Simplified large African carnivore density estimators from track indices

Abstract

BackgroundThe range, population size and trend of large carnivores are important parameters to assess their status globally and to plan conservation strategies. One can use linear models to assess population size and trends of large carnivores from track-based surveys on suitable substrates. The conventional approach of a linear model with intercept may not intercept at zero, but may fit the data better than linear model through the origin. We assess whether a linear regression through the origin is more appropriate than a linear regression with intercept to model large African carnivore densities and track indices.MethodsWe did simple linear regression with intercept analysis and simple linear regression through the origin and used the confidence interval for ß in the linear model y = αx + ß, Standard Error of Estimate, Mean Squares Residual and Akaike Information Criteria to evaluate the models.ResultsThe Lion on Clay and Low Density on Sand models with intercept were not significant (P > 0.05). The other four models with intercept and the six models thorough origin were all significant (P < 0.05). The models using linear regression with intercept all included zero in the confidence interval for ß and the null hypothesis that ß = 0 could not be rejected. All models showed that the linear model through the origin provided a better fit than the linear model with intercept, as indicated by the Standard Error of Estimate and Mean Square Residuals. Akaike Information Criteria showed that linear models through the origin were better and that none of the linear models with intercept had substantial support.DiscussionOur results showed that linear regression through the origin is justified over the more typical linear regression with intercept for all models we tested. A general model can be used to estimate large carnivore densities from track densities across species and study areas. The formula observed track density = 3.26 × carnivore density can be used to estimate densities of large African carnivores using track counts on sandy substrates in areas where carnivore densities are 0.27 carnivores/100 km2 or higher. To improve the current models, we need independent data to validate the models and data to test for non-linear relationship between track indices and true density at low densities.

Assessing the performance of index calibration survey methods to monitor populations of wide‐ranging low‐density carnivores

“…Furthermore, habituation can invalidate such calibrations, if animals reduce their response through time. To avoid this problem, track or spoor surveys are widely used to estimate population densities of many of the African large carnivores: lions, hyaenas, leopards, cheetahs, and African wild dogs (Bauer et al, , , ; Hanssen, Funston, Alfred, & Alfred, ; Funston et al, , ; Groom & Watermeyer, ; Houser, Somers, & Boast, ; Midlane, Justin O'Riain, Balme, & Hunter, ; Stander, ; Winterbach, Ferreira, Funston, & Somers, ). Stander () found a positive correlation between track frequency and independent estimates of population density for African wild dogs, leopards, and lions in northern Namibia.…”

“…Funston et al () refined this method to account for substrate variation and concluded that “a combined model for all carnivore species on sandy soils served as a robust approach to predict large carnivore densities.” The regression model of Funston et al () included a nonzero intercept, which allows a track density of zero to predict a population density above zero. Winterbach et al () refined the model by dropping the nonzero intercept from the regression, but did not alter the way the uncertainty in the estimates were calculated; this methodology is hereafter what we refer to as the track count method.…”

Using the Formozov–Malyshev–Pereleshin formula to convert mammal spoor counts into density estimates for long‐term community‐level monitoring

“…Notably, the assumption of constant day range is implicitly assumed whenever spatial–temporal comparisons of repeat spoor surveys are made, including index‐density calibration approaches (e.g. Winterbach et al, ), unless re‐calibrated to local conditions every survey. The extent by which average day range fluctuates from year to year requires further investigation.…”

“…Spoor tracking is an index widely used globally (Norris, Peres, Michalski, & Hinchsliffe, ; Southgate & Moseby, ; Winterbach, Ferreira, Funston, & Somers, ). However, to date, this method has mostly been used for monitoring carnivore mammals (Bauer, Schiess‐Meier, Mills, & Gusset, ; Fabiano, ; Gusset & Burgener, ) owing to the difficulty detecting and counting them by other means.…”

“…Substantial effort has been made towards gaining a better understanding of the relationship between large carnivore spoor indices and true density. Strong correlations have been noticed between spoor indices and independent density estimates of large carnivores (from direct monitoring of individuals and intensive collaring studies) using linear calibration equations (Funston et al, ; Stander, ; Winterbach et al, ). Based on the success of linear calibration models for large carnivores, Funston et al () tentatively suggested extending such calibrations to large herbivores.…”