New Researchers

 

Four new researchers have joined Grizzly-PAW. With these new additions, we have started research on seven of the eight questions that were scheduled for the first year of Grizzly-PAW. Should you want to know a bit more about any of our researchers, their biographies are on the Grizzly-PAW website.

Q1.1 Characterization of EcoAnthrome Disturbance Regimes, Sean Kearney

Q1.3 Grizzly Bears and Bio-diversity, Emily Cicon

Q2.1 Population Demographic Analysis, Sean Coogan

Q3A.2 Human Use and Mortality, Brandon Prehn

Field Season Update

Summer Activities

This summer’s field season has been very busy. Bear capture activities by Gord Stenhouse at fRI are ongoing until the end of June. Ethan Berman (Q1.2) just returned from a short trip to retrieve data from his snow monitoring equipment. We will be using the same stations to monitor vegetation phrenology over the summer. From UofA, Emily Cicon (Q1.3) isin the field this summer, collecting songbird data from different areas in the Yellowhead region. Chris Souliere (Q2.2) is also in the field for his work on grizzly bear food supply, and will return at the end of the summer.

Feature Researcher

Research Snapshot

Mathieu Bourbonnais is researching Q3A.1 under the supervision of Chris Darimont at the University of Victoria. Among the primary goals of his PhD research has been exploring how grizzly bear movement patterns are influenced by spatial and temporal change in landscape conditions and environmental dynamics. Previous research has shown grizzly bear habitat selection, health, and mortality are strongly influenced by anthropogenic and natural disturbance, land cover, and resource (i.e., food) availability. What is less clear, is how their movements and space use are influenced by these factors. For example, how are the daily movement rates and seasonal ranges of individuals influenced by road and forest harvest densities, as well as landscape productivity, and have these patterns changed over time? By quantifying movement patterns of individuals, we can begin to develop a more complete understanding of grizzly bear population movement and behaviour to support conservation and management efforts. However, providing population scale estimates of movement parameters requires positional data from multiple individuals over large areas, as well as landscape and environmental data that matches the temporal span of the movement data. Thanks to the collaborative efforts of the GPAWS research group, broad scale grizzly bear movement and landscape data are available to help answer these questions.

For this portion of his research, he used GPS telemetry data, collected by the fRI Research Grizzly Bear Program in the Yellowhead and Grande Cache bear management units from 2001 to 2014, to quantify 219 individual movement trajectories. One of the main challenges of working with GPS telemetry data collected over 13 years was the irregular sampling frequency. Prior to 2006, much of the GPS data was collected at 4- or 5-hr intervals while improving collar technology and battery life allowed higher temporal resolution (20- and 30-min, 1-hr) data to be collected later in the study. Differences in sampling frequency, as well as missing data, are problematic when estimating movement parameters including speed, turning angles, and distance travelled, often requiring GPS data to resampled to the lowest temporal resolution resulting in a loss of information. To overcome these limitations, he fitted each of the 219 trajectories as a continuous-time correlated random walk which models the velocity autocorrelation as a continuous process allowing positions to be predicted at a desired resolution (Fig. 1).

Each trajectory was simulated 5000 times and positions were predicted at a 1-hr resolution. I also used the individual CTCRWs to simulate 10 000, 1-min quasi-continuous trajectories to quantify the utilization distribution and 99th percentile range during the hypophagia/mating (den emergence until June 30), early-hyperphagia (July 1 – 31) and late-hyperphagia (August 1 until den entry) seasons (Fig. 2).

 

He used generalized additive mixed models in an information theoretic framework to quantify the influence of landscape disturbance, land cover, productivity, and topography, characterized using a variety of spatial and remotely sensed data, on grizzly bear movement at both the hourly (e.g., the trajectory) and seasonal (e.g., the range) scale. As he was interested in spatial-temporal component of landscape disturbance, an important input for this research was a Landsat disturbance time-series data product developed by the Integrated Remote Sensing Studio (IRSS) where forest disturbances are attributed by type (e.g., road, harvest block, well-site) and the year of disturbance. He also considered the influence of gender, age, and the presence of offspring on the observed movement and space use patterns. The hourly trajectory scale models reveal a clear and persistent diurnal pattern in movement speeds across all years, gender and age classes. To date, the top candidate model shows movement speeds are lowest in relation to high cumulative densities of anthropogenic disturbance and greater productivity as represented by the Normalized Difference Vegetation Index (NDVI). At the season scale, the top candidate model showed range size was inversely related to minimum greenness (modelled using the Dynamic Habitat Index) and seasonality, and range size increased in relation to anthropogenic disturbance densities. Further candidate models are planned which will incorporate the linearity of daily movements as well as temporal overlap in seasonal ranges (e.g., philopatry). The modelling approach and results from this analysis will provide useful context for the remainder of his research examining classified behavioural patterns across temporal scales.

Grizzly-PAW AGM

 

AGM

The first Grizzly-PAW AGM is planned for September or October. At the AGM, PAW researchers will present the progress from our first year of operation. The plan is to tour some of our field data collection sites. All Grizzly-PAW industrial partners and staff of supporting organizations are invited to attend this meeting. More details to follow soon.

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