The challenges of analyzing behavioral response study data : an overview of the MOCHA (Multi-study OCean acoustics Human effects Analysis) project

Date of Acceptance:This paper describes the MOCHA project which aims to develop novel approaches for the analysis of data collected during Behavioral Response Studies (BRSs). BRSs are experiments aimed at directly quantifying the effects of controlled dosages of natural or anthropogenic stimuli (typically sound) on marine mammal behavior. These experiments typically result in low sample size, relative to variability, and so we are looking at a number of studies in combination to maximize the gain from each one. We describe a suite of analytical tools applied to BRS data on beaked whales, including a simulation study aimed at informing future experimental design.Postprin

First direct measurements of behavioural responses by Cuvier's beaked whales to mid-frequency active sonar

Most marine mammal­ strandings coincident with naval sonar exercises have involved Cuvier's beaked whales (Ziphius cavirostris). We recorded animal movement and acoustic data on two tagged Ziphius and obtained the first direct measurements of behavioural responses of this species to mid-frequency active (MFA) sonar signals. Each recording included a 30-min playback (one 1.6-s simulated MFA sonar signal repeated every 25 s); one whale was also incidentally exposed to MFA sonar from distant naval exercises. Whales responded strongly to playbacks at low received levels (RLs; 89–127 dB re 1 µPa): after ceasing normal fluking and echolocation, they swam rapidly, silently away, extending both dive duration and subsequent non-foraging interval. Distant sonar exercises (78–106 dB re 1 µPa) did not elicit such responses, suggesting that context may moderate reactions. The observed responses to playback occurred at RLs well below current regulatory thresholds; equivalent responses to operational sonars could elevate stranding risk and reduce foraging efficiency.Publisher PDFPeer reviewe

Physical activity as an aid to smoking cessation during pregnancy: Two feasibility studies

Background: Pharmacotherapies for smoking cessation have not been adequately tested in pregnancy and women are reluctant to use them. Behavioural support alone has a modest effect on cessation rates; therefore, more effective interventions are needed. Even moderate intensity physical activity (e.g. brisk walk) reduces urges to smoke and there is some evidence it increases cessation rates in non-pregnant smokers. Two pilot studies assessed i) the feasibility of recruiting pregnant women to a trial of physical activity for smoking cessation, ii) adherence to physical activity and iii) womens' perceptions of the intervention. Methods: Pregnant smokers volunteered for an intervention combining smoking cessation support, physical activity counselling and supervised exercise (e.g. treadmill walking). The first study provided six weekly treatment sessions. The second study provided 15 sessions over eight weeks. Physical activity levels and continuous smoking abstinence (verified by expired carbon monoxide) were monitored up to eight months gestation. Results: Overall, 11.6% (32/277) of women recorded as smokers at their first antenatal booking visit were recruited. At eight months gestation 25% (8/32) of the women achieved continuous smoking abstinence. Abstinent women attended at least 85% of treatment sessions and 75% (6/8) achieved the target level of 110 minutes/week of physical activity at end-of-treatment. Increased physical activity was maintained at eight months gestation only in the second study. Women reported that the intervention helped weight management, reduced cigarette cravings and increased confidence for quitting. Conclusion: It is feasible to recruit pregnant smokers to a trial of physical activity for smoking cessation and this is likely to be popular. A large randomised controlled trial is needed to examine the efficacy of this intervention

Kernel density estimation of conditional distributions to detect responses in satellite tag data

Abstract Background As levels of anthropogenic noise in the marine environment rise, it is crucial to quantify potential associated effects on marine mammals. Yet measuring responses is challenging because most species spend the majority of their time submerged. Consequently, much of their sub-surface behavior is difficult or impossible to observe and it can be difficult to determine if—during or following an exposure to sound—an observed dive differs from previously recorded dives. We propose a method for initial assessment of potential behavioral responses observed during controlled exposure experiments (CEEs), in which animals are intentionally exposed to anthropogenic sound sources. To identify possible behavioral responses in dive data collected from satellite-linked time–depth recorders, and to inform the selection and parameters for subsequent individual and population-level response analyses, we propose to use kernel density estimates of conditional distributions for quantitative comparison of pre- and post-exposure behavior. Results We apply the proposed method to nine Cuvier’s beaked whales (Ziphius cavirostris) exposed to a lower-amplitude simulation of Mid-Frequency Active Sonar within the context of a CEE. The exploratory procedure provides evidence that exposure to sound causes animals to change their diving behavior. Nearly all animals tended to dive deep immediately following exposure, potentially indicating avoidance behavior. Following the initial deep dive after exposure, the procedure provides evidence that animals either avoided deep dives entirely or initiated deep dives at unusual times relative to their pre-exposure, baseline behavior patterns. The procedure also provides some evidence that animals exposed as a group may tend to respond as a group. Conclusions The exploratory approach we propose can identify potential behavioral responses across a range of diving parameters observed during CEEs. The method is particularly useful for analyzing data collected from animals for which neither the baseline, unexposed patterns in dive behavior nor the potential types or duration of behavioral responses is well characterized in the literature. The method is able to be applied in settings where little a priori knowledge is known because the statistical analyses employ kernel density estimates of conditional distributions, which are flexible non-parametric techniques. The kernel density estimates allow researchers to initially assess potential behavioral responses without making strong, model-based assumptions about the data. </jats:sec