Camera trapping with capture-recapture analyses has provided estimates of the abundances of elusive species over the last two decades. Closed capture-recapture models (CR) based on the recognition of individuals and incorporating natural heterogeneity in capture probabilities are considered robust tools; however, closure assumption is often questionable and the use of an Mh jackknife estimator may fail in estimations of real abundance when the heterogeneity is high and data is sparse. A novel, spatially explicit capture-recapture (SECR) approach based on the location-specific capture histories of individuals overcomes the limitations of closed models. We applied both methods on a closed population of 16 critically endangered Western Derby elands in the fenced 1,060-ha Fathala reserve, Senegal. We analyzed the data from 30 cameras operating during a 66-day sampling period deployed in two densities in grid and line arrays. We captured and identified all 16 individuals in 962 trap-days. Abundances were estimated in the programs CAPTURE (models M0, Mh and Mh Chao) and R, package secr (basic Null and Finite mixture models), and compared with the true population size. We specified 66 days as a threshold in which SECR provides an accurate estimate in all trapping designs within the 7-times divergent density from 0.004 to 0.028 camera trap/ha. Both SECR models showed uniform tendency to overestimate abundance when sampling lasted shorter with no major differences between their outputs. Unlike the closed models, SECR performed well in the line patterns, which indicates promising potential for linear sampling of properly defined habitats of non-territorial and identifiable herbivores in dense wooded savanna conditions. The CR models provided reliable estimates in the grid and we confirmed the advantage of Mh Chao estimator over Mh jackknife when data appeared sparse. We also demonstrated the pooling of trapping occasions with an increase in the capture probabilities, avoiding violation of results.
- MeSH
- hustota populace * MeSH
- přežvýkavci * MeSH
- teoretické modely * MeSH
- zvířata MeSH
- Check Tag
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Senegal MeSH
Nezbytnou součástí elektronického vzdělávacího procesu jsou testy. Cílem tohoto příspěvku je prezentovat bezpečné elektronické testování studentů na lékařské fakultě v Plzni. Námi navržené a zrealizované řešení nabízí pedagogickým pracovníkům prostředí pro rychlé, jednoduché a hlavně bezpečné zjišťování dosažených znalostí studentů elektronickou formou. Náš systém testování je postaven na bezpečnosti jednotlivých subsystémů, kterými jsou: klientské počítače v učebně, learning managament system Moodle (dále jen LMS), server provozující služby spojené s LMS a aktivní síťový prvek (switch).
Tests are an essential part of the electronic educational process. The aim of this paper is to present a safe electronic testing of students at Charles University Medical Faculty in Pilsen. We suggested and put into practice a solution for teachers, which offers a fast, easy and especially safe survey of knowledge achieved by students in the electronic way. Our system of testing is based on the safety of individual subsystems as follows: client computers in classrooms, a learning management system Moodle (LMS), a server running services connected with LMS, and an active net element (switch).
