Suchergebnisse

Context. Roadkill is a wildlife management issue in areas where high traffic volume passes through relatively intact natural habitat. High density of roadkill in Tasmania is observed in concentrated 'hotspots', and local mitigation of vehicle speed may thus be an appropriate management response. Although warning signage is often advocated, this may not effectively reduce roadkill if the suggested speed does not provide sufficient time for the animal to be detected and for the vehicle to be stopped.
Aims. The detection distance at night for common roadkill species and corresponding driving speeds to avoid collision were determined. The importance of animal size and fur colour in determining detection distance was also evaluated.
Methods. Mounts of nine nocturnal Tasmanian mammal species were used to determine nighttime driver detection distances based on individual driver trials. These were converted to appropriate stopping speeds by accounting for reaction time and braking distance. Photographs and digital image analysis were used to evaluate fur brightness.
Key results. A total of 339 individual detection distances for the 9 species were recorded for 18 drivers. Detection distance differed between the species tested at both high- and low-beam headlight settings. The endangered Tasmanian devil (Sarcophilus harrisii) had the shortest mean detection distance when headlights were on high beam (60.8 m), and the second shortest on low beam (33.9 m), which corresponded to a driving speed which would permit a safe stop of 54 km h–1 and 38 km h–1, respectively. The greatest detection distance was for the introduced hare (Lepus europaeus): 116 m (83 km h–1) and 50.4 m (48 km h–1), respectively.
Conclusions. Nighttime driving speeds slower than 80 km h–1 may be effective in reducing roadkill in wildlife hotspots. Detection distance was significantly related to fur brightness, as determined by image analysis, and not animal size.
Implications. The variation in detection distance allows species-specific nighttime driving speeds to be considered by individual drivers and by road and wildlife managers planning mitigation efforts for vulnerable species.

An obvious sign of potential human impact on animal populations is roadkill. In Tasmania, this impact is perceived as relatively greater than in other Australian states, and is often noted by visitors and locals alike, such that calls for management action are common in the popular press. The goal of this three-year study was to assess the frequency and distribution of species killed on Tasmanian roads. Seasonal surveys were completed along five major routes, for a total of 154 trips. Over 15 000 km of road were surveyed and 5691 individuals in 54 taxa were recorded for an average roadkill density of 0.372 km−1. Over 50% of encountered roadkill could be identified to species, with common brushtail possums (Trichosurus vulpecula) and Tasmanian pademelon (Thylogale billardierii) the most common species identified, both in overall numbers and frequency of trips encountered. The 10 most common taxa accounted for 99% of the items observed. The seasonal occurrence, relationship with vehicle speed, and clustering in local hotspots for particular taxa all suggest that mitigation measures, such as vehicle speed reduction in specific areas, may be effective in reducing the number of animals killed. Mitigation measures, however, will not apply equally to all species and, in particular, success will depend on changing human behaviours.

Context
Wildlife can be injured or orphaned through a range of (often anthropogenic) activities, creating need for volunteer rescuers and wildlife carers, of which a substantial number is active in Australia. However, the causes and contributing factors for rescued wildlife are rarely reported, which limits development of response options to these wildlife issues. An understanding of the distribution and number of rescuers and carers in relation to injured and orphaned wildlife allows training and outreach to be targeted around specific seasonal peaks, species and causes of injury.

Aims and methods
We conducted an analysis of 22723 reports over 7 years to the Bonorong Wildlife Rescue Service in Tasmania, Australia, to determine the frequency of species and types of human–wildlife interaction, the report distances from the central facility, and the report distribution relative to the registered rescuer and carer networks.

Key results
Mammals accounted for over half of all reports, followed by birds, reptiles and invertebrates. Road trauma was the predominant cause for report, followed by orphans. Disease reports and animal attack were also common. Overall, reporting was highest in late spring and summer, but different seasonality in specific causes and species suggests that targeted response options are needed at different times of year. Areas with higher reporting relative to the number of registered rescuers and carers show where volunteer recruitment can be focussed.

Conclusions
We used a wildlife reporting dataset to illustrate trends (such as seasonality and species vulnerability) and causes of human–wildlife interaction to inform potential response options.

