Using lidar data to analyse sinkhole characteristics relevant for understory vegetation under forest cover-case study of a high karst area in the dinaric mountains

Multivariate analysis of the summer herbaceous vegetation and environmental factors of the sub-tropical region

Understanding the distribution of the plant species of an unexplored area is the utmost need of the present-day. In order to collect vegetation data, Quadrat method was used having size of 1 m2. The composite soil samples from each site were tested for various edaphic properties. PC-ORD v.5 was used for the classification of the vegetation while CANOCO v.5.1 was used for ordination of the data and to find out the complex relationship between plants and environment. Survey was conducted during summer season and a total of 216 herbaceous species were recorded from forty different sites of District Kohat, Pakistan. Cluster Analysis (CA) and Two-Way Cluster Analysis (TWCA) classified the vegetation of forty sites into six major plant groups i.e., 1. Paspalum paspalodes, Alternanthera sessilis, Typha domingensis, 2. Cynodon dactylon, Parthenium hysterophorus, Brachiaria ramosa, 3. Cynodon dactylon, Eragrostis minor, Cymbopogon jwarancusa, 4. Cymbopogon jwarancusa, Aristida adscensionis, Boerhavia procumbens, 5. Cymbopogon jwarancusa, Aristida adscensionis, Pennisetum orientale and 6. Heteropogon contortus, Bothriochloa ischaemum, Chrysopogon serrulatus. They were named after the dominant species based on their Importance Value (IV). The detrended correspondence analysis (DCA) analysis further confirmed the vegetation classification. Canonical correspondence analysis (CCA) indicated that the species distribution in the area was strongly affected by various environmental factors including status, soil characteristics, topography and altitude.

Environmental heterogeneity increases the conservation value of small natural features in karst landscapes

Local biodiversity hotspots are often located within regions where extreme and variable environmental - e.g., climatic and soil - conditions occur. These areas are conservation priorities. Although environmental heterogeneity is recognised as an important determinant of biodiversity, studies focusing on the effects of multiple environmental heterogeneity components in the same ecosystem are scarce. Here we investigate how topography and related microclimatic variables and soil properties may influence the biodiversity and conservation value of karst landscapes. Karst landscapes of the world contain millions of dolines (i.e. bowl- or funnel-shaped depressions) that may function as 'small natural features' with a disproportionately large role in maintaining biodiversity relative to their size. We assessed the diversity of microclimates, soils and vegetation and their relationships in six microhabitats (south-facing slopes, east-facing slopes, west-facing slopes, north-facing slopes and bottoms of dolines, and the adjacent plateau) for nine large dolines in a grassland ecosystem. Although there were remarkable differences among the conservation value of these microhabitats (e.g., representation of different species groups, presence of 'climate relicts'), each microhabitat had an important role in maintaining species that are rare or absent in other microhabitats in the landscape. We found that the studied dolines exhibited highly variable environmental conditions and promoted a high diversity of vegetation types with unique species composition, contributing to the topographic, climatic, soil, vegetation and land cover heterogeneity of karst landscapes. Therefore, our findings highlight that dolines may function as local biodiversity hotspots and have a crucial conservation importance. As dolines are widespread topographic features in many karst landscapes throughout the world, our results could be directly applied to other regions as well. An integrated approach is urgently needed to provide guidelines for landscape management, promoting the retention of the microhabitat diversity of small natural features for species vulnerable to climate change and/or various disturbances.

Point Density Variations in Airborne Lidar Point Clouds

In spite of increasing point density and accuracy, airborne lidar point clouds often exhibit point density variations. Some of these density variations indicate issues with point clouds, potentially leading to errors in derived products. To highlight these issues, we provide an overview of point density variations and show examples in six airborne lidar point cloud datasets that we used in our topographic and geospatial modeling research. Using the published literature, we identified sources of point density variations and issues indicated or caused by these variations. Lastly, we discuss the reduction in point density variations using decimations, homogenizations, and their applicability.

