From Pigs to Silkworms: Cognition and Welfare across 10 Farmed Taxa

Abstract

Billions of animals across many taxa are extensively farmed, with critical impacts on animal welfare. Societal efforts to reduce animal suffering lack rigorous and systematic approaches that facilitate maximising welfare improvements, such as informed funding allocation decisions. We present a multi-measure, cross-taxa framework for modelling differences in pain, suffering, and related cognition to assess whether certain animals have larger welfare ranges (how well or badly animals can fare). Measures include behavioural flexibility, cognitive sophistication, and general learning. We evaluated 90 empirically detectable proxies for cognition and welfare range (henceforth proxies) in pigs, chickens, carp, salmon, octopus, shrimp, crabs, crayfish, bees, and silkworms. We grouped a subset of proxies into: A) 10 ideal proxies and B) 10 less ideal proxies but with sufficient data for interspecies comparisons. We graded the strength of evidence per proxy across taxa, and constructed a cognition and welfare range profile, with overall judgement scores (ranging from likely no/low confidence to yes/very high confidence). We discuss the implications of comparisons and highlight key avenues for future research. This work is timely, given recent indications of significant political will towards reducing animal suffering, such as the inclusion of cephalopods and decapods in the Animal Welfare (Sentience) Bill following a UK government-commissioned research review. Given the novelty and robustness of our review, we believe it sets a new standard for investigating interspecies comparisons of cognition and welfare ranges and helps inform future research. This should help streamline funding allocations and improve the welfare of millions of farmed animals. Graphical/ Visual Abstract and Caption O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY Cognition and welfare in farmed animals - from pigs to silkworms (Free stock images: http://www.pixabay.com) C_FIG_DISPLAY