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PeerJ. 2016 Dec 22;4:e2662. doi: 10.7717/peerj.2662. eCollection 2016.

Simplified large African carnivore density estimators from track indices.

Author information

1
Centre for Wildlife Management, University of Pretoria, Pretoria, South Africa; Tau Consultants (Pty) Ltd, Maun, Botswana.
2
Scientific Services, SANParks , Skukuza , South Africa.
3
Panthera , Kongola , Namibia.
4
Centre for Wildlife Management, University of Pretoria, Pretoria, South Africa; Centre for Invasion Biology, University of Pretoria, Pretoria, South Africa.

Abstract

BACKGROUND:

The 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.

METHODS:

We 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.

RESULTS:

The 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.

DISCUSSION:

Our 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.

KEYWORDS:

AIC; Brown hyena; Cheetah; Conservation; Leopard; Lion; Spoor; Spotted hyena; Survey technique; Wild dog

Conflict of interest statement

CW Winterbach and HEK Winterbach are directors and sole shareholders of Tau Consultants (Pty) Ltd., a registered independent research company in Botswana. Paul Funston is an employee of Panthera, and Sam Ferreira is employed by SANParks. Michael Somers is an Academic Editor for PeerJ.

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