Predictors of Imperilment, Spawning Behaviour, Captive Breeding, and Transport Stress for Small-Bodied Species of Freshwater Fishes
Bibliographic record
Abstract
Reintroducing captive-bred species into their natural habitat is important for preserving biodiversity. Reintroductions often involve a series of steps starting with assessing the conservation status of the target species, factors causing its decline, and an evaluation of potential reintroduction sites focusing on habitat quality and threats. Next, source populations need to be selected for reintroductions considering the potential impact on wild populations. When sourcing individuals from wild populations poses significant harm, captive breeding programs are established. After successfully breeding individuals in captivity, the next step is to transport the target species from their captive environment to the reintroduction site where they will be released into their natural habitat. Lastly, post-release monitoring should be conducted to assess population behavior and survival, with adaptive management strategies guiding ongoing efforts. Accordingly, this dissertation contributes knowledge to various facets of the reintroduction process, contributing largely to the captive breeding stage, thus providing valuable insights for advancing reintroduction success and conservation strategies. Chapter 2 of this dissertation reviews species prioritization for captive breeding, focusing on small-bodied minnow and darter species in North America. It explores whether natural history traits could predict conservation status. Habitat and small-body size-related natural history traits were found to be associated with imperilment for both minnows and darters, suggesting species with these natural history traits may be at greater risk of imperilment and should be given consideration for conservation-driven initiatives. Subsequent chapters (Chapters 3, 4, and 5) delve into specific aspects of the captive breeding process, focusing on Redside Dace, an endangered minnow species in Canada. Chapter 3 examines Redside Dace spawning phenology and behavior. We established a 95% probability of spawning initiation at 288 growing degree days (a measure of thermal energy in the environment), while our climate change projections found a potential advancement of spawning initiation by 3 days in 2050 and 7 days in 2100. We also found evidence that Redside Dace spawn separately and in groups on nests and have a polygynandrous mating system. Here, our findings highlight the importance of group spawning and provide insights into predicting spawn timing which may benefit captive breeding. Chapter 4 investigates the impact of environmental enrichment on gamete production, quality, and spawning coloration in hormonally induced Redside Dace, recommending enrichment for improved breeding success. Chapter 5 explores transportation logistics and the effects of transportation on Redside Dace. Here, we found that both maximum metabolic rate and thermal tolerance were not influenced by body condition or transportation, highlighting the feasibility of transporting Redside Dace to reintroduction sites. Overall, this dissertation contributes valuable insights into small-bodied minnow and darter conservation and Redside Dace reintroduction biology, potentially benefiting other small-bodied fishes requiring captive breeding.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".