Confronting Physical, Chemical and Temporal Biases in Experimental Algal Biology

Selective bias in algal research often leads to proposals of what are often unreliable causal relationships. Systematic errors mainly arise from ignoring chemical and physical environmental changes along with increased algal biomass during cultures. This paper examines three interacting bias dimensions using hypothetical cultures and literature examples. Selective bias in choosing basic parameters to measure cell properties, such as using chlorophyll as a biomass proxy, or over-reliance on genomics or proteomics without integrating physiological processes can lead to misinterpretation of cellular processes. Temporal selective bias emerges from sampling windows that ignore phased physiological demands, including marked daytime changes in photosynthesis and molecular signatures even under constant light. Physical bias arises from poorly controlled experimental conditions such as unstandardized hydrodynamics, altering diffusion boundary layers, gas/nutrient delivery and self-shading. Chemical bias stems from uncontrolled carbonate chemistry (pH, pCO2 and dissolved inorganic carbon) and unstable nutrient concentrations. Notably, while changes in carbonate chemistry may leave photosynthetic rates seemingly unchanged due to molecular acclimation (e.g., CO2-concentrating mechanisms), this often masks significant shifts in enzymatic activities, such as that of carbonic anhydrase. Crucially, these biases form reinforcing feedback loops: physical disturbance alters chemical availability, altering temporal physiological states, which then modifies molecular responses. By analyzing this multidimensional interplay, this paper provides essential guidance for designing robust experiments, helping researchers avoid the pitfall of “perfectly measured, wholly wrong” conclusions.