Effect of "owners" selection strategies on autumn weight in reindeer (Rangifer t. tarandus) calves

• Main Authors: Robert B. Weladji, Øystein Holand, Geir Steinheim, Helge Hansen
• Format: Article
• Language: English
• Published: Septentrio Academic Publishing 2002-03-01
• Series: Rangifer
• Subjects: body weight; owner effect; reindeer herding industry; selection strategy; traditional ecological knowledge; TEK
• Online Access: https://septentrio.uit.no/index.php/rangifer/article/view/1529

Many northern indigenous peoples, including the Sami are dependent on reindeer herding for their livelihood. In view of the socio-cultural and economical importance of reindeer herding, emphasis should be put on appropriate herd structure and selection strategies that maximise marketable products, such as meat (the primary marketable product nowadays). Empirical observations reveal that within a herd, some owners seem to have better productivity in term of carcass autumn weight of calves, than others. We hypothesized that there may be an "owner" effect in reindeer herding, i.e. some owners may be applying particular selection strategies that might be beneficial. We investigated this in three reindeer grazing districts in South Norway, using mixed linear models. We found that autumn carcass weight of calves varied significantly with year and "owner" within herd in all three districts. Consistently some particular owners within a herd had higher average autumn carcass weight of their calves than others. We attributed this difference to "individual selection strategies", meaning that some owners may follow more accurately the sex, age and weight-based recommended strategy and in addition, they may make superior choices when selecting animals for slaughtering. We conclude that individual owners have the capability, through appropriate selection decisions to improve the average annual autumn weight of their reindeer calves. This might be an important aspect of "Traditional Ecological Knowledge", in addition to the recommended modern sex, age and weight-based selection criteria.