Wildlife Risk Management at Vancouver International Airport

The Vancouver International Airport (YVR) is the second busiest airport in Canada. YVR is located on Sea Island in the Fraser River Estuary - a world-class wintering and staging area for hundreds of thousands of migratory birds. The Fraser Delta supports Canada’s largest wintering populations of waterfowl, shorebirds, and raptors. The large number of aircraft movements and the presence of many birds near YVR pose a wide range of considerable aviation safety hazards. Until the late 1980s when a full-time Wildlife Control Program (WCP) was initiated, YVR had the highest number of bird strikes of any Canadian commercial airport. Although the risks of bird strikes associated with the operation of YVR are generally well known by airport managers, and a number of risk assessments have been conducted associated with the Sea Island Conservation Area, no quantitative assessment of risks of bird strikes has been conducted for airport operations at YVR. Because the goal of all airports is to operate safely, an airport wildlife management program strives to reduce the risk of bird strikes. A risk assessment establishes the current risk of strikes, which can be used as a benchmark to focus wildlife control activities and to assess the effectiveness of the program in reducing bird strike risks. A quantitative risk assessment also documents the process and information used in assessing risk and allows the assessment to be repeated in the future in order to measure the change in risk over time in an objective and comparative manner. This study was undertaken to comply with new Canadian legislation expected to take effect in 2006 requiring airports in Canada to conduct a risk assessment and develop a wildlife management plan. Although YVR has had a management plan for many years, it took this opportunity to update the plan and conduct a risk assessment.

Spatial modelling and prediction on river networks: up model, down model or hybrid?

Preservation of rivers and water resources is crucial in most environmental policies and many efforts are made to assess water quality. Environmental monitoring of large river networks are based on measurement stations. Compared to the total length of river networks, their number is often limited and there is a need to extend environmental variables that are measured locally to the whole river network. The objective of this paper is to propose several relevant geostatistical models for river modeling. These models use river distance and are based on two contrasting assumptions about dependency along a river network. Inference using maximum likelihood, model selection criterion and prediction by kriging are then developed. We illustrate our approach on two variables that differ by their distributional and spatial characteristics: summer water temperature and nitrate concentration. The data come from 141 to 187 monitoring stations in a network on a large river located in the Northeast of France that is more than 5000 km long and includes Meuse and Moselle basins. We first evaluated different spatial models and then gave prediction maps and error variance maps for the whole stream network.