Diet reconstruction and historic population dynamics in a threatened seabird
Bibliographic record
Abstract
Summary For the overwhelming majority of species, we lack long‐term information on the dynamics of populations. As a consequence, we face considerable uncertainty about how to discriminate among competing hypotheses of population decline and design conservation plans. The marbled murrelet Brachyramphus marmoratus is a small seabird that nests in coastal old‐growth forest but feeds year‐round in near‐shore waters of the north‐eastern Pacific. Although a decline in nesting habitat is the primary reason why marbled murrelets are listed as threatened in Canada, nest predation and food availability may also influence population abundance. To examine the hypothesis that murrelet populations are influenced by variation in diet quality, we analysed stable‐carbon and ‐nitrogen isotopes in feathers of museum specimens collected in the Georgia Basin, British Columbia. Between 1889 and 1996, we found a decline in stable isotopic signatures that was approximately equal to a 62% drop in trophic feeding level. We also found that the estimated proportion of fish in murrelet diet was related closely to murrelet abundance over the past 40 years, as estimated from volunteer surveys. Using these isotopic data, we modelled population size as a function of variation in reproductive rate due to changes in diet quality and found that our model matched closely the 40‐year field estimates. We then applied our 107‐year isotopic record to the model to back‐cast estimates of population growth rate to 1889. Our results suggest that, up to the 1950s, murrelet populations in the Georgia Basin were capable of growing and were probably limited by factors other than diet quality. After this period, however, our results imply that murrelets were often, but not solely, limited by diet quality. Synthesis and applications . Protecting nesting habitat may not be sufficient to rebuild populations of this highly secretive and threatened seabird and recovery might also require the restoration of marine habitat quality, as well as a better understanding of how ocean climate affects prey abundance and reproductive rate. Combined with contemporary demographic data, stable isotope analysis of historic samples provides a unique opportunity to reconstruct population histories for species where we lack long‐term information.
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 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 | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".