Underreporting of wildlife-vehicle collisions does not hinder predictive models for large ungulates

Conflicts from wildlife–vehicle collisions (WVCs) pose serious challenges for managing and conserving large ungulates throughout the world. However, underreporting of large proportions of WVCs (i.e., two-thirds of WVCs in some cases) creates concern for relying on governmental databases to inform management strategies of WVCs. Our objective was to test the sensitivity of WVC studies to underreporting using 2 species of large ungulates that experience substantial incidences of collisions but exist in different environmental settings: white-tailed deer (Odocoileus virginianus) in agricultural-dominated central Illinois and moose (Alces alces) in forest-dominated western Maine, USA. We estimated baseline relationships between the landscape, traffic, and abundance of wildlife on the probabilities of WVCs using the total number of reported WVCs. Then, we simulated underreporting by randomly excluding reports of WVCs and evaluated for relative changes in precision, parameter estimates, and prediction. Point estimates of the relationships between environmental influences and WVCs for both species were reliable until high rates of underreporting occurred (≥70%). When underreporting occurred with spatial bias, shifts in point estimates were detected only for variables that spatially-corresponded with the rate of reporting. Prediction estimates for both species were also reliable until high rates of underreporting occurred (≥75%). These findings suggest that predictive models generate reliable estimates about WVCs with large ungulates unless underreporting is severe; possibly because they occur in non-random patterns (i.e., hotspots) and variability in their environment influences is low. We recommend that concern about underreporting not impede research with existing databases, such as those in this study, for analyzing predictive models and developing management strategies for reducing WVCs

The utility of micro-computed tomography for the non-destructive study of eye microstructure in snails

Molluscan eyes exhibit an enormous range of morphological variation, ranging from tiny pigment-cup eyes in limpets, compound eyes in ark clams and pinhole eyes in Nautilus, through to concave mirror eyes in scallops and the large camera-type eyes of the more derived cephalopods. Here we assess the potential of non-destructive micro-computed tomography (µ-CT) for investigating the anatomy of molluscan eyes in three species of the family Solariellidae, a group of small, deep-sea gastropods. We compare our results directly with those from traditional histological methods applied to the same specimens, and show not only that eye microstructure can be visualised in sufficient detail for meaningful comparison even in very small animals, but also that μ-CT can provide additional insight into gross neuroanatomy without damaging rare and precious specimens. Data from μ-CT scans also show that neurological innervation of eyes is reduced in dark-adapted snails when compared with the innervation of cephalic tentacles, which are involved in mechanoreception and possibly chemoreception. Molecular tests also show that the use of µ-CT and phosphotungstic acid stain do not prevent successful downstream DNA extraction, PCR amplification or sequencing. The use of µ-CT methods is therefore highly recommended for the investigation of difficult-to-collect or unique specimens.Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The attached file is the published pdf

A landscape-based approach for delineating hotspots of wildlife-vehicle collisions

Imposing human perceptions about the scales of ecological processes can produce unreliable scientific inferences in wildlife research and possibly misinform mitigation strategies. An example of this disconnect occurs in studies of wildlife-vehicle collisions (WVCs). Subjective procedures are often used to delineate hotspots of WVCs, resulting in hotspots that are not spatially independent. We developed a new approach that identifies independent hotspots using attributes of the landscape to inform delineations instead of subjective measures. First, we generated a candidate set of grouping scenarios using unique combinations of kernel-density estimation parameterization (i.e., bandwidth and isopleth values). Next, we associated the groups of WVCs with attributes of the surrounding landscape. Finally, we identified the grouping scenario with the highest amount of variation in the landscape among the groups. The highest variation corresponded to hotspots that were most distinguishable from each other (i.e., most independent) based on the surrounding landscape. We tested our approach on 3 species of wildlife [island foxes (Urocyon littoralis) on San Clemente Island, CA; white-tailed deer (Odocoileus virginianus) in Onondaga County, NY; and moose (Alces alces) in western Maine] that exemplified varying degrees of space-use in different landscapes. We found that the landscape based approach was able to effectively delineate independent hotspots for each species without using subjective measures. The landscape-based approach delineated fewer or larger hotspots than currently used methods, suggesting a reduction in spatial dependency among hotspots. Variation in the landscape indicated that hotspots may be larger than previously identified; therefore current mitigation strategies should be adjusted to include larger areas of high risk

A landscape-based approach for delineating hotspots of wildlife-vehicle collisions

