Investigating human impacts to coral reefs in the Republic of the Marshall Islands
Bibliographic record
Abstract
Both local and global threats are affecting the health of coral reefs worldwide. In addition to endangering the livelihoods and source of food for millions of people, threats to coral reefs may result in flattening reefs, which reduce habitat complexity and the ability of reefs to protect shorelines from erosion. This could be particularly detrimental to low-lying Pacific atolls like those found in the Republic of the Marshall Islands (RMI). I examined the influence of local human disturbance and heat stress on coral and algal community composition in Majuro and Arno Atolls in the RMI to explore how human disturbance affects coral and algal communities, and how to best characterize those communities. With a population of approximately 30,000 people, Majuro is home to the largest population of all of the RMI's 29 atolls and underwent extensive human modifications after American occupation during World War II. By contrast, Arno is home to fewer than 2,000 people and has remained relatively undisturbed. In June of 2016, I conducted benthic surveys at 25 sites along a gradient of human impacts across the two atolls. At each site at 10m depth, I measured percent cover of coral and algae genera and size-frequency of coral. I also utilized limited historical data to explore how reefs had recovered after a thermal stress event in 2014. In order to estimate human disturbance, I used the mean normalized difference vegetation index (NDVI) of the nearby coastline, which measures vegetation intensity. The coral and macroalgae composition of sites differed by atoll, mean NDVI, and wind and wave exposure, but not by sea surface temperature. The most degraded sites had low macroalgae cover and were dominated by turf algae, sponges, and cyanobacteria. One genus of macroalgae, Halimeda, was associated with sites that had low disturbance, while another, Hypnea, was correlated with higher disturbance. These results suggest that using macroalgae as an indicator of degradation may mask the influence of local human disturbance on reef community composition. Instead, it is important to consider identifying other indicator taxa and to measure coral and macroalgae cover to at least the genus level.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".