Incorporating protected areas into global fish biomass projections under climate change
Bibliographic record
Abstract
The world has set ambitious goals to protect marine biodiversity and improve ocean health in the face of anthropogenic threats. Yet, the efficiency of spatial tools such as marine reserves to protect biodiversity is threatened as climate change shifts species distributions globally. Here, we investigate the ability of global marine reserves to protect fish biomass under future climate change scenarios. Moreover, we explore regional patterns and compare worlds with and without marine reserves. We rely on computer modeling to simulate an utopian world where all marine reserves thrive and ocean governance is effective. Results suggest that climate change will affect fish biomass in most marine reserves and their surrounding waters throughout the 21st century. The biomass change varies among regions, with tropical reserves losing biomass, temperate ones gaining, and polar reserves having mixed effects. Overall, a world with marine reserves will still be better off in terms of fish biomass than a world without marine reserves. Our study highlights the need to promote climate resilient conservation methods if we are to maintain and recover biodiversity in the ocean under a changing world.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".