Evaluation of Forest Features Determining GNSS Positioning Accuracy of a Novel Low-Cost, Mobile RTK System Using LiDAR and TreeNet

Accurate positioning is one of the main components and challenges for precision forestry. This study was established to test the feasibility of a low-cost GNSS receiver, u-blox ZED-F9P, in movable RTK mode with features that determine its positioning accuracy following logging trails in the forest environment. The accuracy of the low-cost receiver was controlled via a geodetic-grade receiver and high-density LiDAR data. The features of nearby logging trails were extracted from the LiDAR data in three main categories: tree characteristics; ground-surface conditions; and crown-surface conditions. An object-based TreeNet approach was used to explore the influential features of the receiver’s positioning accuracy. The results of the TreeNet model indicated that tree height, ground elevation, aspect, canopy-surface elevation, and tree density were the top influencing features. The partial dependence plots showed that tree height above 14 m, ground elevation above 134 m, western direction, canopy-surface elevation above 138 m, and tree density above 30% significantly increased positioning errors by the low-cost receiver over southern Finland. Overall, the low-cost receiver showed high performance in acquiring reliable and consistent positions, when integrated with LiDAR data. The system has a strong potential for navigating machinery in the pathway of precision harvesting in commercial forests.

The Impact of Digital Elevation Model Preprocessing and Detection Methods on Karst Depression Mapping in Densely Forested Dinaric Mountains

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.

Dolines and Cats: Remote Detection of Karst Depressions and Their Application to Study Wild Felid Ecology

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.

Lidar-Based Morphometry of Conical Hills in Temperate Karst Areas in Slovenia

Conical hills, or residual hills, are frequently mentioned landforms in the context of humid tropical karsts as they are dominant surface elements there. Residual hills are also present in temperate karsts, but generally in a less remarkable way. These landforms have not been thoroughly addressed in the literature to date, therefore the present article is the first attempt to morphometrically characterize temperate zone residual karst hills. We use the methods already developed for doline morphometry, and we apply them to the “inverse” topography using LiDAR-based digital terrain models (DTMs) of three Slovenian sample areas. The characteristics of hills and depressions are analysed in parallel, taking into account the rank of the forms. A common feature of hills and dolines is that, for both types, the empirical distribution of planform areas has a strongly positive skew. After logarithmic transformation, these distributions can be approximated by Inverse Gaussian, Normal, and Weibull distributions. Along with the rank, the planform area and vertical extent of the hills and dolines increase similarly. High circularity is characteristic only of the first-rank forms for both dolines and hills. For the sample areas, the the hill area ratios and the doline area ratios have similar values, but the total extent of the hills is slightly larger in each case. A difference between dolines and hills is that the shapes of hills are more similar to one another than those of dolines. The reason for this is that the larger, closed depressions are created by lateral coalescence, while the hills are residual forms carved from large blocks. Another significant difference is that the density of dolines is much higher than that of hills. This article is intended as a methodological starting point for a new topic, aiming at the comprehensive study of residual karst hills across different climatic areas.

Tree Height Growth Modelling Using LiDAR-Derived Topography Information

The concepts of ecotopes and forest sites are used to describe the correlative complexes defined by landform, vegetation structure, forest stand characteristics and the relationship between soil and physiography. Physically heterogeneous landscapes such as karst, which is characterized by abundant sinkholes and outcrops, exhibit diverse microtopography. Understanding the variation in the growth of trees in a heterogeneous topography is important for sustainable forest management. An R script for detailed stem analysis was used to reconstruct the height growth histories of individual trees (steam analysis). The results of this study reveal that the topographic factors influencing the height growth of silver fir trees can be detected within forest stands. Using topography modelling, we classified silver fir trees into groups with significant differences in height growth. This study provides a sound basis for the comparison of forest site differences and may be useful in the calibration of models for various tree species.

