Linking habitat composition, local population densities and traffic characteristics to spatial patterns of ungulate‐train collisions

Evaluating tramway infrastructure on biodiversity and ecosystem services

Tramways in urban areas for mass transit has been suggested to have a lower environmental footprint than roads. However, studies on the impact of tramways and the surrounding infrastructure on biodiversity is extremely rare despite the potential ecological effects associated with this anthropogenic feature. Surprisingly, we found fewer than 10 papers published on tramway-wildlife interactions, which is significantly lower (vs dozens of thousands) than that of other transportation methods. As tramways and stations may be managed sustainably by planting short vegetation on the track and roofs of tramway stations, they may be good examples of land-sharing policies in green urban planning, improving both biodiversity and people's well-being. The potential environmental benefits of green practices for commercially available tramways should be strictly tested and applied, especially in the context of the growing popularity of tramway systems worldwide.

Opportunities and challenges for monitoring a recolonizing large herbivore using citizen science

Monitoring is a prerequisite for evidence-based wildlife management and conservation planning, yet conventional monitoring approaches are often ineffective for species occurring at low densities. However, some species such as large mammals are often observed by lay people and this information can be leveraged through citizen science monitoring schemes. To ensure that such wildlife monitoring efforts provide robust inferences, assessing the quantity, quality, and potential biases of citizen science data is crucial. For Eurasian moose (Alces alces), a species currently recolonizing north-eastern Germany and occurring in very low numbers, we applied three citizen science tools: a mail/email report system, a smartphone application, and a webpage. Among these monitoring tools, the mail/email report system yielded the greatest number of moose reports in absolute and in standardized (corrected for time effort) terms. The reported moose were predominantly identified as single, adult, male individuals, and reports occurred mostly during late summer. Overlaying citizen science data with independently generated habitat suitability and connectivity maps showed that members of the public detected moose in suitable habitats but not necessarily in movement corridors. Also, moose detections were often recorded near roads, suggestive of spatial bias in the sampling effort. Our results suggest that citizen science-based data collection can be facilitated by brief, intuitive digital reporting systems. However, inference from the resulting data can be limited due to unquantified and possibly biased sampling effort. To overcome these challenges, we offer specific recommendations such as more structured monitoring efforts involving the public in areas likely to be roamed by moose for improving quantity, quality, and analysis of citizen science-based data for making robust inferences.

Is the Lesser Khingan Suitable for the Amur Tiger Restoration? Perspectives with the Current State of the Habitat and Prey Base

The Amur tiger (Panthera tigris) has a status of being endangered on the world's IUCN red list. The northwestern part of its range is situated in Russia and China, where tigers were exterminated by humans in the 1950-1970s. To restore tiger population within a historical range, an estimation of the habitat suitability is firstly needed. The Lesser Khingan mountains (Heilongjiang) was analyzed. Habitat types were mapped by satellite images analysis and field proven. The potential habitats of the main tiger's prey species (wild boar (Sus scrofa), roe deer (Capreolus pygargus), and red deer (Cervus elaphus xanthopygus) were also assessed. Maximum entropy and linear discriminant analysis methods were applied and compared for species distribution modeling (SDM). Species distribution maps were used to design an ecological network. The fragmentation of habitat patches was evaluated by spatial ecological metrics. The habitat patches with the best metrics were assigned as cores for the ecological network, which were connected by calculated corridors. The least cost distance method (based on distance to roads and settlements) was used. The recovery of the Amur tiger in habitats of China's Lesser Khingan is shown to be possible. Types of habitats were calculated as natural corridors for moving tigers. They are mainly located at the forests' edges and characterized with various canopy structures and high variability in the tree species composition. Three potential transboundary corridors are described: (a) foothills and low mountains of the northern Lesser Khingan; (b) connection between the southeast Lesser Khingan and the western part of the Wandashan mountain system; and (c) corridor within foothills and low mountains of the eastern part of Lesser Khingan. It is recommended to establish protected areas for the important tiger core habitats, and the main optimal ways for their migrations are described during the current investigation. Moreover, it is necessary to implement habitat recovery activities for key areas.

