The eriophyid mite, Aceria sheldoni (Ewing), is widely distributed across citrus-producing regions of South Africa. Yet, it remains under-studied in terms of population dynamics and infestation thresholds, especially in citrus varieties other than Eureka lemons. Aceria sheldoni induces morphological abnormalities through disruption of meristematic and floral primordia development, likely mediated by feeding-associated hormonal dysregulation. This results in shoot distortion, blossom and fruit malformation with downstream impacts on canopy architecture, as well as yield potential and market quality. Current management relies mainly on symptom-based judgements and preventive acaricide applications in autumn. The population ecology of these mites remains poorly resolved due to methodological limitations. The species’ minute size, vermiform morphology, and cryptic location within tightly bunched bud scales renders direct detection challenging and time consuming. Practical, high-throughput detection methods are needed to support evidence-based decision-making. This study aims to 1) develop and validate a rapid, scalable extraction and staining protocol for reliable detection and quantification of A. sheldoni in a variety of citrus buds; 2) determine within-plant distribution patterns in trees; and 3) characterise seasonal population dynamics across major citrus growing regions in South Africa. Method development will be focused on refining bud dissection and extraction procedures to maximise mite recovery efficiency while maintaining processing speed. Multiple staining media will be evaluated to enhance contrast and visibility under brightfield microscopy. This will facilitate accurate enumeration of eriophyids within bud tissue. Validation includes comparison of recovery rates and repeatability across replicate samples. Following optimisation, the protocol will be applied to nursery trees to determine within-plant distribution and to commercial orchards in different climatic areas within South Africa. Field sampling will consist of shoot collection from randomly selected trees across multiple seasons. Data will be analysed to assess the spatial distribution within plants, regional incidence, cultivar-associated differences, and temporal population fluctuations. The development of a validated, scalable detection protocol will provide the foundation for the establishment of infestation thresholds aligning intervention timing with biologically relevant population peaks for each area. This improved quantification of A. sheldoni populations will enable a transition from symptom-based inference to evidence-based, data-driven management, strengthening integrated pest management frameworks and refining acaricide timing within the South African citrus industry.