Territorial behaviour and population dynamics in red grouse Lagopus lagopus scoticus. I. Population level experiments

1. According to the 'territorial behaviour' hypothesis, population cycles of red grouse are caused by delayed density-dependent changes in the aggressiveness of territorial cocks. We report here on a replicated population experiment testing assumptions of this hypothesis.

2. We used testosterone implants to increase aggressiveness of cocks for 3 months during autumn, when recruitment and territory establishment take place. On two moors located in northern England, and on two 1-km(2) areas within each moor, we implanted adult cocks with testosterone on an experimental area and with sham implants on a control area.

3. During the first autumn, the testosterone treatment prevented recruitment of young cocks into the territorial populations. This reduced breeding density and altered the age ratio among territorial cocks, and possibly levels of kinship. If so, the 'kinship' hypothesis predicted that density and recruitment should continue to differ between testosterone-treated and control areas.

4. Grouse density remained significantly lower on the experimental than on the control areas for two consecutive breeding seasons. This confirmed a strong spatial structuring within grouse populations, which prevented immigration from neighbouring higher-density areas. In the second autumn, testosterone was not implanted but the recruitment rate remained significantly lower and cock density continued to decline more on the experimental than on the control areas.

5. The results suggest that cocks continued to be aggressive and to maintain large territories for at least a year after aggressiveness was increased experimentally, and therefore that autumn aggressiveness is influenced by previous territorial contests.

6. The experiment validates key assumptions of the 'territorial behaviour' hypothesis for red grouse cycles. Population models in a subsequent paper demonstrate how changes in aggressiveness can cause population cycles.