# On tracks: A spoor-based occupancy survey of lion Panthera leo distribution in Kafue National Park, Zambia

> How do you find lions in a vast park with few roads and no previous data? In northern Kafue National Park, Zambia, researchers drove dirt roads at sunrise reading lion tracks, and used occupancy modelling to estimate that lions use about 72% of the area. Habitat, not prey or distance from people, best explained where lions were, which the authors link to illegal bushmeat hunting reaching deep into the park.

Summary by Kersey Lawrence, Original Wisdom. Updated 9 November 2026. Page: https://www.originalwisdom.com/tracking-literature/2014-midlane-oriain-tracks-spoor-based-occupancy/

## Citation and access

- **Authors:** N. Midlane, M.J. O’Riain, G.A. Balme, H.S. Robinson and L.T.B. Hunter
- **Year published:** 2014
- **Journal or source:** Biological Conservation
- **Full citation:** Midlane, N., O’Riain, M.J., Balme, G.A., Robinson, H.S. and Hunter, L.T.B. 2014. On tracks: A spoor-based occupancy survey of lion Panthera leo distribution in Kafue National Park, Zambia. Biological Conservation 172: 101–108.
- **DOI:** 10.1016/j.biocon.2014.02.006
- **Access status:** Publisher link only
- **Where to find it:** https://doi.org/10.1016/j.biocon.2014.02.006

## Tags

- **Species:** Mammals > Lion
- **Region:** Africa > Zambia
- **Tracking:** Sign surveys; Tracking; Tracks; Tracks and signs identification
- **Behaviour and ecology:** Behaviour; Home range; Human disturbance
- **Methods and technology:** Aerial surveys; Akaike Information Criterion (AIC); Detectability; Distribution mapping; Geographic Information System (GIS); Global Positioning System (GPS) collars; Occupancy modelling; Road transects
- **Data type:** Existing data; New field data
- **Observer qualification:** Reported but not validated
- **Discipline:** Behaviour and ecology; Wildlife tracking
- **Year published:** 2014

## Detailed keywords

- **Species:** Studied: African lion (Panthera leo). Prey: ungulate prey biomass, from an aerial survey (species not named). Mentioned from other studies only: leopard (Panthera pardus), tiger (Panthera tigris), river otter (Lontra canadensis), wolverine (Gulo gulo), jaguar (Panthera onca), grizzly bear (Ursus arctos), American marten (Martes americana), sun bear (Helarctos malayanus) and brown hyaena (Hyaena brunnea).
- **Location and habitat:** Northern Kafue National Park, western Zambia, with parts of the neighbouring Game Management Areas (GMAs) and a privately managed Open Area. Kafue is Zambia’s largest national park (22,319 km²), split into northern and southern sectors by the M9 paved road, which formed the southern edge of the study area. Three habitat classes: miombo and Kalahari woodland (29.0% of the study area), munga and termitaria woodland (32.3%), and munga scrub and grassland, including dambo, floodplain and riverine grasslands (38.5%). Wet season December to May, dry season June to November. Off-road animal trails were mostly on hard clay unsuitable for tracks, so only unpaved roads were surveyed.
- **Topics:** lion distribution; occupancy and imperfect detection; false absences; spoor surveys on roads; proportion of area used; probability of lion use; habitat and lion space use; prey biomass; anthropogenic edge effects; illegal bushmeat hunting and wire snares; trophy hunting ban (Zambia, January 2013); law enforcement patrol effort; protected area management; dry season occupancy. Inconsistencies in the paper: (1) the abstract says lions have lost more than 75% of their historic range, the introduction says more than 80%; (2) the fire covariate covers 2010 to 2012 in Table 1 but 2009 to 2012 in the Table 3 caption; (3) the grid is said to include 11,480 km² of National Park, more than the 10,958 km² given for the whole northern sector; (4) park areas are printed with a full stop as the thousands separator (22.319 km² for 22,319 km²).
- **Statistics or models:** Single-season, single-species occupancy model with the Hines et al. (2010) spatial correlation extension for detections along consecutive road segments, run in the software PRESENCE; model ranking by Akaike Information Criterion corrected for small samples (AICc), evidence ratios and 95% confidence intervals of coefficients; Spearman’s correlation matrix (STATISTICA) to drop strongly correlated covariates (r of 0.80 or more); 90% kernel density home ranges from GPS collar data to set the 200 km² grid cell size; kernel density smoothing of aerial survey prey data; coefficient of variation of probability of use per cell; mapping in ArcGIS 10.1. Distance sampling for prey was trialled on road transects but dropped because of low encounter rates.
- **Data type:** New field data: road spoor surveys, 1 July to 15 October 2012 (dry season). Existing data: GPS collar data from nine lions (five male, four female) in the 2010 and 2011 dry seasons; a 2011 aerial survey of ungulates; satellite habitat and fire data; law enforcement patrol GPS points, January 2009 to October 2012.

## Synopsis

### 1. What they did

Africa’s lions have lost most of their historic range, and Zambia is one of only nine countries thought to hold more than 1000 wild lions. Kafue National Park is a key stronghold, but there were no lion data for its northern half. Lions there are killed in wire snares set by illegal bushmeat hunters, and Zambia banned lion trophy hunting in January 2013. The authors wanted to know where lions are in northern Kafue and what shapes their distribution.

