%0 Journal Article
%T Detecting Honey Bee Colony Decline before Collapse: A Horizon Review of Sensors, Molecular Biomarkers, Microbiome Signatures, and Decision Support
%A Emily Johnson
%A Robert Smith
%A Laura Brown
%A Kevin Miller
%J Entomology and Applied Science Letters
%@ 2349-2864
%D 2026
%V 13
%N 1
%R 10.51847/HA7Nj4i79u
%P 14-23
%X Honey-bee colonies can maintain apparently normal activity while interacting nutritional, parasitic, pathogenic, environmental, and management pressures progressively weaken the collective functions that sustain brood care, thermoregulation, defence, and resource acquisition. This buffering capacity makes early detection scientifically valuable but diagnostically difficult: many measurable deviations are nonspecific, and most candidate signals have not been shown prospectively to predict a defined colony-failure outcome with actionable lead time. This Original Horizon Review critically integrates continuous acoustic, thermal, weight, and behavioural sensing with molecular and physiological biomarkers, microbiome and pathogen signatures, and emerging data-fusion approaches. The analysis compares what each evidence class measures, the biological scale at which it operates, the contexts that alter its meaning, and the validation required before it can support management. The strongest defensible synthesis is that early warning is most plausible as longitudinal estimation of a latent colony state from complementary, biologically interpreted signals rather than as detection of a universal collapse marker. Sensor anomalies may identify departures from expected colony trajectories, whereas molecular and microbial measurements may help explain whether those departures reflect stress, adaptation, infection, resource limitation, or normal seasonal change. However, association is not prognosis, multimodal integration is not inherently interpretable, and earlier recognition cannot improve colony outcomes unless it activates a feasible and effective response. Progress therefore depends on prospective outcome-labelled cohorts, age- and context-standardized biological sampling, transparent models that preserve links to colony processes, and decision pathways evaluated for false alarms, timeliness, practicality, and outcome benefit.
%U https://easletters.com/article/detecting-honey-bee-colony-decline-before-collapse-a-horizon-review-of-sensors-molecular-biomarker-mhvzncvia6113xc