ALAN intensity immune system
Description
The dataset comprises raw and derived data obtained from experimental exposures of the intertidal isopod Tylos spinulosus to a gradient of artificial light at night (ALAN). Individuals were maintained under five nocturnal light treatments (0, 5, 20, 40 and 60 lux) using a single artificial light source. Haemolymph was extracted from each individual at the end of the exposure period. Due to volume limitations inherent to haemolymph extraction in this species, haemocyte counts were obtained only from samples in which sufficient haemolymph volume was available, with priority given to the execution of bacteriolytic challenges. For those samples, haemocyte concentrations were quantified and standardised as cell concentrations per unit volume of haemolymph. These values represent basal cellular immune status under each light treatment. From the haemolymph of each sampled individual, two independent ex vivo bacterial challenges were conducted using Staphylococcus aureus and Bacillus subtilis. Bacterial growth was quantified spectrophotometrically, providing time-resolved optical density measurements that reflect the bacteriolytic capacity of the haemolymph. Thus, for each individual included in the dataset, haemocyte concentration data are paired with bacterial growth responses against two distinct bacterial taxa. The dataset therefore integrates cellular and humoral components of innate immunity at the individual level, allowing direct comparison of immune performance across light treatments and between bacterial challenges. All data are organised by individual, treatment, immune metric, and bacterial species, enabling reproducible statistical analyses of ALAN effects on innate immune function.
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Steps to reproduce
Steps to reproduce the analyses The dataset is organised at the individual level and includes information on nocturnal light treatment, haemocyte concentration, and bacterial growth responses. Each individual was exposed to one of five artificial light at night (ALAN) intensities (0, 5, 20, 40 or 60 lux). For samples with sufficient haemolymph volume, haemocyte counts were obtained and standardised as concentrations per unit volume of haemolymph. To reproduce the analysis of cellular immune responses, haemocyte concentration should be analysed as a continuous response variable in relation to light treatment using a generalised linear modelling framework appropriate for positively skewed data. A Gamma error distribution with a log-link function can be used to account for the non-normal distribution of haemocyte concentrations. Model adequacy should be assessed using residual diagnostics, and differences among light treatments evaluated using post hoc pairwise comparisons with appropriate correction for multiple testing. Humoral immune responses were assessed through ex vivo bacterial challenges using Staphylococcus aureus and Bacillus subtilis. Bacterial growth was quantified as time-resolved optical density (OD₆₀₀) measurements. To reproduce these analyses, bacterial concentration should be modelled as a non-linear function of light intensity using a Michaelis–Menten type model, which captures the saturating relationship between ALAN intensity and bacterial growth. Bacterial species should be included as a categorical factor to allow comparison of modelled responses between taxa. All analyses were conducted using the R statistical environment. Reproducibility requires importing the dataset, structuring the data by individual, treatment and bacterial species, and applying the specified generalised linear and non-linear modelling approaches to haemocyte concentration and bacterial growth data, respectively.