Karst landscapes have an abundance of enclosed depressions. Many studies have detected depressions and have calculated geomorphometric characteristics with computer techniques. These outcomes are somewhat determined by the methods and data used. We aim to highlight the applicability of high-resolution relief laser scanning data in geomorphological studies of karst depressions. We set two goals: geomorphometrically to characterize depressions in different karst plateaus and to examine the influence of data preprocessing and detection methods on the results. The study was performed in three areas of the Slovene Dinaric Karst using the following steps: preprocessing digital elevation models (DEMs), enclosed depression detection, calculating geomorphometric characteristics, and comparing the characteristics of selected areas. We discovered that different combinations of methods influenced the number and geomorphometric characteristics of depressions. The range of detected depressions in the three areas were 442–491, 364–403, and 366–504, and the share of the depressions’ area confirmed with all the approaches was 23%, 29%, and 47%, which resulted in different geomorphometric properties. Comparisons between the study areas were also influenced by the methods, which was confirmed by the Mann–Whitney test. We concluded that preprocessing of high-resolution relief data and the detection methods in karst environments significantly impact analyses and must be taken into account when interpreting geomorphometric results.

Automatic methods for detecting and delineating relief features allow remote and low-cost mapping, which has an outstanding potential for wildlife ecology and similar research. We applied a filled-DEM (digital elevation model) method using LiDAR (Light Detection and Ranging) data to automatically detect dolines and other karst depressions in a rugged terrain of the Dinaric Mountains, Slovenia. Using this approach, we detected 9711 karst depressions in a 137 km² study area and provided their basic morphometric characteristics, such as perimeter length, area, diameter, depth, and slope. We performed visual validation based on shaded relief, which indicated 83.5% accordance in detecting depressions. Although the method has some drawbacks, it proved suitable for detection, general spatial analysis, and calculation of morphometric characteristics of depressions over a large scale in remote and forested areas. To demonstrate its applicability for wildlife research, we applied it in a preliminary study in combination with GPS-telemetry data to assess the selection of these features by two wild felids, the Eurasian lynx (Lynx lynx) and the European wildcat (Felis silvestris). Both species selected for vicinity of karst depressions, among which they selected for larger karst depressions. Lynx also regularly killed ungulate prey near these features, as we found more than half of lynx prey remains inside or in close vicinity of karst depressions. These results illustrate that karstic features could play an important role in the ecology of wild felids and warrant further research, which could be considerably assisted with the use of remote detection of relief features.

Context: Many carnivores are attracted to rugged terrain, rocky areas, and conspicuous relief features. However, most of the previous research is limited to general topographical habitat characteristics and rarely consider the effects of microhabitat characteristics. Objectives: We used the Eurasian lynx (Lynx lynx) as a model species to investigate the effects of microhabitat characteristics and human infrastructure on habitat selection. We also tested whether there is evidence for a functional response in habitat selection across a large gradient of habitat availability. Methods: We developed a new approach for detecting rocky outcrops from airborne LiDAR data. In combination with other remote sensing techniques and GPS-telemetry data, we assessed lynx habitat selection and functional responses across two geologically contrasting areas in Europe. Results: We detected > 1 million rocky outcrops and confirmed their strong selection by lynx. Lynx also selected steep, rugged, and rocky areas, especially for day-resting sites. Furthermore, lynx avoided paths during the day but selected them and other linear anthropogenic infrastructure during the night, indicating the behaviour-specific impact of human infrastructure. We also observed a functional response in the selection of rocky and rugged areas, as lynx’ selection of such habitats increased with their lower availability. This highlights the importance of preserving such terrains, especially when they are rare in a landscape. Conclusions: Our results highlight the importance of incorporating remote sensing techniques and data on microhabitat features in animal habitat selection research. We also recommend caution when developing new infrastructure for human recreation or promoting its use near geomorphological features and in rugged terrain.

Namen prispevka je na varovanem območju Natura 2000 ovrednotiti geodiverziteto in podati smernice za vključitev v obstoječi sistem naravovarstva. Kot območje preučevanja je bilo izbrano porečje Dragonje. Na podlagi kartografskega gradiva in terenskega dela smo izdelali morfografski zemljevid območja, s pomočjo literature pa prilagodili metodo izračuna indeksa geodiverzitete v geografskih informacijskih sistemih. Končni rezultat je zemljevid indeksa geodiverzitete, na podlagi katerega smo določili vroče točke geodiverzitete. // The importance of protection of geodiversity hotspots for the conservation of biodiversity in the Natura 2000 area in the Dragonja river valleyThe purpose of the article is to evaluate geodiversity in Natura 2000 protected area and to provide guidelines for inclusion in the existing nature protection system. The Dragonja River basin (SW Slovenia) was selected as a study area. Based on cartographic material and field work we made a morphographic map of the area, and based on the literature we adjusted the method of calculating the geodiversity index in geographic information systems. The final result is a map of the geodiversity index, on the basis of which geodiversity hotspots were determined.

The book Preteklost in prihodnost ('The past and the future') is the sixteenth volume in the GIS v Sloveniji (GIS in Slovenia) book series and commemorates its 30th anniversary. The goal of the volume is to present the wide variety of research findings on geographical information systems in Slovenia in recent years. Powerful geoinformatic tools and precise data facilitate research on processes and phenomena, and their modelling. The volume presents project outputs and research results in areas such as geology, geomorphology, hydrology, pedology, agriculture, natural disasters, environmental protection, geography, surveying, archaeology, transport, telecommunication infrastructure, tourism, cultural heritage, education, cartography, geographical names, remote sensing, and others. Readers discover new features regarding the applicability of geographical information systems and learn about interesting research findings in many areas.