Nebraska Water and Energy Flux Measurement, Modeling, and Research Network (NEBFLUX)
Bibliographic record
Abstract
Surface energy and water vapor fluxes play a critical role in understanding the response of agro-ecosystems to changes in environmental and atmospheric parameters. These fluxes play a crucial role in exploring the dynamics of water and energy use efficiencies of these systems. Quantification of the fluxes is also necessary for assessing the impact of land use and management changes on water balances. Accomplishing these goals requires measurement of water vapor and energy exchanges between various vegetation surfaces and microclimates for long-enough periods to understand the behavior and dynamics involved with the flux transfer so that robust models can be developed to predict these processes under different scenarios. Networks of flux towers such as AMERIFLUX, FLUXNET, FLUXNET-CANADA, EUROFLUX, ASIAFLUX, and CAR-BOEUROPE have been collecting data on exchange processes between biosphere and atmosphere for multiple years across the globe to better understand the functioning of terrestrial ecosystems and their role in regional and/or continental and global carbon, water, and energy cycles, providing a unique service to the scientific community. Nonetheless, there is an imperative need for these kinds of networks to increase in number and intensity due to the great diversity among ecosystems and agro-ecosystems in species composition, physiological properties, physical structure, microclimatic and climatic conditions, and management practices. The Nebraska Water and Energy Flux Measurement, Modeling, and Research Network (NEBFLUX) is a comprehensive network that is designed to measure surface energy and water vapor fluxes, microclimatic variables, plant physiological parameters, soil water content, surface characteristics, and their interactions for various vegetation surfaces. The NEBFLUX is a network of micrometeorological tower sites that uses mainly Bowen ratio energy balance systems (BREBS) to measure surface water vapor and energy fluxes between terrestrial agro-ecosystems and microclimate. At present, ten BREBSs and one eddy covariance system are operating on a long-term and continuous basis for vegetation surfaces ranging from tilled and untilled irrigated and rainfed croplands, irrigated and rainfed grasslands, alfalfa, to Phragmites (Phragmites australis)-dominated cottonwood (Populus deltoides var. occidentalis) and willow stand (Willow salix) plant communities. The NEBFLUX project will provide good-quality flux and other extensive supportive data on plant physiology [leaf area index, stomatal resistance, within-canopy radiation parameters, productivity (yield and/or biomass), and plant height], soil characteristics, soil water content, and surface characteristics to the micrometeorology, water resources and agricultural engineering, and science community on broad spectrum of agro-ecosystems. The fundamental premise of the NEBFLUX project is to measure continuous and long-term (at least ten complete annual cycles for each surface) exchange of water vapor and energy fluxes. In addition to the scientific and research objectives, information dissemination to educate the general public and youth is another important objective and output of the network. This article describes the specific goals and objectives, basic principles, and operational characteristics of the NEBFLUX.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".