Shallow divers, deep waters and the rise of behavioural stochasticity

Oceanic thermal structure mediates dive sequences in a foraging seabird

“…Previous studies have shown that dive sequences from foraging penguins are best characterized as persistent, long‐range dependent fractional Gaussian noise (Cottin et al., 2014; Le Guen et al., 2018; MacIntosh, Pelletier, Chiaradia, Kato, & Ropert‐Coudert, 2013; Meyer et al., 2017; Meyer, MacIntosh, Kato, Chiaradia, & Ropert‐Coudert, 2015). In other words, dive and postdive durations of a given length are typically followed by dive and postdive durations of a similar length, with such patterns of fluctuation between these two behavioral states persisting across a range of measurement scales.…”

“…It has been proposed that complexity in behavior should correspond to complexity in the environment in terms of resource distributions, such that in heterogeneous environments, behavioral sequences are predicted to be more variable and complex, or in other words less deterministic, to enhance prey encounter rates (Alados, Escos, & Emlen, 1996; Humphries, Weimerskirch, Queiroz, Southall, & Sims, 2012; MacIntosh, 2014; MacIntosh, Alados, & Huffman, 2011; Shimada, Minesaki, & Hara, 1995; Viswanathan et al., 1999). For example, we previously showed that variation in the temporal organization of little penguin ( Eudyptula minor ) dive sequences varied across areas with different bathymetric profiles, with penguins foraging in deeper waters producing less deterministic or more stochastic sequences (Meyer et al., 2017). Thus, measuring temporal organization in behavior sequences across environmental gradients can potentially highlight the oceanographic conditions that represent challenging habitats.…”

“…The balance between the stochastic and deterministic elements in behavioral sequences may be a critical point in the emergence and maintenance of behavioral flexibility (MacIntosh, 2015; Reynolds, Ropert‐Coudert, Kato, Chiaradia, & MacIntosh, 2015). The degree of complexity in these behaviors is shaped by both internal states (e.g., stress, disease; Alados et al., 1996; Cottin et al., 2014; MacIntosh et al., 2011) and external conditions (e.g., environment; MacIntosh et al., 2011; Meyer et al., 2017). Specific “complexity signatures,” as they have been termed (MacIntosh, 2014), are predicted to optimize the efficiency of biological encounters (Alados et al., 1996; MacIntosh et al., 2011; Shimada et al., 1995).…”

“…Specific “complexity signatures,” as they have been termed (MacIntosh, 2014), are predicted to optimize the efficiency of biological encounters (Alados et al., 1996; MacIntosh et al., 2011; Shimada et al., 1995). For example, animals might exhibit greater stochasticity in more challenging environments as described above or rely on more ritualized patterns when conditions are amenable to them (MacIntosh et al., 2011; Meyer et al., 2017). Moreover, the competing demands of exploration versus exploitation of resources appear to be a key factor underlying the emergence of fractal patterns in behavior, providing a way of interpreting variation in the scaling properties observed (Reynolds et al., 2015).…”

Reproductive performance and diving behaviour share a common sea‐ice concentration optimum in Adélie penguins (Pygoscelis adeliae)

“…Interactions between the behavioural strategies of an animal and the prevailing environmental conditions lead to the emergence of observed complexity signatures, which might reflect behavioural adaptations to environmental changes (Cribb & Seuront, 2016). Based on previous research (MacIntosh, Alados, & Huffman, 2011;Meyer et al, 2017;Sims et al, 2008), we hypothesized that foraging sequences would display greater complexity (here decreased long-range dependence and thus increased stochasticity) under more challenging and/or heterogeneous environmental conditions related to sea-ice cover. (2015), we used Detrended Fluctuation Analysis (DFA; Peng et al, 1992) to measure long-range dependence in the sequential distribution of dives and surface times as an indicator of complexity in individual diving sequences.…”