How variable is agonistic behavior among crab species? A case study on freshwater anomurans (Crustacea: Decapoda: Aeglidae)

Harder, better, faster, stronger: Weapon size is more sexually dimorphic than weapon biomechanical components in two freshwater anomuran species

Sexual selection influences the evolution of morphological traits that increase the likelihood of monopolizing scarce resources. When such traits are used during contests, they are termed weapons. Given that resources are typically linked to monopolizing mating partners, theory expects only males to bear weapons. In some species, however, females also bear weapons, although typically smaller than male weapons. Understanding why females bear smaller weapons can thus help us understand the selective pressures behind weapon evolution. However, most of our knowledge comes from studies on weapon size, while the biomechanics of weapons, such as the size of the muscles, efficiency, and shape are seldom studied. Our goal was to test if the theoretical expectations for weapon size sexual dimorphism also occur for weapon biomechanics using two aeglid crab species. Males of both species had larger claws which were also stronger than female claws. Male claws were also more efficient than females' claws (although we used only one species in this analysis). For weapon shape, though, only one species differed in the mean claw shape. Regarding scaling differences, in both species, male claws had higher size scaling than females, while only one species had a higher shape scaling. However, male weapons did not have higher scaling regarding strength and efficiency than females. Thus, males apparently allocate more resources in weapons than females, but once allocated, muscle and efficiency follow a similar developmental pathway in both sexes. Taken together, our results show that sexual dimorphism in weapons involves more than differences in size. Shape differences are especially intriguing because we cannot fully understand its causes. Yet, we highlight that such subtle differences can only be detected by measuring and analysing weapon shape and biomechanical components. Only then we might better understand how weapons are forged.

Aggressive behavior variation and experience effects in three families of juvenile Chinese mitten crab (Eriocheir sinensis)

To assess how variable is the aggressive behavior among families (A, B, and C) and the experience effect of fighting among juvenile Chinese mitten crab (Eriocheir sinensis), we performed a total of 36 pairs of intrafamily and interfamily contests between three families of Eriocheir sinensis, qualifying and quantifying their aggressive acts and 13 pairs of winners within family and between family A and B. A table of aggression intensity was established, ranging from 1 (chasing) to 4 (intense combat). Crabs of intrafamily association performed more aggressive acts of shorter duration than interfamily, family B was more aggressive than those from families A and C: family C was the least aggressive, which is also the most morphologically distinct strain (a new strain with a red carapace). During the second fighting trail, the intensity and number of fights were significantly different to first fight conditions and also differed among families. Therefore, our results suggest that the aggressive behavior of Eriocheir sinensis is different among different families, and the combat experience has a significant effect on the secondary fight. This is the first report of aggressive behavior in Eriocheir sinensis, a reference for crab aquaculture and provides new ideas for genetic breeding work in crab selected breeding programmes. It will be possible to carry out more profound studies of the behavior of these animals.

The Bias of combining variables on fish's aggressive behavior studies

Quantifying animal aggressive behavior by behavioral units, either displays or attacks, is a common practice in animal behavior studies. However, this practice can generate a bias in data analysis, especially when the variables have different temporal patterns. This study aims to use Bayesian Hierarchical Linear Models (B-HLMs) to analyze the feasibility of pooling the aggressive behavior variables of four cichlids species. Additionally, this paper discusses the feasibility of combining variables by examining the usage of different sample sizes and family distributions to aggressive behaviour variables. The subject species were: the angelfish (Pterophyllum scalare), the tiger oscar (Astronotus ocellatus), the Cichlasoma paranaense and the Nile tilapia (Oreochromis niloticus). For each species, 15 groups of 3 individuals were assigned to daily observations (10-min recordings) for 5 days. Aggressive behavior data was labeled according to its aggressive intensity. The variables chase (C), tail beating (TB), push (P), lateral attack (LA) and bite (B) were classified as high intensity. The variables undulation (U), lateral threat (LT) and frontal displays (FD) were classified as low intensity. These behaviors, however, were not present in all species. Model parameters were estimated by Monte Carlo Markov chains using non-informative priors. B-HLMs were performed to assess the impact probability of each variable in the analysis. Results revealed that when combining variables, the resulting distribution is strongly influenced by only one variable in each category. Moreover, in some cases the aggregate values altered the results, which changed the probabilities of the main variables. Species with low aggressive behavior frequencies, such as A. ocellatus, are more sensitive to this bias. LT was the main low intensity variable for all species, while B was the main high intensity variable for the P. scalare and the O. niloticus. LA was the high intensity category variable that was the most relevant for the C. paranaense and A. ocellatus. Moreover, combining the variables did not impact the feasibility of reducing the sample size when compared to using the most quantitative variable. For all species a sample size of 12 did not change the study conclusions. With respect to family distribution, based on DIC values the Gaussian model is more suitable for most of the studied species. However, caution should be taken, because the Gaussian posterior probability distribution overlapped 0 in some cases, which is biologically impossible in aggressive behaviors. The only exception is the A. ocellatus, which, based on DIC values, was the only species better modeled by a Poisson distribution. Bayesian analysis can be therefore considered a strong tool for analyzing aggressive behavior.