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CO<sub>2</sub> exchange in three Canadian High Arctic ecosystems: response to long‐term experimental warming

2004· article· en· W2160181974 on OpenAlexafffundabout
J. M. Welker, J. T. Fahnestock, Greg H. R. Henry, Kevin W. O'Dea, Rodney A. Chimner

Bibliographic record

VenueGlobal Change Biology · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of British Columbia
FundersOffice of Polar ProgramsNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsTundraEcosystemEnvironmental scienceGrowing seasonEcosystem respirationArcticCarbon dioxideSink (geography)Carbon sinkAtmospheric sciencesTerrestrial ecosystemDry seasonPrimary productionEcologyGeographyBiologyGeology

Abstract

fetched live from OpenAlex

Abstract Carbon dioxide exchange, soil C and N, leaf mineral nutrition and leaf carbon isotope discrimination (LCID‐Δ) were measured in three High Arctic tundra ecosystems over 2 years under ambient and long‐term (9 years) warmed (∼2°C) conditions. These ecosystems are located at Alexandra Fiord (79°N) on Ellesmere Island, Nunavut, and span a soil water gradient; dry, mesic, and wet tundra. Growing season CO2 fluxes (i.e., net ecosystem exchange (NEE), gross ecosystem photosynthesis (GEP), and ecosystem respiration (Re)) were measured using an infrared gas analyzer and winter C losses were estimated by chemical absorption. All three tundra ecosystems lost CO2 to the atmosphere during the winter, ranging from 7 to 12 g CO2‐C m−2 season−1 being highest in the wet tundra. The period during the growing season when mesic tundra switch from being a CO2 source to a CO2 sink was increased by 2 weeks because of warming and increases in GEP. Warming during the summer stimulated dry tundra GEP more than Re and thus, NEE was consistently greater under warmed as opposed to ambient temperatures. In mesic tundra, warming stimulated GEP with no effect on Re increasing NEE by ∼10%, especially in the first half of the summer. During the ∼70 days growing season (mid‐June–mid‐August), the dry and wet tundra ecosystems were net CO2‐C sinks (30 and 67 g C m−2 season−1, respectively) and the mesic ecosystem was a net C source (58 g C m−2 season−1) to the atmosphere under ambient temperature conditions, due in part to unusual glacier melt water flooding that occurred in the mesic tundra. Experimental warming during the growing season increased net C uptake by ∼12% in dry tundra, but reduced net C uptake by ∼20% in wet tundra primarily because of greater rates of Re as opposed to lower rates of GEP. Mesic tundra responded to long‐term warming with ∼30% increase in GEP with almost no change in Re reducing this tundra type to a slight C source (17 g C m−2 season−1). Warming caused LCID of Dryas integrafolia plants to be higher in dry tundra and lower in Salix arctic plants in mesic and wet tundra. Our findings indicate that: (1) High Arctic ecosystems, which occur in similar mesoclimates, have different net CO2 exchange rates with the atmosphere; (2) long‐term warming can increase the net CO2 exchange of High Arctic tundra by stimulating GEP, but it can also reduce net CO2 exchange in some tundra types during the summer by stimulating Re to a greater degree than stimulating GEP; (3) after 9 years of experimental warming, increases in soil carbon and nitrogen are detectable, in part, because of increases in deciduous shrub cover, biomass, and leaf litter inputs; (4) dry tundra increases in GEP, in response to long‐term warming, is reflected in D. integrifolia LCID; and (5) the differential carbon exchange responses of dry, mesic, and wet tundra to similar warming magnitudes appear to depend, in part, on the hydrologic (soil water) conditions. Annual net ecosystem CO2‐C exchange rates ranged from losses of 64 g C m−2 yr−1 to gains of 55 g C m−2 yr−1. These magnitudes of positive NEE are close to the estimates of NPP for these tundra types in Alexandra Fiord and in other High Arctic locations based on destructive harvests.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.422

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.275
Teacher spread0.227 · 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".

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Citations231
Published2004
Admission routes3
Has abstractyes

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