Quantifying Climate-Induced Socio-Acoustic Communication Failure in Apis ceranaThrough Sentinel-3 and Integrating Quantum Genomic Tautomerization, Audio-MAE Transformers, and Poincare Hyperbolic Neural Networks Across Geoclimatic Zones

Technical Summary: Quantifying Climate-Induced Socio-Acoustic Communication Failure in Apis cerana

Problem Statement
The paper addresses the critical gap in understanding how macroclimatic warming disrupts the social organization of pollinators, specifically the indigenous honeybee Apis cerana. While prior research has established links between temperature stress and individual insect physiology or population declines, there is limited mechanistic understanding of how thermal stress degrades intra-specific communication, information fidelity, and collective decision-making (quorum sensing). The study posits that climate-induced breakdown is not merely a demographic shift but a multi-scale failure of information processing, ranging from quantum-level genomic instability to colony-level acoustic communication collapse. The author argues that existing ecological models often rely on inadequate Euclidean geometries to represent hierarchical signal divergence and lack a unified framework connecting molecular tautomerization to bio-acoustic diagnostics.

Methodology
The study employs a highly interdisciplinary framework integrating remote sensing, quantum chemistry, self-supervised deep learning, and non-Euclidean geometry.

• Data Acquisition and Harmonization:

  • Biological Data: 90 Apis cerana colonies were monitored across three distinct geoclimatic zones in Bangladesh (Sundarbans Coastal Mangroves, Chittagong Hill Tracts, and Rajshahi Barind Tract) over 24 months (March 2024–February 2026).
  • Audio: Continuous recording yielded 10,800 hours of audio (1,296,000 10-second snippets) at 44.1 kHz/24-bit depth.
  • Environmental Data: Satellite and reanalysis data (Sentinel-3 LST, MODIS NDVI, ERA5-Land, CHIRPS) were harmonized using Ordinary Kriging on a 15-minute grid. Historical thermal trends (2002–2026) were reconstructed via ridge regression calibration between MODIS and Sentinel-3.
  • Ground Truthing: A "Composite Biological Stress Score" (CBSS) was derived from multi-omic assays every two weeks, measuring Phenoloxidase (PO) activity, Malondialdehyde (MDA), Deformed Wing Virus (DWV) loads, Vitellogenin expression, and brood area.

• Signal Processing and Quantum Modeling:

  • Denoising: Raw audio underwent Symlet-8 Discrete Wavelet Transform (DWT) with Stein's Unbiased Risk Estimate (SURE) soft thresholding, achieving a +18.4 dB Signal-to-Noise Ratio (SNR) improvement. This isolated worker wing-beat frequencies (230–270 Hz), queen piping (400–500 Hz), and thermal stress hissing (1–5 kHz).
  • Quantum Mechanics: Hybrid Quantum Mechanics/Molecular Mechanics (QM/MM) simulations (using $\omega$B97X-D/6-311++G(d,p) and Ring-Polymer Molecular Dynamics) modeled temperature-dependent tautomeric proton transfer in DNA base pairs to quantify mutation risks.

• Machine Learning Architecture:

  • Audio-MAE: An Audio Masked Autoencoder was pre-trained on 80% randomly masked log-Mel spectrogram patches (128 Mel bins, 862 time steps) using a 12-layer Vision Transformer (ViT) encoder.
  • Fine-Tuning: The model was fine-tuned as an Audio Spectrogram Transformer (AST) to classify colony stress states (Healthy, Transitional, Collapse).
  • Non-Euclidean Embedding: 768-dimensional AST features were projected onto a 2D Poincaré disk (hyperbolic space) using Riemannian Adam optimization to model hierarchical communication drift.

• Validation Protocol:

  • Strict colony-level data partitioning was enforced: 60% training (54 colonies), 20% validation (18 colonies), and 20% testing (18 colonies).
  • 5-Fold Grouped Stratified Cross-Validation was used to prevent data leakage.
  • Explainable AI (SHAP) and partial dependence plots were used to interpret feature importance.

Key Results

• Thermal and Genomic Impact: A +1.85°C warming trend was observed over the 24-year period. QM/MM simulations revealed that rising temperatures (30°C to 45°C) reduced the activation energy for DNA proton transfer from 14.2 to 9.8 kcal/mol, accelerating tautomeric shift rates by 3.4-fold.
• Physiological Collapse: Colonies in the "Collapse" state (CBSS > 0.70) exhibited a 45.2 to 8.1 mU/mg drop in PO activity, a 92% reduction in Vitellogenin, and a DWV load increase from 2.1 to 9.2 log10 copies/bee.
• Acoustic and Information Degradation:
  • Drift Velocity: The drift velocity of communication patterns in the Poincaré disk accelerated from a baseline of 0.09 units/year (2002–2012) to 0.38 units/year (2013–2026).
  • Fidelity and Latency: Intergenerational transmission fidelity ($F$) dropped from 0.89 to 0.12. Quorum sensing response latency ($\tau_{quorum}$) increased by a factor of 11.6x, rising from 4.2 seconds to 48.6 seconds under severe stress.
  • Entropy: Shannon acoustic entropy increased from 3.2 to 6.8 bits (noting the abstract reports a baseline of 3.02 bit), indicating a shift toward structural chaos.
• Model Performance: The fine-tuned Audio Spectrogram Transformer (AST) achieved an AUC-ROC of 0.968, PR-AUC of 0.954, and a macro F1-Score of 0.921 on the independent test set. A stacked ensemble model (AST + ResNet + XGBoost) achieved an AUC-ROC of 0.985, PR-AUC of 0.972, and a macro F1-Score of 0.962. SHAP analysis identified spectral entropy (0.42) and transmission fidelity (0.38) as the most critical features.
• Thermodynamics: The metabolic temperature coefficient ($Q_{10}$) increased by 2.09x (from 2.35 to 4.85), while thermodynamic efficiency ($\eta_{thermo}$) reduced by 2.6x (from 15% to 2.5%) as energy was diverted to thermoregulation rather than foraging or communication.

Significance and Claims
The paper claims to establish a novel "bio-acoustic and multi-omic paradigm" that bridges the gap between quantum-level genomic instability and colony-level social collapse. Its primary contributions are:

1. Mechanistic Linkage: It provides the first theoretical and empirical link showing how macroclimatic warming drives quantum tautomeric shifts in DNA, which cascades into immunosuppression and communication failure.
2. Methodological Innovation: It introduces the use of Poincaré hyperbolic geometry to quantify "cultural evolutionary drift" in insect communication, arguing that non-Euclidean spaces better capture the hierarchical nature of social signals than Euclidean models.
3. Diagnostic Framework: It validates a non-invasive, self-supervised learning approach (Audio-MAE) for early detection of colony stress, demonstrating that acoustic signatures can serve as sensitive sentinels for ecosystem health.
4. Synergistic Stressors: The study highlights the non-linear, synergistic interaction between thermal stress and pathogen loads (specifically DWV), showing that combined stressors accelerate colony failure more than either factor alone.

The author concludes that this framework offers a practical tool for precision agriculture and ecosystem management, enabling real-time surveillance of pollinator resilience against climate change. They emphasize that the observed breakdown in information processing represents a "critical dialect threshold" beyond which social organization becomes non-viable.