scholarly journals Roadkill-Data-Based Identification and Ranking of Mammal Habitats

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 477
Author(s):  
Andrius Kučas ◽  
Linas Balčiauskas
Keyword(s):  
Species Richness ◽  
Land Cover ◽  
Decision Support Techniques ◽  
Mitigation Measures ◽  
Spatial Decision Support ◽  
Vehicle Collisions ◽  
Vehicle Collision ◽  
Ecological Corridor ◽  
As Species ◽  
The Relationship

Wildlife–vehicle collisions, as well as environmental factors that affect collisions and mitigation measures, are usually modelled and analysed in the vicinity of or within roads, while habitat attractiveness to wildlife along with risk to drivers remain mostly underestimated. The main goal of this study was the identification, characterisation, and ranking of mammalian habitats in Lithuania in relation to 2002–2017 roadkill data. We identified habitat patches as areas (varying from 1 to 1488 square kilometres) isolated by neighbouring roads characterised by at least one wildlife–vehicle collision hotspot. We ranked all identified habitats on the basis of land cover, the presence of an ecological corridor, a mammalian pathway, and roadkill hotspot data. A ranking scenario describing both habitat attractiveness to wildlife and the risk to drivers was defined and applied. Ranks for each habitat were calculated using multiple criteria spatial decision support techniques. Multiple regression analyses were used to identify the relationship between habitat ranks, species richness, and land cover classes. Strong relationships were identified and are discussed between the habitat patch ranks in five (out of 28) land cover classes and in eight (out of 28) species (97% of all mammal road kills). We conclude that, along with conventional roadkill hotspot identification, roadkill-based habitat identification and characterisation as well as species richness analysis should be used in road safety infrastructure planning.

scholarly journals Impact of Road Fencing on Ungulate–Vehicle Collisions and Hotspot Patterns

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 338
Author(s):  
Andrius Kučas ◽  
Linas Balčiauskas
Keyword(s):  
Traffic Accidents ◽  
Road Traffic ◽  
Mitigation Measures ◽  
Traffic Intensity ◽  
Road Traffic Accidents ◽  
Annual Average ◽  
Vehicle Collisions ◽  
Vehicle Collision ◽  
Annual Average Daily Traffic ◽  
The Relationship

The number of road traffic accidents decreased in Lithuania from 2002 to 2017, while the ungulate–vehicle collision (UVC) number increased and accounted for approximately 69% of all wildlife–vehicle collisions (WVC) in the country. Understanding the relationship between UVCs, traffic intensity, and implemented mitigation measures is important for the assessment of UVC mitigation measure efficiency. We assessed the effect of annual average daily traffic (AADT) and wildlife fencing on UVCs using regression analysis of changes in annual UVCs and UVC hotspots on different categories of roads. At the highest rates, annual UVC numbers and UVC hotspots increased on lower category (national and regional) roads, forming a denser network. Lower rates of UVC increase occurred on higher category (main) roads, forming sparser road networks and characterized by the highest AADT. Before 2011, both UVC occurrence and fenced road sections were most common on higher-category roads. However, as of 2011, the majority of UVCs occurred on lower-category roads where AADT and fencing had no impact on UVCs. We conclude that wildlife fencing on roads characterized by higher speed and traffic intensity may decrease UVC numbers and at the same time shifting UVC occurrence towards roads characterized by lower speed and traffic intensity. Wildlife fencing re-allocates wildlife movement pathways toward roads with insufficient or no mitigation measures.

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

2018 ◽  
Author(s):  
Samual T Williams ◽  
Wendy Collinson ◽  
Claire Patterson-Abrolat ◽  
David G Marneweck ◽  
Lourens H Swanepoel
Keyword(s):  
South Africa ◽  
Data Collection ◽  
Road Network ◽  
Mitigation Measures ◽  
Model Species ◽  
Vehicle Collisions ◽  
Factors Associated ◽  
Wildlife Populations ◽  
Pass Through ◽  
The Relationship

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 the number of owls killed on the roads, 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.

