In an effort to build a scientifically robust program, we break down the challenge of trend monitoring for migratory birds to reveal multiple decision points and their impacts on the monitoring information ultimately produced. We conducted a quantitative evaluation of existing programs for monitoring trends of migratory landbirds and waterfowl, and the relative value of augmenting existing designs through simple levers such as sampling intensity, frequency or program duration. Duration of monitoring was consistently the most important factor in trend monitoring, with most common species requiring 10-15 years to detect population trends. Time lags for trend detection highlight the need to pair trend monitoring with spatial comparisons or model- based approaches to estimate change more quickly. Existing program adequately monitor regional trends for common species, while species that are rare, use rarer habitats or possess behaviours that make them difficult to detect using standard surveys require alternate monitoring approaches. We present a stratified sampling program to augment monitoring of landbirds associated with old-growth forests, including Species At Risk. Data collection was initiated in the spring 2014 at 2490 sites, including 715 site revisits, across the Peace, Athabasca and Cold Lake oil sands areas. The stratified design more than doubled the detection frequency of a target species compared to a systematic design. Future work for landbirds will emphasize estimation of inter-annual variability to improve trend detection and efficiency of program design. For waterfowl, existing programs will continue and new efforts focus on waterfowl breeding population distribution and effects assessment monitoring.
Dr. Samantha Song is the Head of the Population Assessment Unit with Canadian Wildlife Service, Prairie & Northern Region, Environment Canada. In addition to oil sands monitoring, Song and her staff hold federal responsibilities for monitoring and management of non-game migratory bird populations across the Prairie Provinces, and regional status assessment and listing of Species at Risk.
Song is also a Steering Committee member of the Boreal Avian Modelling Project, an international collaboration to improve the science of boreal bird ecology, conservation and management. Song holds a PhD from University of Alberta, and an MScF from University of Toronto.