Integrating Hierarchical Bayesian Models and Hydrodynamic Simulations for eDNA Dynamics in Adaptive Ecosystem Management under Global Change
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2025
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| _version_ | 1866901105585160192 |
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| author | Shibah, Sami Rashid Mohammed |
| author_facet | Shibah, Sami Rashid Mohammed |
| contents | <p>Environmental DNA (eDNA) methodologies—encompassing metabarcoding, metagenomics, metatranscriptomics, and digital PCR—herald a paradigm shift in non-invasive biodiversity surveillance amid escalating global stressors like climate change. This conceptual framework synthesizes advanced multi-dimensional mathematical modeling, Bayesian hierarchical inference, rigorous sensitivity analyses, and Python-driven hydrodynamic simulations to translate eDNA signals into falsifiable, actionable strategies for ecosystem resilience. We derive detailed equations for eDNA fate, transport, decay, and detection, incorporating power-law removal kinetics and inhibition effects, validated against empirical parameters (e.g., decay half-lives of 4--5 hours from riverine studies). Reproducible simulations leverage datasets from UNESCO marine expeditions and catchment-scale surveys, quantifying uncertainties via credible intervals and adhering to Popperian falsifiability criteria. Bolstered by quantitative statistics, Bayesian evidence ratios, and integrations with remote sensing, this self-contained framework addresses standardization gaps, stressor-induced microbial shifts, and policy translation, providing a blueprint for scalable conservation in aquatic, terrestrial, and polar realms facing existential threats.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18057500 |
| institution | Zenodo |
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| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Integrating Hierarchical Bayesian Models and Hydrodynamic Simulations for eDNA Dynamics in Adaptive Ecosystem Management under Global Change Shibah, Sami Rashid Mohammed <p>Environmental DNA (eDNA) methodologies—encompassing metabarcoding, metagenomics, metatranscriptomics, and digital PCR—herald a paradigm shift in non-invasive biodiversity surveillance amid escalating global stressors like climate change. This conceptual framework synthesizes advanced multi-dimensional mathematical modeling, Bayesian hierarchical inference, rigorous sensitivity analyses, and Python-driven hydrodynamic simulations to translate eDNA signals into falsifiable, actionable strategies for ecosystem resilience. We derive detailed equations for eDNA fate, transport, decay, and detection, incorporating power-law removal kinetics and inhibition effects, validated against empirical parameters (e.g., decay half-lives of 4--5 hours from riverine studies). Reproducible simulations leverage datasets from UNESCO marine expeditions and catchment-scale surveys, quantifying uncertainties via credible intervals and adhering to Popperian falsifiability criteria. Bolstered by quantitative statistics, Bayesian evidence ratios, and integrations with remote sensing, this self-contained framework addresses standardization gaps, stressor-induced microbial shifts, and policy translation, providing a blueprint for scalable conservation in aquatic, terrestrial, and polar realms facing existential threats.</p> |
| title | Integrating Hierarchical Bayesian Models and Hydrodynamic Simulations for eDNA Dynamics in Adaptive Ecosystem Management under Global Change |
| url | https://doi.org/10.5281/zenodo.18057500 |