Sex-differences in fine-scale home-range use in an upper-trophic level marine predator

Sex mechanisms as nonbinary influences on cognitive diversity

Essentially all neuropsychiatric diagnoses show some degree of sex and/or gender differences in their etiology, diagnosis, or prognosis. As a result, the roles of sex-related variables in behavior and cognition are of strong interest to many, with several lines of research showing effects on executive functions and value-based decision making in particular. These findings are often framed within a sex binary, with behavior of females described as less optimal than male "defaults"-- a framing that pits males and females against each other and deemphasizes the enormous overlap in fundamental neural mechanisms across sexes. Here, we propose an alternative framework in which sex-related factors encompass just one subset of many sources of valuable diversity in cognition. First, we review literature establishing multidimensional, nonbinary impacts of factors related to sex chromosomes and endocrine mechanisms on cognition, focusing on value- based decision-making tasks. Next, we present two suggestions for nonbinary interpretations and analyses of sex-related data that can be implemented by behavioral neuroscientists without devoting laboratory resources to delving into mechanisms underlying sex differences. We recommend (1) shifting interpretations of behavior away from performance metrics and towards strategy assessments to avoid the fallacy that the performance of one sex is worse than another; and (2) asking how much variance sex explains in measures and whether any differences are mosaic rather than binary, to avoid assuming that sex differences in separate measures are inextricably correlated. Nonbinary frameworks in research on cognition will allow neuroscience to represent the full spectrum of brains and behaviors.

Deep vs shallow: GPS tags reveal a dichotomy in movement patterns of loggerhead turtles foraging in a coastal bay

BACKGROUND

Individual variation in movement strategies of foraging loggerhead turtles have been documented on the scale of tens to hundreds of kilometers within single ocean basins. Use of different strategies among individuals may reflect variations in resources, predation pressure or competition. It is less common for individual turtles to use different foraging strategies on the scale of kilometers within a single coastal bay. We used GPS tags capable of back-filling fine-scale locations to document movement patterns of loggerhead turtles in a coastal bay in Northwest Florida, U.S.A.

METHODS

Iridium-linked GPS tags were deployed on loggerhead turtles at a neritic foraging site in Northwest Florida. After filtering telemetry data, point locations were transformed to movement lines and then merged with the original point file to define travel paths and assess travel speed. Home ranges were determined using kernel density function. Diurnal behavioral shifts were examined by examining turtle movements compared to solar time.

RESULTS

Of the 11 turtles tagged, three tracked turtles remained in deep (~ 6 m) water for almost the entire tracking period, while all other turtles undertook movements from deep water locations, located along edges and channels, to shallow (~ 1-2 m) shoals at regular intervals and primarily at night. Three individuals made short-term movements into the Gulf of Mexico when water temperatures dropped, and movement speeds in the Gulf were greater than those in the bay. Turtles exhibited a novel behavior we termed drifting.

CONCLUSIONS

This study highlighted the value provided to fine-scale movement studies for species such as sea turtles that surface infrequently by the ability of these GPS tags to store and re-upload data. Future use of these tags at other loggerhead foraging sites, and concurrent with diving and foraging data, would provide a powerful tool to better understand fine-scale movement patterns of sea turtles.

Individual Quality Drives Life History Variation in a Long-Lived Marine Predator

AbstractIndividual quality and environmental conditions may mask or interact with energetic trade-offs in life history evolution. Deconstructing these sources of variation is especially difficult in long-lived species that are rarely observed on timescales long enough to disentangle these effects. Here, we investigated relative support for variation in female quality and costs of reproduction as factors shaping differences in life history trajectories using a 32-year dataset of repeated reproductive measurements from 273 marked, known-age female gray seals (Halichoerus grypus). We defined individual reproductive investment using two traits, reproductive frequency (a female's probability of breeding) and provisioning performance (offspring weaning mass). Fitted hierarchical Bayesian models identified individual investment relative to conspecifics (over a female's entire life and in three age classes) and subsequently estimated how these investment metrics and the Atlantic Multidecadal Oscillation are associated with longevity. Individual differences (i.e., quality) contributed a large portion of the variance in reproductive traits. Females that consistently invest well in their offspring relative to other females survive longer. The best-supported model estimated survival as a function of age class-specific provisioning performance, where late-life performance was particularly variable and had the greatest impact on survival, possibly indicating individual variation in senescence. There was no evidence to support a trade-off in reproductive performance and survival at the individual level. Overall, these results suggest that in gray seals, individual quality is a stronger driver in life history variation than individual strategies resulting from energetic trade-offs.

