Equilibrium Analyses of a Population's Response to Recovery Activities: A Case Study with Atlantic Salmon
Bibliographic record
Abstract
Abstract Recovery planning for populations in decline requires a thorough understanding of how life history characteristics, environmental conditions, and human activities interact to determine how abundance changes through time. In a detailed case study of the declining population of Atlantic salmon Salmo salar in the Tobique River, New Brunswick, we demonstrate an equilibrium modeling approach to analyzing the dynamics of the population so as to identify stressors and predict the population-level response to potential recovery actions. Parameter values for the equilibrium analysis were obtained by fitting a life history model to population-specific data, including annual estimates of juvenile density and egg deposition as well as the number and age composition of emigrating smolts. Two unique aspects of the statistical analysis—standardization of the electrofishing data using a generalized linear model and scaling of the juvenile density estimates to total abundance using a catchability coefficient—significantly improved model fits and resulted in parameter estimates that were biologically realistic. The subsequent equilibrium analysis was used to evaluate how population size was expected to change in response to recovery actions focused on fish passage, marine survival, and freshwater production. Recovery actions focused only on freshwater habitat or fish passage were not sufficient to produce an equilibrium population size greater than zero; however, either factor could limit the effectiveness of other recovery actions if not included in the recovery plan. The case study highlights the complex dynamics that can limit population growth, illustrates the need to consider the full life cycle of a species as part of the recovery planning process, and shows that responses to multiple threats may be required to bring about recovery.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".