Pandora's Box: A spatiotemporal assessment of elephant-train casualties in Assam, India

Railways are an indispensable component of sustainable transportation systems, but also exact a toll on wildlife. Wild Asian elephants are often killed by trains in Assam, India, where we assess temporal variations in the occurrences of elephant-train collisions (ETCs) and casualties during 1990-2018. This study also assesses spatially varying relationships between elephant-train collision (ETC) rates and elephant and train densities in the adjoining 10 km2 grid cells of 11 prioritized railroad segments using ordinary least squares (OLS) and geographically weighted regression (GWR) models. The temporal analysis indicated that ETCs spiked at certain hours and months. The adult and calf elephant casualties on the railroads were found to be two to fivefold high during the post monsoon season compared to other seasons. During the operation period of meter gauge railroads (1990-1997), the proportions of ETCs and casualties were only 15.6% and 8.7% respectively. However, these increased substantially to 84.4% and 91.3% respectively during the operation of broad gauge railroads (1998-2018). The OLS model indicated that both elephant and train densities explained 37% of the variance of ETC rate, while GWR model showed 83% of the variance of ETC rate. The local coefficient values of GWR indicated that both the predictor variables interplayed significantly and positively to determine ETC rates in the Mariani-Nakachari and Khatkhati-Dimapur railroad segments. However, the relationship between ETC rate and elephant density is significantly negative in the Habaipur-Diphu railroad, implying that the elephant population along this railroad stretch is significantly affected by railways through large scale ETCs. Hence, there is an urgent need to address long-term mitigation strategies so that elephants can be conserved by providing safe passages and survival resources along railway lines.

Ungulates and trains - Factors influencing flight responses and detectability

Wildlife-train collisions can have deleterious effects on local wildlife populations and come with high socio-economic costs, such as damages, delays, and psychological distress. In this study, we explored two major components of wildlife-train collisions: the response of wildlife to oncoming trains and the detection of wildlife by drivers. Using dashboard cameras, we explored the flight response of roe deer (Capreolus capreolus) and moose (Alces alces) to oncoming trains and explored which factors, such as lighting and physical obstructions, affect their detection by drivers. In a majority of cases, roe deer and moose fled from an oncoming train, at an average flight initiation distance (FID) of 78 m and 79 m respectively. Warning horns had unexpected influences on flight behaviour. While roe deer initiated flight, on average, 44 m further away from the train when warned, they usually fled towards the tracks, in the direction of danger. FID of moose, however, was unaffected by the use of a warning horn. As train speed increased, moose had a lower FID, but roe deer FID did not change. Finally, detection of wildlife was obstructed by the presence of vegetation and uneven terrain in the rail-side verge, which could increase the risk of collisions. Our results indicate the need for early detection and warning of wildlife to reduce the risk of collisions. We propose that detection systems should include thermal cameras to allow detection behind vegetation and in the dark, and warning systems should use cues early to warn of oncoming trains and allow wildlife to escape the railway corridor safely.

Influence of infrastructure, ecology, and underpass-dimensions on multi-year use of Standard Gauge Railway underpasses by mammals in Tsavo, Kenya

Rail and road infrastructure is essential for economic growth and development but can cause a gradual loss in biodiversity and degradation of ecosystem function and services. We assessed the influence of underpass dimensions, fencing, proximity to water and roads, Normalized Difference Vegetation Index (NDVI), presence of other species and livestock on underpass use by large and medium-sized mammals. Results revealed hyenas and leopards used the underpasses more than expected whereas giraffes and antelopes used the underpasses less than expected. Generalized linear mixed-effects models revealed that underpass height influenced use by wildlife, with several species preferring to use taller underpasses. Electric fencing increased underpass use by funneling species towards underpasses, except for elephants and black-backed jackal for which it reduced underpass passage. We also found that the use of underpasses by livestock reduced the probability of use by nearly 50% for wildlife species. Carnivore species were more likely to cross underpasses used by their prey. Buffalo, livestock, and hyenas used underpasses characterized by vegetation with higher NDVI and near water sources while baboons, dik-diks and antelope avoided underpasses with high NDVI. Our findings suggest a need for diverse and comprehensive approaches for mitigating the negative impacts of rail on African wildlife.

