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Record W7117366357 · doi:10.1016/j.rsase.2025.101847

Spatiotemporal dynamics of carbon, water, and energy balance in Bangladesh using multi-source remote sensing and climate data

2025· article· en· W7117366357 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRemote Sensing Applications Society and Environment · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of SaskatchewanMcGill UniversityUniversity of Toronto
FundersUniversity of TorontoMcMaster UniversityNational Aeronautics and Space Administration
KeywordsPrimary productionEnergy balanceEvapotranspirationPhotosynthetically active radiationEcosystemPrecipitationEcosystem respirationCarbon cycleRadiative transfer

Abstract

fetched live from OpenAlex

Exploring the complex interactions between climate variables and ecosystem processes is crucial for understanding long-term environmental changes. This study examines the spatiotemporal dynamics of carbon, water and energy fluxes and their impacts on ecosystem processes in Bangladesh from 2005 to 2022 utilizing multi-source remote sensing and ground-based meteorological data. Carbon dynamics are estimated through gross primary productivity (GPP), net primary production (NPP), and ecosystem respiration (RE). Water and energy balances are derived from evapotranspiration (ET), water use efficiency (WUE), net radiation (Rn), and latent heat (LE). Our estimates indicate that GPP varied from 2351.29 g C m -2 y -1 in 2009 to 2178.45 g C m -2 y -1 in 2020, while NPP ranged from 1248.13 g C m -2 y -1 in 2012 to 929.46 g C m -2 y -1 in 2020, reflecting temporal variations in photosynthetic efficiency and carbon storage. The ratio of LE/Rn was found to vary from 0.72 to 1.01, with an average of 83%, indicating that a significant portion of the radiative energy was transferred to the atmosphere as turbulent flux. Validation of LUE-based GPP compared to FLUXCOM-GPP showed a moderate correlation (R 2 = 0.61, p < 0.005), supporting the reliability of the estimates. We also conducted multivariate regression analysis to assess the relationships between climate variables and carbon, water, and energy balance. The results indicate that photosynthetically active radiation (PAR) is the primary and dominant driver of GPP (R 2 = 0.97), while temperature and precipitation are key factors significantly influencing carbon uptake. This study presents a comprehensive, integrated assessment of carbon, water, and energy fluxes at the national scale across Bangladesh, emphasizing the crucial role of climate variables in shaping these fluxes and offering valuable insights for climate-resilient land management and sustainable carbon strategies in monsoon-dominated regions. • Agricultural ecosystems dominate terrestrial ecosystem productivity. • Evergreen forests exhibit stable carbon uptake, while deciduous forests fluctuate. • Gross carbon uptake is highly regulated by photosynthetically active radiation. • Total carbon uptake decreased from 1254 MtCO 2 e in 2005 to 1240 MtCO 2 e in 2022. • Energy, water, and carbon flux variations emphasize climate resilience strategies.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.972
Threshold uncertainty score0.729

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 science0.0000.001
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 head0.012
GPT teacher head0.219
Teacher spread0.207 · 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