Grain spilled from moving trains create a substantial wildlife attractant in protected 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.

Animal Harms and Food Production: Informing Ethical Choices

Simple Summary

Consideration of animal welfare in food choices has become an influential contemporary theme. Traditional animal welfare views about food have been largely restricted to direct and intentional harms to livestock in intensive animal agriculture settings. However, many harms to animals arising from diverse food production practices in the world are exerted indirectly and unintentionally and often affect wildlife. Here we apply a qualitative analysis of food production by considering the breadth of harms caused by different food production systems to wild as well as domestic animals. Production systems are identified that produce relatively few and relatively many harms. The ethical implications of these findings are discussed for consumers concerned with the broad animal welfare impacts of their food choices.

Abstract

Ethical food choices have become an important societal theme in post-industrial countries. Many consumers are particularly interested in the animal welfare implications of the various foods they may choose to consume. However, concepts in animal welfare are rapidly evolving towards consideration of all animals (including wildlife) in contemporary approaches such as “One Welfare”. This approach requires recognition that negative impacts (harms) may be intentional and obvious (e.g., slaughter of livestock) but also include the under-appreciated indirect or unintentional harms that often impact wildlife (e.g., land clearing). This is especially true in the Anthropocene, where impacts on non-human life are almost ubiquitous across all human activities. We applied the “harms” model of animal welfare assessment to several common food production systems and provide a framework for assessing the breadth (not intensity) of harms imposed. We considered all harms caused to wild as well as domestic animals, both direct effects and indirect effects. We described 21 forms of harm and considered how they applied to 16 forms of food production. Our analysis suggests that all food production systems harm animals to some degree and that the majority of these harms affect wildlife, not livestock. We conclude that the food production systems likely to impose the greatest overall breadth of harms to animals are intensive animal agriculture industries (e.g., dairy) that rely on a secondary food production system (e.g., cropping), while harvesting of locally available wild plants, mushrooms or seaweed is likely to impose the least harms. We present this conceptual analysis as a resource for those who want to begin considering the complex animal welfare trade-offs involved in their food choices.

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.

Railway-Associated Attractants as Potential Contaminants for Wildlife

Grizzly bears (Ursus arctos) appear to be attracted to natural and anthropogenic forage along railways, which may increase collision vulnerability, but also potentially causes exposure to contaminants associated with railway infrastructure. We assessed contaminant exposure for a vulnerable population of grizzly bears in the Canadian Rocky Mountains by determining if (1) dandelions (Taraxacum officinale) growing adjacent to a railway and grain spilled from hopper cars contain heavy metals, polycyclic aromatic hydrocarbons (PAHs), and mycotoxins and (2) metal concentrations from hair samples of individual bears correlates with use of the railway or other anthropogenic features. We used principle components analysis to represent 10 heavy metals and 16 PAHs and then compared their concentrations in railway-associated sources of grain and dandelions to reference samples that we purchased (grain) or sampled from nearby sites (dandelions). We also measured metal concentrations in the hair of bears that were captured and fitted with GPS collars. We found significantly higher concentrations in railway-associated samples of dandelion and grain for both metals (particularly lead, iron, and chromium), and the sum of 16 PAHs. Several metals and PAHs in railway-associated samples exceeded regulatory standards for soil or animal feed. Mycotoxins were detectable in grain samples, but occurred well below permissible standards. Metal concentrations in bear hair were not predicted by railway use, but higher metal concentrations occurred in male bears and two individuals that used ski hills during fall. As mitigation to reduce wildlife exposure to contaminants, particularly in protected areas, we encourage removal of railway grain deposits, regular maintenance of railway infrastructure, such as lubricating stations, and investigation of contaminants associated with other human infrastructures, such as ski hills.

Animal learning may contribute to both problems and solutions for wildlife-train collisions

Transportation infrastructure can cause an ecological trap if it attracts wildlife for foraging and travel opportunities, while increasing the risk of mortality from collisions. This situation occurs for a vulnerable population of grizzly bears (Ursus arctos) in Banff National Park, Canada, where train strikes have become a leading cause of mortality. We explored this problem with analyses of rail-associated food attractants, habitat use of GPS-collared bears and patterns of past mortality. Bears appeared to be attracted to grain spilled from rail cars, enhanced growth of adjacent vegetation and train-killed ungulates with rail use that increased in spring and autumn, and in areas where trains slowed, topography was rugged, and human density was low. However, areas with higher grain deposits or greater use by bears did not predict sites of past mortality. The onset of reported train strikes occurred amid several other interacting changes in this landscape, including the cessation of lethal bear management, changes in the distribution and abundance of ungulates, increasing human use and new anthropogenic features. We posit that rapid learning by bears is critical to their persistence in this landscape and that this capacity might be enhanced to prevent train strikes in future with simple warning devices, such as the one we invented, that signal approaching trains. This article is part of the theme issue 'Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation'.

Using road patrol data to identify factors associated with carnivore roadkill counts

As the global road network expands, roads pose an emerging threat to wildlife populations. One way in which roads can affect wildlife is wildlife-vehicle collisions, which can be a significant cause of mortality through roadkill. In order to successfully mitigate these problems, it is vital to understand the factors that can explain the distribution of roadkill. Collecting the data required to enable this can be expensive and time consuming, but there is significant potential in partnering with organisations that conduct existing road patrols to obtain the necessary data. We assessed the feasibility of using roadkill data collected daily between 2014 and 2017 by road patrol staff from a private road agency on a 410 km length of the N3 road in South Africa. We modelled the relationship between a set of environmental and anthropogenic variables on the number of roadkill carcasses, using serval (Leptailurus serval) as a model species. We recorded 5.24 serval roadkill carcasses/100 km/year. The number of carcasses was related to season, the amount of wetland, and NDVI, but was not related to any of the anthropogenic variables we included. This suggests that roadkill patterns may differ greatly depending on the ecology of species of interest, but targeting mitigation measures where roads pass through wetlands may help to reduce serval roadkill. Partnering with road agencies for data collection offers powerful opportunities to identify factors related to roadkill distribution and reduce the threats posed by roads to wildlife.