Rapid and reliable estimation of population size is needed for the efficient monitoring of animal populations of conservation concern. Unfortunately, technical advances in this area have not been paralleled in uptake in conservation, which may be due to difficulties in implementation or the lack of general guidelines for application. Here we tested five different methods used to estimate population size [capture-mark-recapture (CMR), finite-mixture models, model averaging of finite-mixture models, accumulation curve methods (ACM), and the line transect method (LT)] using extensive captureâ¿¿recapture data of the giant day gecko (Gekkonidae, Phelsuma madagascariensis grandis, Gray 1870) at the Masoala rainforest exhibit, Zurich Zoo. When the complete data were analyzed [30 sessions (and 27 sessions for the LT)], all methods except the LT produced similar estimates of population size. The simple ACM gave a small coefficient of variation (CV), but did not cover the most likely value of population size at moderate sampling effort. Nevertheless, the ACM was the only method that showed a reasonable convergence when subsets of data were used. CMR and Pledger models included the reference value in their confidence intervals (CI) after 25 and 30 sessions, respectively. Although model averaging did slightly improve the estimate, the CV was still high for the full dataset. Our method of using subsets of data to test the robustness of estimates is simple to apply and could be adopted more widely in such analyzes to evaluate sensitivity to method of evaluation. In conclusion, simple accumulation methods showed similar efficiency to more complex statistical models, and are likely to be sufficiently precise for most conservation monitoring purposes.
Wanger, T., Motzke, I., Furrer, S., Brook, B., & Gruber, B. (2009). How to monitor elusive lizards: comparison of capture-recapture methods on giant day geckos (Gekkonidae, Phelsuma madagascariensis grandis) in the Masoala rainforest exhibit, Zurich Zoo. Ecological Research, 24, 345-353. https://doi.org/10.1007/s11284-008-0511-3