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

2018 ◽  
Author(s):  
Samual T Williams ◽  
Wendy Collinson ◽  
Claire Patterson-Abrolat ◽  
David G Marneweck ◽  
Lourens H Swanepoel
Keyword(s):  
South Africa ◽  
Data Collection ◽  
Road Network ◽  
Mitigation Measures ◽  
Model Species ◽  
Vehicle Collisions ◽  
Factors Associated ◽  
Wildlife Populations ◽  
Pass Through ◽  
The Relationship

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 the number of owls killed on the roads, 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.

scholarly journals Landscape‐specific thresholds in the relationship between species richness and natural land cover

2019 ◽  
Vol 56 (4) ◽  
pp. 1019-1029 ◽  
Author(s):  
Jeremy S. Simmonds ◽  
Berndt J. Rensburg ◽  
Ayesha I. T. Tulloch ◽  
Martine Maron
Keyword(s):  
Species Richness ◽  
Land Cover ◽  
Natural Land ◽  
The Relationship

scholarly journals Elevated wildlife-vehicle collision rates during the COVID-19 pandemic

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Joel O. Abraham ◽  
Matthew A. Mumma
Keyword(s):  
United States ◽  
The United States ◽  
Traffic Volume ◽  
Vehicle Collisions ◽  
Vehicle Collision ◽  
The Relationship

AbstractWildlife-vehicle collisions threaten both humans and wildlife, but we still lack information about the relationship between traffic volume and wildlife-vehicle collisions. The COVID-19 pandemic allowed us to investigate the effects of traffic volume on wildlife-vehicle collisions in the United States. We observed decreased traffic nationwide, particularly in densely populated states with low or high disease burdens. Despite reduced traffic, total collisions were unchanged; wildlife-vehicle collisions did decline at the start of the pandemic, but increased as the pandemic progressed, ultimately exceeding collisions in the previous year. As a result, nationwide collision rates were higher during the pandemic. We suggest that increased wildlife road use offsets the effects of decreased traffic volume on wildlife-vehicle collisions. Thus, decreased traffic volume will not always reduce wildlife-vehicle collisions.

scholarly journals Probing the troublesome peaked relationship between avian species richness and natural land cover

2021 ◽  
Author(s):  
Rafael Xavier De Camargo ◽  
David Currie
Keyword(s):  
Species Richness ◽  
Land Cover ◽  
Landscape Heterogeneity ◽  
New York State ◽  
Pool Size ◽  
Avian Species ◽  
Temperature Gradients ◽  
Species Pool ◽  
Natural Land ◽  
The Relationship

Abstract Context : Biodiversity models postulate that the relationship between richness and the proportion of natural land cover (pNLC i.e., not dominated by human uses) is: 1) monotonic positive, 2) reasonably strong , 3) consistent in different geographic areas . Earlier work examining 100-km 2 human-dominated landcover in Ontario, Canada, observed that surveyed avian species richness is a peaked function of pNLC. Objective : We tested whether the same relationship between avian species richness and pNLC is also observed in an independent geographic area that has similar biomes. We also tested whether the peaked relations might be caused by temperature gradients, gradients in the size of species pools, grain size in the analyses, and landscape heterogeneity. Methods : Using breeding bird atlases of Ontario (Canada) and New York State (USA), we estimated species richness in landscapes varying from 25 to 900 km 2 . We related richness to the pNLC in each landscape and examined the same relationships after controlling for temperature, habitat heterogeneity, and species pool size. Results : Landscape-level species richness is a peaked, and not very strong function of pNLC. The relationship is not an artefact of temperature gradients, species pool size, or land cover heterogeneity. Conclusions : The proposition that increased amounts of natural land cover promotes species richness is clearly true at the limit, in landscapes with relatively little (<30%) natural cover. In landscapes with higher amounts of natural cover, a certain amount of human-modified land covers can provide habitat for species that prefer open habitats.

scholarly journals Habitat Suitability Based Models for Ungulate Roadkill Prognosis

Animals ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1345
Author(s):  
Linas Balčiauskas ◽  
Jack Wierzchowski ◽  
Andrius Kučas ◽  
Laima Balčiauskienė
Keyword(s):  
Wild Boar ◽  
Habitat Suitability ◽  
Detrimental Effect ◽  
Roe Deer ◽  
Mitigation Measures ◽  
Vehicle Collisions ◽  
Additional Tool ◽  
Vehicle Collision ◽  
Collision Mitigation ◽  
Linkage Models