Karstic Microrefugia Host Functionally Specific Ant Assemblages

Karst landscapes are among the topographically most complex systems with various microhabitats, where species can persist despite unfavourable macro-environmental changes. These microhabitats can also function as stepping stones during range shifts. Although the enclosed depressions (dolines, sinkholes or tiankengs) of karst landscapes may act as such safe havens, data on the functional diversity of their animal assemblages are scarce. Here, we investigate the functional diversity (i.e., certain functional groups and functional traits) of ant assemblages in dolines and study whether dolines surrounded by resource-poor environments (i.e., Fagus sylvatica forests) may function as safe havens for different kinds of ants. We found that dolines have the potential to maintain distinctive ant assemblages characterised by specific functional groups and traits that are rare in the surrounding habitats. Although continuous Fagus sylvatica cover in dolines had a detrimental impact on ant assemblages, grassland dolines surrounded by grasslands or Fagus sylvatica forests supported the presence of some specific functional groups and traits. These results suggest that conservation management needs to consider the influence of vegetation characteristics not only in dolines but also on the surrounding plateau. Moderate grazing and/or mowing would be desirable in order to prevent shrub encroachment into grasslands to ensure optimal vegetation structure for ants in the long run. Therefore, proper management and conservation of these safe havens may mitigate the rate of biodiversity loss under global warming. There is a need to explore a wide variety of taxonomic groups and taxon-specific traits in parallel with the quality of the surrounding habitats when evaluating current and potential microrefugia.

Evaluation and Quantification of the Effects of Climate and Vegetation Cover Change on Karst Water Sources: Case Studies of Two Springs in South-Western Slovenia

Karst aquifers hold important water resources such as regional water budgets and freshwater supply. Due to highly dynamic hydrological processes in comparison to other less permeable systems, they are particularly susceptible to environmental changes. However, little research directly characterizes the impacts of climate and vegetation cover changes on karst water sources. In this study, we aimed to evaluate individual long-term impacts and impacts of sudden large-scale forest disturbances on changes in groundwater recharge and in spring discharge. The work is based on temporal analysis of forest cover and a comparison of trend analysis of hydro-meteorological parameters. To investigate and evaluate vegetation cover change impacts on groundwater recharge, we used a soil water balance model and compared estimated actual daily values of effective precipitation to its fictional estimation disregarding the vegetation cover change. The applied methodology enabled quantification of the impacts of climate and vegetation cover change on selected karst water sources. The study suggests that the vegetation cover can have a significant impact on the spring recharge. Large-scale disturbances that occurred in a short-term mitigated the effects expected from the trend analysis of hydro-meteorological parameters. In the long-term, in addition to climate changes, the multi-decadal natural vegetation overgrowth significantly contributed to the reduction in the spring’s discharge values, especially in the warm season when water demand is higher. Therefore, the results are of key importance for developing proper water management and environmental policies.

Object-Based Image Analysis of Ground-Penetrating Radar Data for Archaic Hearths

Object-based image analysis (OBIA) has been increasingly used to identify terrain features of archaeological sites, but only recently to extract subsurface archaeological features from geophysical data. In this study, we use a semi-automated OBIA to identify Archaic (8000–1000 BC) hearths from Ground-Penetrating Radar (GPR) data collected at David Crockett Birthplace State Park in eastern Tennessee in the southeastern United States. The data were preprocessed using GPR-SLICE, Surfer, and Archaeofusion software, and amplitude depth slices were selected that contained anomalies ranging from 0.80 to 1.20 m below surface (BS). Next, the data were segmented within ESRI ArcMap GIS software using a global threshold and, after vectorization, classified using four attributes: area, perimeter, length-to-width ratio, and Circularity Index. The user-defined parameters were based on an excavated Archaic circular hearth found at a depth greater than one meter, which consisted of fire-cracked rock and had a diameter greater than one meter. These observations were in agreement with previous excavations of hearths at the site. Features that had a high probability of being Archaic hearths were further delineated by human interpretation from radargrams and then ground-truthed by auger testing. The semi-automated OBIA successfully predicted 15 probable Archaic hearths at depths ranging from 0.85 to 1.20 m BS. Observable spatial clustering of hearths may indicate episodes of seasonal occupation by small mobile groups during the Archaic Period.

