Submitted:
30 September 2026
Posted:
02 October 2026
You are already at the latest version
Abstract
In recent years, morphology-driven welfare issues in the domestic dog have moved from the periphery to the center of public and professional attention, driven by breed-specific legislation and bans, dedicated sessions at major welfare conferences, and sustained scrutiny on social media. While these concerns are supported by a growing body of evidence linking extreme traits to chronic disease and compromised welfare, most research has asked only whether one breed or trait extreme differs from another. These approaches leave a critical question unanswered: which range of a given morphological trait is actually healthiest? Advice to “breed away from extremes” therefore lacks an evidence-based target. This review surveys common canine morphological phenotypes including body size, skull shape (brachycephaly), chondrodysplasia and chondrodystrophy, thoracic depth, tail and vertebral conformation, skin folds, and coat-color and hairlessness. For each, we summarize the associated disorders, the underlying biological mechanisms where known, and the welfare consequences. Examining these phenotypes in aggregate rather than trait by trait reveals insights that single-trait studies cannot. Shared mechanisms (e.g., accelerated growth, soft tissue/skeleton mismatch, melanocyte loss) drive multiple disorders simultaneously, and trade-offs across body systems become apparent. We argue that meaningful progress — the kind these legislative, professional, and public efforts are ultimately seeking — requires reframing canine welfare research toward optimization, namely, identifying the phenotypic range that minimizes total morbidity. Such targets are prerequisite to evidence-based breeding goals, revised breed standards, and informed public decision-making. This manuscript is signed by over 30 canine biology and welfare experts who support its content.
Keywords:
dogs
; animal welfare
; canine welfare
; canine health
; animal breeding
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.