- Survey grid. Using home ranges from nine GPS-collared lions, they chose a grid cell size of 200 km² and laid 73 cells (14,600 km²) over northern Kafue. 41 cells had unpaved roads they could survey.

- Spoor surveys (1 July to 15 October 2012). They drove 17 road transects of 17 to 30 km, two to four times each, at least a week apart. Surveys started within 30 minutes of sunrise, when tracks are most visible, at about 10 km per hour. One observer sat on the front left corner of the vehicle and one drove; both scanned the road for lion tracks. Each transect was split into 1 km segments, recorded as lion detected or not.

- Occupancy analysis. An occupancy model uses repeat surveys to estimate how often lions were missed where they were present, and corrects the simple “tracks found” picture for these false absences. They used a version designed for signs found along consecutive stretches of road or trail.

- Testing what drives distribution. They predicted lions would use areas with more prey and areas farther from people. They tested prey biomass, habitat type, fire, water, law enforcement effort, and distance to the park boundary, human activity, tourist camps, safari hunting camps and wildlife authority posts. They also tested whether road surface quality and vehicle traffic affected detection.

### 2. What they found

The survey

- 46 surveys covered 1010 one-km segments. Lion tracks were found on 147 segments (14.6%) and in 24 of the 41 surveyed cells.

- Road surface was good or very good on about a third of segments, moderate on half, and poor or very poor on 15.6%. Most segments (94.3%) showed no impact from other vehicles.

- Neither road surface quality nor vehicle impact had a clear effect on detecting lion tracks.

How much of the area lions use

- Counting only cells with tracks, lions used about 58.5% of the grid (8541 km²).

- After correcting for missed detections, the estimate was 72.1% (about 10,527 km²), 23.3% higher.

What drives where lions are

- Munga and termitaria woodland was the strongest predictor: the more of this habitat in a cell, the more likely lions used it.

- The top-ranked model added proximity to water, but water’s effect was not clear, so the authors used the simpler habitat model for their map.

- Prey biomass had little support, ranking 13th of 14 candidate models in the first round.

- Nothing linked to people (distance to the park boundary, human settlements, safari hunting camps, wildlife authority posts, tourist camps, or patrol effort) fitted the data well.

- Predicted probability of lion use per cell ranged from 0.760 to 0.952. 19 cells were below 0.800, 29 were between 0.800 and 0.899, and 25 were above 0.900.

### 3. What they concluded

- This was the first lion survey using track-based occupancy, and the first use of the Hines et al. (2010) spatial correlation model for an African cat. It worked well over a very large area with limited access and resources.

- Habitat was the main driver of lion use in northern Kafue. The authors suggest the patchy munga and termitaria woodland suits lions’ stalk-and-pounce hunting better than dense miombo woodland or open scrub and grassland.

- They were surprised that human disturbance did not matter. They believe illegal bushmeat hunting is so widespread in Kafue that it no longer shows as an edge effect, so even the interiors of Africa’s largest protected areas are not safe. This does not rule out human effects on lion numbers.

- Results reflect dry season use only. The prey layer came from a single 2011 aerial survey, and prey might have ranked higher if measured during the survey.

- Track surveys need roads with suitable substrate and staff with tracking skills. They may work less well outside protected areas, where carnivores are warier of people and avoid roads; there, audio lures or camera traps may suit better.

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

Lion presence was detected entirely from tracks on unpaved roads. Two observers scanned the road from a slow-moving vehicle at sunrise and identified lion tracks by size and shape. Tracks they were unsure of were left out, because the model assumes there are no false detections. No trailing was reported. The authors chose roads because off-road animal trails were mostly on hard clay where tracks did not show.

### 5. Tracker or observer certification

Reported but not validated. The two observers, one of them the lead author, are described as “competent at detecting and identifying tracks”; no certification or test of their skill is reported. Five people are thanked for help in the field.

### 6. Other technologies, skills or innovations

- GPS collars (Vectronic Aerospace) on nine lions to set the survey grid cell size.

- Google Earth and ArcGIS to choose transects and map covariates and results.

- The occupancy software PRESENCE, using the model of Hines et al. (2010) that allows for detections along consecutive road segments being linked.

- Road surface quality (scale of 1 to 5) and vehicle impact (scale of 0 to 2) recorded for each segment.

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

- The results give the Zambia Wildlife Authority a survey method and focus areas for further lion research in Kafue, and can inform the debate on whether to reopen lion trophy hunting.

- Illegal hunting appears to reach deep into the park, and the authors highlight an urgent need for more effective law enforcement.

- Track-based occupancy surveys can show where large carnivores are in large, previously unsurveyed African protected areas. Multi-season surveys could act as a proxy for population trends where numbers are unknown.

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

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

- The study shows how a simple detected or not-detected record of tracks, collected carefully on repeat surveys, can map a large carnivore across thousands of square kilometres.

- The method rests on the assumption that no track is misidentified, yet the observers’ skill was only described, not tested. An evaluation of observers would strengthen this kind of survey.

## Cite this summary

Lawrence, K. 2026. Summary of: On tracks: A spoor-based occupancy survey of lion Panthera leo distribution in Kafue National Park, Zambia (Midlane and O’Riain et al., 2014). Original Wisdom, Tracking Literature. https://www.originalwisdom.com/tracking-literature/2014-midlane-oriain-tracks-spoor-based-occupancy/