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Mesocarnivores are of particular interest in wildlife management. Their adaptability makes them a focus of public attention globally, as negative interactions with people occur regularly, but their importance to wider ecosystem function is increasingly apparent. Robust methods for estimating mesocarnivore densities are essential for long‐term management strategies. Estimating densities of unmarked populations remains challenging, but new methods, based on camera trapping, have recently become available and require field testing. We conducted two camera trap surveys over two 200 km2 areas of commercial farmland in South Africa. One survey sampled 25 locations, while the second used a migrating grid to sample 59 locations; total sampling effort was similar across the two surveys. We applied distance sampling with camera traps (CTDS), developing a method to estimate animal distances by applying a distance measurement overlay grid to camera trap images. We aimed to establish meaningful density estimates of the mesocarnivore guild and evaluate CTDS's suitability for broader use with these types of species. We obtained density estimates for four carnivores, African civet Civettictis civetta, black‐backed jackal Canis mesomelas, brown hyena Hyaena brunnea and caracal Caracal caracal, providing valuable insight into their status in commercial farmland. Imprecision in the estimates was almost exclusively due to encounter rate variance, which was not reduced with the migrating camera grid. We explored the sensitivity of our results to assumptions determining the value of the ‘snapshot interval’, demonstrating that careful selection of this parameter is vital to ensuring reliable estimates when using rapid‐fire photo burst modes. CTDS can provide useful density estimates for mesocarnivores, but future studies should aim to maximize precision and reliability by increasing sampling locations. More studies are required in areas with known densities to promote confidence in accuracy.
Mesocarnivores are of particular interest in wildlife management. Their adaptability makes them a focus of public attention globally, as negative interactions with people occur regularly, but their importance to wider ecosystem function is increasingly apparent. Robust methods for estimating mesocarnivore densities are essential for long‐term management strategies. Estimating densities of unmarked populations remains challenging, but new methods, based on camera trapping, have recently become available and require field testing. We conducted two camera trap surveys over two 200 km2 areas of commercial farmland in South Africa. One survey sampled 25 locations, while the second used a migrating grid to sample 59 locations; total sampling effort was similar across the two surveys. We applied distance sampling with camera traps (CTDS), developing a method to estimate animal distances by applying a distance measurement overlay grid to camera trap images. We aimed to establish meaningful density estimates of the mesocarnivore guild and evaluate CTDS's suitability for broader use with these types of species. We obtained density estimates for four carnivores, African civet Civettictis civetta, black‐backed jackal Canis mesomelas, brown hyena Hyaena brunnea and caracal Caracal caracal, providing valuable insight into their status in commercial farmland. Imprecision in the estimates was almost exclusively due to encounter rate variance, which was not reduced with the migrating camera grid. We explored the sensitivity of our results to assumptions determining the value of the ‘snapshot interval’, demonstrating that careful selection of this parameter is vital to ensuring reliable estimates when using rapid‐fire photo burst modes. CTDS can provide useful density estimates for mesocarnivores, but future studies should aim to maximize precision and reliability by increasing sampling locations. More studies are required in areas with known densities to promote confidence in accuracy.
The use of multiple‐pulse amperometry (MPA) for the determination of narrow therapeutic index (NTI) drugs using batch injection analysis (BIA) with carbon screen‐printed electrodes (SPE) is proposed, seeking to develop a practical and low‐cost analysis kit for application in routine quality control of these drugs. The electrochemical behaviors of aminophylline, carbamazepine, clindamycin, colchicine, minoxidil, prazosin, procainamide, theophylline, warfarin and verapamil were evaluated in different electrolytes, but just one, the 0.1 mol L−1 phosphate buffer, pH 7.0, was chosen for determination of all the analytes. The amperometric detection was optimized as a function of the best oxidation potential for carbon SPE for each analyte, which was in a range from 0.7 to 1.1 V. The injection conditions were determined as a function of the velocity and the volume injected by the BIA system, which were 92.5 μL s−1 and 100 μL, respectively. Under these conditions, a good repeatability (RSD<3 %), high analytical frequency (>215 determinations per hour), large linear ranges and low LOD (<0.42 μmol L−1) for all the NTI drugs were obtained. Furthermore, the proposed method provided an easy qualitative analysis of the investigated analytes using MPA detection. The addition‐recovery studies in pharmaceutical samples containing NTI drugs and the comparison with official methods showed that the proposed analysis Kit is a very fast, simple and efficient alternative for quantification of these analytes.
Knowledge on the spatio-temporal distribution of invasive plant species is vital to maintain biodiversity in grasslands which are threatened by the invasion of such plants and to evaluate the effect of control activities conducted. Manual digitising of aerial images with field verification is the standard method to create maps of the invasive Lupinus polyphyllus Lindl. (Lupine) in semi-natural grasslands of the UNESCO biosphere reserve “Rhön”. As the standard method is labour-intensive, a workflow was developed to map lupine coverage using an unmanned aerial vehicle (UAV)-borne remote sensing (RS) along with object-based image analysis (OBIA). UAV-borne red, green, blue and thermal imaging, as well as photogrammetric canopy height modelling (CHM) were applied. Images were segmented by unsupervised parameter optimisation into image objects representing lupine plants and grass vegetation. Image objects obtained were classified using random forest classification modelling based on objects’ attributes. The classification model was employed to create lupine distribution maps of test areas, and predicted data were compared with manually digitised lupine coverage maps. The classification models yielded a mean prediction accuracy of 89%. The maximum difference in lupine area between classified and digitised lupine maps was 5%. Moreover, the pixel-wise map comparison showed that 88% of all pixels matched between classified and digitised maps. Our results indicated that lupine coverage mapping using UAV-borne RS data and OBIA provides similar results as the standard manual digitising method and, thus, offers a valuable tool to map invasive lupine on grasslands.
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