Biology subjects

Hunter, W. R.

Publications and source records attributed to Hunter, W. R..

4 recordsLinked to original sources

bioRxiv2026

Attenuation of climatic signals limits prediction of phytoplankton blooms in a temperate shelf sea

Phytoplankton blooms link climatic conditions to marine food webs and carbon cycling, yet relationships between climate forcing and bloom magnitude remain weak and inconsistent in shelf seas. Using a multi-decadal, high-frequency observational record from the western Irish Sea gyre, we investigated how climate variability influences nutrient dynamics and spring phytoplankton bloom development. Sea surface temperature, marine heatwave intensity and the North Atlantic Oscillation exhibited weak and inconsistent relationships with bloom intensity. However, climatic influences were more evident in nutrient dynamics, particularly the timing of seasonal nutrient drawdown, whereas the magnitude of nutrient utilisation was strongly constrained by winter nutrient inventories. Translation of nutrient drawdown into phytoplankton biomass showed marked attenuation: nitrate consumption explained little variability in bloom intensity, whereas silicate drawdown exhibited a moderate, non-deterministic association consistent with functional constraints on diatom growth and community structure. Our results reveal relationships between climate variability and ecosystem function weaken across successive ecosystem levels. While nutrient inventories provide strong constraints on nutrient use, additional ecological and stoichiometric processes influence how nutrient uptake is translated into phytoplankton biomass. Our findings suggest that weak climate-bloom relationships may arise from hierarchical ecological filtering and highlight the importance of biological constraints when assessing ecosystem responses to climate variability in shelf seas.

ecology↗

bioRxiv2026

Sensory variation and behavioural degeneracy: a framework for interpreting heterogeneity in the gut-brain axis

Gut microbiome differences are frequently interpreted as reflecting underlying biological differences between individuals. When outcomes are mediated by behaviour, however, this mapping may be fundamentally non-unique. This limits causal inference in gut-brain research, where microbiome differences in autism and depression are routinely attributed to intrinsic neurobiology despite highly variable, overlapping findings. I built a minimal agent-based model grounded in the known sensory variation across the autism spectrum. Dietary behaviour emerges from latent sensory traits, including sensory drive, predictability preference, and context sensitivity, through reinforcement learning and environmental interaction. This behaviour shapes gut microbiome composition. Behavioural variation organizes endogenously into a continuum of specialist, opportunist, and explorer strategies that maps onto the autism sensory spectrum. The system is fundamentally degenerate. Similar microbiome states arise from distinct behavioural pathways. Similar dietary patterns emerge from divergent latent traits. This many-to-one mapping reflects the structural interaction of behaviour, learning, and environmental variability, not stochasticity alone. Microbiome similarity therefore does not uniquely identify underlying cause. As such, the model provides a theoretical framework for interpreting heterogeneity in gut microbiome research, particularly in autism, and generalizes to any condition where behaviour mediates between neural processes and ecological outcomes.

systems biology↗

bioRxiv2022

Biological and synthetic surfactant exposure increase anti-microbial gene occurrence in a freshwater mixed microbial biofilm environment

Aquatic habitats are particularly susceptible to chemical pollution from domestic, agricultural, and industrial sources. Antimicrobials are commonly used in medical and industrial environments to reduce harmful bacteria and biofilms. This has led to the rapid increase in the prevalence of antimicrobial resistant (AMR) genes. Alternate remedies to fight pathogenic bacteria and biofilms are in development including synthetic and biological surfactants such as sodium dodecyl sulphate (SDS) and rhamnolipids respectively. In the aquatic environment these surfactants are present as pollutants with potential to affect biofilm formation and AMR gene occurrence; however, there is limited research showing the actual environmental impact of such exposure. We tested the effects of rhamnolipid and SDS on natural aquatic biofilms in a freshwater stream in Northern Ireland. We grew biofilms on contaminant exposure substrata deployed within the stream over four weeks, and then carried out shotgun sequencing to determine microbial community composition, through 16s rRNA analyses (64,678 classifiable reads identified), and AMR gene occurrence (81 instances of AMR genes over 9 AMR gene classes) through a metagenomic analysis. There were no significant changes in community composition within all systems; however, biofilm exposed to rhamnolipid had a greater number of unique taxa as compared to our SDS treatments and controls. AMR gene prevalence was higher in surfactant-treated biofilms, with biofilm exposed to rhamnolipids having the highest presence of AMR genes and classes compared to the control or SDS treatments, in which genes encoding for rifampin resistance were detected. Our results suggest that the presence of rhamnolipid, and to a lesser extent SDS, encourages an increase in the prevalence of AMR genes in biofilms produced in mixed use water bodies.

microbiology↗

bioRxiv2019

Using the Tea Bag Index to unravel how interactions between an antibiotic (Trimethoprim) and endocrine disruptor (17a-estradiol) affect aquatic microbial activity.

This study demonstrates that independent additive effects of two human pharmaceuticals, the antibiotic trimethoprim and the artificial estrogen 17a-Ethinylestradiol (EE2), inhibit plant litter decomposition by aquatic microorganisms. The constant release of pharmaceuticals, such as these, has the potential to affect aquatic microbial metabolism and alter biogeochemical cycling of carbon and nutrients. Here we advance the Tea Bag Index (TBI) for decomposition by using it in a series of contaminant exposure experiments testing how interactions between trimethoprim and EE2 affect aquatic microbial activity. The TBI is a citizen science tool used to test microbial activity by measuring the differential degradation of green and rooibos tea as proxies for respectively labile and recalcitrant litter decomposition. Exposure to either trimethoprim or EE2 decreased decomposition of green tea, suggesting additive effects upon microbial activity. Exposure to EE2 alone decreased rooibos tea decomposition. Consequently, trimethoprim and EE2 stabilized labile organic matter against microbial degradation and restricted decomposition. We propose that the method outlined could provide a powerful tool for testing the impacts of multiple interacting pollutants upon microbial activity, at a range of scales, across aquatic systems and over ecologically relevant time scales.

microbiology↗