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Record W2022353014 · doi:10.1890/05-1906

USING NOCTURNAL COLD AIR DRAINAGE FLOW TO MONITOR ECOSYSTEM PROCESSES IN COMPLEX TERRAIN

2007· article· en· W2022353014 on OpenAlexaff
Thomas G. Pypker, M. H. Unsworth, Alan C Mix, W D Rugh, Troy W. Ocheltree, K. P. Alstad, B. J. Bond

Bibliographic record

VenueEcological Applications · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of Victoria
FundersDivision of Environmental Biology
KeywordsEcosystemEnvironmental scienceEddy covarianceDrainageHydrology (agriculture)Drainage basinWatershedAtmospheric sciencesEcologyGeographyGeologyBiology

Abstract

fetched live from OpenAlex

This paper presents initial investigations of a new approach to monitor ecosystem processes in complex terrain on large scales. Metabolic processes in mountainous ecosystems are poorly represented in current ecosystem monitoring campaigns because the methods used for monitoring metabolism at the ecosystem scale (e.g., eddy covariance) require flat study sites. Our goal was to investigate the potential for using nocturnal down-valley winds (cold air drainage) for monitoring ecosystem processes in mountainous terrain from two perspectives: measurements of the isotopic composition of ecosystem-respired CO2 (delta13C(ER)) and estimates of fluxes of CO2 transported in the drainage flow. To test if this approach is plausible, we monitored the wind patterns, CO2 concentrations, and the carbon isotopic composition of the air as it exited the base of a young (approximately 40 yr-old) and an old (>450 yr-old) steeply sided Douglas-fir watershed. Nocturnal cold air drainage within these watersheds was strong, deep, and occurred on more than 80% of summer nights. The depth of cold air drainage rapidly increased to tower height or greater when the net radiation at the top of the tower approached zero. The carbon isotope composition of CO2 in the drainage system holds promise as an indicator of variation in basin-scale physiological processes. Although there was little vertical variation in CO2 concentration at any point in time, we found that the range of CO2 concentration over a single evening was sufficient to estimate delta 13C(ER) from Keeling plot analyses. The seasonal variation in delta 13C(ER) followed expected trends: during the summer dry season delta 13C(ER) became less negative (more enriched in 13C), but once rain returned in the fall, delta 13C(ER) decreased. However, we found no correlation between recent weather (e.g., vapor pressure deficit) and delta 13C(ER) either concurrently or with up to a one-week lag. Preliminary estimates suggest that the nocturnal CO2 flux advecting past the 28-m tower is a rather small fraction (<20%) of the watershed-scale respiration. This study demonstrates that monitoring the isotopic composition and CO2 concentration of cold air drainage at the base of a watershed provides a new tool for quantifying ecosystem metabolism in mountainous ecosystems on the basin scale.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.522
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.261
Teacher spread0.239 · 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 teacher head, 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

Citations42
Published2007
Admission routes1
Has abstractyes

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