Implications
Continued citizen reporting can assist wildlife managers to allocate resources, plan training or recruit additional volunteers, track emerging issues, such as disease and climate-related stressors, and guide the planning of public education and mitigation initiatives, particularly for human-related wildlife issues.

Anthropogenic climate change is already apparent and will have significant, ongoing impacts on Australian fishes and their habitats. Even with immediate actions to reduce greenhouse gases, there will be sustained environmental changes. Therefore, it is necessary to consider appropriate adaptations to minimise detrimental impacts for both fishes and the human populations that utilise them. Climate change will have a range of direct effects on the physiology, fitness, and survivorship of Australia's marine, estuarine and freshwater fishes, but also indirect effects via habitat degradation and changes to ecosystems. Effects will differ across populations, species and ecosystems, with some impacts being complex and causing unexpected outcomes. The range of adaptation options and necessary levels of intervention to maintain populations and ecosystem function will largely depend on the vulnerability of species and habitats. Climate change will also have an impact on people who depend on fishes for food or livelihoods; adapting to a new climate regime will mean trade-offs between biological assets and socioeconomic drivers. Models can be used to help predict trends and set priorities; however, they must be based on the best available science and data, and include fisheries, environmental, socioeconomic and political layers to support management actions for adaptation.

Climate adaptation requires large capital investments that could be provided not only by traditional sources like governments and banks, but also by derivatives markets. Such markets would allow two parties with different tolerances and expectations about climate risks to transact for their mutual benefit and, in so doing, finance climate adaptation. Here we calculate the price of a derivative called a European put option, based on future sea surface temperature (SST) in Tasmania, Australia, with an 18 °C strike threshold. This price represents a quantifiable indicator of climate risk, and forms the basis for aquaculture industries exposed to the risk of higher SST to finance adaptation strategies through the sale of derivative contracts. Such contracts provide a real incentive to parties with different climate outlooks, or risk exposure to take a market assessment of climate change. ; Support for this research came from the CSIRO Climate Adaptation Flagship, Enabling Adaptation Pathways project.

Climate adaptation requires large capital investments that could be provided not only by traditional sources like governments and banks, but also by derivatives markets. Such markets would allow two parties with different tolerances and expectations about climate risks to transact for their mutual benefit and, in so doing, finance climate adaptation. Here we calculate the price of a derivative called a European put option, based on future sea surface temperature (SST) in Tasmania, Australia, with an 18 °C strike threshold. This price represents a quantifiable indicator of climate risk, and forms the basis for aquaculture industries exposed to the risk of higher SST to finance adaptation strategies through the sale of derivative contracts. Such contracts provide a real incentive to parties with different climate outlooks, or risk exposure to take a market assessment of climate change. ; Support for this research came from the CSIRO Climate Adaptation Flagship, Enabling Adaptation Pathways project.

Considerable attention has been directed at understanding the consequences and impacts of long-term anthropogenic climate change. Discrete, climatically extreme events such as cyclones, floods, and heatwaves can also significantly affect regional environments and species, including humans. Climate change is expected to intensify these events and thus exacerbate their effects. Climatic extremes also occur in the ocean, and recent decades have seen many high-impact marine heatwaves (MHWs)—anomalously warm water events that may last many months and extend over thousands of square kilometers. A range of biological, economic, and political impacts have been associated with the more intense MHWs, and measuring the severity of these phenomena is becoming more important. Progress in understanding and public awareness will be facilitated by consistent description of these events. Here, we propose a detailed categorization scheme for MHWs that builds on a recently published classification, combining elements from schemes that describe atmospheric heatwaves and hurricanes. Category I, II, III, and IV MHWs are defined based on the degree to which temperatures exceed the local climatology and illustrated for 10 MHWs. While there is a long-term increase in the occurrence frequency of all MHW categories, the largest trend is a 24% increase in the area of the ocean where strong (Category II) MHWs occur. Use of this scheme can help explain why biological impacts associated with different MHWs can vary widely and provides a consistent way to compare events. We also propose a simple naming convention based on geography and year that would further enhance scientific and public awareness of these marine events.