Testing a Road Mortality Risk Model to Prioritize and Design Turtle Eco-passages at Wetland-road Crossings in New Hampshire, USA

Road-associated mortality can lead to local declines of wildlife populations, and management agencies are actively implementing mitigation measures, especially focused on potential road mortality hotspots. In this study we used a spatially-explicit simulation modeling approach to estimate the hotspots of road mortality for the Eastern Hermann’s tortoise ( Testudo hermanni boettgeri ) within its distribution range in Romania. Using a field experiment, we first evaluated velocities while crossing roads. Adult male tortoises moved faster than females (3.98 m/min vs. 2.51 m/min) which led to higher individual probabilities for females being killed on high-traffic roads (0.61 for females vs. 0.44 for males at traffic levels of 7000 vehicles/day). Both males and females had similar road mortality probabilities for traffic levels <1000 and >35 000 vehicles/day. Our spatially explicit model suggests that, within the entire Romanian distributional range, the tortoises have an overall risk of road mortality 1.6%, which may have a negative impact on tortoise populations. Using the Getis-Ord Gi statistic, we identified road mortality hotspots with mortality rates of 5-30%, in areas bisected by high-traffic national and European-level roads. Our research is timely in that many low-traffic roads are predicted to have increased traffic associated with tourism activities, thus increasing the overall risk of mortality. We suggest that mitigation measures such as signage and roadside fences associated with underpasses have the potential to limit road mortality of this threatened species within predicted current mortality hotspots.

Cumulative Sum Curves and Their Prediction Limits

For depleted wildlife populations, understanding and effectively mitigating the direct and indirect impacts of roads can be a key component of recovery efforts. The ocelot is a federally endangered wild felid at risk of local extinction in south Texas, where vehicle collisions are their largest known source of mortality. To support road mortality mitigation, we evaluated mortality risk across the south Texas road network. We also assessed whether a sympatric carnivore, the bobcat, could serve as a surrogate to inform mortality risk. We used several presence-only species distribution models to evaluate a suite of candidate landscape and road attributes and identify those associated with elevated road mortality risk using a 35-year wild felid road mortality dataset. Consensus predictions among models identified high-risk road segments for ocelots and bobcats. We compared predictions between species to determine overlap of high-risk areas. Areas where core ocelot habitat intersected roadways represented the greatest mortality risk, reflecting ocelot reliance on intact habitat and avoidance of degraded and fragmented landscapes. Bobcat road mortality risk had similar relationships to landscape features, with nearly all areas classified as high-risk for ocelots also identified as high-risk for bobcats. Ocelots are vulnerable to road mortality in areas where roads intersect their intact scrub habitat. Bobcats, with appropriate data filters in place, are an acceptable surrogate for informing ocelot road mortality, particularly when ocelot mortality data are limited and for time-sensitive conservation decision-making. For ocelots and other fragmentation-intolerant carnivore species, wildlife underpasses and fencing in focused areas where roads and intact habitat intersect may be feasible options to reduce road mortality.

The Bayesian intrinsic conditional autoregressive convolution model was used to study the spatial variations in road mortality in the regions of Belgium, France and Germany. In all three countries, the spatial structure behind relative risk is significant and spatial heterogeneity predominates over unstructured heterogeneity. The maps of spatially-structured component of random effect enable the spatial structures of risk to be identified and highlight the zones and areas where the mortality risk exhibits spatial dependency. Hence, a west–east gradient in risk level is found in Germany and a north–south gradient in Belgium. In areas with high road network density (and relatively high population density), there is generally less heterogeneity in road mortality across neighbouring regions, while in areas with high regional disparities, there are significant spatial variations in mortality risk. Furthermore, a model was produced for 272 regions in 13 European continental countries, making it possible to investigate whether national borders have any specific effect on the distribution of road mortality risk compared to what happens within countries’ administrative borders. Cross-border regions were found not to be particularly likely to have similar road mortality risk levels where they shared a common national border. National borders have no specific effect on the distribution of road mortality across Europe.

Risk models for mortality after percutaneous coronary intervention (PCI) are underutilized in clinical practice though they may be useful during informed consent, risk mitigation planning, and risk adjustment of hospital and operator outcomes. This review analyzed contemporary risk models for in-hospital and 30-day mortality after PCI. We reviewed eight contemporary risk models. Age, sex, hemodynamic status, acute coronary syndrome type, heart failure, and kidney disease were consistently found to be independent risk factors for mortality. These models provided good discrimination (C-statistic 0.85-0.95) for both pre-catheterization and comprehensive risk models that included anatomic variables. There are several excellent models for PCI mortality risk prediction. Choice of the model will depend on the use case and population, though the CathPCI model should be the default for in-hospital mortality risk prediction in the United States. Future interventions should focus on the integration of risk prediction into clinical care.

