Evaluating capture–recapture population and density estimation of tigers in a population with known parameters

Conservation strategies for endangered species require accurate and precise estimates of abundance. Unfortunately, obtaining unbiased estimates can be difficult due to inappropriate estimator models and study design. We evaluate population–density estimators for tigersPanthera tigrisin Kanha Tiger Reserve, India, using camera traps in conjunction with telemetry (n=6) in a known minimum population of 14 tigers. An effort of 462 trap nights over 42 days yielded 44 photographs of 12 adult tigers. Using closed population estimators, the best‐fit model (programcapture) accounted for individual heterogeneity (Mh). The least biased and precise population estimate ( (SE) [ ]) was obtained by theMhJackknife 1 (JK1) [14 (1.89)] in programcare‐2. Tiger density ( (SE) [ ]) per 100 km2was estimated at 13 (2.08) when the effective trapping area was estimated using the half mean maximum distance moved (1/2 MMDM), 8.1 (2.08), using the home‐range radius, 7.8 (1.59), with the full MMDM and 8.0 (3.0) with the spatial likelihood method in programdensity4.1. The actual density of collared tigers (3.27 per 100 km2) was closely estimated by home‐range radius at 3.9 (0.76), full MMDM at 3.48 (0.81) and spatial likelihood at 3.78 (1.54), but overestimated by 1/2 MMDM at 6 (0.81) tigers per 100 km2. Sampling costs (Rs. 450 per camera day) increased linearly with camera density, while the precision of population estimates leveled off at 25 cameras per 100 km2. At simulated low tiger densities, a camera density of 50 per 100 km2with an effort of 8 trap nights km−2provided 95% confidence coverage, but estimates lacked precision.