Were Native People Keystone Predators? A Continuous-Time Analysis of Wildlife Observations Made by Lewis and Clark in 1804-1806
Bibliographic record
Abstract
It has long been claimed that native people were conservationists who had little or no impact on wildlife populations. More recently, though, it has been suggested that native people were keystone predators, who lacked any effective conservation strategies and instead routinely overexploited large mammal populations. To test these hypotheses, I performed a continuous-time analysis of wildlife observations made by Lewis and Clark because their journals are often cited as an example of how western North America teemed with wildlife before that area was despoiled by advancing European civilization. This included Bison, Elk, Mule Deer, Whitetailed Deer, Blacktailed Deer, Moose, Pronghorn Antelope, Bighorn Sheep, Grizzly Bears, Black Bears, and Grey Wolves. I also recorded all occasions on which Lewis and Clark met native peoples. Those data show a strong inverse relationship between native people and wildlife. The only places Lewis and Clark reported an abundance of game were in aboriginal buffer zones between tribes at war, but even there, wildlife populations were predator, not food-limited. Bison, Grizzly Bears, Bighorn Sheep, Mule Deer, and Grey Wolves were seldom seen except in aboriginal buffer zones. Moose were most susceptible to aboriginal hunting followed by Bison and then Elk, while Whitetailed Deer had a more effective escape strategy. If it had not been for aboriginal buffer zones, Lewis and Clark would have found little wildlife anywhere in the West. Moreover, prior to the 1780 smallpox and other earlier epidemics that decimated native populations in advance of European contact, there were more aboriginal people and even less wildlife. The patterns observed by Lewis and Clark are consistent with optimal foraging theory and other evolutionary ecology predictions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 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".