Fostering Climate-Resilient Biodiversity and Fisheries in Eastern Tropical Pacific Marine Protected Areas
Bibliographic record
Abstract
Climate change is driving the global redistribution of marine species, impacting local biodiversity patterns. These changes are causing a mismatch between spatial conservation strategies, such as Marine Protected Areas (MPAs), and the distribution of species and ecosystems that they aim to protect. In 2004, Costa Rica, Colombia, Ecuador, and Panama established the Tropical Eastern Pacific Marine Conservation Corridor (CMAR) to protect the migratory corridors of large pelagic species such as sharks, rays, turtles, and marine mammals. While the effects of global warming on the oceans and the expansion of oxygen minimum zones are identified as critical issues, they are not explicitly considered in the management plans for CMAR MPAs. Giving that many MPAs in CEMAR are in the process of updating their management plan, this project assesses the impacts of climate change on these MPAs to inform such process. Specifically, we aim to identify possible adaptation and management strategies to enhance the climate resilience of biodiversity and fisheries in the region. Spatially-explicit integrated climate-fish-fisheries models are used to project the impacts of climate change, fisheries management and marine protection on the biogeography, biomass and potential catches of important marine species in the Eastern Tropical Pacific (ETP) region. Specifically, we use these models to examine the outcomes of four different future scenarios informed by professionals in the field from various countries and institutions within CMAR. These future scenarios allow us to compare results of (1) prioritizing conservation, (2) prioritizing resource extraction, (3) prioritizing both, (4) prioritizing neither, and compare to the results under the status quo. Our results show that biomass and potential catches in the ETP region, and the effectiveness of MPAs within CMAR in supporting biodiversity conservation and seafood production, are strongly impacted by the level of climate change. Thus, sustainable fishing practices and changes in fishery production in the ETP region while adapting the management and conservation plan for MPAs in the CMAR to climate-induced shifts in species distribution are crucial in MPA management plans in order to achieve the previously established conservation objectives. Improving the understanding of climate change impacts on marine biodiversity can enhance the effectiveness of conservation and fishery management plans in building climate resilience of ecosystems in the region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".