Grizzly PAW V1 Issue 3 (Sept 2017)




Grizzly PAW’s Electronic Newsletter
Vol. 2, Issue 1. Date: 10/09/2017

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Welcome to the September edition of the Grizzly-PAW newsletter. This summer was our first field season and despite the tight timeline to get some of our researchers in the field, we had a very active summer.

In this edition:



Grizzly-PAW Research Summary


We are currently working on seven of the 12 research
questions that Grizzly-PAW is mandated to research.  The active research
questions are summarized in the table below.


Project Identifier









Yellowhead Disturbance Assessment and
characterization of EcoAnthromes disturbance regimes




Yellowhead Disturbance Assessment and
Regional Snow Melt and Spring Flush Dynamics




Grizzly Bears and Biodiversity

Population Performance




Yellowhead Population Demographic




Food Supply and Landscape Carrying





Movement and Health




Human Use and Mortality





Physiological Function Markers

Summer Data Collection


This summer, fRI continued bear capture activities. There were 5 bears collared within Jasper National Park , one bear south of Hinton and there were 5 bears translocated and collared into BMA 3 in 2017 to provide data for researchers with the Grizzly Paw program. In addition there were 10 bears collared within the Kakwa area (BMA 2) that can be used for comparative purposes.
Three of our researchers also collected data this summer in the Yellowhead region. Chris Souliere (Q2.1 –Food Supply) collected vegetation data in 99 transects from mid-June to the end of August. Emily Cicon (Q1.3- Biodiversity -Songbirds) also spent much of the summer in the field, collecting data on birds in the region. Last of all, Ethan Berman (Q1.2 – Snow Melt Dynamics) returned to his monitoring setup to pick up data collected during the spring and adjust cameras to monitor vegetation.

New Projects


This summer, we began research on three more questions that were identified by our Industry partners. Sean Kearney started Q1.1 at UBC with Nicholas Coops in July. He is working on eco-Anthrome classification in the Yellowhead region. Emily Cicon officially began her MSc (Q1.3) at UofA with Dr. Scott Nielsen in May. She is researching songbird surrogacy and grizzly bears. Sean Coogan, also at UofA with Scott Nielsen, started his PDF (Q2.2) in mid May. He is analyzing bear demographics in the Yellowhead region.


Ongoing Projects


Ethan Berman (Q1.2 – Snow Melt Dynamics) returned to the field to retrieve snow melt data and adjust cameras to monitor the vegetation cycle. He also developed a new snow cover product that downsizes MODIS snow cover data to Landsat scale.

Chris Souliere (Q2.2 – Food Supply) concentrated on field work for his research on grizzly bear food supply. He spent most of the summer collecting vegetation data in 50×2 m transects from 99 different sites in or near the Yellowhead region.

Matthieu Bourbonnais (Q3A.1 – Movement and Health) is nearing completion of his PhD and expects to defend in December. During the summer, he made revisions for two publications (Daily Movement and Behavioural Strategies, and Behavioural Modes using a Hidden Markov Model) and completed another manuscript on population scale movement probability.

Lucy Kapronsczai (Q3B.1 – Physiological Function Markers) completed her draft proposal, hair cortisol analysis for 2016 data and hair sex hormone preparation. She also sequenced the grizzly bear genome and began analysis of that sequence.

Feature Researcher

Ethan Berman


Ethan Berman, more recently known as “the snow guy”, is an MSc Candidate in the Integrated Remote Sensing Studio at the University of British Columbia. His research investigates connections between snow dynamics in the Yellowhead region and Grizzly Bear behavior. A year into his Masters, Ethan has thus far been focused on creating detailed snow maps using satellite imagery. He has also made several field work trips to Alberta to set up a network of time-lapse cameras to serve as a ground validation of snow conditions. Creating a system of cameras that can function through the Canadian winter has been challenging, but Ethan enjoys the arduous winter excursions and connecting what he sees on the computer to what is actually happening in the field. He looks forward to integrating the Grizzly Bear GPS data with the snow products during the coming year.