Imposing human perceptions about the scales of ecological processes can produce unreliable scientific inferences in wildlife research and possibly misinform mitigation strategies. An example of this disconnect occurs in studies of wildlife-vehicle collisions (WVCs). Subjective procedures are often used to delineate hotspots of WVCs, resulting in hotspots that are not spatially independent. We developed a new approach that identifies independent hotspots using attributes of the landscape to inform delineations instead of subjective measures. First, we generated a candidate set of grouping scenarios using unique combinations of kernel-density estimation parameterization (i.e., bandwidth and isopleth values). Next, we associated the groups of WVCs with attributes of the surrounding landscape. Finally, we identified the grouping scenario with the highest amount of variation in the landscape among the groups. The highest variation corresponded to hotspots that were most distinguishable from each other (i.e., most independent) based on the surrounding landscape. We tested our approach on 3 species of wildlife [island foxes (Urocyon littoralis) on San Clemente Island, CA; white-tailed deer (Odocoileus virginianus) in Onondaga County, NY; and moose (Alces alces) in western Maine] that exemplified varying degrees of space-use in different landscapes. We found that the landscape based approach was able to effectively delineate independent hotspots for each species without using subjective measures. The landscape-based approach delineated fewer or larger hotspots than currently used methods, suggesting a reduction in spatial dependency among hotspots. Variation in the landscape indicated that hotspots may be larger than previously identified; therefore current mitigation strategies should be adjusted to include larger areas of high risk

Surmounting structural barriers to tackle endemic infectious diseases

A unique experiment in bringing academic and industrial scientists together to tackle endemic infectious diseases has proved a success. The Tres Cantos Open Lab Foundation, guided and advised by independent experts, funds extended stays of academics at the campus of a pharmaceutical company, where they access the firm’s resources in partnership with company scientists. Progress in tackling tuberculosis, protozoal infections, and enteric bacterial diseases has sustained the decade-long evolution of the model, whose distinctive features complement other public–private partnerships with similar goals

Elevated estuary water temperature drives fish gut dysbiosis and increased loads of pathogenic vibrionaceae

Marine water temperatures are increasing globally, with eastern Australian estuaries warming faster than predicted. There is growing evidence that this rapid warming of coastal waters is increasing the abundance and virulence of pathogenic members of the Vibrionaceae, posing a significant health risk to both humans and aquatic organisms. Fish disease, notably outbreaks of emerging pathogens in response to environmental perturbations such as heatwaves, have been recognised in aquaculture settings. Considerably less is known about how rising sea surface temperatures will impact the microbiology of wild fish populations, particularly those within estuarine systems that are more vulnerable to warming. We used a combination of Vibrio-specific quantitative PCR and amplicon sequencing of the 16S rRNA and hsp60 genes to examine seawater and fish (Pelates sexlineatus) gut microbial communities across a quasi-natural experimental system, where thermal pollution from coal-fired power stations creates a temperature gradient of up to 6 °C, compatible with future predicted temperature increases. At the warmest site, fish hindgut microbial communities were in a state of dysbiosis characterised by shifts in beta diversity and a proliferation (71.5% relative abundance) of the potential fish pathogen Photobacterium damselae subsp. damselae. Comparable patterns were not identified in the surrounding seawater, indicating opportunistic proliferation within estuarine fish guts under thermal stress. A subsequent evaluation of predicted future warming-related risk due to pathogenic Vibrionaceae in temperate estuarine fish demonstrated that warming is likely to drive opportunistic pathogen increases in the upper latitudinal range of this estuarine fish, potentially impacting adaptations to future warming. These findings represent a breakthrough in our understanding of the dynamics of emerging pathogens in populations of wild aquatic organisms within environments likely to experience rapid warming under future climate change

Legacy metal contamination is reflected in the fish gut microbiome in an urbanised estuary

Estuaries are critical habitats subject to a range of stressors requiring effective management. Microbes are gaining recognition as effective environmental indicators, however, the response of host associated communities to stressors remains poorly understood. We examined microbial communities from seawater, sediments and the estuarine fish Pelates sexlineatus, in Australia\u27s largest urbanised estuary, and hypothesised that anthropogenic contamination would be reflected in the microbiology of these sample types. The human faecal markers Lachno3 and HF183 were not detected, indicating negligible influence of sewage, but a gradient in copy numbers of the class 1 integron (intI-1), which is often used as a marker for anthropogenic contamination, was observed in sediments and positively correlated with metal concentrations. While seawater communities were not strongly driven by metal contamination, shifts in the diversity and composition of the fish gut microbiome were observed, with statistical links to levels of metal contamination (F2, 21 = 1.536, p \u3c 0.01). Within the fish gut microbiome, we further report increased relative abundance of amplicon sequence variants (ASVs; single inferred DNA sequences obtained in sequencing) identified as metal resistant and potentially pathogenic genera, as well as those that may have roles in inflammation. These results demonstrate that microbial communities from distinct habitats within estuarine systems have unique response to stressors, and alterations of the fish gut microbiome may have implications for the adaptation of estuarine fish to legacy metal contamination