Bibliographic record
Abstract
The Ya Ha Tinda Elk project is now amongst the longest running elk research project in the world. Initiated in 2000, the Ya Ha Tinda elk project is the result of a collaboration between University of Alberta, University of Montana, Parks Canada, and Alberta Environment and Parks, Fish and Wildlife Division. While early studies in the late 1970’s and early 1980’s lead by Dr. Luigi Morgantini laid the foundation for our latter studies (Morgantini and Hudson 1988), there was a ~ 20-year gap in active research on Alberta’s most important elk population. Initiated at first because of questions regarding the changing migratory dynamics of the migratory Ya Ha Tinda elk population, the project has since evolved into North America’s longest running wild, free-ranging elk research projects focused on fundamental and applied research. The Ya Ha Tinda is one of Alberta’s most pristine montane rough fescue winter ranges and elk which provides the habitat foundation for one of Canada’s most iconic and largest populations. The Ya Ha Tinda elk population is also a transboundary system, with annual elk migratory cycles that have spanned two provinces (elk have migrated into Yoho National Park, British Columbia), two land management regimes including Banff National Park, Provincial Forest Land Use Zones, and Provincial multiple use zones. Ya Ha Tinda is also managed as a premier bull elk harvest area that provides much sought-after hunting opportunities to residents and guided hunters alike. Meaning mountain prairie in the Stoney Sioux language, Ya Ha Tinda has long been important to First Nation communities for hunting and traditional land use practices. And the region is also home to recovered populations of grizzly bears, wolves, and other large mammal predator-prey species, including for the first time in over a century – Plains bison. In this transboundary setting, our long-term research has contributed directly to enhancing interagency cooperation and management of this important elk population. Our long-term studies have documented dramatic changes in migratory behavior and population dynamics arising from this complex landscape of gradients in carnivore densities, habitat productivity, and differences in land management practices. Over the last 30-40 years migrant to resident ratios have substantially decreased from 12:1 (1977-1987, (Morgantini and Hudson 1988)), 3:1 in the early 2000’s (Hebblewhite et al. 2006), to more recently a ratio closer to 1:1 (Berg 2019). Early studies in the 2000’s demonstrated that migratory elk moving west into BNP experienced much higher forage quality which translated to higher calf 8-month old weights and higher pregnancy rates (Hebblewhite et al. 2008). Yet western migrants also experienced reduced predation risk from wolves, but higher risk from grizzly bear predation (Hebblewhite and Merrill 2007, MacAulay 2019). Resident elk remaining year-round near Ya Ha Tinda, in contrast, experienced lower forage quality, but, compensated for this by reducing predation risk by seeking out fine-scale predation risk refugia surrounding human development at the Ya Ha Tinda (Hebblewhite and Merrill 2009, Robinson et al. 2010). Commensurate with these shifts in the migratory dynamics of this population have been correspondingly significant population shifts and changes (Hebblewhite et al. 2006, Killeen et al. 2015, Berg 2019). In the last decade, a new migratory strategy has emerged with female elk now undertaking an eastward migration into Provincial multiple use lands in and adjacent to the 2001 Dogrib fire (Killeen et al. 2015). Long-term research revealed individual elk are making density-dependent switches in migratory behavior, evidently to seek out these new beneficial areas (Eggeman et al. 2016). In 2013 – 2017, we lead a neonate calf survival research component to understand spatial variation in calf survival (Berg 2019). Calf survival and cow:calf ratios have indicated that calf survival of elk migrating east on to industrial forest experienced higher calf survival. In January 2019, Jodi Berg defended her PhD thesis on elk calf survival, and her thesis details are provided in our publications section below. This new migratory behavior has seemingly stabilized the Ya Ha Tinda elk population, which has fluctuated between 400 – 600 elk now for almost a decade. Our long-term predator-prey research shows, however, that this stabilization is not likely a result of wolf or grizzly bear predation stabilizing the population at low density (Hebblewhite et al. 2018). Instead, our research suggests that migratory behavior itself may be providing escape from low densities (Hebblewhite et al. 2018).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.209 | 0.099 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".