Potential of Henry's Law Constant as a Predictive Indicator of Behavioural Effect in Porcellionides pruinosus:...

Behavioral alterations in terrestrial isopods emerged as early warning signals of soil pollution, but their link to specific physicochemical properties of contaminants remains unexplored. This study investigates whether specific chemical properties can predict two ecologically relevant behavioral endpoints in the gregarious isopod Porcellionides pruinosus. A combined avoidance-disaggregation bioassay was applied to a set of twenty-four substances referred to fourteen pesticides (1,3-dichloropropene (1,3-D), azadirachtin A, chlorpyrifos, dichlobenil, dimethoate, fipronil, glyphosate, parathion, pendimethalin, S-metolachlor, sulfoxaflor, terbuthylazine, triclopyr, trifluralin), five pharmaceutical and personal care products (PPCPs: Benzophenone-1 [BP-1], carbamazepine, N,N-diethyltoluamide [DEET], galaxolide, oxybenzone [BP-3]), and five polifluoro carboxylic acid (PFCAs: Perfluorobutanoic acid [PFBA], perfluorododecanoic acid [PFDoA], perfluorooctanoic acid [PFOA], perfluoropentanoic acid [PFPeA], perfluoropropionic acid [PFPrA]). The substances were categorised according to the effects they induced: Those that induced both avoidance and disaggregation, those that triggered only one of these effects, and those showing no detectable effects. Regression models revealed a significant positive association between disaggregation and the Henry's law constant, with a threshold value estimated at 1 × 10-³ Pa m³ mol⁻¹, beyond which aggregation breaks down. This value can be proposed as a potential indicator in the regulatory field for predicting the impact of a substance on the social behaviour of woodlice, supporting management decisions in assessing the impact of contaminants on soil. Conversely, no predictive descriptors were found for avoidance responses, indicating that the mechanisms underlying migration remain to be elucidated. Furthermore, given the heterogeneity of behavioural responses, the combined use of avoidance and disaggregation endpoints is recommended for a more comprehensive investigation.