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Successful movement of wildlife across highways to effectively provide population-level wildlife linkage is usually viewed in one dimension - movement either exists or it does not. We believe that there are multiple ways to measure both the existence and value of such movement opportunities to better demonstrate success or failure of these efforts. The use of multiple methods to measure success will provide quantitative and qualitative values that can be used to better judge the effectiveness of wildlife movement across highways and to justify investment in the in¬frastructure to create such movement. Currently, many transportation agency administrators view investments in wild¬life crossing infrastructure as outside their responsibility and as fiscal competition for highway projects of greater value to the traveling public. We believe this is a false paradigm that can be changed by enhanced measures of the values of wildlife highways crossing enhancement. Measures of success should include a wide range of factors that transcend wildlife issues. These factors should include biological impacts; economic impacts on highways, public lands, and private lands; public safety measures; social influences and acceptance; and political factors. Biological measures of success should include wildlife movement, gene flow measures, seasonal range access and dispersal opportunity, potential for re-occupancy of historic habitat, reduction in population isolation, effects on endangered species listing and management, and mortality reduction. Economic successes should include improved project planning efficiency, reductions in project time delays, reduced environmental review and court challenge costs, and improved land values adjacent to linkage areas due to healthy wildlife populations. Public safety measures should include road kill reduc¬tion, reduced probability of accidents and human injury, and improved speed limits. Social measures should include attitude surveys measuring public willingness to invest public funds to reduce wildlife collisions, public acceptance of the concept of linkage zones, and public awareness of the multiple benefits of wildlife population connectivity. Political measures should include measuring the knowledge and understanding of this issue by political interests, their willing¬ness to appropriate funding for such projects, and legislation. We review the application of each of these measures of success to wildlife crossing enhancement and suggest a basic measurement approach to all wildlife crossing efforts. In the long term, successful wildlife linkage efforts associated with highways will require improved public understand¬ing and support, improved agency willingness to accept wildlife crossings as part of their responsibility, and improved understanding of the multiple values and benefits that come from enhancing wildlife movement across highways.

Wildlife road killing is a problem for animal conservation in the world. In order to mitigate this problem, it is necessary to understand the factors that affect it, like seasonality and climatic variables. The objective of the study was to evaluate the influence of climatic variables (mean temperature, relative air humidity and accumulated precipitation), seasonality and average daily traffic (ADT) on vertebrate roadkill rates in an area of Cerrado biome, Brazil. The study area is a stretch of 96 km of the highway BR-050, a four-lane road, between the cities of Uberlândia and Uberaba, state of Minas Gerais, Brazil. This area is characterized by intense fragmentation of natural areas, with few remnants of Cerrado biome. The climate has two very defined seasons, a warm and rainy summer and a very dry winter. We analyzed data from roadkill monitoring carried out from April 2012 to March 2013. The road was monitored weekly by car at an average speed of 60 km/h, by two observers, totaling 8,064 km surveyed. The highest roadkill rates for reptiles were recorded in the rainy season, for the other groups (mammals and birds) no difference was found. We also checked seasonality for the most abundant species: the highest number of roadkills was found in the rainy season for the common boa (Boa constrictor amarali) and for the six-banded armadillo (Euphractus sexcinctus). For the crab-eating fox (Cerdocyon thous), crab-eating raccoon (Procyon cancrivorus), striped hog-nosed skunk (Conepatus semistriatus) and red-legged seriema (Cariama cristata) we found no difference. The humidity and accumulated precipitation positively influenced the reptile roadkill rate. As expected, the same result was found for Boa constrictor amarali. Mammal roadkill rate increases with accumulated precipitation, on the other hand, Euphractus sexcinctus roadkill rate increases with temperature. Birds are not affected by climate variables, nevertheless, Cariama cristata roadkill rate decreases as humidity increases. Contrary to expectations, ADT had no influence on roadkill rates. These results show that it is necessary to investigate the influence of possible descriptor variables on mammals, birds and reptiles separately and not for all vertebrates as a group. Furthermore, certain species may even present different temporal patterns.

Wildlife collision data are ubiquitous, though challenging for making ecological inference due to typically irreducible uncertainty relating to the sampling process. We illustrate a new approach that is useful for generating inference from predator data arising from wildlife collisions. By simply conditioning on a second prey species sampled via the same collision process, and by using a biologically realistic numerical response functions, we can produce a coherent numerical response relationship between predator and prey. This relationship can then be used to make inference on the population size of the predator species, including the probability of extinction. The statistical conditioning enables us to account for unmeasured variation in factors influencing the runway strike incidence for individual airports and to enable valid comparisons. A practical application of the approach for testing hypotheses about the distribution and abundance of a predator species is illustrated using the hypothesized red fox incursion into Tasmania, Australia. We estimate that conditional on the numerical response between fox and lagomorph runway strikes on mainland Australia, the predictive probability of observing no runway strikes of foxes in Tasmania after observing 15 lagomorph strikes is 0.001. We conclude there is enough evidence to safely reject the null hypothesis that there is a widespread red fox population in Tasmania at a population density consistent with prey availability. The method is novel and has potential wider application.

