Status, Risk, and Production Practices of Local Sheep and Goat Breeds in Saudi Arabia: Insights from a Breeder Survey

Genetic resources of small ruminants are essential for food security in arid regions; however, basic data for each breed in Saudi Arabia remain incomplete. This study establishes a comprehensive national database through a systematic survey of 104 farms, covering 21,214 heads of livestock (sheep and goats) across the kingdom’s primary agro-ecological zones between January and October 2025. Although national census data indicate that major breeds of sheep such as Naeemi, Najdi, Arabi, and Harri or goats such as Ardi exceed the FAO’s numerical thresholds for “not at risk,” our analysis reveals a fundamental paradox of “genetic vulnerability,” defined as a high risk of inbreeding depression and genetic stagnation despite high census numbers. The results show significant regional variations in prolificacy (p < 0.05), with the southern region displaying a substantial productivity gap compared to the central and eastern regions, mainly due to reliance on traditional grazing (46.7%) and limited infrastructure. This vulnerability is driven by a high risk of systematic inbreeding, with 65.7% of breeders acquiring sires from their own herds, a situation worsened by a severe 80% shortage of high-quality breeding males in the central region. Furthermore, selection criteria heavily emphasize esthetic phenotypic traits (over 80%) rather than production indicators (less than 8%), hindering genetic progress. Correlation analysis showed that higher farmer education levels were negatively associated with reproductive challenges (r = −0.216), while high feed prices remained a near-universal obstacle (97.1%). To mitigate these risks, we recommend implementing region-specific sire exchange programs to break closed breeding loops and establishing a national performance recording system to shift selection focus from phenotypic traits to measurable productivity. This study provides a vital, evidence-based framework for transitioning toward data-driven, resilient conservation and breeding strategies.