Validating two-dimensional leadership models on three-dimensionally structured fish schools

Identifying leader–follower interactions is crucial for understanding how a group decides where or when to move, and how this information is transferred between members. Although many animal groups have a three-dimensional structure, previous studies investigating leader–follower interactions have often ignored vertical information. This raises the question of whether commonly used two-dimensional leader–follower analyses can be used justifiably on groups that interact in three dimensions. To address this, we quantified the individual movements of banded tetra fish (Astyanax mexicanus) within shoals by computing the three-dimensional trajectories of all individuals using a stereo-camera technique. We used these data firstly to identify and compare leader–follower interactions in two and three dimensions, and secondly to analyse leadership with respect to an individual's spatial position in three dimensions. We show that for 95% of all pairwise interactions leadership identified through two-dimensional analysis matches that identified through three-dimensional analysis, and we reveal that fish attend to the same shoalmates for vertical information as they do for horizontal information. Our results therefore highlight that three-dimensional analyses are not always required to identify leader–follower relationships in species that move freely in three dimensions. We discuss our results in terms of the importance of taking species' sensory capacities into account when studying interaction networks within groups

An Empirical Model for Estimating Annual Consumption by Freshwater Fish Populations

Population consumption is an important process linking predator populations to their prey resources. Simple tools are needed to enable fisheries managers to estimate population consumption. We assembled 74 individual estimates of annual consumption by freshwater fish populations and their mean annual population size, 41 of which also included estimates of mean annual biomass. The data set included 14 freshwater fish species from 10 different bodies of water. From this data set we developed two simple linear regression models predicting annual population consumption. Log-transformed population size explained 94% of the variation in log-transformed annual population consumption. Log-transformed biomass explained 98% of the variation in log-transformed annual population consumption. We quantified the accuracy of our regressions and three alternative consumption models as the mean percent difference from observed (bioenergetics-derived) estimates in a test data set. Predictions from our population-size regression matched observed consumption estimates poorly (mean percent difference = 222%). Predictions from our biomass regression matched observed consumption reasonably well (mean percent difference = 24%). The biomass regression was superior to an alternative model, similar in complexity, and comparable to two alternative models that were more complex and difficult to apply. Our biomass regression model, log10(consumption) = 0.5442 + 0.9962 · log10(biomass), will be a useful tool for fishery managers, enabling them to make reasonably accurate annual population consumption predictions from mean annual biomass estimates

Test your surrogate data before you test for nonlinearity

The schemes for the generation of surrogate data in order to test the null hypothesis of linear stochastic process undergoing nonlinear static transform are investigated as to their consistency in representing the null hypothesis. In particular, we pinpoint some important caveats of the prominent algorithm of amplitude adjusted Fourier transform surrogates (AAFT) and compare it to the iterated AAFT (IAAFT), which is more consistent in representing the null hypothesis. It turns out that in many applications with real data the inferences of nonlinearity after marginal rejection of the null hypothesis were premature and have to be re-investigated taken into account the inaccuracies in the AAFT algorithm, mainly concerning the mismatching of the linear correlations. In order to deal with such inaccuracies we propose the use of linear together with nonlinear polynomials as discriminating statistics. The application of this setup to some well-known real data sets cautions against the use of the AAFT algorithm.Comment: 14 pages, 15 figures, submitted to Physical Review

Influence of Diporeia Density on Diet Composition, Relative Abundance, and Energy Density of Planktivorous Fishes in Southeast Lake Michigan

The benthic amphipod Diporeia spp. is an important prey for many fish in offshore areas of the Great Lakes, but its abundance has been rapidly decreasing. To assess the influence of Diporeia availability on the food habits, relative abundance, and energetics of planktivorous fish, the diet composition, catch per unit effort (CPUE), and energy density of plantkivorous fish in southeast Lake Michigan during 2000–2001 were compared among locations with different Diporeia densities. Diporeia densities at St. Joseph, Michigan, were near 0/m2 over much of the bottom but averaged more than 3,800/m2 at Muskegon and Little Sable Point, Michigan. Consistent with these differences in Diporeia density, fish diet composition, CPUE, and energy density varied spatially. For example, alternative prey types comprised a larger fraction of the diets of bloater Coregonus hoyi, large (>100 mm total length) alewife Alosa pseudoharengus, and slimy sculpin Cottus cognatus at St. Joseph than at Muskegon and Little Sable Point. This pattern was seasonally dependent for alewives and bloaters because Diporeia were eaten mainly in June. Food biomass per stomach was not lower at St. Joseph than elsewhere, suggesting that the spatial variation in diet composition was due to greater consumption of alternative prey by fish at St. Joseph. Although slimy sculpin and bloaters were able to feed on alternative prey, the CPUE of these species at certain depths was considerably lower at St. Joseph than at Muskegon or Little Sable Point, indicating that Diporeia availability may also influence fish abundance and distribution. Finally, a link between Diporeia density and fish energetics was suggested by the comparatively low energy density of deepwater sculpin Myoxocephalus thompsonii and large alewives at St. Joseph, a result that may reflect the low energy content of other prey relative to Diporeia.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141042/1/tafs0588.pd

The Smartphone Brain Scanner: A Portable Real-Time Neuroimaging System

Combining low cost wireless EEG sensors with smartphones offers novel opportunities for mobile brain imaging in an everyday context. We present a framework for building multi-platform, portable EEG applications with real-time 3D source reconstruction. The system - Smartphone Brain Scanner - combines an off-the-shelf neuroheadset or EEG cap with a smartphone or tablet, and as such represents the first fully mobile system for real-time 3D EEG imaging. We discuss the benefits and challenges of a fully portable system, including technical limitations as well as real-time reconstruction of 3D images of brain activity. We present examples of the brain activity captured in a simple experiment involving imagined finger tapping, showing that the acquired signal in a relevant brain region is similar to that obtained with standard EEG lab equipment. Although the quality of the signal in a mobile solution using a off-the-shelf consumer neuroheadset is lower compared to that obtained using high density standard EEG equipment, we propose that mobile application development may offset the disadvantages and provide completely new opportunities for neuroimaging in natural settings