Regional analysis of road mortality in Europe

BackgroundUnderstanding the ecological consequences of roads and developing ways to mitigate their negative effects has become an important goal for many conservation biologists. Most mitigation measures are based on road mortality and barrier effects data. However, studying fine-scale individual spatial responses in roaded landscapes may help develop more cohesive road planning strategies for wildlife conservation.Methodology/Principal FindingsWe investigated how individuals respond in their spatial behavior toward a highway and its traffic intensity by radio-tracking two common species particularly vulnerable to road mortality (barn owl Tyto alba and stone marten Martes foina). We addressed the following questions: 1) how highways affected home-range location and size in the immediate vicinity of these structures, 2) which road-related features influenced habitat selection, 3) what was the role of different road-related features on movement properties, and 4) which characteristics were associated with crossing events and road-kills. The main findings were: 1) if there was available habitat, barn owls and stone martens may not avoid highways and may even include highways within their home-ranges; 2) both species avoided using areas near the highway when traffic was high, but tended to move toward the highway when streams were in close proximity and where verges offered suitable habitat; and 3) barn owls tended to cross above-grade highway sections while stone martens tended to avoid crossing at leveled highway sections.ConclusionsMortality may be the main road-mediated mechanism that affects barn owl and stone marten populations. Fine-scale movements strongly indicated that a decrease in road mortality risk can be realized by reducing sources of attraction, and by increasing road permeability through measures that promote safe crossings.

Objective: To develop a prognostic model for the thirty-day mortality risk after adult heart transplantation. Methods: In this report we developed a prediction model for the 30-day mortality risk after adult heart transplantation. Logistic regression analysis was used to develop the model in 1,262 adult patients undergoing primary heart transplantation. We evaluated the accuracy of the prediction model; the agreement between the predicted probability and the observed mortality (calibration); and the ability of the model to correctly discriminate between the discordant survival pairs (discrimination). The internal validity of the prediction model was evaluated using the bootstrapping procedures. Results: Recipients’ age and sex, pre-transplant diagnosis, transplant status, waiting time, cardiopulmonary bypass time, donors’ age and sex, donor-recipient mismatch for BMI and blood type were independent predictors for 30-day mortality risk after adult heart transplantation. The model showed a good calibration and reasonable discrimination (the corrected area under the receiver operating characteristic curve was 0.71). The internal validity of the prediction model was acceptable. For practical use, we converted the prediction model to score chart. Conclusion: The accuracy and the validity of the prediction model were acceptable. This easy-to-use instrument for predicting the 30-day mortality risk after adult heart transplantation would benefit decision-making by classifying recipients according to their mortality risk and allowing optimal allocation of a donor to a recipient for heart transplantation.

Roads fragment our landscape, posing a severe threat to the persistence of wildlife populations through losses of individuals to direct mortality and decreased connectivity. Although they possess a particular suite of life history characteristics that make them especially vulnerable, snakes tend to be underrepresented in research examining vertebrate road mortality. Here, we report a statistical analysis of snake mortality along a 183‐km road circuit in sagebrush‐steppe habitat located in southeastern Idaho. We describe differential road mortality across snake species, season, sex and age. We also analyze both fine‐scale and broad‐scale habitat measurements to identify various habitat and landscape factors associated with snake road mortality. Our results show clearly that snake road mortality is influenced by interactions among demographic, ecological and temporal factors. Vagile species and life stages were particularly vulnerable to road mortality during periods of peak activity. Gophersnakes dominated our road observations, with adult male mortality peaking in spring and high casualties of neonates in the fall. Snake crossings were especially common along roadsides with high vegetative cover, in areas dominated by non‐native grasses. These results suggest the potential for snake populations to become fragmented over time, and that habitat conversion and species invasions may be compounding this effect. This study suggests that conservation efforts need to account for inter‐ and intraspecific differences in road mortality risk and provides guidance for roadside management that may serve to minimize vertebrate mortality on roads.