Evaluating Short-Term Impacts of Forest Management and Microsite Conditions on Understory Vegetation in Temperate Fir-Beech Forests: Floristic, Ecological, and Trait-Based Perspective

Forest understory vegetation is largely influenced by disturbances and given local abiotic conditions. Our research focuses on the early response of understory vegetation to various forest management intensities in Dinaric fir-beech forests in Slovenia: (i) control, (ii) 50% cut of stand growing stock, and (iii) 100% cut of stand growing stock. Apart from identifying overstory removal effects, we were interested in fine-scale variation of understory vegetation and environmental determinants of its species composition. Vegetation was sampled within 27 karst sinkholes, which represent a dominant landform in studied forests. Within each sinkhole, five sampling plots, varying in slope aspect (centre, north, east, south, west), were established (135 in total), where pre-treatment (in 2012) and post-treatment (in 2014) floristic surveys were conducted. The sampled understory species were characterized in terms of Ellenberg’s indicator values (EIVs) and plant functional traits (plant height, seed mass, specific leaf area, leaf dry matter content). Diversity metrics (species richness, total cover, Shannon index) increased in plots where the silvicultural measures were applied. Tree species richness also increased in 100% cutting. A redundancy analysis revealed that species composition was related to environmental variables, which are directly influenced by management interventions (overstory canopy cover, microclimate—maximum daily temperature, soil properties—thickness of organic soil layer) as well as by topographic factors (slope inclination and surface rockiness). EIVs for light were significantly affected by treatment intensity, whereas soil-related EIVs (moisture, reaction, nutrients) depended more on the within-sinkhole position. Canopy gaps, compared with uncut control plots, hosted a higher number of colonizing species with a higher plant height and smaller seeds, while leaf traits did not show a clear response. We found a negative correlation between pre-treatment species (functional) richness and post-treatment shifts in floristic (functional) composition. Plots with higher richness exhibited smaller changes compared with species-poor communities. Incorporating different perspectives, the results of this study offer valuable insights into patterns of understory vegetation response to forest management in fir-beech forests.

A Review of Underground Pipeline Leakage and Sinkhole Monitoring Methods Based on Wireless Sensor Networking

Major metropolitan cities worldwide have extensively invested to secure utilities and build state-of-the-art infrastructure related to underground fluid transportation. Sewer and water pipelines make our lives extremely convenient when they function appropriately. However, leakages in underground pipe mains causes sinkholes and drinking-water scarcity. Sinkholes are the complex problems stemming from the interaction of leaked water and ground. The aim of this work is to review the existing methods for monitoring leakage in underground pipelines, the sinkholes caused by these leakages, and the viability of wireless sensor networking (WSN) for monitoring leakages and sinkholes. Herein, the authors have discussed the methods based on different objectives and their applicability via various approaches—(1) patent analysis; (2) web-of-science analysis; (3) WSN-based pipeline leakage and sinkhole monitoring. The study shows that the research on sinkholes due to leakages in sewer and water pipelines by using WSN is still in a premature stage and needs extensive investigation and research contributions. Additionally, the authors have suggested prospects for future research by comparing, analyzing, and classifying the reviewed methods. This study advocates collocating WSN, Internet of things, and artificial intelligence with pipeline monitoring methods to resolve the issues of the sinkhole occurrence.

Sinkhole Detection and Characterization Using LiDAR-Derived DEM with Logistic Regression

Depressions due to sinkhole formation cause significant structural damages to buildings and civil infrastructure. Traditionally, visual inspection has been used to detect sinkholes, which is a subjective way and time- and labor-consuming. Remote sensing techniques have been introduced for morphometric studies of karst landscapes. This study presents a methodology for the probabilistic detection of sinkholes using LiDAR-derived digital elevation model (DEM) data. The proposed study provides benefits associated with: (1) Detection of unreported sinkholes in rural and/or inaccessible areas, (2) automatic delineation of sinkhole boundaries, and (3) quantification of the geometric characteristics of those identified sinkholes. Among sixteen morphometric parameters, nine parameters were chosen for logistic regression, which was then employed to compute the probability of sinkhole detection; a cutoff value was back-calculated such that the sinkhole susceptibility map well predicted the reported sinkhole boundaries. According to the results of the LR model, the optimal cutoff value was calculated to be 0.13, and the area under the curve (AUC) of the receiver operating characteristic curve (ROC) was 0.90, indicating the model is reliable for the study area. For those identified sinkholes, the geometric characteristics (e.g., depth, length, area, and volume) were computed.