Roads do not only have a detrimental effect on nature (fragmenting habitats, isolating populations and threatening biodiversity), but the increasing numbers of wildlife-vehicle collisions are also a direct threat to humans and property. Therefore, mitigation measures should be placed with respect to animal distribution and movements across the roads. We simulated red deer, roe deer and wild boar movements in Lithuania, focusing on the two main highways A1 and A2. Using regional habitat suitability and linkage models, we calculated movement pathways and the most probable crossing zones in 2009. The prognostic value of these models was tested by comparing the pathway predictions to the real roadkill and roadkill cluster locations in 2002–2009 and 2010–2017. Across both periods and on both highways, the roe deer roadkill locations were significantly closer to the model-predicted pathways than to randomly selected points. The prediction of roadkill locations was also good for wild boar. The roe deer roadkill clusters and multi-species clusters were significantly better represented by the model than by random distribution. On both highways, the biggest differences in distance from the predicted locations were near big cities. We recommended wildlife movement models as an additional tool for planning wildlife-vehicle collision mitigation measures and we advise measures for increasing their predicting power.

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

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6650 ◽  
Author(s):  
Samual T. Williams ◽  
Wendy Collinson ◽  
Claire Patterson-Abrolat ◽  
David G. Marneweck ◽  
Lourens H. Swanepoel
Keyword(s):  
South Africa ◽  
Data Collection ◽  
Road Network ◽  
Mitigation Measures ◽  
Model Species ◽  
Vehicle Collisions ◽  
Factors Associated ◽  
Wildlife Populations ◽  
Pass Through ◽  
The Relationship

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.

scholarly journals Land cover drives large scale productivity-diversity relationships in Irish vascular plants

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7035 ◽  
Author(s):  
Hannah J. White ◽  
Willson Gaul ◽  
Dinara Sadykova ◽  
Lupe León-Sánchez ◽  
Paul Caplat ◽  
...  
Keyword(s):  
Species Richness ◽  
Land Cover ◽  
Large Scale ◽  
Vegetation Index ◽  
Scale Effects ◽  
Spatial Scales ◽  
Vascular Plant ◽  
Regional Scale ◽  
The Impact ◽  
The Relationship

The impact of productivity on species diversity is often studied at small spatial scales and without taking additional environmental factors into account. Focusing on small spatial scales removes important regional scale effects, such as the role of land cover heterogeneity. Here, we use a regional spatial scale (10 km square) to establish the relationship between productivity and vascular plant species richness across the island of Ireland that takes into account variation in land cover. We used generalized additive mixed effects models to relate species richness, estimated from biological records, to plant productivity. Productivity was quantified by the satellite-derived enhanced vegetation index. The productivity-diversity relationship was fitted for three land cover types: pasture-dominated, heterogeneous, and non-pasture-dominated landscapes. We find that species richness decreases with increasing productivity, especially at higher productivity levels. This decreasing relationship appears to be driven by pasture-dominated areas. The relationship between species richness and heterogeneity in productivity (both spatial and temporal) varies with land cover. Our results suggest that the impact of pasture on species richness extends beyond field level. The effect of human modified landscapes, therefore, is important to consider when investigating classical ecological relationships, particularly at the wider landscape scale.

scholarly journals Land use/land cover change detection through temporal imageries and its implications in water induced disaster in Triyuga watershed, east Nepal

2016 ◽  
Vol 51 ◽  
pp. 49-54
Author(s):  
Rabindra Choudhary ◽  
Dinesh Pathak
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Use Planning ◽  
Risk Mitigation ◽  
Land Use Changes ◽  
Meteorological Factor ◽  
Mitigation Measures ◽  
Disaster Loss ◽  
Structural Risk ◽  
The Relationship

Land use and land cover is an important component in understanding the interactions of the human activities with the environment. Land use planning are widely recognized as key non-structural risk mitigation measures. In the present study, decadal land use changes in the Triyuga watershed has been assessed for the period between 1980 and 2015. Satellite images of Landsat (ETM, TM and OLI) have been used to prepare land use maps for respective period. The relationship between disaster loss, land use and meteorological factor (rainfall) has been evaluated. Significant correlation between the parameters has been obtained.

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