Controlling for spatial preferences, the mixture model retrieved a total of 972 significant social clustering events (Y1 = 209; Y2 = 227; Y3 = 277; Y4 = 259). Calculating a weighted assortativity coefficient for each annual network revealed significant social assortment by spatial community membership ( r d w : Y1 = 0.204; Y2 = 0.129; Y3 = 0.176; Y4 = 0.130) when tested against a null model of 10 000 random networks (figure 1c). 074 (0.065), Y2: 0.129 (0.015), Y3: 0.177 (0.025), Y4: ?0.043 (0.042)). Mantel tests revealed that there was a strong correlation in the dyadic association strength between pairs for years 12 (n = 29, Mantel r = 0.74, CI = 0.13–0.30, p < 0.001), 23 (n = 35, Mantel r = 0.85, CI = 0.13–0.29, p < 0.001), 34 (n = 31, Mantel r = 0.78, CI = 0.13–0.27, p < 0.001) and finally for the duration of the study for years 14 (n = 22, Mantel r = 0.76, CI = 0.16–0.35, p < 0.001).
(b) Changes in category dimensions
The number of tagged sharks increased throughout the morning, for both communities (blue and red), peaking about (GLMM R 2 = 0.18, 0.10; F = 244.9, 111.9, p < 0.001, community 2, community 4, respectively; figure 2a). The number of tagged sharks detected then decreased, reaching a minimum by – before starting to increase at – (figure 2a). Footage from camera tags deployed on two sharks showed that group size typically varied between two and 14 individuals, with group size increasing throughout the morning and peaking in the afternoon (figure 2c, electronic supplementary material, video S4). Close following behaviour, where individuals were approximately less than 1 m from a conspecific, was commonly observed (electronic supplementary material, S4). It is likely that detection range of receivers will be reduced at night due to increased noise on the reef, which may influence our ability to detect individuals. However, the more gradual increase in shark numbers throughout the early morning as well camera footage still suggests diel changes in group size are genuine.
Contour dos. Diel period forecasts changes in class proportions within the one or two prominent groups. (a) Level of acoustically marked whales detected during the center receivers raise notably for hours for individuals in the a few premier communities (red and you can blue, contour step 1). (b) Physique get from a pet-borne camera of a grey reef shark entering intimate after the behavior. (c,d) Digital camera mark derived minimum classification proportions transform throughout the day having a few females gray reef sharks within this community 2. (Online type when you look at the the colour.)
(c) Individual-based activities
The very first IBMs showed that individuals using only personal data so you can locate information (loners) provides dramatically hitwe reduced physical fitness compared to those using personal and personal suggestions (digital supplementary matter, S5). Under the artificial problems regarding starting ratios away from target high quality (energetic reward) and you can spot density, this new proportion regarding ‘loner’ people easily denied generally speaking so you’re able to extinction, unless of course effective perks was indeed very high (electronic additional thing, S5). Our very own next series of models (private and you may public info/particular CPFs, anybody else wanderers) revealed that no matter victim top quality, plot density or the creating ratio out of wanderers in order to CPFs, in every modeling issues CPFs had far deeper success times (contour 3, digital supplementary matter, S3 and you will S5). When simulations were manage that have shorter predictable spatial balances out-of target patches, CPFs usually got prolonged endurance moments than drifting foragers irrespective of area occurrence or quality (shape 3c–f). But not, the real difference into the emergency go out try most useful in the highest area densities and you will high quality (contour step 3, electronic secondary material, S3 and you may S5).