Effect of traffic volume on American black bears in central Florida, USA

McCown, J. Walter; Kubilis, Paul; Eason, Thomas; Scheick, Brian K.

doi:10.2192/08gr004r2.1

Cited by 31 publications

(21 citation statements)

References 10 publications

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“…Both grizzly and black bears (U. americanus) modify their crossing attempts to times of lower traffic volume (Waller and Servheen , McCown et al. ). Similarly, moose ( Alces alces) were found to cross roads at night when traffic volume was 33% lower than during daylight hours (Laurian et al.…”

Section: Four Risk‐avoidance Behavioral Responses To Traffic Volumementioning

confidence: 99%

A behavior‐based framework for assessing barrier effects to wildlife from vehicle traffic volume

et al. 2016

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Roads, while central to the function of human society, create barriers to animal movement through collisions and habitat fragmentation. Barriers to animal movement affect the evolution and trajectory of populations. Investigators have attempted to use traffic volume, the number of vehicles passing a point on a road segment, to predict effects to wildlife populations approximately linearly and along taxonomic lines; however, taxonomic groupings cannot provide sound predictions because closely related species often respond differently. We assess the role of wildlife behavioral responses to traffic volume as a tool to predict barrier effects from vehicle‐caused mortality and avoidance, to provide an early warning system that recognizes traffic volume as a trigger for mitigation, and to better interpret roadkill data. We propose four categories of behavioral response based on the perceived danger to traffic: Nonresponders, Pausers, Speeders, and Avoiders. Nonresponders attempt to cross highways regardless of traffic volume. Pausers stop in the face of danger so have a low probability of successful crossing when traffic volume increases. Hence, highway barrier effects are primarily due to mortality for Nonresponders and Pausers at high traffic volumes. Speeders run away from danger but are unable to do so successfully as traffic volume increases. At moderate to high volume, Speeders are repelled by traffic danger. Avoiders face lower mortality than other categories because they begin to avoid traffic at relatively low traffic volumes. Hence, avoidance causes barrier effects more than mortality for Speeders and Avoiders even at relatively moderate traffic volumes. By considering a species’ risk‐avoidance response to traffic, managers can make more appropriate and timely decisions to mitigate effects before populations decline or become locally extinct.

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Section: Four Risk‐avoidance Behavioral Responses To Traffic Volumementioning

confidence: 99%

A behavior‐based framework for assessing barrier effects to wildlife from vehicle traffic volume

et al. 2016

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“…In addition to characteristics of the snake, factors external to the snake can play a role in influencing a snake's decision to cross a road: Blouin-Demers 2013, Hyslop et al 2014). Road noise and traffic levels also have a strong deterrent effect on cross-road movements of snakes and other wildlife (Alexander et al 2005, Andrews and Gibbons 2005, McCown et al 2009, Shannon et al 2014 and increase the risk of on-road mortality (Sutherland et al 2010). We predicted that all measures of road magnitude (e.g., gap width, surface type, traffic volume) would have negative effects on the crossing rates of Brown Treesnakes.…”

Section: Extrinsic Factorsmentioning

confidence: 99%

“…, Andrews and Gibbons , McCown et al. , Shannon et al. ) and increase the risk of on‐road mortality (Sutherland et al.…”

Section: Introductionmentioning

confidence: 99%

To cross or not to cross: modeling wildlife road crossings as a binary response variable with contextual predictors

2016

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Citation: Siers, S. R., R. N. Reed, and J. A. Savidge. 2016. To cross or not to cross: modeling wildlife road crossings as a binary response variable with contextual predictors. Ecosphere 7(5):e01292. 10. 1002/ecs2.1292 Abstract. Roads are significant barriers to landscape-scale movements of individuals or populations of many wildlife taxa. The decision by an animal near a road to either cross or not cross may be influenced by characteristics of the road, environmental conditions, traits of the individual animal, and other aspects of the context within which the decision is made. We considered such factors in a mixed-effects logistic regression model describing the nightly road crossing probabilities of invasive nocturnal Brown Treesnakes (Boiga irregularis) through short-term radiotracking of 691 snakes within close proximity to 50 road segments across the island of Guam. All measures of road magnitude (traffic volume, gap width, surface type, etc.) were significantly negatively correlated with crossing probabilities. Snake body size was the only intrinsic factor associated with crossing rates, with larger snakes crossing roads more frequently. Humidity was the only environmental variable affecting crossing rate. The distance of the snake from the road at the start of nightly movement trials was the most significant predictor of crossings. The presence of snake traps with live mouse lures during a portion of the trials indicated that localized prey cues reduced the probability of a snake crossing the road away from the traps, suggesting that a snake's decision to cross roads is influenced by local foraging opportunities. Per capita road crossing rates of Brown Treesnakes were very low, and comparisons to historical records suggest that crossing rates have declined in the 60+ yr since introduction to Guam. We report a simplified model that will allow managers to predict road crossing rates based on snake, road, and contextual characteristics. Road crossing simulations based on actual snake size distributions demonstrate that populations with size distributions skewed toward larger snakes will result in a higher number of road crossings. Our method of modeling per capita road crossing probabilities as a binary response variable, influenced by contextual factors, may be useful for describing or predicting road crossings by individuals of other taxa provided that appropriate spatial and temporal resolution can be achieved and that potentially influential covariate data can be obtained.

