ArticleEnvironmental management2020
Railway-Associated Attractants as Potential Contaminants for Wildlife.
Article in Environmental management, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 10 citations in OpenAlex.
- Accumulation of metals in the leaves of different urban forest tree species and its relation to the proximity to the airport.Environmental science and pollution research international · 2026Article
- The Initial Detection of Mycotoxins Released and Accumulated in the Golden Jackal (International journal of molecular sciences · 2025Article
- An exploratory spatial contaminant assessment for polar bear (Ursus maritimus) liver, fat, and muscle from northern Canada.Environmental pollution (Barking, Essex : 1987) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.