Validation of commonly used antimicrobial interventions on bob veal carcasses for reducing Shiga toxin producing Escherichia coli surrogate populations

Ruminants are natural reservoirs of Shiga toxin producing Escherichia coli (STEC), and the STEC can be easily transferred to carcasses during the conversion of animals to meat. Three experiments were conducted to validate the efficacy of lactic acid (4%; LA), peroxyacetic acid (300 ppm; PAA), and hot water (80˚C; HW) for their individual or combined abilities to reduce STEC surrogates on bob veal carcasses pre- and post-chill and through fabrication. In experiment 1, hot carcasses (n=9) were inoculated with a 5-strain cocktail (ca. 8 log CFU/mL) containing rifampicin-resistant surrogate Escherichia coli ( E. coli ; BAA-1427, BAA-1428, BAA-1429, BAA-1430, and BAA-1431) and then treated with HW, LA, or PAA. Carcasses were then chilled (0±1°C; 24 h), split in half, and each side was treated with either LA or PAA. In experiment 2, hot carcasses (n=3) were inoculated and chilled (24 h). After 24 h, the carcasses were split, and each side was treated with either LA or PAA. For experiment 3, carcasses (n=3) were chilled for 24 h, split, inoculated, and treated with either LA or PAA. After chilling, carcasses from all three experiments were fabricated to subprimals and the cut surfaces were sampled to determine the translocation. Experiment 1 showed that LA+LA was the most effective ( P ≤ 0.05) treatment for reducing surrogate E. coli on veal. In experiments 2 and 3, LA and PAA were similar ( P > 0.05) in their abilities to reduce E. coli on chilled veal carcasses. In experiments 1 and 2, all antimicrobial treatments resulted in undetectable levels (< 0.2 log CFU/cm 2 ) of surrogate E. coli on cut surfaces after fabrication, while low levels (1.7 and 1.0 log CFU/cm 2 for LA and PAA, respectively) were observed in experiment 3. Of the antimicrobial interventions utilized, lactic acid was more effective for reducing STEC surrogate populations on veal carcasses, pre- and/or post-chill.

The allometry of movement predicts the connectivity of communities

Connectivity has long played a central role in ecological and evolutionary theory and is increasingly emphasized for conserving biodiversity. Nonetheless, connectivity assessments often focus on individual species even though understanding and preserving connectivity for entire communities is urgently needed. Here we derive and test a framework that harnesses the well-known allometric scaling of animal movement to predict community-level connectivity across protected area networks. We used a field translocation experiment involving 39 species of southern African birds to quantify movement capacity, scaled this relationship to realized dispersal distances determined from ring-and-recovery banding data, and used allometric scaling equations to quantify community-level connectivity based on multilayer network theory. The translocation experiment explained observed dispersal distances from ring-recovery data and emphasized allometric scaling of dispersal based on morphology. Our community-level networks predicted that larger-bodied species had a relatively high potential for connectivity, while small-bodied species had lower connectivity. These community networks explained substantial variation in observed bird diversity across protected areas. Our results highlight that harnessing allometric scaling can be an effective way of determining large-scale community connectivity. We argue that this trait-based framework founded on allometric scaling provides a means to predict connectivity for entire communities, which can foster empirical tests of community theory and contribute to biodiversity conservation strategies aimed at mitigating the effects of environmental change.