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Record W2113089691 · doi:10.5194/bg-12-1151-2015

The influence of soils on heterotrophic respiration exerts a strong control on net ecosystem productivity in seasonally dry Amazonian forests

2015· article· en· W2113089691 on OpenAlexafffundabout
Joe R. Melton, R. K. Shrestha, Vivek K. Arora

Bibliographic record

VenueBiogeosciences · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnvironmental sciencePrimary productionSoil waterPlant litterSoil respirationEcosystemSeasonalityDry seasonCarbon cycleGrowing seasonTerrestrial ecosystemVegetation (pathology)Hydrology (agriculture)Atmospheric sciencesEcologySoil scienceBiology

Abstract

fetched live from OpenAlex

Abstract. Net ecosystem productivity of carbon (NEP) in seasonally dry forests of the Amazon varies greatly between sites with similar precipitation patterns. Correctly modeling the NEP seasonality with terrestrial ecosystem models has proven difficult. Previous modelling studies have mostly advocated for incorporating processes that act to reduce water stress on gross primary productivity (GPP) during the dry season, such as deep soils and roots, plant-mediated hydraulic redistribution of soil moisture, and increased dry season leaf litter generation which reduces leaf age and thus increases photosynthetic capacity. Recent observations, however, indicate that seasonality in heterotrophic respiration also contributes to the observed seasonal cycle of NEP. Here, we use the dynamic vegetation model CLASS-CTEM (Canadian Land Surface Scheme–Canadian Terrestrial Ecosystem Model) – without deep soils or roots, hydraulic redistribution of soil moisture, or increased dry season litter generation – at two Large-Scale Biosphere–Atmosphere Experiment (LBA) sites (Tapajós km 83 and Jarú Reserve). These LBA sites exhibit opposite seasonal NEP cycles despite reasonably similar meteorological conditions. Our simulations are able to reproduce the observed NEP seasonality at both sites. Simulated GPP, heterotrophic respiration, latent and sensible heat fluxes, litter fall rate, soil moisture and temperature, and basic vegetation state are also compared with available observation-based estimates which provide confidence that overall the model behaves realistically at the two sites. Our results indicate that representing the effect of soil moisture on heterotrophic respiration in terms of soil matric potential and constraining heterotrophic respiration when absolute soil matric potential is both low (wetter soils) and high (drier soils), with optimum conditions in between, allows %appropriately representing the influence of soil texture and depth, %through soil moisture, on seasonal patterns of GPP and, especially, % heterotrophic respiration is important to correctly simulate NEP seasonality.

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)0.001
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 score0.238
Threshold uncertainty score0.763

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.218
Teacher spread0.205 · 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

Citations34
Published2015
Admission routes3
Has abstractyes

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