Population dynamics of reintroduced elk (Cervus elaphus) in eastern North America
Bibliographic record
Abstract
Studies that focus on identifying factors that influence reintroduction success have often taken an \nindividual population approach; however, investigating multiple populations can provide \nadditional insight. The overall objective of this research was to emphasize the value of using \nwithin- and among-population approaches to identifying factors that influence the population \ndynamics of a reintroduced species. Elk (Cervus elaphus), a species that was extirpated from \neastern North America during the late 1800s, has been reintroduced to portions of its former \nrange over the past century through several initiatives. Today, there are several established \npopulations across eastern regions of the USA and Canada, for which extensive monitoring data \nare available, creating an opportunity to investigate reintroduction success. I aimed to use these \ndata to identify factors associated with changes in the survival and population growth rates of 10 \nreintroduced elk populations across eastern North America. More specifically, I: (1) performed a \nliterature review detailing the history of elk reintroduction in eastern North America over the \npast century, (2) identified factors associated with the variation in population growth rates \n(reintroduction success) for 10 reintroduced elk populations using an among-population \napproach, (3) identified and assessed how climate affected the population growth rates of 7 \nreintroduced elk populations, and (4) investigated direct causes of mortality (predation and train \ncollisions) associated with a single elk population experiencing low population growth. \nAlthough the number of successful elk restoration attempts has increased over the past century, \nthere has been substantial variation in population growth rates among reintroductions. Major \niv \ncauses of elk mortality in restored populations differed between the pre- to post-acclimation \nphases of reintroduction. Population growth rates were negatively related to the percentage of \nconiferous forest within elk population range, suggesting that expansive areas of coniferous \nforests in eastern North America may represent sub-optimal elk habitat. \nThe Burwash elk population in Ontario had low growth rate compared to most other populations \nreintroduced into eastern North America. Predation and train collisions were the most important \nsource of mortality for this population. The number of annual elk-train collisions, as well as their \nlocations, were monitored and recorded over 14 years. Collision locations were highly sitespecific \nand were positively correlated to the proximity of bends in the railway. By relating the \nnumber of annual elk-train collisions to various climate factors, I found that collision rates were \npositively related to snow depth. By analyzing field camera data, I found that elk used the \nrailway mostly during the fall and spring, when elk commonly travel to and from wintering \ngrounds. However, by examining VHF telemetry locations, I determined that elk were closer to \nthe railway in winter than in any other season. Railways likely are perceived by elk as easy travel \ncorridors, especially in the winter, and deep snow might prevent escape from oncoming trains. \nBlack bear (Ursus americanus) and wolves (Canis lupus) were the major predators of elk in the \nBurwash population. White-tailed deer (Odocoileus virginianus), elk (Cervus elaphus), and \nmoose (Alces alces), were the ungulate prey species available to both predators. To determine if \npredators prefer one ungulate species over another, and to identify which predator species is \nlikely to have a greater impact on elk survival, I investigated predator diets. To compare rates of \nv \nungulate use by predators in relation to prey availability, I calculated the relative abundance of \neach ungulate species. I found that wolves used juvenile and adult elk as their primary ungulate \nprey in greater proportions in comparison to their availability. Bears on the other hand, tended to \nuse all ungulate species in proportion to their availability. \nClimate is well known to affect ungulate population dynamics; however, several factors (e.g.: \ndensity, predator presence), can govern the response. Relating the annual growth rates of 7 elk \npopulations to various climate factors I found that responses were population specific. Increased \nannual snow fall was associated with declines in population growth rates for 2 of the 7 \npopulations assessed and only 1 population responded negatively to increased summer \ntemperatures. Climate likely interacts with other environmental variables to influence \nfluctuations in annual population growth rates which warrants further investigation. \nThe results of this research will contribute to informed planning of future elk reintroductions and \nshould support development through improved management. In addition, this research highlights \nthe importance of using within- and among- populations approaches to investigating factors that \ninfluence elk reintroduction success.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".