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Modeling the effects of fire and climate change on carbon and nitrogen storage in lodgepole pine (<i>Pinus contorta</i>) stands

2008· article· en· W2113232720 on OpenAlexaboutno aff
Erica A. H. Smithwick, Michael G. Ryan, Daniel M. Kashian, William H. Romme, D. B. Tinker, Monica G. Turner

Bibliographic record

VenueGlobal Change Biology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersJoint Fire Science Program
KeywordsPinus contortaEnvironmental scienceClimate changeEcosystemEcologyDisturbance (geology)Primary productionAtmospheric sciencesCarbon sequestrationForestryProductivityForest ecologyAgronomyCarbon dioxideGeographyBiologyGeology

Abstract

fetched live from OpenAlex

Abstract The interaction between disturbance and climate change and resultant effects on ecosystem carbon (C) and nitrogen (N) fluxes are poorly understood. Here, we model (using CENTURY version 4.5) how climate change may affect C and N fluxes among mature and regenerating lodgepole pine ( Pinus contorta var. latifolia Engelm. ex S. Wats.) stands that vary in postfire tree density following stand‐replacing fire. Both young (postfire) and mature stands had elevated forest production and net N mineralization under future climate scenarios relative to current climate. Forest production increased 25% [Hadley (HAD)] to 36% [Canadian Climate Center (CCC)], compared with 2% under current climate, among stands that varied in stand age and postfire density. Net N mineralization increased under both climate scenarios, e.g., +19% to 37% (HAD) and +11% to 23% (CCC), with greatest increases for young stands with sparse tree regeneration. By 2100, total ecosystem carbon (live+dead+soils) in mature stands was higher than prefire levels, e.g., +16% to 19% (HAD) and +24% to 28% (CCC). For stands regenerating following fire in 1988, total C storage was 0–9% higher under the CCC climate model, but 5–6% lower under the HAD model and 20–37% lower under the Control. These patterns, which reflect variation in stand age, postfire tree density, and climate model, suggest that although there were strong positive responses of lodgepole pine productivity to future changes in climate, C flux over the next century will reflect complex relationships between climate, age structure, and disturbance‐recovery patterns of the landscape.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.231
Teacher spread0.213 · 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

Citations69
Published2008
Admission routes1
Has abstractyes

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