Predictive modelling of kelp (Laminariales) forest habitat around Haida Gwaii anticipating the return of sea otters (Enhydra lutris)
Why this work is in the frame
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Bibliographic record
Abstract
Kelp (Laminariales), sea urchins (Mesocentrotus franciscanus and Strongylocentrotus spp.) and sea otters (Enhydra lutris) are key components of an ecological paradigm in which kelp forests depend on sea otters as a keystone predator. Sea otters perpetuate trophic cascades \nwhere their predation of herbivorous sea urchins controls urchin grazing pressure on kelp in order to maintain abundant kelp forests. During the maritime fur trade, sea otters were extirpated from most of their geographic range, including Haida Gwaii, by the mid-1800s. The loss of sea otters released their macroinvertebrate prey, including sea urchins, from high predation pressure. Subsequently, urchins overgrazed kelp and created kelp-devoid areas known as urchin barrens. The re-introduction of sea otters to British Columbia (BC) and their eventual recovery to their historic range will again cause dramatic changesin kelp forest \ndistribution and growth. To understand the implications of sea otter return and recovery on the kelp forests of Haida Gwaii in BC, Canada, I created bottom-up, geographic models of potential kelp and urchin barrens habitat to predict the distribution of future kelp growth and \nindicate the spatial extent of kelp forests restored through trophic cascades. All input data were provided by secondary sources and overlaid to map areas with a combination of abiotic conditions that potentially support kelp and sea urchins. I found that potential ecosystem \nshifts from urchin barrens to kelp forests were expected to occur over 92,824 ha of temperate rocky reef and stable mixed substrates. This represents 80% of the total potential kelp forest habitat that shows the total area of suitable habitat for kelp forest growth. The remaining \n20% represents areas of potential kelp forest habitat unimpacted by urchin barrens. The applicability of results to marine management included detailed mapping of areas with predicted changes in kelp forests growth. Relative difference between potential existing kelp \ngrowth and potential increases in kelp growth informs marine spatial planning as a tool for managing vulnerable ecosystems, ecosystem services, and conflicting uses. Kelp management issues for Haida Gwaii include future kelp forest increases that promote and conserve ecosystem services, biodiversity, while building resilience against threats from \nherbivory, climate change, ocean acidification, introduced species and oil spills. Potential habitat mapping can foster improved marine spatial planning within an ecosystem-based management approach that identifies and manages for trade-offs from shifting ecosystems.
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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 | 0.000 | 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 it