Speed regulations of watercraft in protected areas are designed to reduce lethal collisions with wildlife but can have economic consequences. We present a quantitative framework for investigating the risk of deadly collisions between boats and wildlife., We apply encounter rate theory to demonstrate how marine mammal-boat encounter rate can be used to predict the expected number of deaths associated with management scenarios. We illustrate our approach with management scenarios for two endangered species: the Florida manatee Trichechus manatus latirostris and the North Atlantic right whale Eubalaena glacialis. We used a Monte Carlo simulation approach to demonstrate the uncertainty that is associated with our estimate of relative mortality., We show that encounter rate increased with vessel speed but that the expected number of encounters varies depending on the boating activities considered. For instance, in a scenario involving manatees and boating activities such as water skiing, the expected number of encounters in a given area (in a fixed time interval) increased with vessel speed. In another scenario in which a vessel made a transit of fixed length, the expected number of encounters decreases slightly with boat speed. In both cases, the expected number of encounters increased with distanced travelled by the boat. For whales, we found a slight reduction (˜0·1%) in the number of encounters under a scenario where speed is unregulated; this reduction, however, is negligible, and overall expected relative mortality was ˜30% lower under the scenario with speed regulation. The probability of avoidance by the animal or vessel was set to 0 because of lack of data, but we explored the importance of this parameter on the model predictions. In fact, expected relative mortality under speed regulations decreases even further when the probability of avoidance is a decreasing function of vessel speed., By applying encounter rate theory to the case of boat collisions with marine mammals, we gained new insights about encounter processes between wildlife and watercraft. Our work emphasizes the importance of considering uncertainty when estimating wildlife mortality. Finally, our findings are relevant to other systems and ecological processes involving the encounter between moving agents. [ABSTRACT FROM AUTHOR]

Aims: The main aim of this study was to investigate the relationship between the amount of wildlife mortality and traffic rates in Khojir National Park, and with regard to that, finding a suitable location for installing signs according to the standard level sign structure. Materials and Methods: In this study, the current placement of wildlife warning signs was assessed in Khojir National Park, 2010, Tehran, Iran and a method to optimize warning sign placement using kernel density estimations was developed based on existing records for wildlife-vehicle accidents. Kernel density estimation is one of the best methods for finding a suitable location for installing the signs. The most promising of these tools is kernel density estimation, at first with questioner has found nearly point and after that with GPS try to register them in visual page. With kernel density prove to find the best radius, because of installing the sign. Results: Finally in this project, the best radius was found to be 50 m from one accident point, because of supporting the optimum location for installing signs, and finding the four points for installing the signs, and for designing wildlife signs using the symbol of maximum species that was injured in vehicle collision. Conclusion: Finding an area for installing wildlife, the designing of warning signs, and other precautions such as wildlife crossings and overpass creation are useful in decreasing wildlife accidents.

Wildlife collision data are ubiquitous, though challenging for making ecological inference due to typically irreducible uncertainty relating to the sampling process. We illustrate a new approach that is useful for generating inference from predator data arising from wildlife collisions. By simply conditioning on a second prey species sampled via the same collision process, and by using a biologically realistic numerical response functions, we can produce a coherent numerical response relationship between predator and prey. This relationship can then be used to make inference on the population size of the predator species, including the probability of extinction. The statistical conditioning enables us to account for unmeasured variation in factors influencing the runway strike incidence for individual airports and to enable valid comparisons. A practical application of the approach for testing hypotheses about the distribution and abundance of a predator species is illustrated using the hypothesized red fox incursion into Tasmania, Australia. We estimate that conditional on the numerical response between fox and lagomorph runway strikes on mainland Australia, the predictive probability of observing no runway strikes of foxes in Tasmania after observing 15 lagomorph strikes is 0.001. We conclude there is enough evidence to safely reject the null hypothesis that there is a widespread red fox population in Tasmania at a population density consistent with prey availability. The method is novel and has potential wider application., Competing Interests: The authors declare they have no competing interests. All authors are employees of Data61, Commonwealth Scientific and Industrial Research Organisation.