Bioclimatic Emission Amplification: A New Paradigm in Climate Biosphere Feedback Dynamics

Authors

  • Naser Naser

    School of Logistics and Maritime Studies, Faculty of Business and Logistics, Bahrain Polytechnic, Isa Town P.O. Box 33349, Kingdom of Bahrain
  • Nahed Bahman

    School of Logistics and Maritime Studies, Faculty of Business and Logistics, Bahrain Polytechnic, Isa Town P.O. Box 33349, Kingdom of Bahrain
  • Mahmood Shaker

    Business Analytics Program, College of Business Administration, University of Bahrain, Sakhir P.O. Box 32038, Kingdom of Bahrain

DOI:

https://doi.org/10.30564/jees.v7i8.10916
Received: 7 July 2025 | Revised: 28 July 2025 | Accepted: 31 July 2025 | Published Online: 14 August 2025

Abstract

This study introduces the Bioclimatic Emission Amplification Theory (BEAT), a novel framework for detecting and forecasting how terrestrial ecosystems, particularly the Amazon Basin, transition from being carbon sinks to becoming carbon sources under compounded bioclimatic stress. BEAT synthesizes satellite-derived data from 2001 to 2022 and integrates temperature anomalies, vapor pressure deficit (VPD), fire activity, and vegetation degradation into a Compound Stress Index (CSI). Methodologically, the study applies piecewise regression, changepoint analysis, and early warning signal (EWS) metrics, including rolling variance and lag-1 autocorrelation, to identify nonlinear emission tipping points and ecological resilience loss. Machine learning models such as XGBoost and SHAP were employed to evaluate the predictive relevance of CSI components and enhance model interpretability. Results reveal a critical CSI threshold (≥ 0.6), beyond which Net Ecosystem Exchange (NEE) exhibits abrupt positive anomalies, indicating carbon emission amplification. EWS metrics significantly increased prior to emission spikes, validating BEAT’s predictive capacity for ecological destabilization. In addition, spatial clustering and time-lagged correlation analysis confirmed the alignment between compound stress hotspots and emission anomalies, and when compared to traditional Earth System Models (ESMs), BEAT uniquely captures synergistic stress interactions and nonlinearity. The findings underscore BEAT’s potential to improve early warning systems, REDD+ monitoring frameworks, and climate adaptation planning. Its scalable design enables application across vulnerable biomes globally and offers a transformative tool for anticipating biosphere-climate tipping points and informing proactive ecosystem governance.

Keywords:

Climate Change; Machine Learning; Bioclimatic; Feedback Loops; Greenhouse Gas Emissions; Environment Sustainability

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How to Cite

Naser, N., Bahman, N., & Shaker, M. (2025). Bioclimatic Emission Amplification: A New Paradigm in Climate Biosphere Feedback Dynamics. Journal of Environmental & Earth Sciences, 7(8), 51–69. https://doi.org/10.30564/jees.v7i8.10916

Issue

Vol. 7 , Iss. 8 (August 2025): In Progress

Article Type

Article

License

Copyright © 2025 Naser Naser, Nahed Bahman, Mahmood Shaker

Creative Commons License

This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.

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