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Record W2151500527 · doi:10.1890/06-0649

TUNDRA CO<sub>2</sub> FLUXES IN RESPONSE TO EXPERIMENTAL WARMING ACROSS LATITUDINAL AND MOISTURE GRADIENTS

2007· article· en· W2151500527 on OpenAlexaffabout
Steven F. Oberbauer, C. E. Tweedie, Jeff Welker, J. T. Fahnestock, Greg H. R. Henry, Patrick J. Webber, Robert D. Hollister, Marilyn D. Walker, Andrea Kuchy, Elizabeth Elmore, Gregory Starr

Bibliographic record

VenueEcological Monographs · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of British Columbia
FundersDivision of Arctic SciencesOffice of Polar Programs
KeywordsEcosystemEnvironmental scienceEcosystem respirationTundraGlobal warmingGrowing seasonClimate changeTerrestrial ecosystemAtmospheric sciencesEcologyPrimary productionBiology

Abstract

fetched live from OpenAlex

Climate warming is expected to differentially affect CO 2 exchange of the diverse ecosystems in the Arctic. Quantifying responses of CO 2 exchange to warming in these ecosystems will require coordinated experimentation using standard temperature manipulations and measurements. Here, we used the International Tundra Experiment (ITEX) standard warming treatment to determine CO 2 flux responses to growing‐season warming for ecosystems spanning natural temperature and moisture ranges across the Arctic biome. We used the four North American Arctic ITEX sites (Toolik Lake, Atqasuk, and Barrow [USA] and Alexandra Fiord [Canada]) that span 10° of latitude. At each site, we investigated the CO 2 responses to warming in both dry and wet or moist ecosystems. Net ecosystem CO 2 exchange (NEE), ecosystem respiration (ER), and gross ecosystem photosynthesis (GEP) were assessed using chamber techniques conducted over 24‐h periods sampled regularly throughout the summers of two years at all sites. At Toolik Lake, warming increased net CO 2 losses in both moist and dry ecosystems. In contrast, at Atqasuk and Barrow, warming increased net CO 2 uptake in wet ecosystems but increased losses from dry ecosystems. At Alexandra Fiord, warming improved net carbon uptake in the moist ecosystem in both years, but in the wet and dry ecosystems uptake increased in one year and decreased the other. Warming generally increased ER, with the largest increases in dry ecosystems. In wet ecosystems, high soil moisture limited increases in respiration relative to increases in photosynthesis. Warming generally increased GEP, with the notable exception of the Toolik Lake moist ecosystem, where warming unexpectedly decreased GEP &gt;25%. Overall, the respiration response determined the effect of warming on ecosystem CO 2 balance. Our results provide the first multiple‐site comparison of arctic tundra CO 2 flux responses to standard warming treatments across a large climate gradient. These results indicate that (1) dry tundra may be initially the most responsive ecosystems to climate warming by virtue of strong increases in ER, (2) moist and wet tundra responses are dampened by higher water tables and soil water contents, and (3) both GEP and ER are responsive to climate warming, but the magnitudes and directions are ecosystem‐dependent.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.292
Teacher spread0.259 · 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

Citations308
Published2007
Admission routes2
Has abstractyes

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