Measuring repeatability of compositional diet estimates: An example using quantitative fatty acid signature analysis

By measuring the temporal consistency, or repeatability, in the diets of predators, we can gain a better understanding of the degree of individual specialization in resource utilization and implications for predator-prey interactions, population dynamics, and food web structure. To measure repeatability, we require repeated diet estimates of individuals over time, such as those derived from quantitative fatty acid signature analysis (QFASA), a popular diet estimation technique. However, diet estimates are often lengthy compositional vectors with many zeros, as some prey will not be consumed by all individuals, precluding the use of previously proposed measures of repeatability. In this paper, we propose a novel approach for inferring repeatability for multivariate data and, in particular, compositional diet estimates. We extend the commonly used measure of repeatability for univariate data to the multivariate compositional setting by utilizing the mean squares obtained from a nonparametric multivariate analysis of variance, and an appropriate choice of statistical distance. Our measure and its extension are compatible with both balanced and unbalanced data sets. Associated confidence intervals via nonparametric bootstrapping are also developed for the case of QFASA diet estimates that incorporate both sampling error and measurement error, where the latter error arises because the diets of predators are estimated. Simulation study results suggest that for practical levels of repeatability, our methods yield confidence intervals with the desired coverage probability even when the sample size relative to the dimension of the data (i.e., number of prey species eaten) is small. We tested our methods using QFASA diet estimates for free-ranging Northwest Atlantic grey seals. Given the importance of understanding how predator diets vary over time and space, our method may find broad application to other compositional diet estimates, including those derived from the stomach or fecal contents, and stable isotope analyses.

Capitoline Dolphins: Residency Patterns and Abundance Estimate of Tursiops truncatus at the Tiber River Estuary (Mediterranean Sea)

Periodic assessments of population status and trends to detect natural influences and human effects on coastal dolphin are often limited by lack of baseline information. Here, we investigated for the first time the site-fidelity patterns and estimated the population size of bottlenose dolphins (Tursiops truncatus) at the Tiber River estuary (central Mediterranean, Tyrrhenian Sea, Rome, Italy) between 2017 and 2020. We used photo-identification data and site-fidelity metrics to study the tendency of dolphins to remain in, or return to, the study area, and capture-recapture models to estimate the population abundance. In all, 347 unique individuals were identified. The hierarchical cluster analysis highlighted 3 clusters, labeled resident (individuals encountered at least five times, in three different months, over three distinct years; n = 42), part-time (individuals encountered at least on two occasions in a month, in at least two different years; n = 73), and transient (individuals encountered on more than one occasion, in more than 1 month, none of them in more than 1 year; n = 232), each characterized by site-fidelity metrics. Open POPAN modeling estimated a population size of 529 individuals (95% CI: 456-614), showing that the Capitoline (Roman) coastal area and nearby regions surrounding the Tiber River estuary represent an important, suitable habitat for bottlenose dolphins, despite their proximity to one of the major urban centers in the world (the city of Rome). Given the high number of individuals in the area and the presence of resident individuals with strong site fidelity, we suggest that conservation plans should not be focused only close to the Tiber River mouths but extended to cover a broader scale of area.

The role of environmental temperature on movement patterns of giant anteaters

Mammals can show conspicuous behavioral responses to thermal variation, including changes in movement patterns. We used an integrative approach to understand how environmental temperature can drive the movement behavior of a mammal with low capacity for physiological thermoregulation, the giant anteater (Myrmecophaga tridactyla). We tracked 52 giant anteaters in 7 areas throughout the Brazilian savannah. We estimated the distance moved, area used, use of forest areas, and mean environmental temperature for each monitoring day of each individual. We modeled these data with Mixed Structural Equations - considering the possible interactions between our variables and controlling for sex and body mass. Giant anteaters reduced displacement and increased forest use with decreasing environmental temperature, probably because of their low body heat production. It is possible that they reduce distance moved and area used by reducing the duration of activity. With decreasing temperature, forest habitats become warmer than open ones, besides buffer rain and chilly winds. Reducing displacement and using forests are important strategies to reduce body heat loss and the energetic costs of thermoregulation. However, decreasing movement can limit food access and, consequently, fitness. Therefore, we highlight the importance of forests as thermal shelters. With increasing frequency and intensity of extreme weather events, we showed the need to preserve forest patches to offer suitable conditions for tropical mammals' behavioral thermoregulation. In this context, policies favoring deforestation on Brazilian territory are especially worrisome. Finally, we emphasize the need of integrative approaches to understand the complex interactions between organisms and the environment.