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“…changes in the rate of displacement), reduced reproductive success and declining populations of these organisms. However, the given sampling design does not allow for the evaluation of the mechanism responsible for this effect (Mclellan & Shackleton 1988, Beringer et al 1990, Reijnen et al 1995, Yost & Wright 2001, Forman et al 2002, Gibeau et al 2002, Chruszcz et al 2003, Bautista et al 2004, Pellet et al 2004, Waller & Servheen 2005, Gagnon et al 2007, McCown et al 2009, Graham et al 2010.…”

Section: Traffic Volumementioning

confidence: 99%

Review of the Factors Underlying the Mechanisms and Effects of Roads on Vertebrates

Rosa¹,

Bager²

2013

Oecol. Austr.

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Road ecology is an emerging discipline that attempts to understand the patterns and processes related with road-ecosystem interactions to establish effective mitigation measures of the negative effects of roads on wildlife. Although many advances have been made over the past 10 years, many questions are still unanswered or the information is incomplete. We discussed the factors (characteristics of roads) involved in mechanisms and effects of roads on vertebrates and the knowledge gaps. The factors evaluated were road density, road maintenance involving chemicals, presence of vehicles and traffic volume. We identified five mechanisms resulting from these factors: car avoidance, noise avoidance, road surface avoidance, road attraction and wildlife-vehicle-collisions (WVC). Density of roads causes road surface avoidance, road attraction and WVC; maintenance of roads with chemicals causes noise avoidance, road attraction and WVC; vehicle presence causes noise avoidance, car avoidance and WVC; and traffic volume causes noise avoidance and WVC. WVC was the only mechanism linked to all road factors and it occurs in combination with another mechanism (road attraction); therefore, we believe this to be the mechanism that affects most organisms. We identified many knowledge gaps related primarily to identifying the mechanisms triggered by various factors, especially for tropical organisms. We believe that studies involving tropical species could provide new results due to their greater ecological demands compared with temperate species.Palavras-chave: Atropelamentos; evitação de estradas; evitação de ruídos; evitação de carros; atração por rodovias. RESUMEN REVISIÓN DE LOS FACTORES QUE SUBYACEN LOS MECANISMOS Y EFECTOS DE CARRETERAS SOBRE LOS VERTEBRADOS.La ecología de carreteras es una disciplina emergente que pretende entender los patrones y procesos relacionados con las interacciones entre carreteras y ecosistemas, para establecer medidas efectivas de mitigación de los efectos negativos de las carreteras sobre la vida silvestre. Aunque se ha avanzado bastante en los últimos 10 años, varias preguntas siguen sin responder o la información está incompleta. Nuestro objetivo fue discutir los factores (características de las carreteras) involucrados en los mecanismos y efectos de las carreteras sobre los vertebrados y las lagunas en el conocimiento. Los factores evaluados fueron la densidad de la malla vial, el mantenimiento con sustancias químicas, la presencia de vehículos y el volumen del tráfico. Identificamos cinco mecanismos que derivan de estos factores: evitación de los carros, evitación del ruido, evitación de la superficie de la carretera, atracción por la carretera y colisiones entre vehículos y animales silvestres (WVC). La densidad de las vías causa la evitación de la superficie de la carretera, la atracción por la carretera y colisiones con vehículos; el mantenimiento de carreteras con productos químicos causa la evitación del ruido, la atracción por la carretera y colisiones con vehículos; la presencia de vehí...

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Effect of traffic volume on American black bears in central Florida, USA

Cited by 31 publications

References 10 publications

A behavior‐based framework for assessing barrier effects to wildlife from vehicle traffic volume

A behavior‐based framework for assessing barrier effects to wildlife from vehicle traffic volume

To cross or not to cross: modeling wildlife road crossings as a binary response variable with contextual predictors

Review of the Factors Underlying the Mechanisms and Effects of Roads on Vertebrates

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