title: Toward reliable estimates of abundance: comparing index methods to assess the abundance of a Mammalian predator.
abstract: Due to time and financial constraints indices are often used to obtain landscape-scale estimates of relative species abundance. Using two different field methods and comparing the results can help to detect possible bias or a non monotonic relationship between the index and the true abundance, providing more reliable results. We used data obtained from camera traps and feces counts to independently estimate relative abundance of red foxes in the Black Forest, a forested landscape in southern Germany. Applying negative binomial regression models, we identified landscape parameters that influence red fox abundance, which we then used to predict relative red fox abundance. We compared the estimated regression coefficients of the landscape parameters and the predicted abundance of the two methods. Further, we compared the costs and the precision of the two field methods. The predicted relative abundances were similar between the two methods, suggesting that the two indices were closely related to the true abundance of red foxes. For both methods, landscape diversity and edge density best described differences in the indices and had positive estimated effects on the relative fox abundance. In our study the costs of each method were of similar magnitude, but the sample size obtained from the feces counts (262 transects) was larger than the camera trap sample size (88 camera locations). The precision of the camera traps was lower than the precision of the feces counts. The approach we applied can be used as a framework to compare and combine the results of two or more different field methods to estimate abundance and by this enhance the reliability of the result.
authors.affiliation: Chair of Wildlife Ecology and Management, University of Freiburg, Freiburg, Baden-Württemberg, Germany.
authors.forename: Denise
authors.initials: D
authors.lastname: Güthlin
authors.affiliation: Chair of Wildlife Ecology and Management, University of Freiburg, Freiburg, Baden-Württemberg, Germany.
authors.forename: Ilse
authors.initials: I
authors.lastname: Storch
authors.affiliation: Statistical Consulting Unit, Department of Statistics, University of Munich, Munich, Bavaria, Germany.
authors.forename: Helmut
authors.initials: H
authors.lastname: Küchenhoff
mesh_terms: D000818:Animals; D005243:Feces; D005589:Foxes; D015233:Models, Statistical; D011156:Population Density; D011235:Predatory Behavior; D012044:Regression Analysis; D015203:Reproducibility of Results