Detection probability in amphibian monitoring

Anastasia Kuperberg

Bachelor's thesis

Abstract:

The correct data resulting from the biodiversity monitoring are extremely important for conservation and appropriate management decisions. However, data are often biased for many different reasons. One of those is the imperfect detection, which means that individuals, populations or species are not always found even when they are present at a site. There are many causes for the detection to be imperfect, like species ecology, habitat features, weather conditions or even observers’ skills. The way of accounting for the imperfect detection is to determine the detection probability for the species of interest. Even though the popularity of using the detection probability in studies and researches is growing, many biodiversity monitoring programs are still omitting it. This thesis deals with accounting for the imperfect detection and detection probability assessment in amphibian studies. In the literature review part, the theoretical background for this topic is presented. Terms connected with biodiversity monitoring are provided and different sources of error in it are listed. The imperfect detection and detection probability assessment are described deeply with examples in different species. The practical part of the thesis deals with the detection probability in amphibians and consists of two parts. The first part contains a simple meta-analysis of the available studies that account for the detection probability and deal with the amphibian species living in the Czech Republic. The second part includes the analysis of the abundance data of a population of fire salamanders (Salamandra salamandra, Linnaeus, 1758) in Prague, specifically the proportions of active salamanders per visit, and the suggestion for the further analysis of that data accounting for the detection probability.

Keywords

species monitoring, imperfect detection, site occupancy, amphibians

Language used: English

Date on which the thesis was submitted / produced: 30. 3. 2021

Thesis defence

• Supervisor: doc. Ing. Jiří Vojar, Ph.D.

Czech University of Life Sciences Prague

Faculty of Environmental Sciences

Bachelor programme / field:
Environmental Sciences / Applied Ecology