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Record W2029039279 · doi:10.5194/bg-7-585-2010

Dynamics and distribution of natural and human-caused hypoxia

2010· article· en· W2029039279 on OpenAlexaff
Nancy N. Rabalais, Robert J. Díaz, Lisa A. Levin, R. Eugene Turner, Denis Gilbert, J. Zhang

Bibliographic record

VenueBiogeosciences · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsFisheries and Oceans Canada
FundersCenter for Sponsored Coastal Ocean ResearchNational Oceanic and Atmospheric AdministrationTampa Bay Estuary Program
KeywordsHypoxia (environmental)Environmental scienceBottom waterEutrophicationPopulationTotal organic carbonUpwellingAnoxic watersEcologyNutrientOxygenOceanographyBiologyGeologyChemistry

Abstract

fetched live from OpenAlex

Abstract. Water masses can become undersaturated with oxygen when natural processes alone or in combination with anthropogenic processes produce enough organic carbon that is aerobically decomposed faster than the rate of oxygen re-aeration. The dominant natural processes usually involved are photosynthetic carbon production and microbial respiration. The re-supply rate is indirectly related to its isolation from the surface layer. Hypoxic water masses (<2 mg L−1, or approximately 30% saturation) can form, therefore, under "natural" conditions, and are more likely to occur in marine systems when the water residence time is extended, water exchange and ventilation are minimal, stratification occurs, and where carbon production and export to the bottom layer are relatively high. Hypoxia has occurred through geological time and naturally occurs in oxygen minimum zones, deep basins, eastern boundary upwelling systems, and fjords. Hypoxia development and continuation in many areas of the world's coastal ocean is accelerated by human activities, especially where nutrient loading increased in the Anthropocene. This higher loading set in motion a cascading set of events related to eutrophication. The formation of hypoxic areas has been exacerbated by any combination of interactions that increase primary production and accumulation of organic carbon leading to increased respiratory demand for oxygen below a seasonal or permanent pycnocline. Nutrient loading is likely to increase further as population growth and resource intensification rises, especially with increased dependency on crops using fertilizers, burning of fossil fuels, urbanization, and waste water generation. It is likely that the occurrence and persistence of hypoxia will be even more widespread and have more impacts than presently observed. Global climate change will further complicate the causative factors in both natural and human-caused hypoxia. The likelihood of strengthened stratification alone, from increased surface water temperature as the global climate warms, is sufficient to worsen hypoxia where it currently exists and facilitate its formation in additional waters. Increased precipitation that increases freshwater discharge and flux of nutrients will result in increased primary production in the receiving waters up to a point. The interplay of increased nutrients and stratification where they occur will aggravate and accelerate hypoxia. Changes in wind fields may expand oxygen minimum zones onto more continental shelf areas. On the other hand, not all regions will experience increased precipitation, some oceanic water temperatures may decrease as currents shift, and frequency and severity of tropical storms may increase and temporarily disrupt hypoxia more often. The consequences of global warming and climate change are effectively uncontrollable at least in the near term. On the other hand, the consequences of eutrophication-induced hypoxia can be reversed if long-term, broad-scale, and persistent efforts to reduce substantial nutrient loads are developed and implemented. In the face of globally expanding hypoxia, there is a need for water and resource managers to act now to reduce nutrient loads to maintain, at least, the current status.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.007
GPT teacher head0.202
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1,239
Published2010
Admission routes1
Has abstractyes

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