Search

The article presents the results of ecological niche and habitat suitability modelling of Ursus arctos, performed in the Central Forest State Nature Reserve and its buffer zone (Tver region, Russia), using the GNESFA factor analysis method. Briefly discussed are the basic rules for performing such a study, approaches and modelling techniques. The ecological niche was modelled using FANTER, ENFA and MADIFA. The habitat suitability was modelled using Mahalanobis distances analysis. As ecogeographical variables, vegetation indices, morphometric characteristics of the relief, proximity rasters and types of landscape cover were used. The presence points of the species were recorded on permanent routes using a GPS navigator during 2008–2018. As a final result, six models with a different combination of input data (presence points and environmental variables) were selected. As a set of independent test data, we used U. arctos' presence points recorded by the forest rangers and research staff. The scenarios of the influence of utilisation weights on presence points and multicollinearity on variables are separately modelled. The global marginality of the best model was 1.17, while the tolerance was 0.69. The distance to anthropogenic food sources, the NDVI and the projective cover of grasslands made the highest contribution along the marginality axis. In the first three axes of specialisation, coniferous forests, Sphagnum pine (Pinus sylvestris) forests, and the distance to the rivers made the largest contribution. AUC values ranged from 0.66 to 0.73. Values of the continuous Boyce index were from 0.85 to 0.93. The area of the partially violated buffer zone turned out to be more suitable for U. arctos than the inner area of the Central Forest State Nature Reserve. Utilisation weights and the number of ecogeographical variables had a significant impact on the results of all analyses.

This article is a continuation of the review of software for storing, processing and analysing data from camera traps. The review includes the latest software for processing data from camera traps that have appeared in recent years, as well as some already outdated solutions. For the first time, the topics of work of such software with video files and GIS are highlighted in Russian. We provide detailed descriptions of such thematic software as SpeedyMouse, TrophyRoom, ViXeN, camtrapR, CPW Photo Warehouse, Wild.ID, Camelot and ZSL CTAP. We briefly reviewed online services for camera trap data processing and web applications: eMammal, Snapshot Serengeti, Agouti, Western Shield, TRAPPER, as well as the global data repository for camera traps data – Wildlife Insights. The possibilities of working with camera traps in GIS are separately considered: e.g. plugins for QGIS (Geotag and Import Photos and eVis), as well as the GeoTagged Photos to Points tool for ArcGIS. Many advantages and disadvantages of the presented solutions, as well as some methods of working with them, are analysed. On the example of own studies in the Central Forest Nature Biosphere Reserve (Russia) a comparative analysis of various programs and approaches in the use of camera traps as a method of zoological studies was conducted. In addition, general recommendations were given on working with them for other Protected Areas. We identified the key characteristics of the programs for working with camera traps that are worth paying attention to when choosing a particular solution. For all of these software packets, there are hyperlinks for their free download, as well as hyperlinks to user manuals and tutorials. The purpose of the article was not only to identify the most optimal (from author's viewpoint) tools for working with the data of camera traps, but also to acquaint readers with the diversity of such means in world practice.

Here are presented the results of the analysis of daily activity patterns obtained from the data of camera traps for five large mammals (elk Alces alces, wild boar Sus scrofa, brown bear Ursus arctos, grey wolf Canis lupus, Eurasian lynx Lynx lynx) and three medium ones (European badger Meles meles, raccoon dog Nyctereutes procyonoides, mountain hare Lepus timidus) for the territory of the Central Forest Nature Reserve, Valdai Upland, Russia. Data were collected in the period 2010–2017 and the trap effort was 30 158 camera days from 21 locations. Most of the mammals surveyed showed activity at night and twilight hours (71% of the pictures). The hare was most active among all and dominant at night. In many respects it is similar to the activity of a raccoon dog, which type can be defined as nocturnal too. Unlike a hare, a raccoon dog has a weak peak in the daytime and less activity in the night. Badgers movements are confined to the twilight and nighttime. The share of nocturnal activity of large ungulates such as elk and wild boar was approximately the same and amounted to about 45% of all registrations. The wild boar is slightly more active during the day and in the evening and is not active at all in the morning. The elk is active in the morning, and in the daytime and to a lesser extent in the evening. The lynx and the bear have similar cathemeral activity patterns: almost half of all their meetings occurred at daylight hours and only slightly – less than 40% – at night. The brown bear had the maximum number of registrations in the daytime among all the studied species. Despite the fact that the main object of lynx feeding in the reserve is the hare, there was no high degree of overlap between them (γˆ = 0.75). In the group of large carnivores, the wolf was noticeably distinguished, more than half of its registrations were at night, and a third – on daytime. Daily activities of the wolf and its main prey elk showed a large overlap (γˆ = 0.89). The seasonal variations of daily activity of all species were also shown. According to the results of factor analysis, each of the studied species was divided into one of three separate groups. The first group included species with a tendency to nocturnal activity (wolf, elk, hare, badger, and raccoon dog), the second group – cathemeral animals (bear and lynx). In the third group was only the wild boar, whose activity was associated with the evening hours. This is the first long-term continuous camera trap survey in Russia and it provides detailed daily activity patterns for multiple large and medium-sized sympatric mammals.

An overview of the main problems in collection, storage, processing and analysis of data obtained by camera traps is conducted. Basing on reviewed national papers related to this theme, the conclusion is drawn that there is need for a detailed description of methodological approaches and tools for data processing in national studies. The most common software among foreign researchers for camera trap data processing in biodiversity studies and conservation projects is presented. An overview of thematic software such as Photospread, Aardwolf, CameraTrapManager, MapView, CameraBase and DeskTEAM is provided. Advantages and disadvantages, as well as working methods are detailed in the study. The principles of image metadata storage, methods of extraction and processing are considered. Comparative analysis of the different software and approaches to use camera traps as a method of zoological research are provided. General recommendations regarding their use in protected areas are provided, illustrated by studies conducted in the Central Forest Reserve. The key characteristics of software for camera traps that should be considered when choosing a specific solution are identified. Primary characteristics are the ability to import all image metadata, quick and easy tagging, export to the majority of formats. Wishes to improve and discuss methodological approaches among national researchers are expressed. Despite a large variety of available technical means, the need to develop national software for working with camera trap data is separately noted. All listed software items are provided with download hyperlinks, and user's manual hyperlinks.