Hardship and the Granting of Zoning Variances: A New Test in Light of Rousseau v. Zoning Board of Appeals , 17 Neb. App. 469, 764 N.W.2d 130 (2009)
Bibliographic record
Abstract
Climate change is reshaping the way in which contaminants move through the global environment, in large part by changing the chemistry of the oceans and affecting the physiology, health, and feeding ecology of marine biota. Climate change-associated impacts on structure and function of marine food webs, with consequent changes in contaminant transport, fate, and effects, are likely to have significant repercussions to those human populations that rely on fisheries resources for food, recreation, or culture. Published studies on climate change-contaminant interactions with a focus on food web bioaccumulation were systematically reviewed to explore how climate change and ocean acidification may impact contaminant levels in marine food webs. We propose here a conceptual framework to illustrate the impacts of climate change on contaminant accumulation in marine food webs, as well as the downstream consequences for ecosystem goods and services. The potential impacts on social and economic security for coastal communities that depend on fisheries for food are discussed. Climate change-contaminant interactions may alter the bioaccumulation of two priority contaminant classes: the fat-soluble persistent organic pollutants (POPs), such as polychlorinated biphenyls (PCBs), as well as the protein-binding methylmercury (MeHg). These interactions include phenomena deemed to be either climate change dominant (i.e., climate change leads to an increase in contaminant exposure) or contaminant dominant (i.e., contamination leads to an increase in climate change susceptibility). We illustrate the pathways of climate change-contaminant interactions using case studies in the Northeastern Pacific Ocean. The important role of ecological and food web modeling to inform decision-making in managing ecological and human health risks of chemical pollutants contamination under climate change is also highlighted. Finally, we identify the need to develop integrated policies that manage the ecological and socioeconomic risk of greenhouse gases and marine pollutants.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".