Karst dolines provide diverse microhabitats for different functional groups in multiple phyla

Fine-scale topographic complexity creates important microclimates that can facilitate species to grow outside their main distributional range and increase biodiversity locally. Enclosed depressions in karst landscapes (‘dolines’) are topographically complex environments which produce microclimates that are drier and warmer (equator-facing slopes) and cooler and moister (pole-facing slopes and depression bottoms) than the surrounding climate. We show that the distribution patterns of functional groups for organisms in two different phyla, Arthropoda (ants) and Tracheophyta (vascular plants), mirror this variation of microclimate. We found that north-facing slopes and bottoms of solution dolines in northern Hungary provided key habitats for ant and plant species associated with cooler and/or moister conditions. Contrarily, south-facing slopes of dolines provided key habitats for species associated with warmer and/or drier conditions. Species occurring on the surrounding plateau were associated with intermediate conditions. We conclude that karst dolines provide a diversity of microclimatic habitats that may facilitate the persistence of taxa with diverse environmental preferences, indicating these dolines to be potential safe havens for multiple phyla under local and global climate oscillations.

Locating Cave Entrances Using Lidar-Derived Local Relief Modeling

Lidar (Light detection and ranging) scanning has revolutionized our ability to locate geographic features on the earth’s surface, but there have been few studies that have addressed discovering caves using this technology. Almost all attempts to find caves using lidar imagery have focused on locating sinkholes that lead to underground cave systems. As archaeologists, our work in the Chiquibul Forest Reserve, a heavily forested area in western Belize, focuses on locating potential caves for investigation. Caves are an important part of Maya cultural heritage utilized by the ancient Maya people as ritual spaces. These sites contain large numbers of artifacts, architecture, and human remains, but are being looted at a rapid rate; therefore, our goal is to locate and investigate as many sites as possible during our field seasons. While some caves are entered via sinkholes, most are accessed via vertical cliff faces or are entered by dropping into small shafts. Using lidar-derived data, our goal was to locate and investigate not only sinkholes but other types of cave entrances using point cloud modeling. In this article, we describe our method for locating potential cave openings using local relief models that require only a working knowledge of relief visualization techniques. By using two pedestrian survey techniques, we confirmed a high rate of accuracy in locating cave entrances that varied in both size and morphology. Although 100% pedestrian survey coverage delivered the highest rate accuracy in cave detection, lidar image analyses proved to be expedient for meeting project goals when considering time and resource constraints.

Large- and small-scale environmental factors drive distributions of cool-adapted plants in karstic microrefugia

BACKGROUND AND AIMS

Dolines are small- to large-sized bowl-shaped depressions of karst surfaces. They may constitute important microrefugia, as thermal inversion often maintains cooler conditions within them. This study aimed to identify the effects of large- (macroclimate) and small-scale (slope aspect and vegetation type) environmental factors on cool-adapted plants in karst dolines of East-Central Europe. We also evaluated the potential of these dolines to be microrefugia that mitigate the effects of climate change on cool-adapted plants in both forest and grassland ecosystems.

METHODS

We compared surveys of plant species composition that were made between 2007 and 2015 in 21 dolines distributed across four mountain ranges (sites) in Hungary and Romania. We examined the effects of environmental factors on the distribution and number of cool-adapted plants on three scales: (1) regional (all sites); (2) within sites and; (3) within dolines. Generalized linear models and non-parametric tests were used for the analyses.

KEY RESULTS

Macroclimate, vegetation type and aspect were all significant predictors of the diversity of cool-adapted plants. More cool-adapted plants were recorded in the coolest site, with only few found in the warmest site. At the warmest site, the distribution of cool-adapted plants was restricted to the deepest parts of dolines. Within sites of intermediate temperature and humidity, the effect of vegetation type and aspect on the diversity of cool-adapted plants was often significant, with more taxa being found in grasslands (versus forests) and on north-facing slopes (versus south-facing slopes).

CONCLUSIONS

There is large variation in the number and spatial distribution of cool-adapted plants in karst dolines, which is related to large- and small-scale environmental factors. Both macro- and microrefugia are therefore likely to play important roles in facilitating the persistence of cool-adapted plants under global warming.