Road networks pose many well‐documented threats to wildlife, from fragmenting habitats and restricting movement to causing mortality through vehicle collisions. For large, wide‐ranging mammals, home range requirements and seasonal migrations often necessitate road crossings, posing threats to human safety, property, and animal survival. Artificial nightlight, emanating from light posts and urban sky glow, is ubiquitous on and around road networks worldwide; however, its effects on road crossing behavior and the associated mortality risk for wildlife are not well understood. By integrating the latest NASA nightlight products with GPS collar data collected from 67 mule deer (Odocoileus hemionus) over a 7‐year period (2012–2018), we used a resource‐selection framework to assess factors influencing seasonal crossing behavior and road mortality in Salt Lake City, Utah, an expanding metropolitan area in the United States. We found deer preferred to cross the road where surrounding artificial nightlight was lower in both summer and winter seasons, especially during crepuscular and nighttime periods. However, lower nightlight levels also increased the risk of road mortality. Areas with more shrub cover and lower speed limits increased the likelihood of crossing as well as lowered the risk of road mortality. There were five times as many mortality events in winter as in summer, likely because of the combination of deer preference for dark roads mixed with proximity to both higher speed roads and increased human activity. Better understanding how a pervasive and expanding environmental pollutant like artificial nightlight may attract or repel human‐tolerant wildlife species from roadways presents an opportunity to mitigate collision risk while improving population management strategies for this abundant, generalist herbivore and many other economically and ecologically important species.

The existing predictive risk models for the surgical outcome of acute diffused peritonitis (ADP) need renovation by adding relevant variables such as ADP's definition or causative etiology to pursue outstanding data collection reflecting the real world. We aimed to revise the risk models predicting mortality and morbidities of ADP using the latest Japanese Nationwide Clinical Database (NCD) variable set. Clinical dataset of ADP patients who underwent surgery, and registered in the NCD between 2016 and 2019, were used to develop a risk model for surgical outcomes. The primary outcome was perioperative mortality. After data cleanup, 45 379 surgical cases for ADP were derived for analysis. The perioperative and 30-day mortality were 10.6% and 7.2%, respectively. The prediction models have been created for the mortality and 10 morbidities associated with the mortality. The top five relevant predictors for perioperative mortality were age >80, advanced cancer with multiple metastases, platelet count of <50 000/mL, serum albumin of <2.0 g/dL, and unknown ADP site. The C-indices of perioperative and 30-day mortality were 0.859 and 0.857, respectively. The predicted value calculated with the risk models for mortality was highly fitted with the actual probability from the lower to the higher risk groups. Risk models for postoperative mortality and morbidities with good predictive performance and reliability were revised and validated using the recent real-world clinical dataset. These models help to predict ADP surgical outcomes accurately and are available for clinical settings.

Risk of Surgical Mitral Valve Repair for Primary Mitral Regurgitation

Risk of Surgical Mitral Valve Repair for Primary Mitral Regurgitation

While awareness of the public health burden of road insecurity is recent, the idea that it is developing countries, particularly in Africa, that experience high road deaths is older. Tunisia is an example of this. In this context, our article proposes recommendations through the study of the road mortality rate in Tunisia based on population density and belonging to a geographical unit. To do so, we used the Bayesian ecological regression model whose parameters are adjusted by Gibbs sampling. The analysis shows that the variation in road mortality risk is highest at the delegation level but lowest at the district and governorate levels. An estimated elasticity of −0.25 at the district level means that a 10% increase in population density can lead to a 2.5% decrease in road deaths. Bayes Relative Risk Mapping could help identify areas with high road mortality and strengthen road safety decision making.

Dolichophis caspius is frequently affected by road mortality, with many victims recorded also in Romania. Although some regions in the country have a presumptive high risk of road mortality, there is no certain data from all regions. In 2021 and 2024, we analyzed this species’ road mortality at its northern distribution range limit (lower Olt River valley, southern Romania). We identified 66 road-killed D. caspius over the course of eight days. Most victims (62.12%) were juveniles. The high number of road-killed juveniles is a consequence of the road`s features, which crosses many small human settlements (villages) and has numerous curves and speed enforcement cameras; therefore, the speed is reduced to 50 km/h. Consequently, the small-sized road-killed juveniles were easier to observe, as compared to roads of higher speeds, where they can be easily missed. The high number of juveniles indicates that in the region there are large populations that reproduce, as they are probably favored by climate warming. Although the absolute number of road-killed juveniles was higher at the end of summer and autumn, the ratio of juveniles and adults was the same in spring. The differences in road mortality on different days, even of the same month, indicate the importance of local microclimate conditions for the activity and road mortality of D. caspius. The lower Olt River valley region has a high risk of road mortality for this species, as it shows the scale of this phenomenon by highlighting the impact on juveniles.