A test of wildlife warning reflectors as a way to reduce risk of wildlife-train collisions

Looking for an effective method to reduce risk of animal-train collisions, we tested the system of wildlife warning reflectors, a method usually used on roads. The research was conducted in central Poland, along a 2.1 km stretch of the E65 railway line near Warsaw, during eight months, in the years 2010–2011. For six months of a test period, the reflectors were uncovered (active) and, for the next two months of the control period, they were covered (non-active). Digital cameras were used to register animal reactions to trains 24-hours per day. We compared the probability of escape (escape = 1; no reaction = 0) from an oncoming train during test and control periods of the research, in different parts of a day (i.e. day vs. night) and compared escape time of roe deer between day and night and with reflectors covered and uncovered. Roe deer (Capreolus capreolus), red fox (Vulpes vulpes) and brown hare (Lepus europaeus) were observed most often (702 observations in total). The status of reflectors (covered/uncovered) did not influence the probability of animals’ escape from an oncoming train. The only factors that affected the probability of escape were animal species and time of a day. Of the three species, roe deer was most likely to escape from an oncoming train (89% of probability at day and 52% during night, pooled data for covered and uncovered reflectors). Timing of roe deer escape from an oncoming train did not differ between day (6.4 seconds) and night, with either reflectors covered (7.5 seconds) or uncovered (4.6 seconds). The results indicated that wildlife warning reflectors were not effective to modify animal behaviour and to reduce risk of animal-train collisions.

A Systematic Review of Artificial Intelligence Public Datasets for Railway Applications

The aim of this paper is to review existing publicly available and open artificial intelligence (AI) oriented datasets in different domains and subdomains of the railway sector. The contribution of this paper is an overview of AI-oriented railway data published under Creative Commons (CC) or any other copyright type that entails public availability and freedom of use. These data are of great value for open research and publications related to the application of AI in the railway sector. This paper includes insights on the public railway data: we distinguish different subdomains, including maintenance and inspection, traffic planning and management, safety and security and type of data including numerical, string, image and other. The datasets reviewed cover the last three decades, from January 1990 to January 2021. The study revealed that the number of open datasets is very small in comparison with the available literature related to AI applications in the railway industry. Another shortcoming is the lack of documentation and metadata on public datasets, including information related to missing data, collection schemes and other limitations. This study also presents quantitative data, such as the number of available open datasets divided by railway application, type of data and year of publication. This review also reveals that there are openly available APIs—maintained by government organizations and train operating companies (TOCs)—that can be of great use for data harvesting and can facilitate the creation of large public datasets. These data are usually well-curated real-time data that can greatly contribute to the accuracy of AI models. Furthermore, we conclude that the extension of AI applications in the railway sector merits a centralized hub for publicly available datasets and open APIs.

Impact of Road Fencing on Ungulate–Vehicle Collisions and Hotspot Patterns

The number of road traffic accidents decreased in Lithuania from 2002 to 2017, while the ungulate–vehicle collision (UVC) number increased and accounted for approximately 69% of all wildlife–vehicle collisions (WVC) in the country. Understanding the relationship between UVCs, traffic intensity, and implemented mitigation measures is important for the assessment of UVC mitigation measure efficiency. We assessed the effect of annual average daily traffic (AADT) and wildlife fencing on UVCs using regression analysis of changes in annual UVCs and UVC hotspots on different categories of roads. At the highest rates, annual UVC numbers and UVC hotspots increased on lower category (national and regional) roads, forming a denser network. Lower rates of UVC increase occurred on higher category (main) roads, forming sparser road networks and characterized by the highest AADT. Before 2011, both UVC occurrence and fenced road sections were most common on higher-category roads. However, as of 2011, the majority of UVCs occurred on lower-category roads where AADT and fencing had no impact on UVCs. We conclude that wildlife fencing on roads characterized by higher speed and traffic intensity may decrease UVC numbers and at the same time shifting UVC occurrence towards roads characterized by lower speed and traffic intensity. Wildlife fencing re-allocates wildlife movement pathways toward roads with insufficient or no mitigation measures.

Railway mortality for several mammal species increases with train speed, proximity to water, and track curvature

Railways are a major source of direct mortality for many populations of large mammals, but they have been less studied or mitigated than roads. We evaluated temporal and spatial factors affecting mortality risk using 646 railway mortality incidents for 11 mammal species collected over 24 years throughout Banff and Yoho National Parks, Canada. We divided species into three guilds (bears, other carnivores, and ungulates), compared site attributes of topography, land cover, and train operation between mortality and paired random locations at four spatial scales, and described temporal patterns or mortality. Mortality risk increased across multiple guilds and spatial scales with maximum train speed and higher track curvature, both suggesting problems with train detection, and in areas with high proximity to and amount of water, both suggesting limitations to animal movement. Mortality risk was also correlated, but more varied among guilds and spatial scales, with shrub cover, topographic complexity, and proximity to sidings and roads. Seasonally, mortality rates were highest in winter for ungulates and other carnivores, and in late spring for bears, respectively. Our results suggest that effective mitigation could address train speed or detectability by wildlife, especially at sites with high track curvature that are near water or attractive habitat.