with carnivore densities from long-term monitoring of known individuals (radio collars, coat or spot patterns, whisker spot patterns, brands) or from published studies.

- Models. They fitted relationships between track density (tracks per 100 km) and carnivore density (animals per 100 km²) by species and by soil type, then worked out how far a survey team needs to drive to get a precise estimate, how to put confidence intervals on the estimate, and how often surveys need to be repeated to detect a 10% change per year.

### 2. What they found

Track density and true density

- One relationship for all cats regardless of soil did not work well: it explained only 21% of the variation.

- Sandy soils: lion density explained 97% of the variation in lion track density. Cheetah, leopard and hyaena tracks fitted the lion model just as well, so one combined model for all species on sandy soils explained 96% of the variation (about 3.15 tracks per 100 km for each animal per 100 km², plus 0.40).

- Clay soils: lions and cheetahs did not differ, and a combined cat model explained 71% of the variation. Spotted hyaenas on clay, at very high densities in the Serengeti, were the only case where the index levelled off (saturated) as density rose.

- The sandy and clay models differed, so soil type matters.

How much survey effort is needed

- Track density fell steeply as the distance between track finds grew.

- On average, finding 19 sets of tracks gave a coefficient of variation (a measure of precision) under 20% for the distance between finds, but 30 sets of tracks most often ensured it. This held across densities and soils.

- The distance needed to find 30 sets of tracks on sandy soils dropped sharply as lion density increased. For the one clay-soil case, the sandy-soil model predicted 22.5 km, but 274.1 km had been surveyed in the Serengeti long-grass wet season.

Lion estimates and trends

- Lion densities estimated from tracks matched the other estimates inconsistently. The authors report that the confidence interval included the other estimate in three of nine sites (Table 3 shows two), but low track-based estimates went with sites that also had low densities by other methods.

- Most sites were precise enough that a 10% change could be detected with two surveys one year apart. Less precise sites needed up to three surveys up to three years apart, with up to six years of not knowing the trend, by which time numbers could have changed by up to 77%.

### 3. What they concluded

- Indices based on track counts can give useful estimates of large carnivore abundance, once soil type is taken into account.

- On sandy soils a single model works for lions, leopards, cheetahs and hyaenas, despite their different behaviour and ecology. Stander’s advice to treat indices as site-specific is a sensible starting point, but these results show helpful generalization is possible.

- Saturation was a problem only for spotted hyaenas at very high density.

- A particular strength of the method is that it gives confidence intervals; only a third of the lion estimates from other methods did.

- Two conditions are needed for success: suitable substrate with sufficiently skilled trackers, and, especially where the substrate is less suitable, calibration of track density against known local carnivore density.

- They offer a flow diagram (Figure 3) for designing a track survey, estimating density with confidence intervals, and planning repeat surveys.

### 4. How tracking was or was not used

Tracking is the core method. Trackers seated on the vehicle bonnet spotted fresh carnivore tracks (footprints) on roads and routes, identified the species, and left out any tracks they could not identify reliably. Each set of tracks was counted once per day; if trackers found two similar sets within 500 m and could not tell them apart as individuals, the second was not counted. No trailing was reported. Radio-tracking (telemetry flights or ground-tracking) was used separately to estimate the known densities.

### 5. Tracker or observer certification

Reported but not validated. Where available, expert indigenous local trackers were used, and every survey team included “a competent track interpreter”. Different trackers worked at different study areas, each site directed by its lead researcher. The authors were confident this avoided observer bias (citing Stander et al. 1997), but the trackers’ skill was not tested or certified in the study, and they are not named.

### 6. Other technologies, skills or innovations

- Handheld geographical positioning systems (GPS) and digital road maps to log routes and measure transect lengths, and to map vegetation cover along them.

- Brush drags towed behind the vehicle to sweep roads clean of old tracks.

- Simulation (10 000 random draws) to put confidence intervals on track-based density estimates.

- A flow diagram guiding survey design, density estimation and trend monitoring.

### 7. Implications for conservation (from the paper)

- Track surveys are cost effective and repeatable, which matters because changes in numbers are often more important to managers than absolute numbers.

- The method allows confidence intervals to be calculated, so managers can weigh trade-offs between survey effort, survey interval and the risk of missing a decline.

- Where soils are less suitable, local calibration against known densities remains a sensible precaution.

### 8. Implications for tracking (Original Wisdom's observations)

_These are Original Wisdom's observations, not the authors'._

- The authors name sufficiently skilled trackers as one of two conditions for track counts to work, yet the trackers’ skill was not tested in the study. A tracker evaluation would let others judge how much of the remaining variation comes from the ground and how much from the observers.

- The combined sandy-soil model rests on trackers telling apart lion, leopard, cheetah and hyaena tracks from a moving vehicle, and on judging whether nearby tracks belong to different individuals.

## Cite this summary

Lawrence, K. 2026. Summary of: Substrate and species constraints on the use of track incidences to estimate African large carnivore abundance (Funston and Frank et al., 2010). Original Wisdom, Tracking Literature. https://www.originalwisdom.com/tracking-literature/2010-funston-frank-substrate-species-constraints-use/