Biodiversity estimates from different camera trap surveys: a case study from Osogovo Mt., Bulgaria

Abstract

Inventorying mammal assemblages is vital for their conservation and management, especially when they include rare or endangered species. However, obtaining a correct estimation of the species diversity in a particular area can be challenging due to uncertainties regarding study design and duration. In this paper, we present the biodiversity estimates derived from three unrelated camera trap studies in Osogovo Mt., Bulgaria. They have different duration and positioning schemes of the camera trap locations: Study 1 -grid based, 34 days; Study 2 -random points based, 138 days; Study 3 -locations based on expert opinion, 1437 days. Utilising EstimateS, we compare a number of estimators (Shannon diversity index, Coleman rarefaction curve, ACE (Abundance-based Coverage Estimator), ICE (Incidence-based Coverage Estimator), Chao 1, Chao 2 and Jackknife estimators) to the number of present and confirmed and/or potentially present mammals (excluding bats) in the mountains. A total of 17 mammal species were registered in the three studies, which represents around 76% of the permanently present mammals in the mountain that inhabit its forested area and can be detected by a camera trap. The results point to some guidelines that can aid future camera trap research in temperate forested areas. A grid-based design works best for very short study periods (e.g. 10 days), while the opportunistic expert-based positioning scheme provides good results for longer studies (approx. a month). However, the grid-based design needs to be further tested for longer periods. Generally, the random points approach does not yield satisfactory results. In agreement with other studies, analysis based on the Jackknife procedure (Jack 2) appears to result in the best estimate of species richness. When performing camera trap studies, special care should be taken to minimise the number of unidentifiable photos and to take into account «trap-shy» individuals. The results from this study emphasise the need for careful preliminary planning of camera trap studies depending on aims, duration and target species.

Patterns of spatial distribution and diel activity in carnivore guilds (Carnivora)

“…The present study showed low detection rates for the two largest species, the grey wolf and brown bear, by camera-trapping survey. This outcome was similar to the result from a previous study conducted in the Osogovo Mountains on the Bulgarian-North Macedonian border (Zlatanova & Popova 2018). Low detectability of these large carnivores was typically owing to their large home-range sizes and low occurrence rates at a given trapping station (Chutipong et al 2014).…”

Changes in rhizosphere bacterial and fungal community composition with vegetation restoration in planted forests

“…The remaining high‐quality sequences were clustered using UPARSE software to generate operational taxonomic units (OTUs) at 97% similarity level (Edgar, ). We used four indices to estimate the community diversity: (a) Shannon indices, expressing the relative evenness component and sensitivity to changes in the importance of the rare species in the sample, (b) Simpson indices, expressing the dominance component and sensitivity to changes in the most abundant species in the sample (Whittaker, ), (c) abundance‐based coverage estimator (ACE), a coverage estimator of species richness, and (d) the Chao1, an estimator of true species diversity (Zlatanova & Popova, ). We obtained rarefaction curves using QIIME (Version 1.7.0) and displayed using R software (Version 3.3.1).…”

Effects of dietary wheat supplementation levels on growth performance, rumen bacterial community and fermentation parameters in Chinese Tibetan Sheep

“…Our results were in agreement with Savin et al (2022), in which dairy cows fed wheat‐based diet tended to exhibit greater Chao1 index than dairy cows fed wheat‐based diet in rumen. As an estimator of community richness, Chao1 index reflected the specific community richness (Zlatanova & Popova, 2018). It might be reasonable speculation that dietary wheat decreased the ruminal pH because of the higher degradability of starch in wheat, thereby influencing the community richness of rumen microorganism.…”