Altered Larval Yellow Perch Swimming Behavior Due to Methylmercury and PCB126 Detected Using Hidden Markov Chain Models.

Fish swimming behavior is a commonly measured response in aquatic ecotoxicology because behavior is considered a whole organism-level effect that integrates many sensory systems. Recent advancements in animal behavior models, such as hidden Markov chain models (HMM), suggest an improved analytical approach for toxicology. Using both new and traditional approaches, we examined the sublethal effects of PCB126 and methylmercury on yellow perch (YP) larvae (Perca flavescens) using three doses. Both approaches indicate larvae increase activity after exposure to either chemical. The middle methylmercury-dosed larvae showed multiple altered behavior patterns. First, larvae had a general increase in activity, typically performing more behavior states, more time swimming, and more swimming bouts per second. Second, when larvae were in a slow or medium swimming state, these larvae tended to switch between these states more often. Third, larvae swam slower during the swimming bouts. The upper PCB126-dosed larvae exhibited a higher proportion and a fast swimming state, but the total time spent swimming fast decreased. The middle PCB126-dosed larvae transitioned from fast to slow swimming states less often than the control larvae. These results indicate that developmental exposure to very low doses of these neurotoxicants alters YP larvae overall swimming behaviors, suggesting neurodevelopment alteration.

Efficient Mammal Biodiversity Surveys for Ecological Restoration Monitoring.

Efficient biodiversity surveys are critical for successful restoration monitoring and management. We studied the effect of varying sampling effort on the observed species richness of surveys of small mammals (trapping transects), bats (passive acoustic detection), and medium to large mammals (trail cameras). Field studies provided mammalian biodiversity data for 4 bottomland hardwood restoration sites in northeastern Indiana. Subsampled data were used to simulate monitoring surveys with a range of levels of effort. We then used hierarchical Bayesian nonlinear mixed models to analyze how different components of sampling effort affected observed species richness, a key monitoring outcome. We found that observed small mammal richness increased with the increased number of transects in a survey, while observed bat and medium to large mammal richness increased with the increased duration of sampling. Variation between sites was important for the observed richness of small mammals and bats but not for medium to large mammals. The key driver of richness observed in simulated surveys was related to the spatial scale at which target fauna interact with the habitat, with decreasing richness accompanied by a greater spatial scale of animal-habitat interactions. Our findings suggest taxon-specific recommendations for efficiently quantifying the mammalian diversity of managed sites. Integr Environ Assess Manag 2020;00:1-13. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).