Anthropogenic, Direct Pressures on Coastal Wetlands
Bibliographic record
Abstract
:Coastal wetlands, such as saltmarshes and mangroves, that fringe transitional waters deliver important ecosystem services that support human development. Coastal wetlands are complex social-ecological systems that occur at all latitudes, from polar regions to the tropics. This overview covers wetlands in five continents. The wetlands are of varying size, catchment size, human population and human development. Economic sectors and activities in and around the coastal wetlands and their catchments exert multiple pressures that affect the state of the wetlands and the delivery of valuable ecosystem services. All the coastal wetlands were found to be affected in some ways, irrespective of the conservation status. The main economic sectors were identified as agriculture, animal rearing including aquaculture, fisheries, tourism, urbanisation, shipping, industrial development and mining. Specific human activities include land reclamation, damming, draining and water extraction, construction of ponds for aquaculture and salt extraction, construction of ports and marinas, dredging, discharge of effluents from urban and industrial areas and logging, in the case of mangroves. The main pressures were loss of wetland habitat, changes in connectivity affecting hydrology and sedimentology, as well as contamination and pollution. These pressures lead to changes in environmental state, such as erosion, subsidence and hypoxia that threaten the sustainabilty of the wetlands. There are also changes in the state of the ecology, such as loss of saltmarsh plants and seagrasses, and mangrove trees, in tropical wetlands. These changes in the structure and function of the wetland ecosystems affect the delivery of important ecosystem services that are often underestimated. The loss of ecosystem services impacts human welfare as well as the regulation of climate change by coastal wetlands. These impacts are likely to be further aggravated by climate change..
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".