Ethan holds a B.A. in Math from the University of Virginia. Before moving to Vancouver, he spent several years as a Princeton in Asia fellow in Thailand, teaching math and working as an outdoor and experiential educator. Through work and a personal fixation with natural and wild places, Ethan has witnessed first-hand many of the challenges related to environmental management and the balancing of different land-use values. His interaction with these issues – from the marine parks of Southern Thailand to the mountains of Western Canada – has led to his interest in spatial data related to environmental and conservation issues. When not in the lab or in the field, you are most likely to find Ethan slogging up to a cold mountain summit or eating the spiciest food he can find. He is thrilled to be a part of the Grizzly-PAW research team.

Research Snapshot


Chris Souliere

Chris Souliere is researching Q2.2 (food supply and landscape carrying capacity) under the supervision of Dr. Scott Nielsen at the University of Alberta. The Alberta foothills have seen extensive land-use change in the past few decades, with forestry being a dominant contributor. Previous research has shown that grizzly bears frequent forestry cutblocks as the removal of canopy allows for light to penetrate to the ground encouraging growth of early seral vegetation that are preferred by bears (Nielsen et al., 2004). Furthermore, open habitats (e.g. meadows/shrubfields) that are more typical of southern interior populations (e.g. Montana) are in short supply in the forest-dominated foothills. As such, there may be benefits in exploring whether cutblocks can act as surrogates or emulate natural forest fires. To address such premises, his PhD has begun to explore whether forestry-based habitat disturbances (i.e., cutblocks) can act as surrogates to natural forest fires in relation to grizzly bear food-resource supply, habitat selection and local population densities.

To begin addressing this question, a field season was conducted this summer in the Yellowhead and Grand Cache bear management areas. Field work involved sampling common grizzly bear foods in approximately 100 belt transects (50 X 2 m) with emphasis on measuring understory fruiting shrubs, forbs and graminoids that are preferred by bears. To ensure proportionality of early, mid and late successional stages, three different age classes/strata (~ 5, 20 and 60 years) were considered among both fire and cutblock treatments. In the coming months, these data will be analyzed to compare total digestible energy among treatments and strata using bioenergetics models and energy budgets that should assist in assessing differences in productivity between fire and cutblock treatments. Further analyses will explore how these models can be extended to estimate habitat-based landscape carrying capacity, habitat selection, and local population densities.

Chris’ PhD research will also explore how grizzly bear recovery can be better integrated within forest harvest planning, as well as using individual-based simulation (IBM) models to examine behavioural to population responses. Specifically, Chris has an interest in assessing how grizzly bear food-resource supply and bioenergetics models can be incorporated within the existing forest planning harvest optimization used by industry through multi-optimization (bears and timber). This retrofitted optimization model should help in designing appropriate management scenarios that can be used in the event of competing interests in a multi-use landscape. He is also interested in constructing a spatially explicit IBM that focuses on the emergent properties of grizzly bear ecology by simulating the autonomous interactions between individual bears and their environment. This model should help forecast aspects of grizzly bear ecology under alternative land-use and/or management scenarios.

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.



LiDAR Workshops

On Oct. 19-20th, AWARE and the Canadian Wood Fibre Centre (CWFC) will be holding introductory workshops on LiDAR data processing in Edmonton and Whitecourt. These workshops, targeted towards foresters with minimal exposure to LiDAR, will show participants how to process a LiDAR point cloud with FUSION to develop a simple model in Excel. If you are interested in this workshop, the registration link for:

Edmonton, Oct. 19th

Whitecourt, Oct. 20th

Grizzly-PAW AGM

Last of all, the Grizzly-PAW AGM will be held at the Sutton Place Hotel in Edmonton from Oct. 10-12th, 2017. If you would like to register to attend and haven’t yet registered, please contact us as soon as possible.



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