Towards adaptive management of reindeer grazing resources

Abstract: This thesis aims to create a scientifically founded proposal for improvement of optimal and sustainable use of reindeer pasture resources by an adaptive management approach. Hence, the adaptive management concept is reviewed and discussed with specific reference to reindeer husbandry. Two potential indicators of changes in the grazing resources of reindeer husbandry were investigated and proposals for how these indicators could be monitored are given. Reindeer body condition, estimated from commercial slaughter data, was suggested as proxy for monitoring pasture condition during the snow-free season. Altogether, 430 000 carcass records from 1994-2007 were analysed, together with additional information on body sizes of 699 reindeer. The results showed that between-year variations in body condition (reflecting pasture conditions) were similar in all animal categories. Accuracy of monitoring could be improved by ensuring that ages of calves are correctly classified, differentiating calves by sex, separating yearlings from older animals, and adjusting data for slaughter date. Lichen height measurements were suggested for monitoring changes in winter grazing resources. Results from analysing data collected at totally 31 study sites showed that distances between measurement points should exceed 4 m and that 200-2000 points are needed for detecting changes in lichen height with sufficient statistical power. Large-scale spatial gradients, forest stand structure and moisture levels of lichen also need to be considered. A dynamic model of the reindeer-pasture system was developed. The model consists of three modules describing lichen dynamics in winter pastures, energy dynamics of reindeer and reindeer population dynamics at herd level. The model appears to capture important empirically known mechanisms of the system and have potential utility, after adaptation to the conditions of individual herding districts, as a tool for interpreting monitoring results and evaluating management actions.