From Genes to Communities: Effects of Habitat Change over Space and Time on Fish Diversity
Bibliographic record
Abstract
Rapid habitat changes, caused by human activities within the last century, have resulted in biodiversity loss at all levels of biological organization. In light of these changes in the recent past, this thesis explores some of the effects of such changes on fish and wildlife populations, species, and communities using theoretical and empirical approaches. Using simulated genetic data, I first investigated the effects of recent population connectivity changes on the reliability of genetic inferences about connectivity. I found that, when connectivity has declined in the recent past, commonly-used genetic methods for estimating connectivity tend to overestimate current connectivity and underestimate historical connectivity. This could lead to incorrect inferences about gene flow and have negative consequences for conservation of populations and species at risk. Next, I conducted two empirical studies focusing on Canadian fishes that are threatened by habitat changes, making them excellent systems to investigate the effects of habitat change on their ecology and evolution. For Sockeye salmon populations in the Fraser River, I found that hydroelectric dams have fragmented habitats, changed connectivity among populations, and had significant effects on the ecology and evolution of some populations. Based on molecular data, I found evidence indicating very early differentiation between anadromous and resident forms of Sockeye salmon within one reservoir, where a dam has prevented the historically anadromous salmon from migrating to the ocean. In a second case study, on freshwater fish communities in northern Canadian lakes that were thought to be depauperate in biodiversity, I found higher species diversity and fish biomass than expected based on species-energy theory. My analyses indicate that fish diversity and biomass in northern lakes are not substantially lower than southern Canadian lakes. Thus, northern lakes could be important reserves of coldwater fish in light of climate change. In summary, I examined some effects of habitat change on populations, species and communities, and my thesis highlights: (i) areas for the improvement of methodologies and inferences used by conservation biologists; and (ii) specific northern communities of Canadian fishes that warrant attention to preserve Canadian fish diversity.
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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 | 0.002 | 0.013 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".