Dark refuges decrease aggression throughout the tank.

<p>Overall aggression (total number of aggressive acts occurring per 10-min trial) throughout the tank decreased with average tank darkness (p < 0.01), but especially when the tank contained an area available with darkness of .55 or greater (p < 0.0001). Dots represent aggression counts in a trial for each tank. Background darkness ranges from 0 (white) to 1 (black). Filled-in circle (◯) colour corresponds to the average tank darkness and the triangle (▿) indicates the average tank darkness of the pattern vs. black trial. The bi-colour panel at the bottom of the plot shows the two colours tested in the trial.</p

Dark backgrounds decrease aggression.

<p>Average aggression (the total number of aggressive acts displayed divided by the average number of fish across a 10-min trial) on a side (log scale) decreased with background darkness (p < 0.0001). Background darkness ranges from 0 (white) to 1 (black). Filled-in circle (◯) colour corresponds to the background colour (white, blue, light grey, dark grey, or black) and the triangle (▿) indicates the patterned background.</p

Salmon prefer darker backgrounds.

<p>Preference strength increased with increasing background darkness (p < 0.0001). For the (a) black-trials and (b) blue-trials, dots represent each tank’s average number of Coho salmon (<i>Oncorhynchus kisutch</i>) located on the comparison side. Background darkness ranges from 0 (white) to 1 (black). Large symbols represent average values across all tanks (n = 10) with the fill colour corresponding to the background darkness of the comparison side (white, light grey, dark grey, or black) and the triangle (▿) indicating the patterned background trial.</p

A theoretical approach to improving interspecies welfare comparisons

Peer reviewed: TrueThe number of animals bred, raised, and slaughtered each year is on the rise, resulting in increasing impacts to welfare. Farmed animals are also becoming more diverse, ranging from pigs to bees. The diversity and number of species farmed invite questions about how best to allocate currently limited resources towards safeguarding and improving welfare. This is of the utmost concern to animal welfare funders and effective altruism advocates, who are responsible for targeting the areas most likely to cause harm. For example, is tail docking worse for pigs than beak trimming is for chickens in terms of their pain, suffering, and general experience? Or are the welfare impacts equal? Answering these questions requires making an interspecies welfare comparison; a judgment about how good or bad different species fare relative to one another. Here, we outline and discuss an empirical methodology that aims to improve our ability to make interspecies welfare comparisons by investigating welfare range, which refers to how good or bad animals can fare. Beginning with a theory of welfare, we operationalize that theory by identifying metrics that are defensible proxies for measuring welfare, including cognitive, affective, behavioral, and neuro-biological measures. Differential weights are assigned to those proxies that reflect their evidential value for the determinants of welfare, such as the Delphi structured deliberation method with a panel of experts. The evidence should then be reviewed and its quality scored to ascertain whether particular taxa may possess the proxies in question to construct a taxon-level welfare range profile. Finally, using a Monte Carlo simulation, an overall estimate of comparative welfare range relative to a hypothetical index species can be generated. Interspecies welfare comparisons will help facilitate empirically informed decision-making to streamline the allocation of resources and ultimately better prioritize and improve animal welfare.</jats:p

Evolutionary trends in host physiology outweigh dietary niche in structuring primate gut microbiomes.

Over the past decade several studies have reported that the gut microbiomes of mammals with similar dietary niches exhibit similar compositional and functional traits. However, these studies rely heavily on samples from captive individuals and often confound host phylogeny, gut morphology, and diet. To more explicitly test the influence of host dietary niche on the mammalian gut microbiome we use 16S rRNA gene amplicon sequencing and shotgun metagenomics to compare the gut microbiota of 18 species of wild non-human primates classified as either folivores or closely related non-folivores, evenly distributed throughout the primate order and representing a range of gut morphological specializations. While folivory results in some convergent microbial traits, collectively we show that the influence of host phylogeny on both gut microbial composition and function is much stronger than that of host dietary niche. This pattern does not result from differences in host geographic location or actual dietary intake at the time of sampling, but instead appears to result from differences in host physiology. These findings indicate that mammalian gut microbiome plasticity in response to dietary shifts over both the lifespan of an individual host and the evolutionary history of a given host species is constrained by host physiological evolution. Therefore, the gut microbiome cannot be considered separately from host physiology when describing host nutritional strategies and the emergence of host dietary niches